ES3035814T3 - Compositions for reprogramming cells into dendritic cells or antigen presenting cells, methods and uses thereof - Google Patents

Abstract

The present disclosure relates to compositions, nucleic acid constructs, methods, and kits for the induction or reprogramming of cells to the dendritic cell state or the antigen-presenting cell state, based, in part, on the surprising effect described herein of the novel use and combinations of transcription factors that allow the induction or reprogramming of differentiated or undifferentiated cells into dendritic cells or antigen-presenting cells. Such compositions, nucleic acid constructs, methods, and kits can be used for the induction of dendritic cells in vitro, ex vivo, or in vivo, and these induced dendritic cells or antigen-presenting cells can be used in immunotherapy applications. (Automatic translation with Google Translate, no legal value)

Description

DESCRIPTION

Compositions for reprogramming cells into dendritic cells or antigen-presenting cells, methods and uses thereof

Technical field

The present disclosure relates to the development of methods for manufacturing dendritic cells or antigen-presenting cells capable of antigen presentation from differentiated, multipotent, or pluripotent stem cells by the introduction and expression of isolated transcription factors. More particularly, the disclosure provides methods for redirecting differentiated, multipotent, or pluripotent stem cells to a dendritic cell or antigen-presenting cell state by direct cellular reprogramming with surprising use of combinations of transcription factors.

Background

Cellular reprogramming relies on rewiring the epigenetic and transcriptional network from one cellular state to that of a different cell type. Transcription factor (TF) transduction experiments have highlighted the plasticity of adult somatic or differentiated cells, providing new technologies to generate any desired cell type. Through forced TF expression, it is possible to reprogram somatic or differentiated cells into induced pluripotent stem cells (iPSCs) that are remarkably similar to embryonic stem cells (1, 2). Alternatively, a somatic cell can also be converted into another specialized cell type (3). Direct lineage conversion has been shown to be successful in reprogramming mouse and human fibroblasts into various cell types, such as neurons, cardiomyocytes, and hepatocytes, using TFs that specify the identity of the target cell (4). Lineage conversions have also been demonstrated in the hematopoietic system, where forced TF expression induced a macrophage fate in B cells and fibroblasts (5) and direct reprogramming of mouse fibroblasts into clonogenic hematopoietic progenitors is achieved with Gata2, Gfilb, cFos and Etv6 (6). These four TFs induce a dynamic multistep hemogenic process that progresses through an endothelial-like intermediate, recapitulating developmental hematopoiesis in vitro (7). Other transcription factors have also been suggested to be important in dendritic cell function and development (Schlitzer et al., 2011, Yáñez and Goodridge, 2016, Laiosa et al., 2016, Onai et al., 2013). The prior art also describes the use of transcription factors as molecular complexes for use in the treatment of inflammatory diseases (International Publication Wo 2013/036829).

Reprogrammed cells are very promising therapeutic tools for regenerative medicine, and cells obtained by iPSC differentiation are already being tested in clinical studies. However, for hematopoietic regeneration, approaches to generate mature blood cells from iPSCs are still lacking. Although Laiosa et al. (2006) describe the reprogramming of committed T cell progenitors to macrophages and dendritic-like cells using the transcription factors C/EBP alpha and PU.1, it has not been possible to generate functional DCs, capable of inducing immune responses, from unrelated, distant cell types by cellular reprogramming. Therefore, alternative strategies are needed to generate patient-specific definitive hematopoietic cells that can be used as blood products. Given the opportunity for direct TF-mediated cellular reprogramming, the generation of antigen-presenting cells (APCs) of the immune system, such as dendritic cells (DCs), can be envisioned.

DCs are professional APCs capable of activating T cell responses by presenting peptide antigens complexed with the major histocompatibility complex (MHC) on their surface, along with all necessary soluble and membrane-associated costimulatory molecules. DCs induce primary immune responses, enhance the effector functions of previously primed T cells, and orchestrate the crosstalk between innate and adaptive immunity. DCs are found in most tissues, where they continuously sample the antigenic environment and use various types of receptors to monitor invading pathogens. In a steady state, and at an increased rate following pathogen detection, sentinel DCs in non-lymphoid tissues migrate to lymphoid organs where they present T cells with the antigens they have collected and processed. The phenotype acquired by the T cell depends on the context in which the DC presents its antigen. When the antigen is transmitted from a pathogen or from self-damage, DCs receive danger signals, are activated, and are stimulated to become effector T cells, which are necessary to provide protective immunity. DCs arise by differentiation from hematopoietic progenitors that progressively become more committed and diverge into a heterogeneous family of cells, including different subsets such as conventional DC type 1 (cDC1), type 2 (cDC2), and plasmacytoid DCs (pDC). These subsets differ in their phenotype, functional specialization, and TFs that regulate their specification. Several transcription factors have also been suggested to be important in DC function and development (Schlitzer et al., 2011; Yáñez and Goodridge, 2016; Onai et al., 2013). Schlitzer et al. (2011) describe that the CCR9(-) plasmacytoid DC (pDC) precursor population has the plasticity to acquire the phenotype and function of major histocompatibility complex class II (high) CD11 b(+) CD8a(-) conventional DC-like cells (cDC) under the influence of soluble factors produced by intestinal epithelial cells or recombinant GM-CSF. Furthermore, they show that this is regulated at the level of transcription factors, reflected in the downregulation of TCF4 (also known as E2-2) and the upregulation of ID2, PU.1 and BATF3. Yáñez and Gooridge (2016) link the involvement of the transcription factor IRF8 in the inhibition of neutrophils and the promotion of monocyte and dendritic cell differentiation from progenitors. Onai et al. (2013) refers to DC progenitors with prominent pDC differentiation potential, where said progenitors expressed high amounts of the transcription factor TCF4. The prior art also describes the use of transcription factors as molecular complexes for use in the treatment of inflammatory diseases (International Publication WO 2013/036829).

The ability of DCs to induce adaptive immunity has prompted research into DC vaccine strategies for bacterial, viral, and parasitic pathogens and for cancer immunotherapy. Indeed, clinical trials using DC-mediated immunotherapy are underway for several tumor types, including solid and hematological tumors (8). However, clinical results have not been consistent, probably associated with variable efficiency in DC generation in vitro: autologous monocytes give rise to less efficient DCs, and hematopoietic progenitors are isolated in very low numbers. Moreover, these precursor cells are typically compromised in cancer patients, resulting in the generation of dysfunctional DCs (8, 9). Cancer evasion mechanisms may also underlie the lack of consistent therapeutic advantages of DC-based immunotherapies. During tumor progression, cancer cells exploit various immune processes to escape immune surveillance. These adaptations, together with the heterogeneity of cancer antigens, prevent the immune system from recognizing tumor antigens and are therefore responsible for the reduced immunogenicity of tumor cells and current immunotherapies.

The generation of APCs by direct reprogramming opens new opportunities for a better understanding of DC specification and cellular identity, contributing to more efficient control of immune responses using autologous modified cells.

These facts are described in order to illustrate the technical problem addressed by the present description.

Summary

A first aspect of the present invention relates to a construct or vector comprising a combination of at least two polynucleotide sequences encoding at least two transcription factors selected from the group consisting of: BATF3, IRF8 and PU.1, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1.

A second aspect of the present invention relates to a composition comprising a combination of at least two isolated transcription factors encoded by a sequence at least 90% identical to a sequence from a list consisting of that selected from a list consisting of: BATF3 (SEQ. ID. 1, SEQ. ID. 2), IRF8 (SEQ. ID. 5, SEQ. ID. 6), PU.1 (SEQ. ID. 7, SEQ. ID. 8), TCF4 (SEQ. ID. 13, SEQ. ID. 14), and mixtures thereof, for use in medicine, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1.

A third aspect of the present invention relates to a composition comprising a combination of at least two isolated transcription factors encoded by a sequence at least 90% identical to a sequence from a list consisting of that selected from a list consisting of: BATF3 (SEQ. ID. 1, SEQ. ID. 2), IRF8 (SEQ. ID. 5, SEQ. ID. 6), PU.1 (SEQ. ID. 7, SEQ. ID. 8), TCF4 (SEQ. ID. 13, SEQ. ID. 14), and mixtures thereof, for use in the treatment of a disease selected from the group consisting of: cancer, neurodegenerative diseases and infectious diseases, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1.

A fourth aspect of the present invention relates to a method for reprogramming or inducing a cell into a dendritic cell or antigen-presenting cell, comprising the following steps:

(a) transducing a cell with one or more vectors comprising at least two polynucleotide sequences encoding at least two transcription factors selected from the group consisting of: BATF3, IRF8 and PU.1, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1; and

(b) culturing the transduced cell in a cell medium that favors the growth of dendritic cells or antigen-presenting cells.

A fifth aspect of the present invention relates to an induced antigen presenting cell or an induced dendritic cell as defined in the claims.

Overview

The invention is as defined in the claims. Any matter beyond the scope of the claims is provided for informational purposes only. The present subject matter identifies several isolated transcription factors that surprisingly reprogram or induce differentiated cells, multipotent or pluripotent stem cells, into dendritic cells, in vitro, ex vivo, or in vivo.

Surprisingly, induced dendritic cells generated by reprogramming as described herein are intrinsically more mature than splenic DCs (natural DCs) and are less dependent on exogenous activating stimuli for antigen presentation.

DCs are professional APCs found throughout the body that function at the interface of the innate and adaptive immune systems. DCs may provide a crucial link between the external environment and the adaptive immune system through their ability to capture, process, and present antigens to T cells, directing them toward different types of immune responses or toward tolerance. First, DCs must capture antigens and process them through major histocompatibility complex (MHC) class I and MHC class II antigens. After activation, DCs can migrate toward local draining lymph nodes, priming multiple B cell and T cell responses, a key feature of adaptive immunity. Early protective efficacy is conferred primarily by the induction of antigen-specific antibodies produced by B lymphocytes. Long-term protection against specific antigens requires the persistence of specific antibodies and the generation of immunological memory that can provide a rapid and efficient response after subsequent antigen exposure. DCs, as professional APCs, have the ability to cross-present antigens, meaning that in addition to their classic ability to present exogenous antigens on MHC class II and endogenous antigens on MHC class I, they can also present exogenous antigens on MHC class I, a critical step for the generation of cytotoxic T lymphocyte (CTL) responses.

The ontogeny and/or microenvironment in which DCs are positioned can result in the expression of distinct combinations of surface receptors by DCs. For example, phenotypic criteria alone allow mouse DC cells to be classified into different subpopulations. Of these, conventional DCs (cDCs) in lymphoid tissues are traditionally subdivided into cDC1 and cDC2 subpopulations. It has been argued that different DC subsets may be involved in the specific recognition of certain pathogens and/or regulate different immune responses, e.g., Th1 or Th2 (immunity) or regulatory T cells (tolerance). However, the phenotype and functional behavior of DCs are also significantly conditioned by external activating stimuli, indicating significant plasticity. cDC1 and cDC2 subsets differentially prime Th1 and Th2 responses in vivo. Immune therapy for cancer relies on the use of DCs to prime cytotoxic T cell or Th1 responses to promote tumor elimination.

Currently, DC-based immunotherapies rely on autologous DC precursors: either monocytes, which are associated with less efficient DC production, or hematopoietic progenitors, which are isolated in very low numbers. Moreover, these precursor cells are typically compromised in cancer patients, resulting in the generation of dysfunctional DCs. In contrast, non-hematopoietic cell types, such as fibroblasts, are typically unaffected. Human dermal fibroblasts (HDFs) also have other competitive advantages: they are easily obtained from a small skin punch biopsy, readily expanded in vitro for multiple passages (15–20 million cells after 4 weeks), and can be stored frozen and used on demand. Given the pivotal role of DCs as APCs functioning at the interface of the innate and adaptive immune systems, there remains a clinical need to find alternative strategies to generate functional DCs to prime antigen-specific immune responses.

One aspect of the present disclosure relates to a construct or vector comprising the combination of at least two polynucleotide sequences encoding at least two transcription factors selected from the group consisting of: BATF3, IRF8 and PU.1, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1.

In some embodiments, variant polypeptides or family members having the same or similar activity as the reference polypeptide encoded by the sequences provided in the sequence listing can be used in the compositions, methods, and kits described herein. Generally, variants of a particular polypeptide encoding a DC-inducing factor for use in the compositions, methods, and kits described herein will have at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99% or more sequence identity to that particular reference polynucleotide or polypeptide as determined by the sequence alignment programs and parameters described herein and known to those of skill in the art.

Methods for sequence alignment for comparison are well known in the art, such methods include GAP, BESTFIT, BLAST, FASTA, and TFASt A. GAP uses the algorithm of Needleman and Wunsch ((1970)J Mol Biol48:443-453) to find the global (across the entire sequence) alignment of two sequences that maximizes the number of matches and minimizes the number of gaps. The BLAST algorithm (Altschul et al. (1990)J Mol Biol215:403-10) calculates the percentage sequence identity and performs a statistical analysis of the similarity between the two sequences. Software for performing BLAST analysis is publicly available through the National Center for Biotechnology Information (NCBI). Overall similarity and identity percentages can also be determined using one of the methods available in the MatGAT software package (Campanella et al., BMC Bioinformatics. 2003 Jul 10; 4:29. MatGAT: An application that generates similarity/identity matrices using protein or DNA sequences). Minor manual editing can be performed to optimize alignment between conserved motifs, as would be apparent to one of skill in the art. Sequence identity values, reported herein as a percentage, were determined for the entire amino acid sequence using BLAST with default parameters.

In one embodiment to obtain better results, the construct or vector may be the combination of three transcription factors isolated in the following sequential order from 5' to 3': PU.1 (SEQ. ID. 7, SEQ. ID.

8), IRF8 (SEQ. ID. 5, SEQ. ID. 6), BATF3 (SEQ. ID. 1, SEQ. ID. 2); or IRF8 (SEQ. ID. 5, SEQ. ID. 6), PU.1 (SEQ. ID. 7, SEQ. ID. 8), BATF3 (SEQ. ID. 1, SEQ. ID. 2).

In one embodiment, the vector is a viral vector; in particular a retrovirus, an adenovirus, a lentivirus, a herpes virus, a smallpox virus, or adeno-associated virus vectors.

In one embodiment, to obtain better results, the transduction step further comprises at least one vector selected from a list consisting of: a nucleic acid sequence encoding IL-12; a nucleic acid sequence encoding GM-CSF; a nucleic acid sequence encoding IL-7; a nucleic acid sequence encoding siRNA targeting IL-10 RNA, and mixtures thereof.

In one embodiment, to obtain better results, the transduction step further comprises at least one vector comprising nucleic acids encoding immunostimulatory cytokines.

Another aspect of the present description relates to a method for programming or inducing a cell into a dendritic cell or antigen-presenting cell, comprising the following steps:

(a) transducing a cell with one or more vectors comprising at least two polynucleotide sequences encoding at least two transcription factors selected from the group consisting of: BATF3, IRF8 and PU.1, wherein the at least two encoded sequences are BATF3 and PU.1 or IRF8 and PU.1; and

(b) culturing the transduced cell in a cell medium that favors the growth of dendritic cells or antigen-presenting cells.

In one embodiment, the combination of isolated transcription factors is selected from the following encoded combinations: BATF3 and PU.1; or IRF8 and PU.1; or BATF3, IRF8, and PU.1.

In one embodiment, for best results, the construct or vector may be a combination of at least two transcription factors isolated in the following sequential order from 5' to 3': PU.1, IRF8, BATF3; or IRF8, PU.1, BATF3.

In one embodiment, to obtain better results, the transduction step may further comprise at least one vector comprising nucleic acids encoding immunostimulatory cytokines and/or siRNA targeting IL-10. Other immunostimulatory cytokines include, for example, a nucleic acid sequence encoding IL-12; a nucleic acid sequence encoding M-CSF; a nucleic acid sequence encoding IL-7; a nucleic acid sequence encoding siRNA targeting IL-10 RNA, and mixtures thereof.

In one embodiment, for improved results, the cell may be selected from the group consisting of a pluripotent stem cell, a multipotent stem cell, a differentiated cell, and mixtures thereof. In particular, an endoderm-derived cell, a mesoderm-derived cell, or an ectoderm-derived cell, a multipotent stem cell, including a mesenchymal stem cell, a hematopoietic stem cell, an intestinal stem cell, a pluripotent stem cell, a tumor or cancer cell, and cell lines.

In one embodiment for best results, the cell may be a non-human cell, preferably a mouse or human cell, more preferably the cell is a human or mouse fibroblast, or a mammalian umbilical cord blood stem cell.

Another aspect of the present description relates to a dendritic cell or induced antigen-presenting cell obtained by the method described in the present description.

Another aspect of the present disclosure relates to an induced antigen-presenting cell obtained by the method described herein. In particular, an induced antigen-presenting cell capable of presenting a cancer antigen, an autoantigen, an allergen, or an antigen from a pathogenic and/or infectious organism.

Another aspect of the present disclosure relates to a composition comprising a combination of at least two isolated transcription factors encoded by a sequence at least 90% identical to a sequence from a list consisting of that selected from a list consisting of: BATF3 (SEQ. ID. 1, SEQ. ID. 2), IRF8 (SEQ. ID. 5, SEQ. ID. 6), PU.1 (SEQ. ID. 7, SEQ. ID. 8), TCF4 (SEQ. ID. 13, SEQ. ID. 14), and mixtures thereof, for use in medicine, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1.

In a preferred embodiment, the composition may be used in veterinary or human medicine, in particular in the treatment or therapy of neurodegenerative diseases, or in the treatment or therapy of cancer or in the treatment or therapy of an infectious disease, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1.

In a preferred embodiment, the composition may be used in the treatment, diagnosis or therapy of benign tumor, malignant tumor, early cancer, basal cell carcinoma, cervical dysplasia, soft tissue sarcoma, germ cell tumor, retinoblastoma, Hodgkin's lymphoma, blood cancer, prostate cancer, ovarian cancer, cervical cancer, uterine cancer, vaginal cancer, breast cancer, nasopharyngeal cancer, tracheal cancer, laryngeal cancer, bronchial cancer, bronchiole cancer, lung cancer, hollow organ cancer, esophageal cancer, stomach cancer, bile duct cancer, bowel cancer, colon cancer, colorectal cancer, rectal cancer, bladder cancer, ureter cancer, kidney cancer, liver cancer, gallbladder cancer, spleen cancer, brain cancer, cancer of the lymphatic system, bone cancer, pancreatic cancer, leukemia, skin cancer or myeloma.

The compositions and methods for inducing dendritic cells or for reprogramming cells to dendritic cells of the present disclosure are based on the use of a novel combination of transcription factors that allow direct reprogramming of differentiated cells to the dendritic cell state. Such compositions, nucleic acid constructs, and methods can be used to induce dendritic cells in vitro, ex vivo, or in vivo, as described herein, and these induced dendritic cells can be used in immunotherapies.

Immune responses stimulated by iDCs involve the proliferation of T cells, which can be CTLs or helper T cells. Antigen-presenting cells (and iDCs in particular) can induce the proliferation of both CD8+ T cells and CD4+ T cells, and can stimulate the proliferation of both types of T cells in any given immune response.

iDCs can be involved in at least Th1, Th2, and Th17 type immune responses. Therefore, the methods of the disclosure can be applied to the stimulation of various types of immune responses against any antigen. However, these cells are believed to be particularly important in generating CTL responses, so the immune response to be stimulated is preferably a CTL response. The method may comprise determining the production and/or proliferation of CTLs, which are typically CD8-expressing T cells capable of cytotoxic activity against cells presenting their cognate antigen in the context of MHC class I molecules.

Therefore, it will be further understood that iDCs may be used for the prophylaxis and/or treatment of any condition in which it is desirable to induce a CTL response, such as cancer, or infection by an intracellular parasite or pathogen, such as a viral infection.

However, if modified, iDCs can lead to the proliferation of helper T cells as well as, or instead of, CTLs.

It is believed that, under certain conditions, iDCs may be able to stimulate the proliferation of regulatory T cells (Tregs). Treg cells are characterized by the expression of the transcription factor Foxp3 (Forkhead box p3). The majority of Treg cells are CD4+ and CD25+, and can be considered a subset of helper T cells, although a small population may be CD8+. Therefore, the immune response to be stimulated by a method of the present disclosure may comprise inducing the proliferation of Treg cells in response to an antigen. Because Treg cells may be able to modulate the response of other cells of the immune system against an antigen in other ways, e.g., by inhibiting or suppressing their activity, the effect on the immune system as a whole may be to modulate (e.g., suppress or inhibit) the response against that antigen. Therefore, the methods of this aspect of the description may also be referred to as methods of modulating (e.g., inhibiting or suppressing) an immune response against an antigen. This may be particularly useful (for example) in the treatment of autoimmune diseases.

iDCs promote antigen-specific responses. The antigen can be any protein or fragment thereof against which it is desirable to produce an immune response, particularly a CTL response, but also a Th17 response or a Treg response. These can include antigens associated with, expressed by, presented on, or secreted by cells against which it is desirable to stimulate a CTL response, including cancer cells and cells containing intracellular pathogens or parasites. For example, the antigen can be, or may comprise, an epitope peptide from a protein expressed by an intracellular pathogen or parasite (such as a viral protein) or from a protein expressed by a cancer or tumor cell. Therefore, the antigen can be a tumor-specific antigen. The term "tumor-specific antigen" should not be construed as being restricted to solid tumor antigens, but should encompass antigens specifically expressed by any cancerous, transformed, or malignant cell.

Thus, the invention provides a primed antigen-presenting cell or population thereof. By "primed" is meant that the cell has come into contact with an antigen, presents that antigen or an epitope thereof in the context of MHC molecules, preferably MHC I molecules, and is capable of activating or stimulating T cells to proliferate and differentiate into effector cells in response.

The term "antigen" is well understood in the art and includes immunogenic substances as well as antigenic epitopes. It will be appreciated that any antigen is envisioned for use in the present disclosure and thus includes, but is not limited to, an autoantigen (whether normal or disease-related), an infectious antigen (e.g., a microbial antigen, viral antigen, etc.), or some other foreign antigen (e.g., a food component, pollen, etc.). Loading antigen-presenting cells with an antigen can be accomplished using conventional methods, e.g., pulsing, transduction, transfection, and/or electrofusion. It is envisioned that the antigen may be nucleic acids (DNA or RNA), proteins, protein lysate, whole cell lysate, or antigenic proteins bound to other proteins, i.e., heat shock proteins. Antigens may be derived or isolated from a pathogenic microorganism such as viruses including HIV, influenza virus, herpes simplex, human papillomavirus, hepatitis B, hepatitis C, EBV, cytomegalovirus (CMV), and the like. The antigen may be derived or isolated from pathogenic bacteria such as Chlamydia, Mycobacteria, Legionella, Meningiococcus, Group A Streptococcus, Salmonella, Listeria, Haemophilus influenzae, and the like. In addition, the antigen may be derived or isolated from pathogenic yeasts, including Aspergillus, invasive Candida, Nocardia, Histoplasmosis, Cryptosporidia, and the like. The antigen may be derived or isolated from pathogenic protozoa and pathogenic parasites, including, but not limited to, Pneumocystis carinii, Trypanosoma, Leishmania, Plasmodium, and Toxoplasma gondii. In certain embodiments, the antigen includes an antigen associated with a preneoplastic or hyperplastic state. Antigens may also be associated with or cause cancer. Such antigens include tumor-specific antigen, tumor-associated antigen (TAA), or tissue-specific antigen, epitope thereof, and agonist of epitope thereof. Such antigens include, but are not limited to, carcinoembryonic antigen (CEA) and epitopes thereof, such as CAP-1, CAP-1-6D, MART-1, MAGE-1, MAGE-3, GAGE, GP-100, MUC-1, MUC-2, point mutated ras oncogene, normal and point mutated p53 oncogenes, PSMA, tyrosinase, TRP-1 (gp75), NY-ESO-1, TRP-2, TAG72, KSA, CA-125, PSA, HER-2/neu/c-erb/B2, BRC-I, BRC-II, bcr-abl, pax3-fkhr, ews-fli-1, TAA modifications and tissue specific antigen, TAA splice variants, epitope agonists, and the like.

The term "agent" as used herein means any compound or substance such as, but not limited to, a small molecule, nucleic acid, polypeptide, peptide, drug, ion, etc. An "agent" can be any chemical substance, entity, or moiety, including without limitation synthetic and naturally occurring proteinaceous and non-proteinaceous entities. In some embodiments, an agent is nucleic acid, nucleic acid analogs, proteins, antibodies, peptides, aptamers, nucleic acid oligomers, amino acids, or carbohydrates, including without limitation proteins, oligonucleotides, ribozymes, DNAzymes, glycoproteins, siRNA, lipoproteins, aptamers, and modifications and combinations thereof, etc. In some embodiments, the nucleic acid is DNA or RNA, and nucleic acid analogs, for example, can be PNAs, pcPNAs, and LNAs. A nucleic acid may be single-stranded or double-stranded, and may be selected from a group comprising: nucleic acid encoding a protein of interest, oligonucleotides, PNAs, etc. Such nucleic acid sequences include, for example, but are not limited to, nucleic acid sequences encoding proteins that act as transcriptional repressors, antisense molecules, ribozymes, small inhibitory nucleic acid sequences, for example, but not limited to, RNAi, shRNAi, siRNA, micro RNAi (mRNAi), antisense oligonucleotides, etc. A protein and/or peptide agent or fragment thereof, may be any protein of interest, for example, but not limited to; mutated proteins; therapeutic proteins; truncated proteins, wherein the protein is normally absent or expressed at lower levels in the cell. The proteins of interest can be selected from a group comprising: mutated proteins, genetically modified proteins, peptides, synthetic peptides, recombinant proteins, chimeric proteins, antibodies, humanized proteins, humanized antibodies, chimeric antibodies, modified proteins and fragments thereof.

As used herein, the term "transcription factor" or "TF" refers to a protein that binds to specific parts of DNA using DNA-binding domains and is part of the system that controls the transcription of genetic information from DNA to RNA.

The term "DC-inducing factor," as used herein, refers to a factor that alters developmental potential, as that term is defined herein, such as a protein, RNA, or small molecule, the expression of which contributes to the reprogramming of a cell, e.g., a somatic cell, to the DC state. A DC-inducing factor can be, for example, transcription factors that can reprogram cells to the DC state, such as PU.1, IRF8, BATF3, and TCF4, and the like, including any gene, protein, RNA, or small molecule that can substitute for one or more of these factors in a method of making iDCs in vitro. In some embodiments, exogenous expression of a DC-inducing factor induces endogenous expression of one or more DC-inducing factors, such that exogenous expression of the one or more DC-inducing factors is no longer necessary for stable maintenance of the cell in the iDC state.

The term "antigen-presenting cell" (APC), as used herein, refers to a cell that presents antigen complexed with major histocompatibility complexes (MHC) on its surface; this process is known as antigen presentation. T cells can recognize these complexes using their T cell receptors (TCRs). These cells process antigens and present them to T cells.

The term "somatic cell" as used herein refers to any biological cell that forms the body of an organism; that is, in a multicellular organism, any cell that is not a gamete, germ cell, gametocyte, or undifferentiated stem cell.

The expression of endogenous DC-inducing factors can be induced by the use of DNA targeting systems capable of modulating the expression of mammalian genes in a cell with or without the use of chromatin-modifying drugs. The DNA targeting system can comprise a clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9-based system (as described in international publication WO 2014/197748 A2) that can include any modified protein, isolated polynucleotide, or vector contacted with the cell and at least one guide RNA targeted to a promoter region of at least one gene selected from the group consisting of PU.1, IRF8, and BATF3. The DNA targeting system can comprise dCas9-VP64. In some embodiments, the DNA targeting system may comprise two or more transcription activator-like effector transcription factors (as described in US 2014/0309177 A1) that bind to different target regions of at least one gene selected from the group consisting of PU.1, iRf 8 and BATF3.

The pluripotent stem cells used in the present invention are obtained without resorting to a method that necessarily involves the destruction of human embryos, specifically through the use of induced pluripotent stem cells. Induced pluripotent stem cells (also known as iPS cells or iPSCs) are a type of pluripotent stem cell that can be generated directly from adult cells through cellular reprogramming.

Induced dendritic cells (iDC) obtainable by this method express MHC-I and II on the cell surface and the costimulatory molecules CD80, CD86 and CD40.

The DC-inducing factors of the present disclosure may be administered to induce reprogramming in vitro, ex vivo, or in vivo.

The differentiated cells of the present invention can be isolated from a subject in need thereof, and DC-inducing factors can be introduced to induce reprogramming into iDCs. The generated iDCs can then be infused back into the patient.

Alternatively, DC-inducing factors can be administered to induce in vivo reprogramming of, for example, cancer cells into iDCs capable of presenting cancer antigens.

Preferred routes of administration include, but are not limited to, oral, parenteral, intramuscular, intravenous, in situ injection, intranasal, sublingual, intratracheal, and inhalation.

The use of polycistronic viral expression systems can increase the efficiency of in vivo reprogramming of somatic cells to iDCs. Accordingly, in some embodiments of the aspects described herein, a polycistronic lentiviral vector is used. In such embodiments, sequences encoding two or more of the DC-inducing factors described herein are expressed from a single promoter, as a polycistronic transcript. A 2A peptide strategy can be used to create polycistronic vectors (see, e.g., Expert Opin Biol Ther. 2005 May;5(5):627-38). Polycistronic expression vector systems can also utilize internal ribosome entry site (IRES) elements to create multigene or polycistronic messages. IRES elements can bypass the ribosome scanning model of 5'-methylated Cap-dependent translation and initiate translation at internal sites (Pelletier and Sonenberg, 1988). IRES elements can bind to heterologous open reading frames. Multiple open reading frames, each separated by an IRES, can be co-transcribed, thus creating polycistronic messages. By virtue of the IRES element, each open reading frame is accessible to ribosomes for efficient translation. Multiple genes can be efficiently expressed using a single promoter/enhancer to transcribe a single message. See, e.g., U.S. Patent Nos. 4,980,285; 5,925,565; 5,631,150; 5,707,828; 5,759,828; 5,888,783; 5,919,670; and 5,935,819; and Sambrook et al., Molecular Cloning: A Laboratory Manual, 2nd Ed., Cold Spring Harbor Press (1989).

Brief description of the drawings

The following figures provide illustrations of the description.

Figure 1. Schematic representation of hematopoietic differentiation. Whereas hematopoietic differentiation normally proceeds from hematopoietic stem cells (HSCs) through progressively more restricted progenitors into differentiated blood-borne effector cells such as dendritic cells (DCs) (highlighted with a dashed box), the results described here aim to use DC-enriched transcription factors to reprogram differentiated somatic cells of other lineages into antigen-presenting dendritic cell fates. Multipotent progenitor cells (MPP), common myeloid progenitor cells (CMP), common lymphoid progenitor cells (CLP), granulocyte-monocyte progenitor cells (GMP), premegakaryocyte-erythrocyte progenitor cell (pre-MEG/E), megakaryocyte-erythrocyte progenitor cells (MEP), colony-forming unit erythroid (CFU-E), megakaryocytic progenitor MkP, promast cells (ProMC), monocytic DC progenitors (MDP), common dendritic cell precursors (CDP), predendritic cell (pre-DC), double-negative T-lineage precursors (DN1, DN2).

Figure 2. Generation of antigen-presenting cells by direct cellular reprogramming. Observation of the effect of the TF combination described herein for the induction of dendritic cells (iDCs) from mouse and human fibroblasts. The induced DCs can be applied to generate personalized immunotherapy after loading them with defined cell extracts or antigens (iDC-primed). DCs are specialized in presenting antigens to macrophages (M0), T, B, and NK cells. The induced DCs stimulate antigen-specific immune responses against cancer, viral, parasitic, or bacterial infections.

Figure 3. Direct in situ or ex vivo reprogramming of cancer cells to stimulate antigen-specific immune responses. Effect of TF (GDP) cocktail on DC fate induction and antigen-presenting capacity, when this cocktail is directly introduced into cancer cells in vivo or in situ, ex vivo or in vitro. This strategy allows tumor cells to present their specific antigens (tumor-APCs) to CD4+ and CD8+ T cells, triggering a tumor-directed immune response.

Figure 4. 18 candidate TFs for direct DC reprogramming. (A) Heatmap showing gene expression of the 18 candidate factors in multiple mouse tissues (MOE430 Gene Atlas). The majority of the 18 factors are specifically enriched in DCs (black box), but not in other tissues (right). (B) Heatmaps showing higher gene expression of the 18 factors in mouse DCs compared to bone marrow-derived macrophages (M9) (left panel, GSE62361). Heatmaps showing gene expression of the 18 TFs in common dendritic cell precursors (CDPs), pre-conventional DCs (Pre-cDC1 and Pre-cDC2), and conventional DCs (cDC1 and cDC2) (right panel, GSE66565). Gene expression data were analyzed using Cluster 3.0 and presented using Treeview. Red indicates higher expression, while blue indicates lower expression relative to the mean. (C) Gene Ontology biological process enrichment analysis (left) and mouse loss-of-function mutant phenotype (right) were performed for the 18 candidate TFs using Enrichr (http://amp.pharm.mssm.edu/Enrichr/). The lists show the most enriched terms (top 19) and the left columns show the respective p-values. The top enriched biological processes are leukocyte differentiation (p=2.51E-12), leukocyte activation (p=1.02E-11), DC differentiation (p=9.58E-12), and DC activation (p=6.31E-11), while mutant phenotypes include abnormal adaptive immunity (p=1.19E-04) and abnormal antigen presentation (p=1.25E-03).

Figure 5. Clec9a expression is specifically restricted to the conventional DC lineage. (A) The Clec9a-Cre X R26-stop-Tomato double transgenic mouse allows the identification of conventional DCs and their committed precursors (CDPs, common dendritic cell precursors), but not other leukocytes, due to restricted expression of tdTomato. (B) Clec9a expression profile in DCs and various hematopoietic cell lineages obtained from data available at the Immune Genome Project (www.immgen.org). (C) Gene expression of the Clec9a gene in monocytic DC progenitors (MDPs) and DC-committed precursors (CDPs and pre-DCs) at the single-cell level (GSE60783).

Figure 6. Clec9a is highly expressed in mature cDC1. (A) Clec9a gene expression in DC precursors (cDC, pre-DC1, and pre-DC2) and mature cells (cDC1 and cDC2) (GSE60782). (B) Confirmation of Clec9atdTomato in splenic cDC1 (MHC-II+ CD11c+ CD8+ cells) isolated from double-transgenic C9a-tdT animals. CD8+ T cells not expressing Clec9a were included as a control.

Figure 7. Isolation and purification of MEFs with Clec9a reporters to screen candidate TFs. (A) Double-transgenic pregnant females (Clec9a-Cre X R26-stop-Tomato) were used to isolate MEFs at embryonic day E13.5. After removal of the head, fetal liver, and internal organs, MEFs were cultured to confluence. MEFs were sorted to remove residual CD45+ and tdTomato+ cells that could represent cells with hematopoietic potential. (B) Gating strategy to remove residual CD45+ and tdTomato+ cells. Double-negative MEFs, approximately 97% of the population, were sorted. (C) Confirmation of the purity of the sorted population.

Figure 8. Experimental design to screen the ability of candidate TFs to activate MEFs with Clec9a reporters. Purified MEFs were transduced with different pools of inducible lentiviral vectors encoding DC-specific TFs. MEFs were cultured in the presence of Dox to induce TF expression, and tdTomato expression was monitored from day 1 to 15. Activation of the Clec9a promoter induces the expression of Cre recombinase, which mediates stop codon cleavage and subsequent tdTomato expression.

Figure 9. Candidate DC-inducing TF combinations induce Clec9atdTomato reporter activation. (A) MEFs were transduced with M2rtTA (as control), all 18 candidate TFs, and pools of 3–4 TFs and analyzed by fluorescent microscopy and flow cytometry 5 days after Dox addition. (B) Quantification of tdT+ cells after transduction with M2rtTA, the 18 TFs, or smaller pools on day 8. Mean ± SD, n = 2. (C) Quantification of tdT+ cells after knockdown of individual TFs from the 4-TF pool or their individual expression on day 8. Mean ± SD, n = 2.

Figure 10. The minimal transcription factor network activates the Clec9a reporter and induces DC morphology in mouse fibroblasts. (A) MEFs were transduced with M2rtTA (as control) or PU.1, IRF8, and BATF3 (PIB – mixture of all 3 TFs) and analyzed by fluorescent microscopy and flow cytometry 5 days after Dox addition. (B) Kinetics of Clec9a-tdTomato reporter activation analyzed by flow cytometry. (C) Quantification of tdTomato+ cells after knockdown of individual TFs from the PIB pool or their individual expression at day 5 after Dox addition. (D) Flow cytometry histograms showing size (FSC) and complexity (SSC) in PIB-transduced cells (gated in the tdTomato+ or total population) and M2rtTA-transduced cells. (E) Morphology of tdTomato+ cells at day 5 after Dox addition. (F) Immunofluorescence for F-actin at day 8 after Dox addition.

Figure 11. Kinetics of Clec9a reporter activation analyzed by time-lapse microscopy from day 0 to day 7. Scale bars represent 200 µm.

Figure 12. The minimal transcription factor network induces expression of the pan-hematopoietic marker CD45. Flow cytometry analysis on day 8 for CD45 and tdTomato expression in PIB-transduced MEFs.

Figure 13. TCF4 increases the efficiency of Clec9a reporter activation. (A) MEFs were transduced with PU.1, IRF8 and BATF3, PIB (black bar), or PIB combined with individual TFs from the 18 candidates (gray bars). tdTomato+ cells were quantified at day 8. M2rtTA transduction was included as a control. Mean ± SD, n = 2–6. (B) MEFs were transduced with PIB (black bar) or PIB combined with individual hematopoietic TFs (gray bars). tdTomato+ cells were quantified at day 8. Mean ± SD, n = 2–6.

Figure 14. Optimal culture conditions for inducing Clec9a reporter activation. (A) Quantification of tdTomato+ cells in PIB-transduced MEFs (PU.1, IRF8, and BATF3) cultured under different conditions at day 10 after Dox addition. (B) Absolute number of tdTomato+ cells in PIB-transduced MEFs (black bar) co-cultured with OP9 and OP9-DL1 cells at day 10 after Dox addition. OP9 and OP9-DL1 cultures were included as controls.

Figure 15. Single-cell expression profiles of PU.1, IRF8, BATF3, and TCF4. Gene expression of PU.1, IRF8, BATF3, and TCF4 in single monocytic dendritic cell precursors (MDPs) and restricted DC precursor cells (CDPs and pre-DCs) (GSE60783). Gene expression levels are shown in reads per kilobase of the exon model per million mapped reads (RPKM).

Figure 16. Expression analysis of PU.1, IRF8, and BATF3 in mouse cells/tissues. (A) Combined gene expression levels of Pu.1, Ir8, and Batf3 in 96 tissues and cell types. Gene expression data for different mouse tissues and cell types were obtained from the MOE430 Gene Atlas database. The program “GPSforGenes” was written and used to classify tissues where TF combinations were most enriched (best fit = 1). (B) Gene expression of Pu.1, Irf8, and Batf3 in DC precursors (cDCs, pre-DC1, and pre-DC2) and mature cells (cDC1 and cDC2) (GSE60782). The gene expression level is shown as relative gene expression. (C) Heat map showing the higher expression of Clec9a, PU.1, IRF8, and BATF3 in CD103+ DCs (highlighted in red) belonging to the cDC1 subset compared to other DC subsets and various hematopoietic cell lineages available at the Immune Genome Project (www.immgen.org). Gene expression data were analyzed using Cluster 3.0 and presented using Treeview. Red indicates higher expression, while blue indicates lower expression relative to the mean.

Figure 17. Induced DCs express cDC1 markers on the cell surface. (A) Flow cytometry analysis of the surface phenotype of PIB-transduced MEFs 8 days after Dox addition. Quantification of CD103, CD8a, CD4, C11b, and B220 expression in tdT+ and tdT- populations. (B) Representative flow cytometry graphs.

Figure 18. Induced DCs express antigen-presenting machinery on the cell surface. (A) Flow cytometry analysis of MHC-II expression in MEFs transduced with M2rtTA (as control) and PIB (PU.1, IRF8, and BATF3) 7 days after Dox addition. TdTomato+ and tdTomato- populations are shown. (B) Kinetics of MHC-II surface expression in cells transduced with M2rtTA and PIB. MEFs were analyzed by flow cytometry from days 1 to 15 after Dox addition. (C) Quantification of the percentage of cells expressing MHC-II at high and low levels in bulk cultures after knockdown of individual TFs from the PIB group, on day 5 after Dox addition. (D) Quantification of MHC-II+ cells on day 5 within the tdTomato+ population after transduction with 4TF or after its individual deletion.

Figure 19. Induced DCs express MHC-I on the cell surface. Flow cytometry analysis of MHC-I expression in MEFs transduced with M2rtTA and PIB at day 7 after Dox addition.

Figure 20. Induced DCs express costimulatory molecules on the cell surface. Flow cytometric analysis of costimulatory molecules (CD80 and CD86) on the cell surface of the tdTomato+ population in PIB-transduced MEFs (PU.1, IRF8, and BATF3) 5 days after Dox addition. The MHC-II+ and MHC-II- populations are shown.

Figure 21. Induced DCs upregulate CD40 expression following LPS stimulation. (A) Flow cytometry analysis of CD40 expression in the tdTomato- and tdTomato+ populations in PIB-transduced MEFs at day 8. (B) Histograms show CD40 expression with or without overnight LPS stimulation at day 13.

Figure 22. PIB factors induce the global dendritic cell gene expression program in fibroblasts. (A) Clec9a reporter MEFs were transduced with Pu.1 (P), Irf8 (I), and Batf3 (B) to generate iDCs. Transduced cells were sorted by FACS and sampled using full-length single-cell RNA-seq using the Fluidigm C1 system, on day 3 (d3, 20 Clec9a-tdTomato+ cells), day 7 (d7, 40 Clec9a-tdTomato+ cells), and day 9 (d9, 36 Clec9a-tdTomato+ MHC-II+ cells). Non-transduced MEFs on day 0 (30 cells) and splenic DC cells (sDCs, 66 CD11c+ MHC-II+ CD8a+ cells) isolated from C57BI/6 animals were used as controls. (B) t-distributed stochastic linear insertion (tSNE) analysis of genome-wide transcriptomes showing the clustering of 163 individual cells. Each point represents an individual cell. The number of cells in each sample group is shown in parentheses. (C) Full hierarchical clustering^union of the consensus matrix obtained using the SC3 clustering algorithm. (D) Heatmap showing the expression of the 6525 most variable genes across the 5 different biological sample groups (columns, MEF, d3, d7, d9, and sDC). Four gene groups are shown: Group I (3014 genes), II (530 genes), III (347 genes), and IV (2634 genes). The color scheme is based on the z-score distribution, from -2 (blue) to 2 (red). Examples of genes from each group are shown (right panel). (E) Fibroblast gene expression levels are shown as median Census counts ± 95% confidence interval. (F) Gene expression levels in cluster II (Eea1, Aldh1a2, Ifit3), cluster III (H2-Pb, Ctsc, Cd74), and cluster IV (Clec9a, Cd45, Cd11c, Tlr3, Ccr2, Nlrc5), presented as violin plots (height, gene expression; width, abundance of cells expressing the gene). Log Census counts are shown, horizontal lines correspond to median values.

Figure 23. PIB factors induce the expression of DC transcriptional regulators, including endogenous Pu.1, Irf8, and Batf3. (A) Violin plots showing the expression levels of the DC transcriptional regulators Zbtb46, Bcl11a, Stat2, Irf7, Stat6, and Statl. (B) Expression levels of the genes Pu.1, Irf8, and Batf3 are shown as log counts presented as a box-and-whisker plot extending to ±1.5 x interquartile range. Total (left panel) and endogenous (right panel) transcript levels are shown.

Figure 24. Pathway enrichment for stepwise transitions during iDC reprogramming. (A) Gene set enrichment analysis (GSEA) was performed for stepwise iDC reprogramming using annotated gene sets of signaling pathways from NetPath. Day 3 refers to pathways upregulated on day 3 versus MEF, day 7 refers to pathways upregulated on day 7 versus day 3, and day 9 refers to pathways upregulated on day 9 versus day 7. Data sets were sorted according to the normalized enrichment score (NES), and the false discovery rate (FDR) q-value is shown. The bottom panel shows the enrichment plots for the IL-4 (day 3) and Oncostatin M (day 9) gene sets.

Figure 25. Transcriptional networks for stepwise transitions during iDC reprogramming. (A) Covariance networks of transcription factors during iDC reprogramming for each stepwise transition. Transcriptional regulators with more than five edges are shown, with each edge reflecting a correlation >0.35 between connected transcriptional regulators. Transcription factors PU.1, IRF8, and BATF3 are highlighted in red. (B) Heatmaps showing the expression of the transcriptional regulators shown in panel A in DC precursors (DC1s and pre-DC1s) and mature cells (cDC1s) from bone marrow (GSE60782). Gene expression data were analyzed using Cluster 3.0 and presented using Treeview. Red indicates higher expression, while blue indicates lower expression relative to the mean. (C) Hematopoietic colony formation was analyzed in PIB-transduced MEFs on days 3, 5, 7, 10, and 25 after Dox addition (mean ± SD, n = 2). Sorted sDC1 and unsorted splenocytes and bone marrow cells were included as controls.

Figure 26. PIB factors induce transcriptional reprogramming toward the cDC1 expression program. Expression signatures of cDC1 and cDC2 genes were generated by analyzing the datasets of Schlitzer et al. (11) (GSE60783). Cumulative median expression levels of cDC1 and cDC2 gene signatures during reprogramming.

Figure 27. Reconstruction of the reprogramming trajectory of a single cell. (A) Genome-wide transcriptomes of single cells were sorted using TSCAN software (Pseudotime). The sorting of untransduced MEFs, Clec9a-tdTomato+ induced DCs (iDCs) on day 3 (d3), day 7 (d7), Clec9a-tdTomato+ MHC-II+ day 9 (d9), and splenic DCs (sDCs, CD11c+ MHC-II+ CD8a+) is shown. Each point represents an individual cell. (B) Cell expression profiles in two-dimensional independent component space according to the predicted trajectory. The solid black line shows the pseudotime sorting constructed by Monocle2. Each point represents an individual cell, colored according to biological sample groups (left panel) or cell state (right panel). The number of cells in each sample group assigned to each cell state is shown in parentheses.

Figure 28. Reconstruction of the reprogramming trajectory of a single cell highlights different iDC maturation states. (A) Five branch-dependent gene kinetic clusters identified by BEAM. (B) Gene set enrichment analysis (GSEA) was performed between cell state 2 and cell state 3 using gene sets present in the immunosignature collection (4872 gene sets, FDR < 0.02 or maximum of 200 genes per gene set). Gene sets were sorted by the normalized enrichment score (NES), and the false discovery rate (FDR) q-value is shown. Black lines represent DC gene sets. The right panel shows enrichment plots for gene sets of mature stimulatory DCs, IFNγ-stimulated DCs, and IFNα-stimulated DCs (all enriched in state 3).

Figure 29. PIB factors induce high levels of expression of genes associated with DC maturation. (A) GSEA for day 9 iDC and sDC1 showing enrichment of two MSigDB gene sets (left). Violin plots (right) show the expression distribution of the enriched day 9 genes.

Figure 30. PIB factors induce high levels of expression of genes associated with DC maturation. (A) Expression levels of the genes Ciita, H2-Aa, H2-Ab1, and H2-Eb1 in single cells from states 1, 2, and 3 sorted with Monocle2 (Pseudotime). Each point represents relative expression values for single cells. The lines represent branch kinetic curves for state 2 (solid line) and state 3 (dashed line). (B) Violin plots showing the expression levels of the genes Ciita, Acp5, Tnfrsf1a, Tapbp, Inpp5d, Traf6, and Itga4. Log values of the census counts are shown, horizontal lines correspond to median values.

Figure 31. Induced DCs secrete inflammatory cytokines upon TLR stimuli. (A) Cytokine secretion by MEFs transduced with PIB (PU.1, IRF8, and BATF3) or PIBT (PU.1, IRF8, BATF3, and TCF4) with or without TLR4 (LPS) or TLR3 (PolyI:C) stimuli overnight. Supernatants from MEFs transduced with PIB or PIBT factors were collected on day 10 after Dox addition and analyzed for cytokine concentrations using the BD Cytometric Bead Array Mouse Inflammation Kit. Cytokine levels are shown for untreated cells, cells treated with 100 ng/ml LPS or 25 pg/ml PolyI:C overnight; black or gray bars represent MEFs transduced with PIB or PIBT, respectively.

Figure 32. Induced DCs are capable of uptake of small particles. PIB-transduced MEFs (PU.1, IRF8, and BATF3) were incubated overnight with FITC-labeled latex beads (1 pm) and analyzed by fluorescent microscopy on day 7 after Dox addition.

Figure 33. Induced DCs are capable of uptake of proteins and dead cells. (A) GDP-transduced MEFs were sorted by FACS, and tdTomato- and tdTomato+ (iDC) populations were incubated with AlexaFluor647-labeled ovalbumin (OVA-Alexa647) at 37°C on day 11 and analyzed by flow cytometry. Controls were kept on ice (4°C). (B) tdTomato- and tdTomato+ (iDC) populations sorted on day 11 were incubated overnight with dead cells labeled with Claret’s CellVue Far Red membrane stain and analyzed by flow cytometry. (C, D) Day 11 iDCs were incubated overnight with DAPI-labeled dead cells and analyzed by fluorescent or (D) time-lapse microscopy.

Figure 34. Induced DCs express genes involved in TLR signaling and the endocytic pathway. Violin plots for genes regulating (A) TLR signaling and (B) antigen uptake.

Figure 35. Induced DCs capture and present antigens to CD4+ T cells. (A) Schematic representation of the antigen presentation assay. iDCs at day 8 after Dox addition were cocultured with OT-II CD4+ T cells isolated from OT-II Rag2KO mice and labeled with CFSE in the presence of ovalbumin (OVA) or OVA 323-339 peptide. After 7 days, CD4+ T cell activation was assessed by CFSE dilution and the expression of the T cell activation marker CD44. (B) Flow cytometry graphs of CFSE-labeled CD4+ T cells cocultured with PIB or PIB plus TCF4-transduced MEFs, in the presence of OVA, stimulated or not with LPS. CD4+ T cells cocultured with splenic CD11c+ MHC-II+ DCs were included as controls. Gray lines correspond to intact CD4+ T cells. (C) Flow cytometry graphs showing CD44 expression of CFSE-labeled CD4+ T cells cocultured with PIB-transduced MEFs in the presence of LPS and OVA or OVA peptide.

Figure 36. Induced DCs capture and present antigens to CD4+ T cells. Quantification of the percentage of CFSE-low CD4+ T cells cocultured with PIB-transduced MEFs (iDCs) in the presence of LPS and OVA or OVA peptide. Splenic DCs were included as a control.

Figure 37. Induced DCs efficiently export endocytic cargo to the cytoplasm and express cross-presentation genes. (A) Day 16 iDCs were loaded with a FRET-sensitive cytosolic β-lactamase substrate, CCF4, followed by incubation with β-lactamase. The kinetics of β-lactamase export to the cytosol was measured as CCF4 cleavage by flow cytometry. (B) Violin plots for genes regulating cross-presentation.

Figure 38 Induced DCs capture and cross-present exogenous antigens to CD8+ T cells. (A) Day 16 iDCs were coincubated with B3Z T cell hybridomas for 16 h and increasing concentrations of soluble OVA protein in the absence (left panel) or presence of LPS or poly-I:C (PIC) stimulation (right panel). T cell activation was measured as up-regulation of p-galactosidase expression in B3Z (driven by the IL-2 promoter) and quantified using a colorimetric substrate, CPRG. (B) Schematic representation of the cross-presentation assay (left panel). iDCs at day 8 after Dox addition were cocultured with OT-I CD8+ T cells isolated from OT-I Rag2KO mice and labeled with CFSE in the presence of ovalbumin (OVA) or the OVA peptide 257-264. After 4 days, CD4+ T cell activation was assessed by FSE dilution and the expression of the T cell activation marker CD44. Flow cytometry graphs showing CD44 expression of CFSE-labeled CD8+ T cells cocultured with PIB or PIB plus TCF4-transduced MEFs in the presence of OVA. CD8+ T cells cocultured with splenic CD11c+ MHC-II+ DCs were included as controls (middle panel) and quantification was performed (right panel).

Figure 39. PU.1, IRF8, and BATF3 induce DC-like morphology in human fibroblasts. (A) Human dermal fibroblasts (HDFs) were transduced with PIB (PU.1, IRF8, BATF3) and cultured in the presence of Dox. (B) Bright-field images of PIB-transduced HDFs at day 3 after Dox addition. White arrowheads mark cells with typical DC-like morphology. M2rtTA-transduced HDFs are shown as a control. (C) Higher magnification of bright-field images of PIB-transduced HDFs with DC-like morphology.

Figure 40. PU.1, IRF8, and BATF3 induce HLA-DR and CLEC9A expression in human fibroblasts. Flow cytometric analysis of HLA-DR and CLEC9A expression in PIB-transduced human fibroblasts at day 9 after Dox addition.

Figure 41. PU.1, IRF8, and BATF3 induce the ability to capture beads and proteins in human fibroblasts. (A) PIB-transduced HDFs were incubated overnight with FITC-labeled latex beads (1 pm) and analyzed by fluorescent microscopy on day 7 after Dox addition. Claret’s CellVue Far Red and DAPI were used to stain cell membranes and nuclei, respectively. (B) Flow cytometry analysis of PIB-transduced HDFs after incubation with Ovalbumin-AlexaFluor647 for 20 min at 37°C on day 7 after Dox addition. Controls were kept on ice (4°C).

Figure 42. PIB factors induce Clec9a and MHC-II expression in lung cancer cells. Flow cytometry analysis of Clec9a and MHC-II expression in PIB-transduced 3LL cells at day 8 after Dox addition. Cells transduced with M2rtTA are included as a control.

Figure 43. PIB factors induce CLec9a and MHC-II expression in melanoma cells. Flow cytometric analysis of CLec9a and MHC-II expression in PIB-transduced B16 cells at day 8 after Dox addition. Cells transduced with M2rtTA are included as a control.

Figure 44. Delivery of PIB factors in a polycistronic vector increases reprogramming efficiency. (A) Schematic representation of polycistronic regions encoding Pu.1, Irf8, and Batf3 (PIB) or Irf8, Pu.1, and Batf3 (IPB) separated by 2A-like sequences. (B) Flow cytometry analysis of Clec9a reporter activation in MEFs transduced with Pu.1, Irf8, and Batf3 in single vectors (top right panel) or polycistronic vectors (PIB and IPB) at day 7 after Dox addition. Cells transduced with M2rtTA are included as a control. (C) Quantification of tdTomato+ cells after transduction with PIB factors in single or polycistronic vectors at day 7.

Detailed description

The invention is defined by the appended claims. Any embodiment not falling within the scope of the appended claims is not part of the invention. The present disclosure relates to compositions, nucleic acid constructs, and methods thereof for cell induction or cellular reprogramming to the dendritic cell state or the antigen-presenting cell state, based, in part, on the surprising effect described herein of the novel use and combinations of transcription factors that allow the induction or reprogramming of differentiated or undifferentiated cells into dendritic cells or antigen-presenting cells. Such compositions, nucleic acid constructs, methods, and kits can be used to induce dendritic cells in vitro, ex vivo, or in vivo, and these induced dendritic cells or antigen-presenting cells can be used for immunotherapy applications.

Naturally occurring DCs are bone marrow-derived cells that are seeded into all tissues. DCs are primed to sample the environment and transmit the gathered information to cells of the adaptive immune system (T cells and B cells). Upon antigen uptake, DCs initiate an immune response by presenting the processed antigen, which is in the form of peptide-major histocompatibility complex (MHC) molecule complexes, to naive (i.e., antigen-inexperienced) T cells in lymphoid tissues. After activation, DCs typically overexpress costimulatory and MHC molecules in addition to secreting several cytokines responsible for initiating and/or enhancing many T and B cell responses, i.e., type I interferon, tumor necrosis factor (TNF)-α, IFN-γ, IL-12, and IL-6. Therefore, DCs are generally identified by their elevated expression of major histocompatibility complex class II (MHC-II) molecules, costimulatory molecules such as CD80/86 and CD40, and the integrin CD11c, as well as by their superior ability to secrete inflammatory cytokines and migrate from non-lymphoid to lymphoid organs and stimulate naive T cells. In mice and humans, distinct DC subsets can be variably defined by phenotype, ontogeny, and function. These include the conventional DC 1 (cDC1, also known as the CD8a+ DC subset) found in mouse lymphoid organs and the related CD103+ DC subset in non-lymphoid tissues. Cells bearing a similar phenotype have recently been described in humans, humanized mice, and sheep, indicating interspecies conservation of the cDC1 family. This extended family has distinctive functional properties, most notably a remarkable efficiency in capturing material from dead or dying cells, as well as in processing exogenous antigens for cross-presentation on MHC class I. These two features allow cDC1 DCs to cross-present cell-associated antigens and trigger CTL responses against infectious agents or tumors. In addition to priming CD8+ T cells, cDC1+ DCs have been implicated in establishing cross-tolerance to tissue-specific cell-associated antigens. The ability of cDC1 DCs to cross-prime or cross-tolerize CD8+ T cells against cell-associated antigens implies that they can decode the context in which they encounter dead cells. DNGR-1, also known as CLEC9A, is a receptor for necrotic cells that promotes CTL cross-priming to dead cell-associated antigens in mice. DNGR-1 is selectively expressed at high levels by mouse cDC1+, CD103+, and human DCs, and is responsible for recognizing an exposed intracellular ligand after cell death. Recently, it has been shown that Clec9a expression allows the identification of DC lineage-committed precursors (CDPs) and their progeny in lymphoid tissues (10).

The successful identification of DC-inducing factors capable of reprogramming differentiated cells to induced DCs, as described here, can advance the basic understanding of DC biology in several ways. This work will provide in-depth knowledge of minimal DC transcriptional networks. Furthermore, the identification of DC-inducing factors offers unprecedented opportunities to understand how the DC state is established and how key regulatory machinery is operationalized.

Transcription factors play a critical role in the specification of all cell types during development. The success of direct reprogramming strategies using transcription factor-mediated reprogramming indicates that it is equally plausible to direct the differentiation of pluripotent ES/iPS cells or multipotent stem cells to specific fates using such factors. Accordingly, using the DC-inducing factors identified here, directed differentiation of ES/iPS cells to a definitive DC fate can be achieved by expressing DC-enriched transcription factors. Furthermore, using the DC-inducing factors identified here, directed differentiation of multipotent hematopoietic stem and progenitor cells to a definitive DC fate can be achieved by expressing DC-enriched transcription factors (forcing differentiation along the hematopoietic tree depicted in Figure 1).

Typically, nucleic acids encoding DC-inducing factors, e.g., DNA or RNA, or constructs thereof, are introduced into a cell, using viral or non-viral vectors, by single or repeated transfections, and expression of the gene products and/or translation of the RNA molecules result in cells that are morphologically, biochemically, and functionally similar to DCs, as described herein. These induced DCs (iDCs) then primed with appropriate antigens have the ability to capture, process, and present them to effector cells of the immune system (macrophages, T cells, B cells, NK cells) eliciting antigen-specific immune responses against cancer, viral, and parasitic/bacterial infections (Figure 2).

TFs can be used, for example, in cancer cells (in situ or ex vivo) to force them to present their own antigens to immune cells (Figure 3). This method represents a feasible strategy to improve the clinical outcome of cancer immunotherapies, as it circumvents cancer evasion mechanisms and increases tumor immunogenicity.

Eighteen candidate TFs were selected due to their specifically enriched gene expression in DCs (Figure 4A), enriched in DCs compared to macrophages, which are less efficient APCs (Figure 4B, left panel) (20) and during DC ontogeny (Figure 4B, right panel). Gene ontology (GO) enrichment analysis for the 18 TFs highlighted their pivotal roles in leukocyte and DC differentiation (p=2.51E-12 and p=9.58E-12, respectively) and activation (p=1.02E-11 and p=6.31E-11), while mouse mutant phenotype enrichment analysis confirmed that genetic perturbations in those genes primarily cause hematopoietic phenotypes, particularly abnormal adaptive immunity (p=1.19E-04) and abnormal antigen presentation (p=1.25E-03) (Figure 4C). Eighteen candidate TFs were individually cloned into a doxycycline (Dox)-inducible lentiviral vector tested with reprogramming (6).

To detect the effect of novel dendritic cell-inducing TFs and DC-inducing TF combinations by cellular reprogramming, mouse embryonic fibroblasts (MEFs) harboring a DC-specific reporter (Clec9a-Cre X R26-stop- tdTomato) were used, and reporter gene activation was used to display DC-inducing TFs. In the Clec9a- tomato reporter mouse, the fluorescent protein tdTomato is expressed exclusively in DCs, pre-DCs, and cDCs (10). Macrophages, other immune lineages, or monocyte-derived DCs in culture do not express Clec9a and therefore the tdTomato protein (Figure 5A). Within the immune system, Clec9a gene expression is selectively restricted to DCs and their progeny (pre-cDCs and cDCs) (Figure 5B). The results of cDC and precursor gene expression analysis also highlighted that Clec9a expression is acquired after cDC lineage commitment in both pre-DC and monocytic DC progenitors (MDPs) (Figure 5C) (11). Clec9ase is expressed in cDCs, both pre-DC and cDC subsets, reaching high levels in the cDC1 subset (Figure 6A) (21). Spleen cells isolated from Clec9a reporter mice were analyzed, confirming that 98.8% of cDC1 cells (MHC-II+CD11c+CD8a+ selected) express the fluorescent protein tdTomato (Figure 6B).

MEFs with double transgenic Clec9a-tdTomato reporters were isolated from E13.5 embryos and excluded from any contaminating tdTomato+ or CD45+ cells that might already be committed to the hematopoietic lineage (Figure 7A and 7B) by fluorescence-activated cell sorting (FACS). MEFs used for detection and in the subsequent experiments were tdTomato- CD45- with a purity of 99.8% (Figure 7C).

MEFs with Clec9a reporters were transduced with candidate TF combinations and tdTomato expression was assessed (Figure 8). After transduction with either all 18 candidate TFs or one of the 4-TF pools, the appearance of tdTomato+ cells was observed 5 days after Dox addition (Figure 9A, Figure 9B). The pool composed of Pu.1, Irf4, Irf8, and Batf3 generated more tdTomato+ cells than 18 TFs (2.36% versus 0.59%, respectively), suggesting that the minimal combination of factors necessary to induce reporter activation is contained within this pool. No tdTomato+ cells were detected after transduction with the control vector M2rtTA. Each of the factors was then deleted individually (Figure 9C). Deletion of Pu.1, Irf8, and Batf3 (PIB) reduced reporter activation, whereas deletion of Irf4 had no impact. These results suggest that PIBs are essential for DC reprogramming.

When the combination of PU.1, IRF8, or BATF3 (PIB) was expressed in MEFs, the Clec9 reporter was activated with increased efficiency (approximately 3.96%, Figure 10A). The kinetics of reporter activation were then assessed.

(Figure 10B). tdTomato+ cells began to be detected between day 1 and day 2 and peaked between day 5 and day 7 (Figure 10B). Knockdown of PU.1, IRF8, or BATF3 completely abrogated reporter activation, while their individual expression was not sufficient to generate tdTomato+ cells (Figure 10C). These data suggest that PIB constitutes the minimal TF combination for Clec9a activation and the generation of induced dendritic cells (iDCs). Importantly, tdTomato+ cells display increased size and complexity (Figure 10D), consistent with the observed stellate morphology and establishment of dendrites characteristic of DCs (Figure 10E, Figure 10F). Activation of the reporter was confirmed to occur at approximately 30 hours by time-lapse microscopy, and tdTomato+ cells were observed to exhibit changes in morphology, migration capacity, and dendrites that gradually established over 6 days (Figure 11). The panhematopoietic marker CD45 was expressed on approximately 20% of PIB-transduced MEFs, with approximately 6.6% of tdT+ cells included in this population (Figure 12).

The impact of expressing additional factors other than PIB was assessed. The individual impact of each of the TFs from the candidate pool of 18 TFs (Figure 13A), as well as other hematopoietic TFs (Figure 13B), was evaluated. Of the 31 TFs analyzed, STAT3, IKZF1, IRF2, NFIL3, BCL6, L-MYC, RUNX1, and KLF4 were found to negatively affect the number of tdTomato+ cells generated. The addition of TCF4 and Gfilb showed a 2.2-fold and 1.9-fold increase in reporter activation, respectively.

In an effort to optimize culture conditions for iDC generation, the addition of the cytokines granulocyte macrophage colony-stimulating factor (GM-CSF), IL-4, and FMS-like tyrosine kinase 3 ligand (Flt3l) was tested during induction (Figure 14A) because of their important roles in DC specification (12). The addition of lipopolysaccharide (LPS), different media compositions (RPMI, 2-mercaptoethanol (2-ME), and 4 mM L-Glutamine (2xGlut), and co-culture with OP-9 and OP9-DL1 stromal cells (Figure 14B) was also tested (13). These culture modifications did not increase the number of induced tdTomato+ cells.

The in vivo expression patterns of PIB and TCF4 were analyzed. The transcripts PU.1, IRF8, BATF3, and TCF4 are expressed in individual DC precursor cells (Figure 15). While Pu.1 is equally expressed in MDP, CDP, and pre-DC, IRF8 expression is markedly increased in CDP and maintained in pre-DC. BATF3 and TCF4 are only upregulated at a later stage, in pre-DC. Furthermore, the combined expression of PU.1 IRF8 + BATF3 is mainly enriched in CD8a + DCs among 96 cells and tissues (Figure 16A). Importantly, Pu.1 levels are highest at both pre-DC stages, whereas Irf8 and Batf3 are specifically enriched in pre-cDC1 and cDC1 subsets (Figure 16B). Compared with other DC subsets and several hematopoietic cell lineages, Clec9a, Pu.1, Irf8, and Batf3 are more highly expressed in CD103+ DCs belonging to the cDC1 subset (Figure 16C).

We assessed whether C9a-tdTomato reporter activation was reflected in the expression of DC markers, such as typical surface markers used to discriminate between conventional cDC and pDC subsets (Figure 17A, Figure 17B). Interestingly, the cDC1 marker CD103 was expressed on 25±13.65% of tdTomato+ cells in contrast to undetectable levels on tdTomato- cells, suggesting the specification of a non-lymphoid migratory cDC1 program. Furthermore, only residual expression of cDC2 and pDC markers was detected (0.41±0.58% CD4+, 2.56±0.18% CD11b+, 0.77±1.09% B220+ cells, respectively).

We assessed whether Clec9a-tdTomato reporter activation was reflected in the expression of key components of the antigen presentation machinery on the cell surface. Notably, 71.4% of tdTomato+ cells at day 7 expressed surface MHC-II (Figure 18A), a key molecule for the establishment of APC functionality. MHC-II expression is gradually acquired starting between day 1 and day 2 and peaks between day 7 and day 11 (Figure 18B). The kinetics of MHC-II activation resembles Clec9a reporter activation (Figure 10B). On day 7, the tdTomato- compartment contained a lower percentage of MHC-II+ cells (14.2%) (Figure 18A). We then addressed whether MHC-II expression is directly controlled by PIB factors. When each factor was excluded individually, we found that PU.1 expression, but not IRF8 or BATF3, is important for MHC-II activation (Figure 18C), consistent with the reported role of Pu.1 in regulating the Class II Transactivator (CIITA) through its promoter I (CIITApl) (14, 15). CIITA is known as the master regulator of MHC class II gene expression by determining cell type-specific, cytokine-induced, and developmentally derived modulation of MHC-II expression through differential usage of CIITA promoters (16). In conventional DCs, CIITApl has been associated with the regulation of MHC-II genes.

Due to the described involvement of IRF4 in the induction of MHC-II expression through interaction with CIITA (17), we evaluated whether IRF4 could compensate for Pu.1 in the generation of MHC-II+ cells within the tdTomato+ population. Therefore, we assessed MHC-II expression in tdTomato+ cells generated by 4TF (including IRF4) or its individual exclusion (Figure 18D). Inclusion of IRF4 in the combination did not increase MHC-II expression in tdTomato+ cells, and IRF4 could not compensate for the loss of Pu.1. Accordingly, we found that IRF4 and PU.1 synergistically promote MHC-II expression through the CIITA promoter III in B cells, but not in DCs (17). During reprogramming to iDCs, no synergy was observed with PU.1, which was strictly required for MHC-II expression in tdTomato+ cells.

The expression of MHC class I molecules, key molecules for establishing APC functionality, was assessed. On day 7, 56.7% of tdTomato+ cells expressed MHC-I on their surface (Figure 19). On day 7, the tdT- compartment contained a lower percentage of MHC-I+ cells (11.2%) (Figure 19).

The expression of the costimulatory molecules CD80 and CD86, required for efficient antigen presentation, was assessed (Figure 20). CD80 and CD86 are expressed on 35.2% of tdTomato+MHC-II+ cells compared to only 12.9% of tdTomato+MHC-II- cells. This characterization of MHC-II, CD80, and CD86 expression on the cell surface of iDCs suggests that a cohort of tdTomato+MHC-II+ cells would be competent in antigen presentation. An additional costimulatory molecule, CD40, is expressed on 16.1% of tdTomato+ cells, compared to only 2.8% of tdTomato- cells (Figure 21A). Resting cDCs, particularly the cDC1 subset, have been reported to respond to microbial stimulation by upregulating the expression of costimulatory molecules and becoming more efficient APCs (25). Accordingly, tdTomato+ cells upregulate CD40 expression (4-fold increase) on the cell surface after Toll-like receptor TLR4 (LPS) stimulation (Figure 21B).

In order to define the extent of transcriptional changes during iDC reprogramming, full-length single-cell transcriptomes were measured after GDP transduction (Figure 22A). Initially, 192 cells from untransduced MEFs, day 3 Clec9a-tdTomato+, day 7 Clec9a-tdTomato+, day 9 Clec9- tdTomato+MHC-II+ cells, and freshly isolated CD11c+ MHC-II+ CD8a+ splenic DCs (sDCs) were profiled. Of these, 163 single cells passed quality control filters and were used for analysis. After alignment of reads to individual gene loci, the Census algorithm was used to convert relative RNAseq expression levels (transcripts per million, TPM) into relative transcript counts (Census counts) without the need for added experimental controls and improving the accuracy of differential expression analysis. The t-distributed stochastic linear insertion (tSNE) algorithm was first employed to perform genome-wide transcriptome clustering analysis (Figure 22B) and two main groups of cells were observed. iDCs at day 3 and most cells at day 7 mapped close to MEFs, while the remaining iDCs at day 7 and all of those at day 9 clustered together with sDCs. Unsupervised clustering was performed using single-cell consensus (SC3) clustering, confirming the overall similarity of sDCs to the day 9 group and some of the day 7 iDCs (Figure 22C). Furthermore, the timing of global transcriptome reprogramming correlates well with the peak generation of Clec9a-tdTomato+ MHC-II+ cells between days 7 and 15 (Figure 18B). TdTomato+ cells display time-dependent transcriptional changes starting as early as day 3; by day 9, iDCs are remarkably similar to authentic DCs. This analysis suggests that PIB factors induce a global transcriptional reprogramming towards the DC fate. The 6525 most variable genes were extracted from the dataset, which after clustering could be organized into 4 groups (Figure 22D). Group I comprises highly expressed genes in MEFs, which are silenced during DC reprogramming. These include typical fibroblast markers such as Col5a2, Greml, Lox, Acta2, and Thy1 (Figure 22E). Cluster II includes transcripts enriched at day 3 and day 7, suggesting activation during the early stages of reprogramming. This cluster includes genes such as Eea1 and Aldh1a2 that are associated with intracellular trafficking and metabolism, as well as type I interferon (IFN) signaling (Ifit3) (Figure 22F). In contrast, cluster III encompasses genes enriched at day 9 (Figure 22D). Interestingly, MHC-II-related genes (such as H2-Pb), as well as genes regulating cross-presentation on DCs (such as cathepsin Ctsc and Cd74), are enriched in this cluster (Figure 22F). Finally, cluster IV includes genes enriched in reprogrammed sDC1 and iDC (Figure 22D), such as the pan-hematopoietic marker Cd45 and the general DCC marker d11c (Figure 22F). Importantly, cDC1-restricted genes were also upregulated, such as the gene Clec9a and Tlr3 (22), and the key regulator of MHC class I-dependent immune responses (Nlrc5) required for antigen cross-presentation, a key feature of cDC1 (23). Indeed, a robust upregulation of cDC1 signature genes was detected during the reprogramming process compared to cDC2 signature genes (Figure 26) (11). Together, these data suggest complete DC reprogramming favoring the cDC1 subset. Therefore, GO analysis showed that categories related to antigen processing and presentation (p-value = 3.34E-08, 1.80E-06, 3.53E-06, 4.03E-06) enriched the main biological processes and pathways (Table 1). The top GO categories of cellular components included lysosomes (p-value = 1.31E-07) and lytic vacuoles (p-value = 1.44E-07), consistent with the reported role of lysosomal signaling in coordinating antigen processing and DC migration (24). MicroRNA (miRNA) target prediction showed the highest enrichment of miR-155 (p-value=1.41E-11) and miR-124 (p-value=1.00E-10) targets (Table 2), which have been implicated in DC function and specification, respectively (25, 26).

Table 1. Top 5 Gene Ontology Biological Processes (left) and Cellular Component (right) enriched in Clusters I to IV.

Table 2. Gene ontology analysis of mouse loss-of-function mutant phenotype enrichment (top panel), KEGG pathways (middle panel), and microRNA target interactions (bottom panel) was performed on the four gene groups identified using the 6,525 most variable genes across the five sample groups (referring to Figure 22). The lists show the most enriched terms, and the right columns show the respective p-values per fold change relative to the most enriched term.

This analysis also revealed the activation of DC transcriptional regulators, including Zbtb46 and Bcl11a, which were originally included in our list of candidate TFs (Figure 23A). Several members of the interferon (IFN) regulatory factor and signal transducer and activator of transcription (STAT) protein families were also identified. For example, Stat2 and Irf7, key mediators of TLR-induced DC activation and type I IFN responses, respectively, are detected at elevated levels at 3 and 7 days. Stat6 also shows elevated median expression values for days 3 and 7, while Stat1 expression increases at day 9 to levels 128-fold higher than splenic DCs. DC maturation has been described to be accompanied by a shift in STAT6 to STAT1 utilization, suggesting that overexpression of Pu.1, Irf8, and Batf3 can also induce DC maturation. High levels of Pu.1, Irf8, and Batf3 expression were observed at day 3, day 7, and day 9 compared to sDCs, consistent with lentivirus-mediated expression of all 3 TFs (Figure 23B, top panel). Since our lentiviral vectors encode coding sequences without UTRs, expression levels of endogenous transcripts were quantified using reads in the 3' and 5' UTRs. Importantly, expression of endogenous Pu.1, Irf8, and Batf3 was observed starting at day 3 (Figure 23B, bottom panel). On day 9 of reprogramming, endogenous expression levels are comparable to splenic DCs.

In order to better characterize the dynamic nature of transcriptional reprogramming, gene set enrichment analysis (GSEA) was performed using NetPath gene sets to compare transitions between days 0, 3, 7, and 9 (Figure 24, top panel). Several immune-related gene sets were observed to be highly enriched on day 3 compared to MEFs. Interestingly, IL-4 used for in vitro differentiation of DCs ranked first (NES: 1.97, FDR q-value: 0.02) (Figure 24, bottom left panel). Some gene sets were also enriched on day 7, albeit with lower NES values, suggesting that more subtle transitions might occur during this phase. In contrast, several sets of genes were highly enriched on day 9 compared to day 7, including the interleukin and oncostatin M pathways, previously associated with DC maturation (Figure 24, bottom right panel).

Transcriptional networks were assessed for stepwise transitions during iDC reprogramming (Figure 25A). The transition of MEFs at day 3 was observed to be associated with the expression of a dense network of TFs that was highly connected to PIB reprogramming factors; the transition from day 3 to day 7 was smoother, characterized by a less dense TF network, which does not include PIB factors; and the transition from day 7 to day 9, characterized by a dense TF network that can be divided into 2 TF groups, a denser one that includes the cDC marker Zbtb46, and one composed of fewer TFs that include PIB factors. This reinforces the idea that a more subtle transition could occur between day 3 and day 7, and suggests that iDCs at day 9 may have acquired a stable cell fate. Importantly, all of these transcriptional regulators are enriched in mature DCs and not in DC progenitors, regardless of the day they are activated, suggesting that the reprogramming process does not go through an intermediate progenitor state (Figure 25B). Furthermore, the absence of intermediate progenitor cells in the iDC reprogramming process was further validated by performing hematopoietic colony formation assays with PIB-transduced MEFs on days 3, 5, 7, 10, and 25 after Dox addition, including sorted sDC1 and unsorted splenocytes and bone marrow cells as controls (Figure 25C). No colonies were observed in iDC or sDC1 cultures, while, as expected, unsorted splenocytes and bone marrow cells in culture gave rise to colonies. This supports the idea that the reprogramming process is direct and does not transit through intermediate progenitor cells.

We proposed to reconstruct the DC reprogramming pathway by establishing a pseudotemporal order based on the gradual transition of cellular transcriptomes (Figure 27A). Using pseudotemporal reconstruction in single-cell RNA-seq analysis software (TSCAN), we observed that the order is consistent with temporal reprogramming events, with MEFs followed by iDCs on day 3 and subsequently by the majority of iDCs on day 7. Interestingly, 4 individual iDCs on day 7 and some on day 9 are located in line with sDCs in the pseudotemporal ordering, suggesting that transcriptome reprogramming was complete. However, the remaining iDCs on day 9 appear to be further away from the initial time point than splenic DCs. In order to confirm the reliability of these results, a pseudotemporal ordering was performed using Monocle2, an alternative algorithm for delineating differentiation pathways. This reconstruction placed the biological sample groups along three branches of the pseudotemporal ordering (Figure 27B, left panel). MEFs, d3 iDCs, and 26 iDCs at day 7 fell along the first branch, deemed cell state 1 (Figure 27B, right panel), which then reaches a branch point and divides into State 2 and State 3. State 2 includes 82% of the sDCs, as well as 3 iDCs from day 7 and 13 from day 9. However, 55% of the iDCs from day 9, as well as all 11 sDCs, fall within state 3, consistent with the TSCAN results. To understand the transcriptional differences between these 2 states, GO enrichment analysis was performed using the differentially expressed genes (Table 3), which showed that the major biological processes and pathways in State 3 include type I and type II IFN (IFN-γ) signaling, known inflammatory mediators of DC activation and maturation (38, 39). Genetic perturbations of the genes enriched in State 3 highlighted corresponding immune phenotypes, such as abnormal APC and abnormal immune system. Consistently, BEAM analysis revealed 2 kinetic groups of upregulated branch-dependent genes in State 3 (clusters 2 and 4) functionally enriched for antigen presentation and other immune-related processes (Figure 28A and Table 4).

Table 3. Top 5 Gene Ontology biological processes, mouse phenotypes, and Wiki pathway enrichment analysis of differentially expressed genes between state 2 and state 3. Relative to Figure 27.

Table 4. Top 5 Gene Ontology Biological Processes and Phenotype Enrichment Analysis of Loss-of-Function Mutants from Groups 1 to 5 Mouse. Refers to Figure 28.

GSEA also showed that 4,705 versus 167 gene sets for immunosignatures were upregulated in state 3 compared to state 2, such as the gene sets for mature stimulatory DCs, IFNγ-stimulated DCs, and IFNα-stimulated DCs (Figure 28B). As state 3 contained the majority of day 9 iDCs, we sought to confirm that a similar maturation signature was observed by comparing sDC1 (naive) with day 9 iDCs. GSEA showed that gene sets for antigen processing and presentation and DC maturation were enriched in day 9 iDCs (Figure 29A). Interestingly, Stat6, which is associated with immature DCs, was upregulated in sDC1s, while Stat1, which is described to increase with maturation, was upregulated in day 9 iDCs (Figure 23A).

Since iDCs were previously observed to express high levels of MHC-II molecules, which is described to be associated with DC maturation (Figure 18), we sought to investigate whether the observed pseudotemporal trajectories were indicative of different maturation states. The kinetic curves of the branches were observed to reflect a continuous upregulation of Ciita, the known master regulator of MHC-II gene expression, and several MHC-II genes (H2-Aa, H2-Ab1, and H2-Eb1) towards state 3 compared to state 2 (Figure 30A). Consistently, the expression of Ciita and genes associated with mouse (Tnfrsla, Tapbp, Inpp5d, and Traf6) and human (Acp5eItag4) DC maturation were enriched in day 9 iDCs (Figure 30B). These data suggest that iDCs are intrinsically more mature than sDCs and may be less dependent on exogenous activating stimuli for antigen presentation.

Induced dendritic cells, although similar in functional characteristics, differ in their gene expression from naturally occurring endogenous dendritic cells (Table 5).

Table 5. Top 500 differentially expressed genes between iDC and sDC1 cells at day 9 ranked by fold change.

In addition to membrane-associated costimulatory molecules, mature DCs express cytokines with a proinflammatory function that are important for the development of T cell responses. These responses can be initiated by the activation of at least 11 different Toll-like receptors (TLRs), allowing for the specific recognition of distinct conserved microbial or viral structures. We investigated whether iDCs secrete cytokines into the medium when stimulated with TLR3 (using polyinosinusin-polycytidylic acid (poly-I:C)) or TLR4 (lipopolysaccharides (LPS)) (Figure 31). Following stimulation of iDCs with LPS or polyI:C, an increase in IL-6 secretion was observed (14- or 10-fold, respectively). An increase in the secretion of tumor necrosis factor (TNF) (7-fold) and interferon (IFN-γ) (2-fold) was also observed after stimulation with LPS or polyI:C, respectively. Cells transduced with PIB plus TCF4 (PIBT) responded equivalently to stimulation, exhibiting increased secretion of IL-6, TNF, and IFN-γ. Importantly, no increase in the secretion of the anti-inflammatory cytokine IL-10 was observed after iDC stimulation. These results suggest that iDCs underwent maturation toward a proinflammatory profile.

The ability of iDCs to generate an antigen-specific immune response was assessed. First, we tested whether iDCs could take up particles by incubating them with 1 pm FITC-labeled latex beads. After incubation, tdTomato+ cells contained numerous fluorescent beads in the cytoplasm (Figure 32), suggesting that iDCs had established competence for phagocytosis.

The ability of iDCs to capture soluble proteins was then assessed. Notably, 13.8% of tdTomato+ cells were able to actively take up soluble protein after incubation at 37°C for 20 min in contrast to only 5.6% when incubated at 4°C (Figure 33A), further suggesting that iDCs have established competence for phagocytosis/endocytosis. In contrast, only 4.6% of tdTomato- cells displayed a similar ability. We then assessed whether iDCs were able to internalize dead cell material in vitro (Figure 33B-D). This unique ability has been shown to be associated with cDC1 DC subtypes to cross-present cell-associated antigens on MHC-I (27). After overnight incubation with labeled dead cells, 65.7% of purified tdTomato+ cells had incorporated dead cell material in contrast to only 10.5% of tdTomato- cells (Figure 33B). Dead cell uptake was further analyzed by live imaging, and tdTomato+ cells were observed to avidly accumulate dead cell material in the cytoplasm (Figure 33C). TdTomato+ cells actively move and, upon encountering a dead cell, project cellular protrusions to incorporate and engulf it (Figure 33D).

Furthermore, we have confirmed that iDCs express genes encoding TLRs (Tlr3 and Tlr4) and other mediators of TLR signaling, including MyD88-dependent (TRAM (encoded by Ticam2) and Traf6) and -independent (IKKe) pathways (Figure 34A). We have further confirmed that iDCs express key mediators of receptor-mediated endocytosis (Fcgr2b, Tfr2, and Mrc1) and macropinocytosis of dead cells (Axl, Lrp1, and Scarfl), further suggesting that iDCs have acquired the ability to sense and incorporate antigens (Figure 34B).

The functional capacity of iDCs to promote antigen-specific proliferation of CD4 T cells was assessed (Figure 35A). For this purpose, MHC class II-restricted ovalbumin-specific T cells (OT-II cells) isolated from the lymph nodes and spleen of OT-II Rag2 KO mice (18) were used. In this model, T cells respond to the processed antigenic peptide (OVA 323-339) when displayed in the context of MHC-II on DCs. Therefore, OT-II CD4 T cells were cocultured with iDCs when either ovalbumin (OVA) protein or preprocessed antigenic peptide (OVA 323-339) was administered. Functional DCs are able to capture the protein, process it, and present the processed antigenic peptide in the context of MHC-II. Induced CD4+ T cell proliferation was measured by CFSE dilution and the activation of the T cell activation marker CD44 after 7 days of coculture. Notably, 56% of CD4+ T cells diluted CFSE when cocultured with PIB-generated iDCs in the presence of OVA protein (Figure 35B). When cocultured with PIB+TCF4-transduced MEFs, 38.2% of CD4+ T cells diluted CFSE content, suggesting that the inclusion of TCF4 in the reprogramming combination does not enhance the stimulatory capacity of iDCs. MHC-II+CD11c+ splenic DCs were used as controls and generated 24.1% proliferating T cells. Importantly, the addition of LPS stimuli, commonly used to induce DC “maturation,” increased the antigen-specific stimulatory capacity of MEFs transduced with PIB (1.5-fold) or PIB+TCF4 (2-fold) and also of splenic DCs (3-fold) (Figure 35B and Figure 36). As expected, non-cocultured T cells did not proliferate with or without LPS stimuli. To further assess the stimulatory capacity of iDCs, we assessed whether they were able to induce the expression of T cell activation markers such as CD44. When supplied with preprocessed antigen, OT-II CD4 T cells diluted CFSE and upregulated CD44 expression when cocultured with both PIB-generated iDCs and splenic HC-II+CD11c+ mDCs (Figure 35C). Importantly, when supplied with OVA protein, iDCs displayed a comparable ability to induce CD44 expression on OT-II T cells compared to splenic DCs (52.2% versus 63.8%). These data support the functional capacity of iDCs to incorporate and process OVA protein followed by the presentation of processed ovalbumin peptides in MHC-II complexes on the cell surface. Collectively, these results highlight the functional capacity of iDCs and support the feasibility of using directly reprogrammed fibroblasts to present antigens and induce antigen-specific adaptive immune responses.

We assessed whether iDCs acquire the ability to export antigens to the cytosol and express key genes essential for cross-presentation. Cross-presentation via the cytosolic pathway involves the export of antigen from endocytic compartments to the cytosol. Therefore, we assessed the ability of iDCs to perform antigen export using a cytofluorimetry-based assay (Figure 37A). Notably, after 90 minutes of incubation with β-lactamase, approximately 80% of CCF4-loaded iDCs expressed cleaved CCF4. Therefore, iDCs could take up β-lactamase and efficiently export it to the cytoplasm, leading to the generation of cleaved CCF4. We also confirmed that iDCs express genes involved in the cross-presentation pathway, such as Cybb, Atg7, Tap1, and Tap2 (Figure 37B).

We assessed whether iDCs were capable of cross-presenting antigens to CD8+ T cells. To do this, we assessed cross-presentation of OVA to MHC-I molecules by co-culturing iDCs with B3Z T cell hybridoma cells expressing p-galactosidase under the control of the IL-2 promoter (Figure 38A, left panel). We found that iDCs could induce antigen-specific T cell activation in a concentration-dependent manner. Furthermore, increased B3Z T cell activation was observed after TLR3 stimulation with polyI:C but not LPS (Figure 38A, right panel). Accordingly, maturation of cDC1 with polyI:C has been reported to enhance the MHC-I cross-presentation process (28). Furthermore, cross-presentation was also assessed using MHC class I restricted ovalbumin-specific T cells (OT-I cells) isolated from lymph nodes and spleen of OT-I Rag2 KO mice (19). In this model, T cells respond to the processed antigenic peptide (OVA 257-264) when displayed in the context of MHC-I DCs. Therefore, OT-I CD8 T cells were co-cultured with iDCs in the presence of ovalbumin (OVA) protein and polyI:C stimulation (Figure 38B). Functional DCs are able to capture the exogenous protein, process it, and cross-present the processed antigenic peptide in the context of MHC-I, inducing CD8+ T cell activation. Induced CD8+ T cell proliferation was measured by CFSE dilution and the activation of the T cell activation marker CD44 after 4 days of co-culture. Notably, in the presence of OVA protein, 11.3±1.13% of D8+ cT cells diluted CFSE and upregulated CD44 expression when cocultured with iDC, respectively (Figure 38B). Splenic MHC-II+CD11c+ DC were used as controls and generated 18.05±0.78% of CD44+ and proliferating T cells.

Human dermal fibroblasts (HDFs) were transduced with PIB (Figure 39A). Importantly, morphological alterations were observed when PIB TFs were introduced into HDFs. Three days after transduction, HDFs were observed to lose their characteristic bipolar and elongated shapes and acquire a stellate-like morphology (Figures 39B and 39C). Furthermore, the expression of typical DC surface markers was evaluated. PIB-transduced BJ human foreskin fibroblasts express HLA-DR and CLEC9A molecules, known human-specific DC markers (Figure 40), suggesting that the PIB combination of DC-inducing factors is conserved between mouse and human and is sufficient to generate human iDCs.

We assessed whether human iDCs could take up particles by incubating them with 1 pm FITC-labeled latex beads. After incubation, PIB-transduced HDFs contained numerous fluorescent beads in the cytoplasm (Figure 41A), suggesting that iDCs had established competence for phagocytosis. Furthermore, we assessed the ability to take up proteins by incubating iDCs with AlexaFluor647-labeled ovalbumin (Figure 41B). After incubation at 37°C, 1.2% of PIB-transduced HDFs contained labeled protein, suggesting that iDCs can actively take up proteins.

We assessed whether cancer cells would acquire DC phenotypic traits after transduction with PU.1, IRF8, and BATF3. Notably, 2.13% of PIB-transduced lung cancer cells (3LL cell line) expressed MHC-I molecules and 2.33% co-expressed MHC-II and CLEC9A on the cell surface 8 days after Dox addition (Figure 42). Similarly, 26% of PIB-transduced B16 melanoma cancer cells expressed CLEC9A, while 1.04% of cells co-expressed it with MHC-II molecules (Figure 43). These results suggest that it is possible to induce the DC phenotype in cancer cells using PIB factors.

The coding regions of PU.1, IRF8, and BATF3 were cloned into polycistronic inducible lentiviral vectors expressing the three nucleic acid sequences, each separated by 2A peptide sequences (Figure 44A). The 3 TFs were included in different orders, PU.1, IRF8, and BATF3 (PIB) or IRF8, PU.1, and BATF3 (IPB). Impressively, Clec9a reporter activation was observed in 10.8% and 6.6% of MEFs transduced with the polycistronic vectors (PIB and IPB, respectively). In contrast, only 1.9% of tdTomato+ cells were observed in MEFs transduced with lentiviral vectors encoding individual factors (Figures 44B and 44C). As expected, delivery of PIB factors in polycistronic vectors increased reprogramming efficiency up to sixfold.

The coding regions of each candidate TF were individually cloned into an inducible lentiviral vector pFUW-TetO (6) in which TF expression is under the control of the tetracycline operator and a minimal CMV promoter. A previously described lentiviral vector containing the tetracycline reverse transactivator M2rtTA under the control of a constitutively active human ubiquitin C promoter (FUW-M2rtTA) was used in combination. Human embryonic kidney (HEK) 293T cells were transfected with a mixture of plasmids encoding TFs, packaging constructs, and the VSV-G envelope protein. Viral supernatants were harvested after 36, 48, and 60 hours, filtered (0.45 pm, Corning), and used freshly or concentrated 40-fold with Amicon ultracentrifugal filters (Millipore).

Polypeptide variants or family members having the same or similar activity as the reference polypeptide encoded by the sequences provided in the sequence listing may be used in the compositions, methods, and kits described herein. Generally, variants of a particular polypeptide encoding a DC-inducing factor for use in the compositions, methods, and kits described herein will have at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more sequence identity to that particular reference polynucleotide or polypeptide as determined by the sequence alignment programs and parameters described herein and known to those of skill in the art.

The Homo sapiens basic leucine zipper ATF-like transcription factor (BATF3), mRNA (SEQ. ID. 1) and a codon optimized, or different codons encoding the same amino acids, are naturally also contemplated as covered by the nucleic acid reference as set forth herein.

The Homo sapiens Spi-1 proto-oncogene (PU.1), mRNA (SEQ. ID. 7) and a codon optimized, or different codons encoding the same amino acids, are naturally also contemplated as covered by the nucleic acid reference as set forth herein.

Homo sapiens interferon regulatory factor 8 (IRF8) mRNA (SEQ. ID. 5) and a codon optimized, or different codons encoding the same amino acids, are naturally also contemplated as covered by the nucleic acid reference as set forth herein.

Homo sapiens transcription factor 4 (TCF4) mRNA (SEQ. ID. 13) and a codon optimized, or different codons encoding the same amino acids, are naturally also contemplated as covered by the nucleic acid reference as set forth herein.

Also provided herein, in various aspects of the compositions and methods, are isolated amino acid sequences and isolated DNA or RNA nucleic acid sequences encoding one or more DC-inducing factors for use in the manufacture of iDCs.

In some embodiments of the compositions and methods described herein, the nucleic acid sequence or construct encoding the DC-inducing factor(s), such as PU.1, IRF8, BATF3, and TCF4, is inserted or operably linked into an expression vector suitable for transfection of cells using conventional molecular biology techniques. As used herein, a "vector" refers to a nucleic acid molecule, such as a dsDNA molecule that provides a useful biological or biochemical property to an inserted nucleotide sequence, such as the nucleic acid constructs or replacement cassettes described herein. Examples include plasmids, phages, autonomously replicating sequences (ARS), centromeres, and other sequences that can replicate or be replicated in vitro or in a host cell, or transport a desired nucleic acid segment to a desired location within a host cell. A vector may have one or more restriction endonuclease recognition sites (either type I, II, or IIs) at which sequences can be cut in a determinable manner without loss of an essential biological function of the vector, and into which a nucleic acid fragment can be spliced or inserted to achieve replication and cloning. Vectors may also comprise one or more recombination sites that allow the exchange of nucleic acid sequences between two nucleic acid molecules. Vectors may further provide primer sites, e.g., for PCR, transcription and/or translation initiation and/or regulation sites, recombination signals, replicons, additional selectable markers, etc. A vector may further comprise one or more selectable markers suitable for use in identifying cells transformed with the vector.

In some embodiments of the compositions and methods described herein, the expression vector is a viral vector. Some viral-mediated expression methods employ retrovirus, adenovirus, lentivirus, herpesvirus, poxvirus, and adeno-associated virus (AAV) vectors, and such expression methods have been used in gene delivery and are well known in the art.

In some embodiments of the compositions and methods described herein, the viral vector is a retrovirus. Retroviruses provide a convenient platform for gene delivery. A selected gene can be inserted into a vector and packaged into retroviral particles using techniques known in the art. The recombinant virus can then be isolated and administered to target cells in the subject, either in vivo or ex vivo. Various retroviral systems have been described. See, e.g., U.S. Patent No. 5,219,740; Miller and Rosman (1989) BioTechniques 7:980-90; Miller, A. D. (1990) Human Gene Therapy 1:5-14; Scarpa et al. (1991) Virology 180:849-52; Burns et al. (1993) Proc. Nati. Acad. Sci. USA 90:8033-37; Boris-Lawrie and Temin (1993)Curr. Opin. Genet. Develop. 3:102-09. In some embodiments of the compositions and methods described herein, the retrovirus is replication-deficient. Retroviral vector systems take advantage of the fact that a minimal vector containing the 5' and 3' LTRs and the packaging signal are sufficient to allow packaging, infection, and integration of the vector into target cells, provided that the viral structural proteins are delivered in trans into the packaging cell line. Key advantages of retroviral vectors for gene transfer include efficient infection and gene expression in most cell types, precise integration of a single copy of vector into the chromosomal DNA of the target cell, and ease of manipulation of the retroviral genome.

In some embodiments of the compositions and methods described herein, the viral vector is an adenovirus-based expression vector. Unlike retroviruses, which integrate into the host genome, adenoviruses persist extrachromosomally, thus minimizing the risks associated with insertional mutagenesis (Haj-Ahmad and Graham (1986)J. Virol.57:267-74; Bett et al. (1993)J. Virol.67:5911-21; Mittereder et al. (1994)Human Gene Therapy5:717-29; Seth et al. (1994)J. Virol.68:933-40; Barr et al. (1994)Gene Therapy1:51-58; Berkner, K. L. (1988)BioTechniques6:616-29; and Rich et al. (1993)Human Gene Therapy4:461-76). Adenoviral vectors infect a wide variety of cells, have a broad host range, exhibit high infectivity efficiencies, direct expression of heterologous genes at high levels, and achieve long-term expression of those genes in vivo. The virus is fully infectious as a cell-free virion, so injection of producer cell lines is not necessary. Regarding safety, adenovirus is not associated with severe human pathology, and recombinant vectors derived from the virus can be rendered replication-defective by deletions in the early 1 ("E1") region of the viral genome. Adenovirus can also be produced in large quantities with relative ease. Adenoviral vectors for use in the compositions, methods, and kits described herein may be derived from any of the various adenoviral serotypes, including, without limitation, any of the more than 40 strains of adenovirus serotypes, such as serotypes 2, 5, 12, 40, and 41. The adenoviral vectors used herein are preferably replication-deficient and contain the DC-inducing factor of interest operably linked to a suitable promoter.

In some embodiments of the compositions and methods described herein, nucleic acid sequences encoding DC-inducing factor(s), such as PU.1, IRF8, BATF3, and TCF4, are introduced or delivered using one or more inducible lentiviral vectors. Controlling the expression of DC-inducing factors delivered using one or more inducible lentiviral vectors can be achieved, in some embodiments, by contacting a cell having at least one DC-inducing factor in an expression vector under the control of, or operably linked to, an inducible promoter, with a regulatory agent (e.g., doxycycline) or other inducing agent. When some types of inducible lentiviral vectors are used, contacting said cell with an inducing agent induces expression of the DC-inducing factors, while withdrawal of the regulatory agent inhibits expression. When other types of inducible lentiviral vectors are used, the presence of the regulatory agent inhibits expression, while removal of the regulatory agent allows expression. As used herein, the term "induction of expression" refers to the expression of a gene, such as a DC-inducing factor encoded by an inducible viral vector, in the presence of an inducing agent, for example, or in the presence of one or more agents or factors that cause endogenous expression of the gene in a cell.

In some embodiments of the aspects described herein, a doxycycline (Dox)-inducible lentiviral system is used. Unlike retroviruses, lentiviruses can transduce quiescent cells, making them suitable for transducing a wider variety of hematopoietic cell types. For example, the pFUW-tetO lentivirus system has been shown to transduce primary hematopoietic progenitor cells with high efficiency.

In some embodiments of the methods described herein, nucleic acid sequences encoding DC-inducing factor(s), such as PU.1 (SEQ. ID. 7, SEQ. ID. 8), IRF8 (SEQ. ID. 5, SEQ. ID. 6), BATF3 (SEQ. ID. 1, SEQ. ID. 2), and/or TCF4 (SEQ. ID. 13, SEQ. ID. 14), are introduced or delivered using a non-integrating vector (e.g., adenovirus). While integrating vectors, such as retroviral vectors, are incorporated into the host cell genome and can potentially disrupt normal gene function, non-integrating vectors control the expression of a gene product by extrachromosomal transcription. Since non-integrating vectors do not become part of the host genome, non-integrating vectors tend to express a nucleic acid transiently in a population of cells. This is due in part to the fact that non-integrating vectors often become replication-deficient. Therefore, non-integrating vectors have several advantages over retroviral vectors including, but not limited to: (1) no alteration of the host genome, (2) transient expression, and (3) no remaining viral integration products. Some non-limiting examples of non-integrating vectors for use with the methods described herein include adenovirus, baculovirus, alphavirus, picornavirus, and vaccinia virus. In some embodiments of the methods described herein, the non-integrating viral vector is an adenovirus. Other advantages of non-integrating viral vectors include the ability to produce them at high titers, their stability in vivo, and their efficient infection of host cells.

Nucleic acid constructs and vectors for use in generating iDCs in the compositions and methods described herein may further comprise, in some embodiments, one or more sequences encoding selection markers for positive and negative selection of cells. Such selection marker sequences typically can provide antibiotic resistance or sensitivity properties not normally found in cells in the absence of the introduction of the nucleic acid construct. A selectable marker can be used in conjunction with a selection agent, such as an antibiotic, to select in culture for cells that express the inserted nucleic acid construct. Sequences encoding positive selection markers generally provide antibiotic resistance, i.e., when the positive selection marker sequence is present in the genome of a cell, the cell is sensitive to the antibiotic or agent. Sequences encoding negative selection markers generally provide sensitivity to an antibiotic or agent, i.e., when the negative selection marker is present in the genome of a cell, the cell is sensitive to the antibiotic or agent.

The nucleic acid constructs and vectors for use in making iDCs in the compositions and methods described herein may further comprise, in some embodiments, other nucleic acid elements for regulation, expression, stabilization of the construct or other genetic elements of the vector, for example, promoters, enhancers, TATA box, ribosome binding sites, IRES, as known to one of skill in the art.

In some embodiments of the compositions and methods described herein, the DC-inducing factor(s), such as PU.1 (SEQ. ID. 7, SEQ. ID. 8), IRF8 (SEQ. ID. 5, SEQ. ID. 6), BATF3 (SEQ. ID. 1, SEQ. ID. 2), and/or TCF4 (SEQ. ID. 13, SEQ. ID. 14), are provided as synthetic modified RNAs, or are introduced or delivered into a cell as a synthetic modified RNA, as described in U.S. patent publication US 2012/046346 A1. In those embodiments where synthetic modified RNAs are used to reprogram cells to iDCs according to the methods described herein, the methods may involve repeated contacting of the cells or involve repeated transfections of the synthetic modified RNAs encoding DC-inducing factors, such as, for example, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 25, at least 30 or more transfections.

In addition to one or more modified nucleosides, the modified mRNAs for use in the compositions, methods, and kits described herein may comprise any additional modifications known to one of skill in the art and as described in U.S. patent publications US 2012/0046346 A1 and US 2012/251618 A1, and PCT publication WO 2012/019168. Such other components include, for example, a 5' cap (e.g., the anti-reverse cap analog (ARCA) cap, which contains a guanine-guanine 5'-5'-triphosphate linkage where one guanine contains an N7-methyl group as well as a 3'-O-methyl group; caps created using the recombinant vaccinia virus capping enzyme and the recombinant 2'-O-methyltransferase enzyme, which can create a canonical 5'-triphosphate linkage between the 5'-most nucleotide of an mRNA and a guanine nucleotide where the guanine contains an N7 methylation and the final 5' nucleotide contains a 2'-O-methyl generating the Cap1 structure); a poly(A) tail (e.g., a poly-A tail more than 30 nucleotides in length, more than 35 nucleotides in length, at least 40 nucleotides, at least 45 nucleotides, at least 55 nucleotides, at least 60 nucleotides, at least 70 nucleotides, at least 80 nucleotides, at least 90 nucleotides, at least 100 nucleotides, at least 200 nucleotides, at least 300 nucleotides, at least 400 nucleotides, at least 500 nucleotides, at least 600 nucleotides, at least 700 nucleotides, at least 800 nucleotides, at least 900 nucleotides, at least 1000 nucleotides or more); a Kozak sequence; a 3' untranslated region (3' UTR); a 5' untranslated region (5' UTR); one or more intronic nucleotide sequences capable of being cleaved from the nucleic acid, or any combination thereof.

The modified mRNAs for use in the compositions and methods described herein may further comprise an internal ribosome entry site (IRES). An IRES may act as the sole ribosome binding site or may serve as one of multiple ribosome binding sites on an mRNA. An mRNA containing more than one functional ribosome binding site may encode multiple peptides or polypeptides, such as the DC-inducing factors described herein, that are independently translated by ribosomes ("multicistronic mRNA"). When nucleic acids are provided with an IRES, a second translatable region is optionally further provided. Examples of IRES sequences that may be used according to the disclosure include, but are not limited to, those from picornaviruses (e.g., FMDV), plague virus (CFFV), polio virus (PV), encephalomyocarditis virus (ECMV), foot and mouth disease virus (FMDV), hepatitis C virus (HCV), classical swine fever virus (CSFV), murine leukemia virus (MLV), simian immunodeficiency virus (SW), or cricket paralysis virus (CrPV).

In some embodiments of the compositions and methods described herein, the synthetic modified RNA molecule comprises at least one modified nucleoside. In some embodiments of the compositions and methods described herein, the synthetic modified RNA molecule comprises at least two modified nucleosides.

In some embodiments of the compositions and methods described herein, the modified nucleosides are selected from the group consisting of 5-methylcytosine (5mC), N6-methyladenosine (m6A), 3,2'-O-dimethyluridine (m4U), 2-thiouridine (s2U), 2'-fluorouridine, pseudouridine, 2'-O-methyluridine (Um), 2'-deoxyuridine (2'dU), 4-thiouridine (s4U), 5-methyluridine (m5U), 2'-O-methyladenosine (m6A), N6,2'-O-dimethyladenosine (m6Am), N6,N6,2'-O-trimethyladenosine (m62Am), 2'-O-methylcytidine (Cm), 7-methylguanosine (m7G), 2'-O-methylguanosine (Gm), N2,7-dimethylguanosine (m2,7G), N2,N2,7-trimethylguanosine (m2,2,7G), and inosine (I). In some embodiments, the modified nucleosides are 5-methylcytosine (5mC), pseudouracil, or a combination thereof.

Modified mRNAs need not be uniformly modified along the entire length of the molecule. Different nucleotide modifications and/or backbone structures may exist at various positions in the nucleic acid. One of skill in the art will understand that nucleotide analogs or other modification(s) may be found at any position in a nucleic acid so that the function of the nucleic acid is not substantially diminished. A modification may also be a 5' or 3' terminal modification. Nucleic acids may contain at least one and at most 100% modified nucleotides, or any percentage in between, such as at least 50% modified nucleotides, at least 80% modified nucleotides, or at least 90% modified nucleotides.

In some embodiments, it is preferred, but not absolutely necessary, that each occurrence of a given nucleoside in a molecule be modified (e.g., each cytosine is a modified cytosine, e.g., 5-methylcytosine, each uracil is a modified uracil, e.g., pseudouracil, etc.). For example, modified mRNAs can comprise a modified pyrimidine such as uracil or cytosine. In some embodiments, at least 25%, at least 50%, at least 80%, at least 90%, or 100% of the uracil in the nucleic acid is replaced with a modified uracil. It is also contemplated that different occurrences of the same nucleoside may be modified differently in a given synthetic modified RNA molecule. The modified uracil can be replaced by a compound having a single structure, or it can be replaced by a plurality of compounds having different structures (e.g., 2, 3, 4, or more single structures). In some embodiments, at least 25%, at least 50%, at least 80%, at least 90%, or 100% of the cytosine in the nucleic acid can be replaced by a modified cytosine. The modified cytosine can be replaced by a compound having a single structure, or it can be replaced by a plurality of compounds having different structures (e.g., 2, 3, 4, or more single structures) (e.g., some cytosines modified as 5mC, others modified as 2'-O-methylcytosine or another cytosine analog). Such multi-modified synthetic RNA molecules can be produced using a combination or mixture of ribonucleosides comprising all of the desired modified nucleosides, such that when the RNA molecules are synthesized, only the desired modified nucleosides are incorporated into the resulting RNA molecule encoding the DC-inducing factor.

In certain embodiments, it is desirable to intracellularly degrade a modified nucleic acid introduced into the cell, for example, if precise timing of protein production is desired. Therefore, in some embodiments of the compositions and methods described herein, modified nucleic acids comprising a degradation domain are provided herein, which is capable of being targeted within a cell.

While it is understood that iDCs can be generated by administering DC-inducing factors in the form of nucleic acid (DNA or RNA) or amino acid sequences, in some embodiments of the compositions and methods described herein, iDC induction can be induced using other methods, such as, for example, by treating cells with an agent, such as a small molecule or cocktail of small molecules, that induces expression of one or more of the DC-inducing factors.

Detection of the expression of DC-inducing factors introduced into cells or induced in a population of cells using the compositions and methods described herein can be achieved by any of several techniques known to those skilled in the art, including, for example, Western blot analysis, immunocytochemistry, and fluorescence-mediated detection.

In order to distinguish whether a given combination of DC-inducing factors has generated iDCs, one or more DC activities or parameters, such as the differential expression of surface antigens, can be measured. Generation of induced DCs using the compositions, methods, and kits described herein preferably results in the appearance of the cell surface phenotype characteristic of endogenous DCs, such as CLEC9A, MHC-I, MHC-II, CD40, CD80, CD86, CD103, for example.

DCs are most reliably distinguished from other immune cells by their functional behavior. Functional aspects of DC phenotypes, or dendritic cell activities, such as the ability of a dendritic cell to induce antigen-specific T cell responses, can be readily determined by one of skill in the art using routine methods known in the art, and as described herein, for example, in the drawings, i.e., FIGS. 1-44 . In some embodiments of the aspects described herein, functional assays can be used to identify reprogramming factors. For example, in some embodiments, antigen presentation and antigen cross-presentation assays can be used to confirm the induction of antigen-specific T cell responses (antigen-presenting potential) of iDCs generated using the compositions, methods, and kits thereof. Cytokine secretion can be used to confirm the immunomodulatory properties of iDCs generated using the compositions, methods, and kits described herein. The ability of iDCs generated using the compositions, methods and kits described herein to take up particles, proteins and dead cells can be assessed by culturing transduced cells in the presence of labeled beads, ovalbumin or dead cells, followed by flow cytometry analysis, respectively.

As used herein, "cellular parameter," "DC parameter," or "antigen presentation activity" refers to measurable components or qualities of endogenous or naturally occurring DCs, particularly components that can be accurately measured. A cellular parameter can be any measurable parameter related to a cell's phenotype, function, or behavior. Such cellular parameters include changes in the characteristics and markers of a DC or DC population, including, but not limited to, changes in viability, cell growth, expression of one or more or a combination of markers, such as cell surface determinants such as receptors, proteins, including conformational or post-translational modifications thereof, lipids, carbohydrates, organic or inorganic molecules, nucleic acids, e.g., mRNA, DNA, global gene expression patterns, etc. Such cellular parameters can be measured using any of a variety of assays known to one of skill in the art. For example, cell viability and growth can be measured by assays such as trypan blue exclusion, CFSE dilution, and 3H-thymidine incorporation. The expression of protein or polypeptide markers can be measured, for example, using flow cytometric assays, Western blotting techniques, or microscopy methods. Gene expression profiles can be assayed, for example, using RNA sequencing methodologies and quantitative or semi-quantitative real-time PCR assays. A cellular parameter can also refer to a functional parameter or functional activity. Although most cellular parameters will provide a quantitative readout, in some cases a semi-quantitative or qualitative result may be acceptable. Readouts may include a single given value, or they may include the mean, median, or variance. Typically, a range of parameter readout values for each parameter can be obtained from a multiplicity of the same assays. Variability is expected and a range of values will be obtained for each of the test parameter sets using conventional statistical methods and a common statistical method used to provide single values.

In some embodiments of the compositions and methods described herein, additional factors and agents can be used to enhance iDC reprogramming. For example, factors and agents that modify epigenetic pathways can be used to facilitate reprogramming in iDC.

Essentially, any type of primary somatic cell can be used to produce iDCs or reprogram somatic cells to iDCs according to the presently described compositions, methods, and kits. Such primary somatic cell types also include other types of stem cells, including pluripotent stem cells, such as induced pluripotent stem cells (iPS cells); other multipotent stem cells; oligopotent stem cells; and (5) unipotent stem cells. Non-limiting examples of primary somatic cells useful in the various aspects and embodiments of the methods described herein include, but are not limited to, fibroblasts, epithelial, endothelial, neuronal, adipose, cardiac, skeletal muscle, hematopoietic or immune cells, liver, spleen, lung, circulating blood, gastrointestinal, kidney, bone marrow, and pancreatic cells, as well as stem cells from which such cells are derived. The cell may be a primary cell isolated from any somatic tissue, including, but not limited to, spleen, bone marrow, blood, brain, liver, lung, abdomen, stomach, intestine, fat, muscle, uterus, skin, spleen, endocrine organ, bone, etc. The term "somatic cell" further encompasses, in some embodiments, cultured primary cells, provided that the somatic cells are not immortalized. When the cell is maintained under in vitro conditions, conventional tissue culture conditions and methods, known to those skilled in the art, may be used. Methods of isolating and culturing various primary somatic cells are within the skill of one of ordinary skill in the art.

In some embodiments of these aspects and all aspects described herein, the somatic cell is a fibroblast cell.

In some embodiments of these aspects and all aspects described herein, the somatic cell may be a cell of hematopoietic lineage.

In some embodiments of these aspects and all aspects described herein, the somatic cell may be a cancer cell or a tumor cell.

In some embodiments of the compositions and methods described herein, a somatic cell to be reprogrammed or converted into an iDC cell is a cell of hematopoietic origin. As used herein, the terms "hematopoietic-derived cell," "hematopoietic-derived differentiated cell," "hematopoietic lineage cell," and "cell of hematopoietic origin" refer to cells derived from or differentiated from a multipotent hematopoietic stem cell (HSC). Accordingly, hematopoietic lineage cells for use with the compositions, methods, and kits described herein include multipotent, oligopotent, and lineage-restricted hematopoietic progenitor cells, granulocytes (e.g., promyelocytes, neutrophils, eosinophils, basophils), erythrocytes (e.g., reticulocytes, erythrocytes), platelets (e.g., megakaryoblasts, platelet-producing megakaryocytes, platelets), monocytes (e.g., monocytes, macrophages), dendritic cells, and lymphocytes (e.g., T cells, which bear T cell receptors (TCRs), B cells or B cells, which express immunoglobulin and produce antibodies, NK cells, NKT cells, and innate lymphocytes). As used herein, the term "hematopoietic progenitor cells" refers to multipotent, oligopotent, lineage-restricted hematopoietic cells capable of differentiating into two or more cell types of the hematopoietic system, including, but not limited to, granulocytes, monocytes, erythrocytes, megakaryocytes, lymphocytes, B cells, and T cells. Hematopoietic progenitor cells encompass multipotent progenitor cells (MPPs), common myeloid progenitor cells (CMPs), common lymphoid progenitor cells (CLPs), granulocyte-monocyte progenitor cells (GMPs), and premegakaryocyte-erythrocyte progenitor cells. Lineage-restricted hematopoietic progenitor cells include megakaryocyte and erythrocyte progenitor cells (MEP), ProB cells, PreB cells, PreProB cells, ProT cells, double-negative T cells, pro-NK cells, pregranulocyte/macrophage cells, granulocyte/macrophage progenitor cells (GMP), and promast cells (ProMC). A diagram of hematopoietic lineage differentiation is provided in Figure 1.

Cells of hematopoietic origin for use in the compositions and methods described herein may be obtained from any source known to comprise such cells, such as fetal tissues, umbilical cord blood, bone marrow, peripheral blood, mobilized peripheral blood, spleen, liver, thymus, lymph, etc. Cells obtained from these sources may be expanded ex vivo using any method acceptable to those of skill in the art prior to use with the compositions, methods, and kits for producing iDCs described herein. For example, the cells may be separated, fractionated, treated to eliminate specific cell types, or otherwise manipulated to obtain a population of cells for use in the methods described herein using any procedure acceptable to those of skill in the art. Mononuclear lymphocytes can be collected, for example, by repeated lymphocytopheresis using a continuous flow cell separator as described in U.S. Patent No. 4,690,915, or isolated using an affinity purification step of the CLP method, such as flow cytometry using a cytometer, magnetic separation, using antibody or protein coated beads, affinity chromatography or solid support affinity separation where cells are retained on a substrate according to their expression or lack of expression of a specific protein or protein type, or batch purification using one or more antibodies against one or more surface antigens specifically expressed by the cell type of interest. Cells of hematopoietic origin can also be obtained from peripheral blood. Prior to collecting the cells from peripheral blood, the subject can be treated with a cytokine, such as e.g. granulocyte colony-stimulating factor, to promote cell migration from the bone marrow to the blood compartment and/or promote activation and/or proliferation of the population of interest. Any suitable method for identifying surface proteins, for example, can be used to isolate cells of hematopoietic origin from a heterogeneous population. In some embodiments, a clonal population of cells of hematopoietic origin, such as lymphocytes, is obtained. In some embodiments, the cells of hematopoietic origin are not a clonal population.

Furthermore, with respect to the various aspects and embodiments of the compositions and methods described herein, a somatic cell can be obtained from any mammalian species, with non-limiting examples including a murine, bovine, simian, porcine, equine, ovine, or human cell. In some embodiments, the somatic cell is a human cell. In some embodiments, the cell is from a non-human organism, such as a non-human mammal.

In general, the methods for producing iDCs described herein involve the cultivation or expansion of somatic cells, such as cells of hematopoietic origin, in any available culture medium well known to one of skill in the art. Such media include, but are not limited to, Dulbecco's Modified Eagle's Medium (DMEM), DMEM F12 Medium, Eagle's Minimal Essential Medium, F-12K Medium, Iscove's Modified Dulbecco's Medium, RPMI-1640 Medium, and a serum-free medium for DC culture and expansion. Many media are also available as low glucose formulations, with or without sodium. The medium used with the methods described herein may, in some embodiments, be supplemented with one or more immunostimulatory cytokines. Commonly used growth factors include, but are not limited to, G-CSF, GM-CSF, TNF-α, IL-4, Flt-3 ligand, and Kit ligand. Furthermore, in preferred embodiments, the immunostimulatory cytokine is selected from the group consisting of interleukins (e.g., IL-1α, IL-β, IL-2, IL-3, IL-4, IL-6, IL-8, IL-9, IL-10, IL-12, IL-18, IL-19, IL-20), interferons (e.g., IFN-α, IFN-β, IFN-γ), tumor necrosis factor (TNF), transforming growth factor-β (TGF-β), granulocyte colony-stimulating factor (G-CSF), macrophage colony-stimulating factor (M-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), Flt-3 ligand, and kit ligand.

Cells in culture may be maintained in suspension or attached to a solid support, such as extracellular matrix components or seeding on feeder cells, for example. Cells used in the methods described herein may require additional factors that promote their attachment to a solid support, in some embodiments, such as collagen type I and type II, chondroitin sulfate, fibronectin, "superfibronectin" and fibronectin-like polymers, gelatin, poly-D and poly-L-lysine, thrombospondin, and vitronectin. In some embodiments, the cells are suitable for growth in suspension culture. Competent host cells in suspension are generally monodisperse or grow in loose aggregates without substantial aggregation. Suspension-competent host cells include cells that are suitable for suspension culture without adaptation or manipulation (e.g., cells of hematopoietic origin, such as lymphoid cells) and cells that have been rendered suspension-competent by adhesion-dependent cell modification or adaptation (e.g., epithelial cells, fibroblasts).

Those skilled in the art are aware of a variety of means for administering cells to subjects. Such methods may include systemic injection, e.g., intravenous injection, or implantation of cells into a target site in a subject. The cells may be inserted into a delivery device that facilitates their introduction by injection or implantation into the subject. Such delivery devices may include tubing, e.g., catheters, for injecting cells and fluids into the body of a recipient subject. The cells may be prepared for administration in a variety of different ways. For example, the cells may be suspended in a solution or gel or inserted into a support matrix when contained in such a delivery device. The cells may be mixed with a pharmaceutically acceptable carrier or diluent in which the cells remain viable.

Accordingly, cells produced by the methods described herein can be used to prepare cells to treat or alleviate various cancers and tumors, including, but not limited to, breast cancer, prostate cancer, lymphoma, skin cancer, pancreatic cancer, colon cancer, melanoma, malignant melanoma, ovarian cancer, brain cancer, primary brain carcinoma, head and neck cancer, glioma, glioblastoma, liver cancer, bladder cancer, non-small cell lung cancer, head or neck carcinoma, breast carcinoma, ovarian carcinoma, lung carcinoma, small cell lung carcinoma, Wilms tumor, cervical carcinoma, testicular carcinoma, bladder carcinoma, pancreatic carcinoma, stomach carcinoma, colon carcinoma, prostatic carcinoma, genitourinary carcinoma, thyroid carcinoma, esophageal carcinoma, myeloma, multiple myeloma, adrenal carcinoma, renal cell carcinoma, endometrial carcinoma, adrenocortical carcinoma, malignant pancreatic insulinoma, malignant carcinoid carcinoma, choriocarcinoma, mycosis fungoides, malignant hypercalcemia, cervical hyperplasia, leukemia, acute lymphocytic leukemia, chronic lymphocytic leukemia, acute myeloid leukemia, chronic myeloid leukemia, chronic granulocytic leukemia, acute granulocytic leukemia, hairy cell leukemia, neuroblastoma, rhabdomyosarcoma, Kaposi's sarcoma, polycythemia vera, essential thrombocytosis, Hodgkin's disease, non-Hodgkin's lymphoma, soft tissue sarcoma, osteogenic sarcoma, primary macroglobulinemia and retinoblastoma, and the like.

In addition to the foregoing, the methods of the disclosure may be used to prevent or eliminate infections by pathogens known to predispose to certain cancers. Pathogens of particular interest for use in the cancer vaccines provided herein include hepatitis B virus (hepatocellular carcinoma), hepatitis C virus (heptomas), Epstein Barr virus (EBV) (Burkitt's lymphoma, nasopharyngeal cancer, PTLD in immunocompromised individuals), HTLVL (adult T-cell leukemia), oncogenic human papillomavirus types 16, 18, 33, 45 (adult cervical cancer), and the bacterium Helicobacter pylori (gastric B-cell lymphoma). Other medically relevant microorganisms that may serve as antigens in mammals, and more particularly in humans, are extensively described in the literature, e.g., [1] e.g., C. G. A Thomas, Medical Microbiology, Bailliere Tindall, (1983).

In addition to the above, the methods of the invention can be used for viral infections. Exemplary viral pathogens include, but are not limited to, infectious viruses that infect mammals and, more particularly, humans. Examples of infectious viruses include, but are not limited to: Retroviridae (e.g., human immunodeficiency viruses, such as HIV-1 (also called HTLV-III, LAV, or HTLV-III/<l>A<v>, or HIV-III; and other isolates, such as HIV-LP); Picornaviridae (e.g., poliovirus, hepatitis A virus; enterovirus, human coxsackievirus, rhinovirus, echovirus); Calciviridae (e.g., strains causing gastroenteritis); Togaviridae (e.g., equine encephalitis virus, rubella virus); Flaviridae (e.g., dengue virus, encephalitis virus, yellow fever virus); Coronoviridae (e.g., coronaviruses such as SARS coronavirus); Rhabdoviradae (e.g., vesicular stomatitis virus, rabies virus); Filoviridae (e.g., Ebola virus); Paramyxoviridae (e.g., parainfluenza virus, mumps virus, measles virus, respiratory syncytial virus); Orthomyxoviridae (e.g., influenza viruses); Bungaviridae (e.g., Hantaan virus, Bunga virus, phlebovirus, and Nairo virus); Arenaviridae (hemorrhagic fever viruses); Reoviridae (e.g., reoviruses, orbiviruses, and rotaviruses); Birnaviridae; Hepadnaviridae (hepatitis B virus); Parvovirida (parvovirus); Papovaviridae (papillomaviruses, polyoma viruses); Adenoviridae (most adenoviruses); Herpesviridae (herpes simplex viruses (HSV) 1 and 2, varicella-zoster virus, cytomegalovirus (CMV), herpes viruses); P.oxyiridae (variola virus, vaccinia virus, smallpox); and Iridoviridae (e.g., African swine fever virus); and unclassified viruses (e.g., the etiologic agents of spongiform encephalopathies, the hepatitis delta agent (thought to be a defective satellite of hepatitis B virus), the agents of non-A, non-B hepatitis (class I = internally transmitted; class 2 = parenterally transmitted (i.e., hepatitis C); Norwalk and related viruses, and astroviruses).

In addition to the foregoing, the methods of the disclosure may be used to target Gram-negative and Gram-positive bacteria in vertebrate animals. These Gram-positive bacteria include, but are not limited to, Pasteurella sp., Staphylococci sp., and Streptococcus sp. Gram-negative bacteria include, but are not limited to, Escherichia coli, Pseudomonas sp., and Salmonella sp. Specific examples of infectious bacteria include, but are not limited to: Helicobacter pylori, Borella burgdorferi, Legionella pneumophilia, Mycobacteria sp. (e.g. M. tuberculosis, M. avium, M. intracellular, M. kansaii, M. gordonae), Staphylococcus aureus, Neisseria gonorrhoeae, Neisseria meningitidis, Listeria monocytogenes, Streptococcus pyogenes (group A streptococcus), Streptococcus agalactiae (group B streptococcus), Streptococcus (group viridans), Streptococcus faecalis, Streptococcus bovis, Streptococcus (anaerobic species), Streptococcus pneumoniae, Campylobacter sp. pathogenic, Enterococcus sp., Haemophilus influenzae, Bacillus antracis, Corynebacterium diphtheriae, Corynebacterium sp., Erysipelothrix rhusiopathiae, Clostridium perfringers, Clostridium tetani, Enterobacter aerogenes, Klebsiella pneumoniae, Pasturella multocida, Bacteroides sp., Fusobacterium nucleatum, Streptobacillus moniliformis, Treponema pallidium, Treponema pertenue, Leptospira, Rickettsia and Actinomyces israelii.

In addition to the foregoing, the methods of the disclosure may be used to target pathogens including, but not limited to, infectious fungi and parasites that infect mammals, and more particularly humans. Examples of infectious fungi include, but are not limited to: Cryptococcus neoformans, Histoplasma capsulatum, Coccidioides immitis, Blastomyces dermatitidis, Chlamydia trachomatis, and Candida albicans.

In addition to the foregoing, the methods of the disclosure may be used to target parasites such as intracellular parasites and obligate intracellular parasites. Examples of parasites include, but are not limited to, Plasmodium falciparum, Plasmodium ovale, Plasmodium malariae, Plasmodium vivax, Plasmodium knowlesi, Babesia microti, Babesia divergens, Trypanosoma cruzi, Toxoplasma gondii, Trichinella spiralis, Leishmania major, Leishmania donovani, Leishmania braziliensis, Leishmania tropica, Trypanosoma gambiense, Trypanosoma rhodesiense, Wuchereria bancrofti, Brugia malayi, Brugia timori, Ascaris lumbricoides, Onchocerca volvulus, and Schistosoma mansoni.

If modified, the induced dendritic cells can be used to induce a tolerogenic response, including suppression of an existing or future immune response to one or more target antigens. Thus, the induced DCs are useful for treating or preventing an undesirable immune response, including, for example, transplant rejection, graft-versus-host disease, allergies, parasitic diseases, inflammatory diseases, and autoimmune diseases. Examples of transplant rejection that can be treated or prevented according to the present disclosure include rejections associated with bone marrow transplantation and of organs such as heart, liver, pancreas, kidney, lung, eye, skin, etc. Examples of allergies include seasonal respiratory allergies; aeroallergen allergies such as hay fever; allergies treatable by reducing serum IgE and eosinophilia; asthma; eczema; animal allergies, food allergies; latex allergies; dermatitis; or allergies treatable by allergy desensitization. Autoimmune diseases that may be treated or prevented by the present disclosure include, for example, psoriasis, systemic lupus erythematosus, myasthenia gravis, stiff-man syndrome, thyroiditis, Sydenham's chorea, rheumatoid arthritis, diabetes, and multiple sclerosis. Examples of inflammatory diseases include Crohn's disease, chronic inflammatory eye diseases, chronic inflammatory lung diseases, and chronic inflammatory liver diseases, autoimmune hemolytic anemia, idiopathic leukopenia, ulcerative colitis, dermatomyositis, scleroderma, mixed connective tissue disease, irritable bowel syndrome, systemic lupus erythematosus (SLE), multiple sclerosis, myasthenia gravis, Guillain-Barré syndrome (antiphospholipid syndrome), primary myxedema, thyrotoxicosis, pernicious anemia, autoimmune atrophic gastritis, Addison's disease, insulin-dependent diabetes mellitus (IDDM), Goodpasture's syndrome, Behpet's syndrome, Sjogren's syndrome, rheumatoid arthritis, sympathetic ophthalmia, Hashimoto's disease/hypothyroiditis, celiac disease/dermatitis herpetiformis, and demyelinating disease primary biliary cirrhosis, mixed disease connective tissue, chronic active hepatitis, Graves' disease/hyperthyroiditis, scleroderma, chronic idiopathic thrombocytopenic purpura, diabetic neuropathy, and septic shock.

Pharmaceutically acceptable carriers and diluents include saline solutions, aqueous buffer solutions, solvents, and/or dispersion media. The use of such carriers and diluents is well known in the art. The solution is preferably sterile and fluid. Preferably, prior to the introduction of cells, the solution is stable under the conditions of manufacture and storage and is preserved against the contaminating action of microorganisms such as bacteria and fungi by the use of, for example, parabens, chlorobutanol, phenol, ascorbic acid, thimerosal, and the like.

It is preferred that the mode of cell administration be relatively noninvasive, for example, by intravenous injection, pulmonary administration via inhalation, topical administration, or intranasal administration. However, the route of cell administration will depend on the tissue being treated and may include implantation. Methods for cell delivery are known to those skilled in the art and can be extrapolated by one skilled in the art of medicine for use with the methods and compositions described herein.

Mouse embryonic fibroblasts (MEFs) were isolated and purified as follows: Clec9aCre/Cre animals (10) were crossed with Rosa26-stopflox- tdTomato reporter mice (The Jackson Laboratory) to generate Clec9aCre/CreRosatdT°mat°/tdT°mat° (C9A-tdTomato) doubly homozygous mice. C57BL/6 mice, Rag2/OT-II knockout (KO) mice (Rag2KO/OT-II), and Rag2KO/OT-I random transgenic mice were purchased from Charles River and Taconic, respectively (17, 19). All animals were housed in a controlled temperature environment (23 ± 2°C), subject to a fixed 12-h light/dark cycle, with free access to food and water.

Primary MEF cultures were isolated from E13.5 embryos of C9A-tdTomato or C57BL/6 mice (6, 10). The head, fetal liver, and all internal organs were removed, and the remaining tissue was mechanically dissociated. Dissected tissue was enzymatically digested using a 0.12% trypsin/0.1 mM ethylenediaminetetraacetic acid (EDTA) solution (3 ml per embryo) and incubated at 37°C for 15 min. An additional 3 ml of the same solution was added per embryo, followed by another 15-min incubation period. A single-cell suspension was obtained and plated on 10-cm tissue culture dishes coated with 0.1% gelatin in growth medium. Cells were cultured for 2–3 days to confluence, dissociated with Tryple Express, and frozen in 10% fetal bovine serum (FBS) in dimethyl sulfoxide (DMSO). Before seeding for lentiviral transduction, MEFs were sorted to remove residual CD45+ and tdTomato+ cells that might represent cells with hematopoietic potential. MEFs used for screening and subsequent experiments were tdTomato-CD45- cells with a purity of 99.8% and expanded up to 4 passages.

HEK293T cells, MEFs, and human dermal fibroblasts (HDFs, ScienCell) were maintained in growth medium [Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% (v/v) FBS, 2 mM L-glutamine, and antibiotics (10 pg/ml penicillin and streptomycin)], OP-9 and OP-9-DL1 cell lines were cultured in minimal essential medium (MEM) alpha containing 20% FBS, 1 mM L-glutamine, and penicillin/streptomycin (10 pg/ml). OP-9 and OP-9-DL1 were routinely passaged at 80% confluence. All cells were maintained at 37°C and 5% (v/v) CO2. All tissue culture reagents were from Thermo Fisher Scientific unless otherwise stated.

Viral transduction and reprogramming experiments were performed as follows: C9A-tdTomato MEFs were seeded at a density of 40,000 cells per well in 0.1% gelatin-coated 6-well plates. Cells were incubated overnight with a 1:1 ratio of FUW-TetO-TF and FUW-M2rtTA lentiviral particles in growth medium supplemented with 8 pg/ml polybrene. When assaying TF combinations, equal MOIs of each individual viral particle were applied. Cells were transduced twice on consecutive days, and after overnight incubation, the medium was replaced with fresh growth medium. After the second transduction, the growth medium was supplemented with doxycycline (1 pg/ml) - day 0. The medium was changed every 2-3 days for the duration of the cultures. Emerging tdTomato+ cells were analyzed 1–15 days post-transduction. Variations in culture conditions were applied where indicated, specifically RPMI-1640, lipopolysaccharide (LPS, 100 ng/ml, Sigma), 2-mercaptoethanol (1x104 pM; 2-ME), L-glutamine (2 pmol/ml), γ M-CSF (10 ng/ml, STEMCELL Technologies), IL-4 (20 ng/ml, STEMCELL Technologies), and Flt3l (100 ng/ml, STEMCELL Technologies).

Fluorescence microscopy and immunofluorescence were assessed as follows: C9A-driven tdTomato in transduced MEFs and HDFs were directly visualized in 6-well plates using an inverted microscope (Zeiss AxioVert 200M), and images were processed using AxioVision and Adobe Photoshop software. DAPI (4',6-diamidino-2-phenylindole, 1 pg/ml, Sigma) and phalloidin (50 pg/ml, Sigma) were used to stain nuclei and F-actin, respectively. For time-lapse microscopy, fluorescent images were acquired after adding Dox every 1 h for 6 days and 4 h using an INCELL 2200 analyzer (GE Healthcare). Movies were generated using ImageJ software (NIH).

Flow cytometry analysis was performed as follows: transduced C9A-tdTomato MEFs or transduced human fibroblasts were dissociated with TrypLE Express, resuspended in 200 μl of PBS/5% FBS, and maintained at 4°C prior to analysis on a BD Accuri C6 flow cytometer (BD Biosciences). Sample acquisition was performed using the 3-blue-1-red setting (filter 533/30 in FL1; 585/40 in FL2, 670<l>P in FL3, and 675/25 in FL4). tdTomato fluorescence was analyzed in the FL2 channel. For analysis of cell surface marker CD45 or MHC-II expression, dissociated cells were incubated with rat anti-mouse CD45 APC-Cy7 or rat anti-mouse I-A/I-E-Alexa Fluor 647 diluted in 5% FBS/PBS at 4°C for 30 min in the presence of rat serum (1/100, GeneTex) to block nonspecific binding. Cells were washed with 5% FBS/PBS, resuspended in 5% FBS/PBS, and analyzed on a BD Accuri C6 flow cytometer. CD45 APC-Cy7 and I-A/I-E Alexa Fluor 647 fluorescence was analyzed in channel FL4. For combined analysis of cell surface expression of MHCII, CD80, and CD86, dissociated cells were stained with Alexa Fluor 647-rat anti-mouse I-A/I-E antibody, BV650-rat anti-mouse CD80 antibody, and PE-CY7-rat anti-mouse CD86 antibody and analyzed on BD FACSAria III (BD Biosciences). For analysis of transduced HDFs, dissociated cells were stained with APC-mouse anti-human CLEC9A antibody and FITC-mouse anti-human HLA-DR antibody. To assess CD4+ and CD8+ T cell proliferation and activation after 7 days of coculture with ACP, carboxyfluorescein succinimidyl ester (CFSE)-labeled T cells were incubated with PE-rat anti-mouse CD44 antibody and analyzed on a BD Accuri C6. Flow cytometry data were analyzed using FlowJo software (FLOWJO, LLC, version 7.6).

Fluorescence-activated cell sorting (FACS) was performed as follows: to purify C9A-tdTomato MEFs, cells were incubated at 4°C for 30 min with APC-Cy7-anti-CD45 antibody diluted in 5% FBS in PBS. MEFs were subsequently washed with 5% FBS in PBS, resuspended in 5% FBS in PBS, and tdTomato- CD45- MEFs were purified on BD FACSAria III. Where described, tdTomato+ cells were purified using BD FACSAria III and cultured in the absence or presence of doxycycline. For splenic DC isolation, splenic cells were incubated with Alexa Fluor 647-rat anti-mouse I-A/I-E antibody, FITC-rat anti-mouse CD11 c antibody, and APC-Cy7-rat anti-mouse CD8a antibody. CD11c+MHCII+CD8a+ splenic DCs were purified on a BD FACSAria III (BD Biosciences). FACS data were processed using FlowJo software.

GPSforGenes software was used to calculate the DC lineage specificity of the Pu.1, Irf8, and Batf3 combination. Gene expression data were downloaded from the BioGPS database (GeneAtlas MOE430), transformed to log space, and normalized to bring expression values within the 0–1 range for each gene in different samples. The resulting data were then searched for samples with the highest average expression for Pu.1+Irf8+Batf3.

Single-cell mRNAseq analysis was performed as follows: single-end reads were matched to the mouse genome mm10 (Ensembl annotation, version 89) using Salmon v0.8.1 with k=21. The resulting TPMs were imported into R using the tximport library and converted to mRNA counts using the Census algorithm implemented in the monocle library. The Scatter library was used to discard cells and genes that did not pass the quality control threshold. The following QC criteria were used: 1) library size per cell; 2) number of genes detected in each single cell; 3) percentage of counts in mitochondrial genes. Of the 192 cells initially profiled, 163 single cells passed quality control filters and were used for analysis. Custom R scripts were used to perform t-distributed stochastic neighbor embedding (tSNE) (Monocle and scatter packages), principal component analysis (PCA) (Monocle and scatter packages), hierarchical clustering (SC3 package), analysis of variance, and to construct heatmaps, boxplots, scatterplots, violin plots, dendrograms, bar charts, and histograms. Typically, the ggplot2, gplots, graphics, and pheatmap packages were used to generate data graphics.

Differential expression analysis was performed using the Monocle package, selecting genes with a BH-corrected p-value less than 0.05. The resulting genes were then variance filtered (genes with variance >= 1 were selected under all conditions). Finally, the resulting 6,525 genes were grouped into four distinct clusters based on hierarchical clustering.

Endogenous gene expression was determined using STAR v2.5.3a with default settings. A window based on -10 kb, gene start and gene end, 10 kb, corresponding to the 5' and 3' untranslated regions (UTRs), was defined and used to calculate the number of reads in the UTRs using multicov from bedtools v2.27.0.

The DC lineage of iDCs was determined using Schlitzer’s cDC1 and cDC2 gene signatures (11). Most genes were highly expressed in MEFs and across all of our conditions. These genes were discarded. Additionally, as sDC cells were purified for the cDC1 markers CD11c, MHC-II, and CD8a, genes that were expressed in sDCs but were also present in the cDC2 signature list were discarded. The gene lists in cDC1/cDC2 were then used to perform hierarchical clustering. Next, only clusters where median gene expression in MEF cells was significantly lower compared to day 3, day 7, and day 9 were selected. In addition to that, for the gene list in cDC2, in addition to the procedure described above, gene clusters with significantly higher median gene expression in sDC cells compared to day 3, day 7, and day 9 were also discarded. The median gene expression of each selected gene was then calculated for each particular condition. Finally, the median gene expression across all gene signatures in pre-separated cDC1 and cDC2 defined by Schlitzer et al.

The Monocle package, an algorithm that uses independent component analysis with a minimum spanning tree to connect cells along a pseudotemporally ordered path, was used to order cells in a pseudotime course during reprogramming of MEF cells to iDCs. Monocle analysis was performed based on the genes in cDC1 and cDC2 from Schlitzer, 2015 (11) as genes that define a cell's progress, as this was an alternative approach to demonstrate that day 9 cells are cDC1-like cells. The resulting trajectories were visualized using Monocle functions. Since individual cell trajectories included branches, branched expression analysis modeling (BEAM), a special statistical test implemented in the Monocle package, was used to find differentially expressed genes between branches. As an alternative approach to the Monocle branching algorithm, TSCAN, which combines clustering with pseudotime analysis, was used by constructing a minimum spanning tree to connect the clusters. TSCAN, unlike Monocle, can use all genes to sort cells.

Gene ontology (biological process, cellular component, and KEGG pathway) was performed using Enrichr (http://amp.pharm.mssm.edu/Enrichr/) and the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (david.ncifcrf.gov/).

MicroRNA target interaction analysis was performed using miRTarBase 2017, Enrichr website (http://amp.pharm.mssm.edu/Enrichr/).

Mouse phenotype analysis was performed using Network2canvas (http://www.maayanlab.net/N2C/#.WmRvOjLc8yk).

Gene set enrichment analysis (GSEA) was performed across all possible conditions and states against C7: immunosignatures from the Molecular Signatures Database (MSigDB) and NetPath.

TF network analysis was calculated using a pairwise correlation matrix using Pearson's correlation. TFs were selected based on the DBD: Transcription Factor Prediction Database (http://www.transcriptionfactor.org/) in mice. As the aim was to investigate the change from mef condition to day 9, three lists were created corresponding to the change from mef to day 3; from day 3 to day 7; from day 7 to day 9, and included only those TFs with logFC=0.5 for the condition pair. Then, from the TFs defined based on logFC for three condition pairs, TFs with a Pearson correlation greater than 0.35 with at least five other TFs were selected. Considering that such results could be obtained by chance, permutations were used to determine the probability of TFs passing this threshold by chance. 100 permutations were performed, all of which resulted in 0 TFs passing this threshold. The graph.adjacency() function from the igraph R package was used, which considered the Pearson pairwise correlation matrix for the selected TFs for 3 pairs of conditions.

Methylcellulose clonogenic assays were performed as follows: PIB-transduced MEFs at days 3, 5, 7, 10, and 25 after Dox addition were analyzed in 1% methylcellulose medium (Methocult M3434, Stem Cell Technologies). Separated sDC1 (MHC-II+CD11c+CD8a+) as well as unseparated splenocytes and bone marrow cells were used as controls. Hematopoietic colonies were scored and counted after 7–10 days of culture in 5% CO2 at 37°C.

The bead incorporation assay was evaluated as follows: transduced C9A-tdTomato MEF cultures or transduced HDFs were incubated with 2.5% yellow-green fluorescence-coupled solid latex beads (carboxylate-modified polystyrene, Sigma) at a 1:1000 ratio in growth medium. Sixteen hours later, cells were washed twice in 5% FBS in PBS and analyzed using an inverted microscope. DAPI (1 pg/ml, Sigma) was used for nuclear staining.

Labeled ovalbumin incorporation was assessed as follows: transduced MEFs and human fibroblast cultures were incubated with Alexa647-labeled ovalbumin (Life Technologies) for 20 minutes at 37°C or 4°C. After washing with 5% FBS in PBS, cells were analyzed on BD Accuri C6.

Dead cell uptake was assessed as follows: HEK293T cells were exposed to ultraviolet (UV) irradiation to induce cell death and labeled with the Claret Fluorescent Cell Linker Kit (Sigma) using the CellVue® Far Red Fluorescent Cell Linker Kit, according to the manufacturer’s instructions. Transduced MEFs were incubated with Far Red-labeled dead cells overnight and analyzed on a BD Accuri C6.

The inflammatory cytokine assay was performed as follows: the levels of the cytokines interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-12p70 (IL-12p70), interferon-γ (IFN-γ), and tumor necrosis factor (TNF) were assessed in iDC culture supernatants 10 days after Dox supplementation. On day 9, 100 ng/ml LPS or 25 pg/ml polyinosinic-polycytidylic acid (Polyl:C) (Invivogen) was added for overnight stimulation. 50 μl of culture supernatants was collected from a 6-well plate and analyzed using the CBA Mouse Inflammation Kit (BD Biosciences) according to the manufacturer's instructions. Acquisition was performed using a BD Accuri C6, and data were analyzed using FCAP array software, version 3.0 (BD Biosciences). The detection limit in CBA was: IL-6, 20.91 pg/ml; IL-10, 10.55 pg/ml; IFN-γ, 18.2 pg/ml; TNF, 18.13 pg/ml; IL-12p70, 20.05 pg/ml.

Splenic DC isolation was assessed as follows: freshly isolated spleens were homogenized using the ground ends of two sterile slides. Cells were harvested in PBS supplemented with 2% FBS and filtered through a 70 µm cell strainer (BD Biosciences). Red blood cells were lysed with BD Pharm Lyse (BD Biosciences) for 8 min at room temperature. MHC-II+<c>D11<c>+ DC were FACS purified (<b>D FACSAria III, BD Biosciences) and immediately used for antigen presentation assays.

CD4+ T cell isolation and antigen presentation assays were assessed as follows: CD4+ T cells from the spleens of Rag2KO/OT-II mice were enriched using the Dynabeads Intact Mouse CD4 Cell Kit (BD Biosciences) according to the manufacturer’s instructions. Enriched CD4+ T cells were labeled with 5 pM CFSE at room temperature for 10 min, washed, and counted before being cultured with APCs. iDC cultures at day 8 after Dox addition or splenic CD11c+ MHC-II+ DC cells were incubated with OVA protein (10 pg/ml) or OVA323-339 peptide (10 pg/ml) in the presence or absence of 100 ng/ml LPS and cocultured with intact CFSE-labeled OT-II CD4+ T cells. iDC cultures (20,000 cells) or 20,000 splenic CD11c+ MHC-II+ DC were incubated with 20,000 CFSE-labeled CD4+ T cells in 96-well round-bottom tissue culture plates. T cell proliferation (CFSE staining dilution) and activation (CD44 expression) were assessed by flow cytometry after 7 days of coculture.

CD8+ T cell isolation and antigen cross-presentation were assessed as follows: CD8+ T cells from the spleens of Rag2KO/OT-I mice were enriched using the Dynabeads Intact Mouse CD8 Cell Kit (BD Biosciences) according to the manufacturer’s instructions. Enriched CD8+ T cells were labeled with 5 pM CFSE at room temperature for 10 min, washed, and counted before being cultured with APCs. iDC cultures at day 8 after Dox addition or splenic CD11c+ MHC-II+ DC cells were incubated with OVA protein (10 pg/ml) in the presence of 25 pg/ml polyl:C and cocultured with intact CFSE-labeled OT-I CD8+ T cells. iDC cultures (20,000 cells) or 20,000 splenic CD11c+ MHC-II+ DC were incubated with 20,000 CFSE-labeled CD8+ T cells in 96-well round-bottom tissue culture plates. T cell proliferation (CFSE staining dilution) and activation (CD44 expression) were assessed by flow cytometry after 4 days of coculture.

Hybridoma cross-presentation assays were performed as follows: PIB-transduced Clec9atdTomato MEFs at day 16 after Dox addition were dissociated with TrypLE Express, resuspended in growth medium, and incubated for 4 h with different concentrations of OVA protein. After extensive washing, PIB-transduced MEFs (100,000 cells) were co-cultured with 100,000 B3Z cells in 96-well round-bottom tissue culture plates in the presence or absence of 100 ng/ml LPS or 25 pg/ml PIC. After 18 h, cells were lysed in a buffer containing 0.125% Nonidet P-40 (substitute), 9 mM MgCl2, and a CPRG colorimetric substrate of p-galactosidase. p-galactosidase activity was measured in a microplate reader as optical density at 590 nm.

The efficiency of antigen export to the cytosol by Clec9a- tdTomato+ cells was analyzed by cytofluorimetry-based assay. Briefly, GDP-transduced E cells at day 16 after Dox addition were dissociated with TrypLE Express, resuspended in loading buffer, and loaded with 1 pM CCF4-AM for 30 min at room temperature. Cells were then washed and incubated with 2 mg/ml β-lactamase at 37°C for 30, 60, and 90 min. To stop the reaction, cells were transferred to ice-cold PBS. Immediately prior to flow cytometry analysis on a BD FACSArialll, cells were stained with the fixable viability dye eFluor 780 (eBioscience). The percentage of live Clec9a-tdTomato+ cells with a high blue-to-green fluorescence ratio (V450/V500) was used as a measure of the efficiency of antigen export to the cytosol.

Comparisons between groups were performed using one-way ANOVA followed by Bonferroni's multiple comparison test using GraphPad Prism 5 software. P values are shown where relevant (*p<0.05; **p<0.01, ***p<0.001, ****p<0.0001).

Table 6 - Primary antibodies used in the analysis

Those skilled in the art will recognize or be able to determine, without using anything more than routine experiments, many equivalents to specific embodiments of the description. The scope of this description is not intended to be limited to the foregoing description, but is set forth in the appended claims.

When singular forms of elements or features are used in the specification of the claims, the plural form is also included, and vice versa, if not specifically excluded. For example, the term "a cell" or "the cell" also includes the plural forms "cells" or "the cells," and vice versa. In the claims, articles such as "a," "an," and "the" may mean one or more than one unless otherwise indicated or otherwise evident from the context. Claims or descriptions that include "or" among one or more members of a group are considered satisfied if one, more than one, or all of the members of the group are present in, employed in, or are otherwise relevant to a given product or process, unless otherwise indicated or otherwise evident from the context. The description includes embodiments in which exactly one member of the group is present in, employed in, or is otherwise relevant to a given product or process. The description also includes embodiments in which more than one, or all, of the group members are present in, employed in, or are otherwise relevant to a given product or process.

Furthermore, it is to be understood that the description encompasses all variations, combinations, and permutations in which one or more limitations, elements, clauses, descriptive terms, etc., of one or more of the claims or relevant portions of the description are introduced into another claim. For example, any claim dependent upon another claim may be modified to include one or more limitations found in any other claim dependent upon the same base claim. Furthermore, where the claims refer to a composition, it is to be understood that these include methods of using the composition for any of the purposes described herein, and that these include methods of making the composition according to any of the methods of making described herein or other methods known in the art, unless otherwise indicated or unless it would be apparent to one skilled in the art that a contradiction or inconsistency may arise.

Where ranges are provided, the endpoints are included. Furthermore, it should be understood that, unless otherwise indicated or otherwise evident from the context and/or the understanding of one skilled in the art, values expressed as ranges may assume any specific value within the ranges set forth in different embodiments of the disclosure, down to the tenth of a unit of the lower limit of the range, unless the context clearly dictates otherwise. It should also be understood that, unless otherwise indicated or otherwise evident from the context and/or the understanding of one skilled in the art, values expressed as ranges may assume any subrange within the given range, wherein the subrange endpoints are expressed to the same degree of precision as the tenth of a unit of the lower limit of the range.

Furthermore, it should be understood that any particular embodiment of the present disclosure may be explicitly excluded from one or more of the claims. Where ranges are given, any value within the range may be explicitly excluded from one or more of the claims. Any embodiment, element, feature, application, or aspect of the compositions and/or methods of the present disclosure may be excluded from one or more claims. For the sake of brevity, not all embodiments in which one or more elements, features, purposes, or aspects are excluded are explicitly set forth herein.

The embodiments of the description described above are combinable.

The following claims further set forth particular embodiments of the present disclosure.

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Claims (14)

1. A construct or vector comprising a combination of at least two polynucleotide sequences encoding at least two transcription factors selected from the group consisting of: BATF3, IRF8 and PU.1, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1. 2. The construct or vector according to claim 1, wherein the at least two transcription factors are encoded by a sequence at least 90%, such as at least 95%, identical to a sequence selected from the group consisting of: to. SEQ. ID. 1 or SEQ. ID. 2 (BATF3), b. SEQ. ID. 5 or SEQ. ID. 6 (IRF8), and c. SEQ. ID. 7 or SEQ. ID. 8 (PU.1). 3. The construct or vector according to any one of the preceding claims, wherein the combination of the at least two transcription factors is in the following sequential order from 5' to 3': PU.1, IRF8, BATF3; or IRF8, PU.1, BATF3. 4. The vector according to any one of the preceding claims, wherein the vector is a viral vector. 5. The vector according to claim 4, wherein the viral vector is selected from the group consisting of: lentiviral, retroviral, adenoviral, herpes viral, smallpox viral and adeno-associated viral vector. 6. A composition comprising a combination of at least two isolated transcription factors encoded by a sequence at least 90% identical to a sequence selected from a list consisting of: BATF3 (SEQ. ID. 1, SEQ. ID. 2), IRF8 (SEQ. ID. 5, SEQ. ID. 6), PU.1 (SEQ. ID. 7, SEQ. ID. 8), TCF4 (SEQ. ID. 13, SEQ. ID. 14), and mixtures thereof, for use in medicine, wherein the at least two transcription factors are bAt F3 and PU.1 or IRF8 and PU.1. 7. A composition comprising a combination of at least two isolated transcription factors encoded by a sequence at least 90% identical to a sequence selected from a list consisting of: BATF3 (SEQ. ID. 1, SEQ. ID. 2), IRF8 (SEQ. ID. 5, SEQ. ID. 6), PU.1 (SEQ. ID. 7, SEQ. ID. 8), TCF4 (SEQ. ID. 13, SEQ. ID. 14), and mixtures thereof, for use in the treatment of a disease selected from the group consisting of: cancer, neurodegenerative diseases and infectious diseases, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1. 8. The composition for use according to claim 7, wherein the cancer is selected from the group consisting of: benign tumor, malignant tumor, early cancer, basal cell carcinoma, cervical dysplasia, soft tissue sarcoma, germ cell tumor, retinoblastoma, Hodgkin's lymphoma, blood cancer, prostate cancer, ovarian cancer, cervical cancer, uterine cancer, vaginal cancer, breast cancer, nasopharyngeal cancer, tracheal cancer, laryngeal cancer, bronchus cancer, bronchiole cancer, lung cancer, hollow organ cancer, esophageal cancer, stomach cancer, bile duct cancer, bowel cancer, colon cancer, colorectal cancer, rectal cancer, bladder cancer, ureter cancer, kidney cancer, liver cancer, gallbladder cancer, spleen cancer, brain cancer, lymphatic system cancer, bone cancer, pancreatic cancer, leukemia, breast cancer, skin or myeloma. 9. A method for reprogramming or inducing a cell into a dendritic cell or antigen-presenting cell, comprising the following steps: a. transducing a cell with one or more vectors comprising at least two polynucleotide sequences encoding at least two transcription factors selected from the group consisting of: BATF3, IRF8 and PU.1, wherein the at least two transcription factors are BATF3 and PU.1 or IRF8 and PU.1; and b. culturing the transduced cell in a cellular medium that favors the growth of dendritic cells or antigen-presenting cells. 10. The method according to claim 9, wherein the at least two transcription factors are selected from the group consisting of: BATF3 and PU.1; IRF8 and PU.1; and BATF3, IRF8 and PU.1. 11. The method according to any one of claims 9 to 10, wherein the combination of at least two isolated transcription factors is in the following sequential order from 5' to 3': PU.1, IRF8, BATF3; or IRF8, PU.1, BATF3. 12. The method according to any one of claims 9 to 11, wherein the transduction step further comprises at least one vector comprising nucleic acids encoding immunostimulatory cytokines and/or siRNAs targeting IL-10. 13. The method according to any one of claims 9 to 12, wherein the cell is selected from the group consisting of: differentiated cell, endoderm-derived cell, mesoderm-derived cell, ectoderm-derived cell, multipotent stem cell including mesenchymal stem cell, hematopoietic stem cell, intestinal stem cell, pluripotent stem cell, human or mouse fibroblast, mammalian umbilical cord stem cell, and cancer cell and cell line. 14. An induced antigen-presenting cell or induced dendritic cell obtained by a method comprising the following steps: a. transducing a cell selected from a list consisting of: stem cell or differentiated cell, and mixtures thereof, such as a cancer cell or cell line, one or more vectors comprising at least two nucleic acid sequences encoding a sequence at least 90% identical, preferably at least 95% identical, to a sequence from a group consisting of SEQ. ID. 1, SEQ. ID. 2, SEQ. ID. 5, SEQ. ID. 6, SEQ. ID. 7, SEQ. ID. 8, SEQ. ID. 13, SEQ. ID. 14, and mixtures thereof; wherein the at least two nucleic acid sequences are BATF3 (SEQ. ID. 1 or SEQ. ID. 2) and PU.1 (SEQ. ID. 7 or SEQ. ID. 8), or IRF8 (SEQ. ID. 5 or SEQ. ID. 6) and PU.1 (SEQ. ID. 7 or SEQ. ID. 8); and b. culturing the transduced cell in a cell medium that favors the growth of dendritic cells or antigen-presenting cells.