ES2849965B2 - METHOD TO PREDICT OR FORECAST THE RESPONSE TO CANCER TREATMENT - Google Patents

Description

DESCRIPTION

METHOD FOR PREDICTING OR FORECASTING THE RESPONSE TO

CANCER TREATMENT

FIELD OF THE INVENTION

The present invention is within the field of medicine, and refers to a biomarker and a method for predicting or prognosticating the response to cancer treatment, preferably to the treatment of sarcomas.

STATE OF THE ART

Primary bone sarcomas, mainly including osteosarcoma, chondrosarcoma, and Ewing sarcoma, are a group of rare tumors of mesenchymal or ectodermal origin that constitute <0.2% of all malignant neoplasms in adults. However, high-grade osteosarcomas and Ewing sarcomas primarily affect children and young adults (<20 years) where they represent approximately 3.5% and 2%, respectively, of all solid cancers. Although advances in surgery and multiagent chemotherapy have markedly improved the prognosis of bone sarcoma, the 5-year survival rate remains at 60-70% for patients with localized disease, and as low as 20-30% for patients with metastasis. The poor prognosis of bone sarcomas is partly related to their resistance to conventional chemotherapy and radiation therapies. This makes bone and cartilage cancers the third leading cause of cancer death in children and adolescents in the United States. Therefore, there is an urgent need for new therapies, biomarkers (diagnostic, prognostic or therapeutic), and greater understanding of the mechanisms behind chemo- and radioresistance of bone sarcomas.

Transforming growth factor (TGF)-p is a pleiotropic cytokine that regulates proliferation, angiogenesis, carcinogenesis, and immune responses. TGF-β is produced as an inactive complex consisting of the mature TGF-β homodimer linked to the latency-associated peptide (LAP). A conformational change of LAP induced by integrins, proteases, reactive oxygen species or low pH, releases TGF-p which can then bind to its receptors and induce signaling through canonical (SMAD) and non-canonical pathways. Although TGF-p initially acts as a tumor suppressor, in later stages of carcinogenesis it promotes tumor growth and metastasis through induction of epithelial-to-mesenchymal transition (EMT), promotion of tumor cell proliferation, inhibition of antitumor immune response, and recruitment/induction of cancer-associated fibroblasts in the tumor microenvironment . Importantly, recent data suggest that TGF-p may also play a role in tumor chemo- and radioresistance. Glycoprotein A predominant repeats (GARP), also known as leucine-rich repeats containing 32 (LRRC32) bind latent TGF-P1 to the surface of activated regulatory T cells (Tregs) and B cells where they promote activation of TGF-P1 and is essential for its suppressive functions and isotype switching, respectively. Recent studies have shown that GARP expression in human lung cancer and colorectal tumors is associated with a worse prognosis. However, the expression and role of GARP in mesenchymal neoplasms is unknown. Mesenchymal stem cells (MSCs) are multipotent nonhematopoietic cells that can differentiate into osteoblasts, chondroblasts, and adipocytes. MSCs represent an important component of the bone marrow (BM) where they regulate hematopoiesis and participate in bone homeostasis. Abundant evidence may contain that oncogenic events during MSC differentiation may give rise to bone sarcomas. In fact, some sarcomas include surface markers and gene expression profiling with MSCs and murine BM-MSCs can give rise to an osteosarcoma through spontaneous transformation and genetic modification. However, it is unknown whether GARP is expressed in bone sarcoma cells and the possible effects of GARP on their tumorgenicity and chemo/radiosensitivity are unknown.

DESCRIPTION OF THE INVENTION

The authors of the present invention show, in the examples of the invention, that GARP is expressed in BM-derived MSCs and in several established and recently isolated primary patient-derived bone sarcoma cell lines. Also, GARP silencing inhibited its proliferation, while GARP overexpression increased its proliferation in vitro and in vivo, through a TGF-p-dependent mechanism. GARP-overexpressing bone sarcoma cells were more resistant to in vitro cell death induced by etoposide, doxorubicin, and irradiation, which again depended on increased TGF-P activation. They also show that GARP is overexpressed in osteo, chondro and sarcomas. human pleomorphisms and is associated with a significantly worse prognosis. Importantly, GARP expression in human sarcoma tumors was associated with decreased survival and a trend was observed toward GARP expression having independent prognostic value. Therefore, GARP could serve as a therapeutic target for the treatment of bone sarcoma and also as a possible prognostic and predictive marker for the response of bone sarcomas to chemotherapy and radiotherapy.

Therefore, GARP could serve as a marker with therapeutic, prognostic and predictive value for tumors, and more specifically, bone sarcoma.

Therefore, a first aspect of the invention relates to GARP for use as a biomarker to predict or prognosticate the response to cancer treatment in an individual.

GARP (also called Glycoprotein A Repetitions Predominant, Leucine Rich Repeat Containing 32, Transforming Growth Factor Beta Activator LRRC32, Leucine-Rich Repeat-Containing Protein 32, D11S833E, Garpin, LRRC32) is understood herein to be a key regulator of growth factor transformant beta (TGFB1, TGFB2 and TGFB3) that controls the activation of TGF-beta by keeping it in a latent state during storage in the extracellular space. It specifically associates via disulfide bonds with latency-associated peptide (LAP), which is the regulatory chain of TGF-beta, and regulates the integrin-dependent activation of TGF-beta. Able to compete with LTBP1 to bind to the LAP regulatory chain of TGF-beta. It controls the activation of TGF-beta-1 (TGFB1) on the surface of activated regulatory T cells (Tregs). Required for epithelial fusion during palate development by regulating TGF-beta-3 (TGFB3) activation (by similarity).

In the context of the present invention, "GARP" is also defined by a nucleotide or polynucleotide sequence, which constitutes the sequence of the "GARP" gene, and which would comprise various variants from:

a) Nucleic acid molecules that encode a polypeptide comprising the amino acid sequence of SEQ ID NO: 2,

b) Nucleic acid molecules whose complementary chain hybridizes with the polynucleotide sequence of a),

c) Nucleic acid molecules whose sequence differs from a) and/or b) due to the degeneration of the genetic code.

d) Nucleic acid molecules that encode a polypeptide comprising the amino acid sequence with an identity of at least 80%, 90%, 95%, 98% or 99% with SEQ ID NO: 2, in which that the polypeptide encoded by said nucleic acids has the activity and structural characteristics of the GARP protein. Among other possible nucleotide sequences that encode GARP is, but not limited to, SEQ ID NO: 1.

Gene ID: 2615

Gene location: 11q13.5

SEQ ID NO: 1

SEQ ID NO: 2

In a preferred embodiment of this aspect of the invention, the treatment is chemotherapy and/or radiotherapy. Preferably the chemotherapy treatment is selected from a topoisomerase inhibitor, an antitumor antibiotic, or any combination thereof. More preferably the topoisomerase inhibitor is selected from topotecan, irinotecan (CPT-11), Etoposide (VP-16), teniposide, or mitoxantrone. In another preferred embodiment, the antitumor antibiotic is selected from the list consisting of: Daunorubicin, Doxorubicin, Epirubicin, Idarubicin, Actinomycin D, Bleomycin, Mitomycin C, Mitoxantrone, or any of their combinations. In a particular relationship, the chemotherapy treatment is etoposide and/or doxorubicin.

In another preferred embodiment of this aspect of the invention the cancer is selected from the list consisting of: leukemia, sarcoma, bladder cancer, breast cancer, brain cancer, colon cancer, stomach cancer, lung cancer, ovarian cancer, thyroid cancer, multiple myeloma. More preferably the cancer is sarcoma. Even more preferably the sarcoma is selected from the list consisting of chondrosarcoma, osteosarcoma, pleomorphic sarcoma and synovial sarcoma. Much more preferably is osteosarcoma. In another particular embodiment it is Ewing's sarcoma.

METHODS FOR PREDICTING OR FORECASTING THE RESPONSE TO

CANCER TREATMENT OF THE INVENTION

A second aspect of the invention refers to an in vitro method of obtaining data useful for predicting or prognosticating the response to cancer treatment in an individual, hereinafter first method of the invention, which comprises measuring in an isolated biological sample the GARP expression product. More preferably, the first method of the invention further comprises comparing the quantities obtained with a reference quantity.

A third aspect of the invention relates to an in vitro method to predict or forecast the response to cancer treatment in an individual, hereinafter second method of the invention, which comprises measuring in an isolated biological sample the expression product of GARP, compare the quantities obtained with a reference quantity, and include the individual in the group of individuals with a lower probability of response to treatment, when the expression of GARP is significantly higher (p < 0.05) than that of the reference sample .

There are also in vivo tests. In a series of 11 sarcoma patients for whom response data to different first-line treatments are available (A), the The authors of the present invention found that the only two complete responses occurred in 2 of the 4 patients who presented low levels of GARP. On the other hand, the only case in which treatment had no effect on tumor growth (PD) corresponds to a patient with high levels of GARP. Despite the small number of patients included in this analysis, we found significant differences (p=0.039) between patients with high and low levels of GARP when doing a dichotomous analysis of complete responses versus the rest of the response options (partial response, stable disease and progressive disease) (B). Therefore, these data suggest that sarcomas expressing high levels of GARP respond less well to antitumor treatments.

In immunohistochemistry studies, GARP expression was assessed using a semiquantitative system in which the following values are assigned depending on the percentage of cells expressing GARP: 1: 0%; 2: <10%; 3: 10-50%; and 4: >50%. According to this system, tumors from patients who responded worse (progressive disease, stable disease, partial response) to treatments have GARP expression values 3.6 times higher than tumors from patients who presented a complete response.

Therefore, preferably, the individual is included in the group of individuals with a lower probability of response to treatment, when the GARP expression product is at least 1.5-fold, more preferably at least 2-fold. , more preferably, at least 2.5 times, 2.6 times, 2.7 times, 2.8 times, 2.9 times, 3 times, 3.1 times, 3.2 times, 3.3 times, 3.4 times, or 3.5 times the expression product of the reference sample. In a particular embodiment, the individual is included in the group of individuals with a lower probability of response to treatment, when the expression product of GARP is at least 3.6 times the expression product of the reference sample.

In a preferred embodiment, the steps of the methods described above can be fully or partially automated and/or computerized, for example, by means of a robotic liquid dispensing equipment, a robotic sensor equipment for detecting the amount or product of expression, or computerized comparison.

The described comparison of the methods of the invention can be performed manually or computer assisted.

The term “expression product”, also called “gene product” refers to the biochemical material, whether RNA (for example microRNA) or protein, resulting from the expression of a gene. A measure of the amount of gene product is sometimes used to infer how active a gene is.

Expression of a biomarker of the invention can be assessed by any of a wide variety of methods well known to those skilled in the art to detect the expression of a transcribed molecule or its corresponding protein. If the biomarkers are nucleic acid molecules, expression can be detected and/or quantified using nucleic acid hybridization methods, nucleic acid reverse transcription methods, nucleic acid amplification methods, and the like.

Thus, quantification can be performed by polymerase chain reaction (PCR) or a technique that includes PCR, and more preferably by real-time PCT (Q-RT-PCR).

The measurement of the expression levels of a gene, preferably quantitatively, is based on a signal that is obtained directly from the transcripts of said genes (mRNA, microRNA, etc.), and that is directly correlated with the number of molecules of RNA produced by genes. Said signal - which we can also refer to as an intensity signal - can be obtained, for example, by measuring an intensity value of a chemical or physical property of said products. On the other hand, it could be carried out by indirect measurement that refers to the measurement obtained from a secondary component or a biological measurement system (for example the measurement of cellular responses, ligands, "tags" or enzymatic reaction products).

Thus, in a preferred embodiment, the expression of a marker gene is evaluated by preparing mRNA/cDNA (i.e., a transcribed polynucleotide) from a sample, and by hybridizing the mRNA/cDNA with a reference polynucleotide that is complementary to a polynucleotide comprising the marker gene, and/or fragments thereof. The cDNA can, optionally, be amplified using any of several polymerase chain reaction methods prior to hybridization with the reference polynucleotide.

Preferably, determination of the levels of the GARP expression product is performed by immunoassay or immunohistochemistry. More preferably, the determination of GARP levels is performed by a technique selected from: immunoblot, enzyme-linked immunosorbent assay (ELISA), linear immunoassay (LIA), radioimmunoassay (RIA), immunofluorescence, x-map or protein chips . IN an even more preferred embodiment, the determination of the GARP expression product is performed by immunohistochemistry.

In a preferred embodiment of this aspect of the invention, the treatment is chemotherapy and/or radiotherapy. Preferably the chemotherapy treatment is selected from a topoisomerase inhibitor, an antitumor antibiotic, or any combination thereof. More preferably the topoisomerase inhibitor is selected from topotecan, irinotecan (CPT-11), Etoposide (VP-16), teniposide, or mitoxantrone. In another preferred embodiment, the antitumor antibiotic is selected from the list consisting of: Daunorubicin, Doxorubicin, Epirubicin, Idarubicin, Actinomycin D, Bleomycin, Mitomycin C, Mitoxantrone, or any of their combinations. In a particular relationship, the chemotherapy treatment is etoposide and/or doxorubicin.

In another preferred embodiment of this aspect of the invention the cancer is selected from the list consisting of: leukemia, sarcoma, bladder cancer, breast cancer, brain cancer, colon cancer, stomach cancer, lung cancer, ovarian cancer, thyroid cancer, multiple myeloma. More preferably the cancer is sarcoma. Even more preferably the sarcoma is selected from the list consisting of chondrosarcoma, osteosarcoma, pleomorphic sarcoma and synovial sarcoma. Much more preferably is osteosarcoma. In another particular embodiment it is Ewing's sarcoma.

A "prognostic method" (or "prognostic method") refers to a procedure where, based on clinical analysis, the disease or illness, such as a cancer, preferably a sarcoma, that the person suffers is identified and, based on experiences with other patients suffering from the same disease or illness, such as cancer, preferably sarcoma, predict what the individual's health status will be like in the future; that is, the evolution of the disease or illness over time. The term "prognosis" in the present invention also refers to the ability to detect asymptomatic patients or subjects who have a high probability of suffering from a disease or illness, such as cancer, preferably a sarcoma, even when at the time of diagnosis they do not present said pathologies or obvious manifestations thereof. As experts in the field will understand, such an assessment, although it is preferred, may not normally be correct for 100% of the subjects to be predicted. The term, however , requires that a statistically significant portion of the subjects can be identified as suffering from the disease or having a predisposition to it. Whether a portion is statistically significant can simply be determined by the person skilled in the art using several well-known statistical evaluation tools, for example, determination of confidence intervals, determination of p-values, Student's t- test , Mann-Whitney test, etc. Preferred confidence intervals are at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%. The p values are, preferably but not limited to, 0.2, 0.1, 0.05.

The degree of identity between two sequences can be determined by conventional methods, for example, by means of standard sequence alignment algorithms that are known in the state of the art, such as BLAST (Altschul S.F. et al. Basic local alignment search tool. J Mol Biol. 1990 Oct 5; 215(3):403-10).

A "biological sample", as defined herein, is a small part of a subject, representative of the whole and may consist of a biopsy or a sample of body fluid. Biopsies are small pieces of tissue and can be fresh, frozen, or fixed, such as formalin-fixed and paraffin embedded (FFPE). Body fluid samples may be blood, plasma, serum, urine, sputum, cerebrospinal fluid, milk, or ductal fluid samples and may also be fresh, frozen, or fixed. Specimens can be removed surgically, by extraction i.e. by hypodermic or other needles, by microdissection or laser capture. The sample must contain any biological material suitable for detecting the desired biomarker(s), therefore, said sample must advantageously comprise material from the subject's cells.

A "tissue sample", "tissue sample" or "isolated tissue/tissue sample" includes, but is not limited to, cells and/or tissues from a subject, obtained by any method known to a person skilled in the art. The tissue sample may be, for example, but not limited to, a biopsy or fine needle aspirate. Preferably, the cells are tumor cells.

In another preferred embodiment, the sample is a body fluid sample such as a plasma, serum and/or blood sample.

The terms "individual", "patient" or "subject" are used interchangeably in this description, and are not intended to be limiting in any respect, and may be the "individual", "patient" or "subject" of any age, sex and physical condition.

As described above, the measurement of the quantity or concentration, preferably in a semi-quantitative or quantitative manner, can be carried out in directly or indirectly, as previously stated in this description. The direct measurement refers to the measurement of the amount or concentration of the expression products, based on a signal that is obtained directly from the expression products, and which is correlated with the number of molecules of said expression products. Said signal - which we can also refer to as an intensity signal - can be obtained, for example, by measuring an intensity value of a chemical or physical property of said expression products. Indirect measurement includes measurement obtained from a secondary component or biological measurement system (for example measurement of cellular responses, ligands, “tags” or enzymatic reaction products).

A “reference sample” refers to a similar sample obtained from a subject or control individual (patient) who does not have the disease or condition, such as a cancer, preferably a sarcoma, that is intended to be diagnosed or prognosticated. The “quantity reference" or “reference level” refers to the absolute quantity (or levels) obtained from the reference sample. A “reference sample” may also refer to a similar sample obtained from the same subject or individual at an earlier point in time.

A "reference value" refers to the set of values that are used to interpret the results of diagnostic, prognostic and/or follow-up tests in a subject or individual (patient). For example, the reference values for a given test are They are based on the results of that same test in 95% of the healthy population. The reference values of a test may be different in different groups of people (for example, between women and men, or between children and adults). may be called 'reference interval', 'reference limit', and 'normal limit'.

In the context of the present invention, "Response" refers to the clinical outcome of the subject, "Response" may be expressed as overall survival or progression-free survival. Survival of cancer patients is usually adequately expressed by Kaplan-Meier curves, named after Edward L. Kaplan and Paul Meier, who first described it (Kaplan, Meier: J. Amer. Statist. Assn. 53: 457-481). The Kaplan-Meier estimator is also known as the product limit estimator. It is used to estimate the survival function from lifetime data. A plot of the Kaplan-Meier estimate of the survival function is a series of horizontal steps of decreasing magnitude that, when a large enough sample is taken, approaches the true survival function for that population. It is assumed that the value of the survival function between successive different sampled observations is constant. With respect to the present invention, the Kaplan-Meier estimator can be used to measure the fraction of patients who live for a certain period of time after the start of chemotherapy and/or radiotherapy. The predicted clinical outcome may be survival (overall/progression-free) in months/years from the time of sampling. It can be survival for a certain period from when the sample was taken, such as six months or more, one year or more, two years or more, three years or more, four years or more, five years or more, six years or more. In each case, "survival" may refer to "overall survival" or "progression-free survival."

Therefore, in one embodiment, the answer is the clinical outcome, which is "overall survival" (OS). "Overall survival" denotes the chances of a patient staying alive for a group of people with cancer. The decisive question is whether the individual is alive or dead at any given time.

KIT AND DEVICES OF THE INVENTION

A fifth aspect of the present invention refers to a kit or device, hereinafter kit or device of the invention, which comprises the elements and/or reagents necessary to quantify the GARP expression product.

In another preferred embodiment, the kit or device of the invention comprises primers, probes and/or antibodies capable of quantifying the GARP expression product, and where:

- the primers or primers are polynucleotide sequences of between 10 and 30 base pairs, more preferably between 15 and 25 base pairs, even more preferably between 18 and 22 base pairs, and even more preferably around 20 base pairs, which have an identity of at least 80%, more preferably of at least 90%, even more preferably of at least 95%, even more preferably of at least 98%, and particularly of 100 %, with a fragment of the sequence complementary to SEQ ID NO: 1

- the probes are polynucleotide sequences of between 30 and 1100 base pairs, more preferably between 100 and 1000 base pairs, and even more preferably between 150 and 500 base pairs, which have an identity of at least 80% , more preferably at least 90%, even more preferably at least 95%, even much more preferably at least 98%, and particularly 100%, with a fragment of the sequences complementary to SEQ ID NOT: 1,

- the antibodies are capable of specifically binding to a region formed by the amino acid sequence SEQ ID NO: 2.

In another preferred embodiment of this aspect of the invention, the primers or probes are modified, for example, but not limited to, by radioactive or immunological labeling.

In another preferred embodiment of this aspect of the invention, the oligonucleotides have modifications in some of their nucleotides, such as, but not limited to, nucleotides that have some of their atoms with a radioactive isotope, usually 32P or tritium, immunologically labeled nucleotides. , such as with a digoxigenin molecule, and/or immobilized on a membrane. Several possibilities are known in the state of the art.

In another preferred embodiment of this aspect of the invention, the antibody is human, humanized or synthetic. In another preferred embodiment, the antibody is monoclonal and/or is labeled with a fluorochrome. Preferably, the flurochrome is selected from the list comprising Fluorescein (FITC), Tetramethylrhodamine and derivatives, Phycoerythrin (PE), PerCP, Cy5, Texas, allophycocyanin, or any combination thereof.

The kit may also include, without limitation, buffers, protein extraction solutions, contamination prevention agents, protein degradation inhibitors, etc.

On the other hand, the kit can include all the supports and containers necessary for its start-up and optimization. Preferably, the kit further comprises instructions for carrying out the methods of the invention.

In a preferred embodiment of this aspect of the invention, the treatment is chemotherapy and/or radiotherapy. Preferably the chemotherapy treatment is selected from a topoisomerase inhibitor, an antitumor antibiotic, or any combination thereof. More preferably the topoisomerase inhibitor is selected from topotecan, irinotecan (CPT-11), Etoposide (VP-16), teniposide, or mitoxantrone. In another preferred embodiment, the antitumor antibiotic is selected from the list consisting of: Daunorubicin, Doxorubicin, Epirubicin, Idarubicin, Actinomycin D, Bleomycin, Mitomycin C, Mitoxantrone, or any of their combinations. In a particular relationship, the chemotherapy treatment is etoposide and/or doxorubicin.

In another preferred embodiment of this aspect of the invention the cancer is selected from the list consisting of: leukemia, sarcoma, bladder cancer, breast cancer, brain cancer, colon cancer, stomach cancer, lung cancer, ovarian cancer, thyroid cancer, multiple myeloma. More preferably the cancer is sarcoma. Even more preferably the sarcoma is selected from the list consisting of chondrosarcoma, osteosarcoma, pleomorphic sarcoma and synovial sarcoma. Much more preferably is osteosarcoma. In another particular embodiment it is Ewing's sarcoma.

A sixth aspect of the invention refers to the use of the kit or device of the invention, the microarray, or the microarray of the invention, for obtaining data useful for predicting or prognosticating the response to cancer treatment in an individual.

In a preferred embodiment of this aspect of the invention, the treatment is chemotherapy and/or radiotherapy. Preferably the chemotherapy treatment is selected from a topoisomerase inhibitor, an antitumor antibiotic, or any combination thereof. More preferably the topoisomerase inhibitor is selected from topotecan, irinotecan (CPT-11), Etoposide (VP-16), teniposide, or mitoxantrone. In another preferred embodiment, the antitumor antibiotic is selected from the list consisting of: Daunorubicin, Doxorubicin, Epirubicin, Idarubicin, Actinomycin D, Bleomycin, Mitomycin C, Mitoxantrone, or any of their combinations. In a particular relationship, the chemotherapy treatment is etoposide and/or doxorubicin.

In another preferred embodiment of this aspect of the invention the cancer is selected from the list consisting of: leukemia, sarcoma, bladder cancer, breast cancer, brain cancer, colon cancer, stomach cancer, lung cancer, ovarian cancer, thyroid cancer, multiple myeloma. More preferably the cancer is sarcoma. Even more preferably the sarcoma is selected from the list consisting of chondrosarcoma, osteosarcoma, pleomorphic sarcoma and synovial sarcoma. Much more preferably is osteosarcoma.

AUTOMATED METHOD OF THE INVENTION

A seventh aspect of the invention relates to a computer program comprising program instructions for causing a computer to carry out the method according to any of the methods of the invention.

In particular, the invention encompasses computer programs arranged on or in a carrier. The carrier can be any entity or device capable of supporting the program. When the program is embedded in a signal that can be carried directly by a cable or other device or medium, the carrier can be constituted by said cable or other device or medium. As a variant, the carrier could be an integrated circuit in which the program is included, the integrated circuit being adapted to execute, or to be used in the execution of, the corresponding processes.

For example, the programs could be embedded in a storage medium, such as a ROM memory, a CD ROM memory or a semiconductor ROM memory, a USB memory, or a magnetic recording medium, for example, a floppy disk or a disk. hard. Alternatively, the programs could be supported on a transmissible carrier signal. For example, it could be an electrical or optical signal that could be transported via electrical or optical cable, by radio, or by any other means.

The invention also extends to computer programs adapted so that any processing means can implement the methods of the invention. Such programs may be in the form of source code, object code, an intermediate source code and object code, for example, as in partially compiled form, or in any other form suitable for use in implementing the processes according to the invention. . Computer programs also include cloud applications based on this procedure.

An eighth aspect of the invention relates to a computer-readable storage medium comprising program instructions capable of causing a computer to carry out the steps of any of the methods of the invention.

A ninth aspect of the invention relates to a transmissible signal comprising program instructions capable of causing a computer to carry out the steps of any of the methods of the invention.

The terms "polynucleotide" and "nucleic acid" are used interchangeably here, referring to polymeric forms of nucleotides of any length, both ribonucleotides (RNA or RNA) and deoxyribonucleotides (DNA or DNA).

A nucleic acid or polynucleotide sequence may comprise the five biologically occurring bases (adenine, guanine, thymine, cytosine and uracil) and/or bases other than the five biologically occurring bases. These bases can serve different purposes, for example, to stabilize or destabilize hybridization; to stimulate or inhibit degradation of the probe; or as attachment points for detectable debris or shielding debris. For example, a polynucleotide of the invention may contain one or more modified, non-standard, derivatized, base residues. including, but not limited to, N6-methyl-adenine, N6-tert-butyl-benzyl-adenine, imidazole, substituted imidazoles, 5-fluorouracil, 5-bromouracil, 5-chlorouracil, 5-iodouracil, hypoxanthine, xanthine, 4- acetylcytosine, 5- (carboxyhydroxymethyl) uracil, 5-carboxymethylaminomethyl-2-thiouridine, 5- carboxymethylaminomethyluracil, dihydrouracil, beta-D-galactosylqueosine, inosine, N6- isopentenyladenine, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2 -methyladenine, 2-methylguanine, 3-methylcytosine, 5-methylcytosine, N6-methyladenine, 7-methylguanine, 5-methylaminomethyluracil, 5-methoxyaminomethyl-2-thiouracil, beta-D-mannosylqueosine, 5'-

methoxycarboxymethyluracil, 5-methoxyuracil, 2-methylthio-N6-isopentenyladenine, uracil-5-oxyacetic acid, wybutoxosin, pesudouracil, queosin, 2-thiocytesine, 5-methyl-2-thiouracil, 2-thiouracil, 2-thiouracil, 4-thiouracil , 5-methyluracil (i.e., thymine), uracil-5-oxyacetic acid methyl ester, 3-(3-amino-3-N-2-carboxypropyl) uracil, (acp3)w, 2,6-diaminopurine, and 5-propynyl pyrimidine. Other examples of modified, non-standard, or derivatized base moieties can be found in US Patent Nos. 6,001,611; 5,955,589; 5,844,106; 5,789,562; 5,750,343; 5,728,525; and 5,679,785. Additionally, a nucleic acid or polynucleotide sequence may comprise one or more modified sugar moieties including, but not limited to, arabinose, 2-fluoroarabinose, xylulose, and a hexose.

The terms "amino acid sequence", "peptide", "oligopeptide", "polypeptide" and "protein" are used interchangeably herein, and refer to a polymeric form of amino acids of any length, which may be coding or non-coding, chemically or biochemically modified.

Throughout the description and claims the word "comprises" and its variants are not intended to exclude other technical characteristics, additives, components or steps. For those skilled in the art, other objects, advantages and features of the invention will emerge partly from the description and partly from the practice of the invention. The following examples and figures are provided by way of illustration, and are not intended to be limiting of the present invention.

DESCRIPTION OF THE FIGURES

Figure 1. Several sarcoma cell lines express GARP and its silencing blocks the proliferation of these lines. (A) GARP mRNA expression data in various cancer cell lines retrieved from the CCLE database. Log2 RMA mRNA expression values are shown as boxplots and sorted in ascending order from the median. Outliers are displayed as filled circles. (B) GARP mRNA expression in primary BM-MSCs and various cancer cell lines. Data are shown as the mean (SD), relative to GARP expression in BM-MSCs. (C) Summary of GARP expression (% relative to isotype control) in primary BM-MSCs and the selected bone sarcoma cell lines. Data are shown as the mean (SD) of three individual stains. (D) GARP silencing in BM-MSCs and in the osteosarcoma cell lines G292, T1-73 and SAOS-2 inhibits their proliferation. Proliferation (cell index) of nontransduced (NT), LV-CTRL, GARPKO1, and GARPKO2 cells was measured in real time for 7 days. Data are shown as the mean (SD) of experimental duplicates. A representative experiment of 3 is shown. (E) Graphs of three individual experiments showing the mean (SD) proliferation as a cell index at 160 hours divided by the corresponding cell index at 10 hours. *=P<0.05;***=P<0.001. (F) GARP silencing in osteosarcoma cell lines induces cell death by apoptosis. Apoptosis was measured in G292 NT, LV-CTRL, GARPKO1 and GARPKO2 (left graph), T1 -73 (middle graph) and SA0S-2 (right graph) cells by staining the cells with 7AAD/Annexin V and analyzed cells by flow cytometry. Data are shown as the mean (SD) of three independent experiments. *=P<0.05.

Figure 2. GARP promotes the proliferation of bone sarcoma cell lines through the activation of TGF-p. (A) Overexpression of GARP in bone sarcoma cell lines. Representative dot plots of untransduced (NT) and GARP-overexpressing (GARP++) G292 (top panel), SAOS-2 (middle panel), and RD-ES (bottom panel). The staining of the corresponding isotype is represented with vertical lines in all graphs. (B) Overexpression of GARP increases the proliferation of bone sarcoma cell lines. Growth curves of G292, SAOS-2, and RD-ES NT, GARP++, and EGFP-overexpressing (EGFP++) cells were generated by plotting the number of accumulated cells versus time. Data are shown as the mean (SD) of three individual experiments. *=P<0.05. (C) The increase in the number of EGFP++ and GARP++ cells relative to NT cells at the end of each experiment is shown as the mean (SD) of three individual experiments. *=P<0.01. (D) GARP++ sarcoma cells produce more active TGF-β compared to NT cells. G292, SAOS-2, and RD-ES NT and GARP++ cells were co-cultured with SBE-HEK293 cells for 24 hours and then analyzed for luciferase activity. The increase in TGF-p activity of GARPP++ cells is relative to NT for each cell line.

Data are represented as the mean (SD) of three independent experiments. *=P<0.05, **=P<0.01. (E) Increased proliferation of GARP++ sarcoma cells depends on TGF-p. G292, SAOS-2, and RD-ES NT and GARP++ cells were cultured in the presence or absence of SB431542 or anti-TGF-p1/2/3 antibody (11D1) for 3 days and then the cells were counted. The increase in the number of cells is relative to the NT for each cell line. Data are shown as the mean (SD) of three independent experiments. *=P<0.05; **=P<0.01.

Figure 3. GARP increases the growth of tumors from G292 cells in vivo. (A) G292 NT (n=10), LV-CTRL (n=6), GARPKO2 (n=10), and GARP++ (n=10) cells were injected subcutaneously into NSG mice and tumor growth was followed for 70 days. Tumor weight and width were measured weekly using an automatic caliper and tumor volume was calculated as described in materials and methods. Data are shown as the mean (SD). *=P<0.05 GARP++ vs NT. (B) Representative image of isolated NT and GARP++ tumors at the end of the experiment (upper panel). The volumes (left graph) and weights (right graph) of the isolated tumors were measured as described in materials and methods. Data are shown as the mean (SD) with white (NT) and orange (GARP++) circles representing individual tumors. (C) Representative image of isolated LV-CTRL and GARPKO tumors at the end of the experiment (upper panel). The volumes (left graph) and weights (right graph) of isolated tumors were measured as described in materials and methods. Data are shown as the mean (SD) with black (LV-GARP) and blue (GARPKO2) circles representing individual tumors. Tumor cell proliferation was analyzed by Ki67 immunohistochemical staining in NT (n=10) and GARP++ (n=10) tumors. Data are shown as the mean (SD) with white (NT) and orange (GARP++) circles representing individual tumors. *=P<0.05. (E) Ki67 staining in LV-CTRL (n=6) and GARPKO2 (n=3) tumors. Data are shown as the mean (SD) with black (LV-CTRL) and blue (GARPKO2) circles representing individual tumors. (F) Activation of the TGF-β signaling pathway was analyzed by phospho-SMAD3 immunohistochemistry in NT and GARP++ tumors. Data are shown as the mean (SD) with white (NT) and orange (GARP++) circles representing individual tumors. *=P<0.05.

Figure 4. Overexpression of GARP in bone sarcoma cell lines makes them more resistant to death induced by etoposide and doxorubicin. G292, SAOS-2 and RD-ES cells without transducing (NT), overexpressing GARP (GARP++) and overexpressing EGFP (EGFP++) were subjected to different concentrations of etoposide in vitro. (A) Cell viability was measured using CelltiterBIue and represented as % control (cells without etoposide). Data are shown as the mean (SD) of three individual experiments. *=P<0.05;**=P<0.01;***=P<0.001. (B) G292, SAOS-2, and RD-ES NT and GARP++ cells were subjected to 80 μM (G292) or 10 μM (SAOS-2 and RD-ES) etoposide, with or without SB431542 or the anti-TGF-antibody. pi/2/3 (11D1). Cell viability was analyzed using CelltiterBlue and represented as % control (cells without etoposide). Data are shown as the mean (SD) of three individual experiments. *=P<0.05. (C) G292, SAOS-2, and RD-ES NT and GARP++ cells were subjected to 2.5 μM doxorubicin with or without SB431542. Cell viability was analyzed using CelltiterBlue and represented as % control (cells without doxorubicin). Data are shown as the mean (SD) of three individual experiments. *=P<0.05.

Figure 5. Overexpression of GARP in bone sarcoma cell lines makes them more resistant to irradiation-induced death and DNA damage.

Irradiation susceptibility was analyzed by clonogenicity assay. SAOS-2 (A) and RD-ES (B) NT and GARP++ cells were seeded at low density in 6-well plates and cultured with or without SB431542 as described in materials and methods. Cells were irradiated at 2, 4, and 8 Gy. After 2 weeks, colonies were fixed, stained with crystal violet, and counted as described in materials and methods. Data are represented as the survival fraction (relative to nonirradiated cells) and are shown as the mean (SD) of three independent experiments. *=P<0.05; ***=P<0.001 GARP++ vs. NT, #=P<0.05; ##=P<0.01; ###=P<0.001 GARP++ SB431542 vs. GARP++. (C, D) SAOS-2 (C) and RD-ES (D) NT and GARP++ cells were cultured with or without SB431542, irradiated at 4 Gy, and analyzed for g-H2AX by flow cytometry. Data are shown as the mean (SD) of 3 independent experiments. (E,F)SAOS-2 (E) and RD-ES (F) NT and GARP++ cells were cultured with or without SB431542, irradiated at 4 Gy, and analyzed for g-H2AX using the Imagestream flow cytometer. The number of g-H2AX-positive foci per nucleus is shown as the mean (SD). A representative experiment of 3 is shown.

Figure 6. Cell lines derived from tumors of patients with osteosarcoma and chondrosarcoma express GARP. (A) Patient-derived tumor cells were extracted from two osteosarcoma tumors (OST-3 and OST-4) and from one chondrosarcoma tumor (T-CDS17). These cell lines were stained for surface GARP expression and analyzed by flow cytometry. Representative staining is shown. (B) Proliferation of OST-4 NT, LV-CTRL and GARPKO2 using the xCelligence real-time proliferation analyzer system. Data are shown as the mean (SD) of experimental duplicates. One representative experiment of two is depicted.

Figure 7. Immunohistochemical analysis and impact on patient survival of GARP expression in sarcoma tissue samples. (A) Representative examples of the indicated sarcoma types showing high and low GARP staining. Scale bars: 500 gm (red) or 100 gm (black). (B) Distribution of sarcoma cases (N=89) according to their GARP expression level in the categories of indicated patient characteristics and tumor clinicopathological parameters (a more comprehensive description is shown in Table S2) . P values are shown. (C) Kaplan-Meier cumulative survival curves classified by GARP protein expression in the sarcoma patient cohort. P values were estimated using the log-rank test.

Figure 8. GARP expression and response to treatment - Pilot study. (A) Information regarding the type of tumor, treatment received and corresponding response. CR: complete response, EE: stable disease, PR: partial response, PD: progressive disease, GIST: Gastrointestinal stromal tumor, S. Ewing: Ewing sarcoma. (B) Dichotomous analysis of patients with complete response vs. RC RP PD EE.

Figure 9. GARP silencing in bone sarcoma cell lines. The G292, T1-73, and SAOS-2 cell lines were transduced with LV-CTRL, LV-GARPKO1, and LV-GARPKO2 as described in materials and methods. Four days later, GARP expression was measured by flow cytometry. Data are shown as the mean (SD) of two (T1-73) or three (G292, SAOS-2) independent experiments.

Figure 10. Overexpression of GARP in G-292, SAOS-2 and RD-ES cells makes them more resistant to etoposide-induced apoptosis compared to NT cells. G292, SAOS-2, and RD-ES NT and GARP++ cells were exposed to different concentrations of etoposide for 24 hours, stained for Annexin V/7AAD, as described in supplementary materials and methods, and analyzed by flow cytometry. Data are shown as the mean (SD) of at least three individual experiments. *=P<0.05, **=P<0.01.

Table S1. Distribution of sarcoma cases (N=89) according to their GARP expression levels in the categories of indicated patient characteristics and clinicopathological parameters. P values are shown.

Table S2. Univariate and multivariate Cox analysis of GARP expression and clinicopathological parameters, including tumor necrosis, tumor grade, tumor count, and tumor type.

EXAMPLES OF THE INVENTION

This is the first study to analyze GARP expression in human sarcoma samples. The inventors found that 100% (8/8) of osteosarcomas and 73% (8/11) of chondrosarcomas expressed high levels of GARP. This is in agreement with the expression of GARP in BM-MSCs and the relatively higher expression of GARP in the osteo cancer and chondrosarcoma cell lines shown in the study.

The current treatment for bone sarcoma is surgery and multimodal chemotherapy and, in some cases, radiation therapy when the tumor cannot be removed surgically. In general, doxorubicin, cisplatin and iphosfamide represent first-line drugs for the treatment of localized bone sarcoma, while cyclophosphamide in combination with etoposide are important for the treatment of recurrent osteosarcoma and Ewing sarcoma. The combination of improved surgical procedures with efficient chemotherapy (CT) and radiotherapy (ET) has substantially increased the survival rate of patients with bone sarcoma. However, over the past 30 years no further improvements have been achieved and patients with metastatic or recurrent disease still have a <20% chance of long-term survival despite aggressive therapies. One explanation for this lack of progress is the frequent radioresistance exhibited by osteo and chondrosarcoma tumors.

Materials and methods

Animals

NOD scid gamma (NSG) mice were obtained from the internal stock of the Biomedical Research Center (CIBM, Granada, Spain). All experiments were performed in accordance with the Institutional Guidelines for the Care and Use of Laboratory Animals in Research, with approval from the Animal Research Ethics Committee of the University of Granada (Granada, Spain).

Osteosarcoma cell lines G292, T1-73, and SAOS-2 were obtained from the American Type Culture Collection (ATCC) and cultured in advanced DMEM (Invitrogen) with 10% FBS (Biowest), 1% Glutamax (Gibco, Thermo Fisher Scientific) and 100 U/ml penicillin/streptomycin (Gibco, Thermo Fisher Scientific). The Ewing sarcoma cell line RD-ES was cultured in RPMI-1640 (Gibco, Thermo Fisher Scientific) supplemented with 10% FBS and 100 U/ml penicillin/streptomycin. The primary cell lines OST-3 and OST-4 were generated from surgically resected tumor samples at the Central University Hospital of Asturias (Oviedo, Spain). OST-3 derives from a conventional osteoblastic osteosarcoma resected from a 10-year-old patient and OST-4 corresponds to a dedifferentiated osteosarcoma from a 69-year-old woman. The T-CDS17 chondrosarcoma cell line was previously reported (Rey, V et al., 2019. J Clin Med ^{8(4): 455)} . The above cell lines were cultured in high glucose DMEM (Gibco, Thermo Fisher Scientific) with 10% FBS and 100 U/ml penicillin/streptomycin. All cell lines were maintained at 37°C with partial pressure levels of 21% O2 and 5% CO2. GARP mRNA levels in cell lines were measured by RT-PCR as described in supplementary materials and methods.

Lentiviral vector (LV) production and cell transduction.

LVs encoding human GARP-specific shRNAs (MISSION® shRNA plasmid DNA, RefSeq: SHCLND-NM_005512; Sigma-Aldrich, MO, USA), referred to in the manuscript as GARPKO1 (TRCN0000005218) and GARPKO2 (TRCN0000005219) were used. ). A non-mammalian shRNA control plasmid from μLKO.1-MISSION® (Sigma-Aldrich), referred to in the text as LV-CTRL, was used as a control. An LV encoding human codon-optimized GARP cDNA, LV-GARP, (Carrillo-Gálvez et al., Submitted) was used to overexpress GARP and LV-CEWP was used as a control. LVs were produced by co-transfecting 293T cells with: 1) LV-CTRL/GARPKO1/GARPKO2/LV-GARP/LV-CEWP plasmid, 2) pCMVAR8.91 packaging plasmid and 3) μMD.G envelope plasmid as described previously (Carillo-Gálvez AB et al., 2015. Stem Cell. 33 : 183-195). The LVs were subsequently concentrated (×30) using centrifugal filter devices (Amicon Ultra-15, 100 kD, Merck). GARP was silenced in BM-MSC, G292, T1-73, SAOS-2 and OST-4 cells as previously described (Carrillo-Gálvez et al., Stem Cells 2015). To overexpress GARP (GARP++), RD-ES and SAOS-2 cells were transduced once with concentrated LV-GARP (30x), for 5 hours and subsequently expanded, while G292 cells were transduced twice on consecutive days with LV-GARP (x30). Cells were transduced with LV-CEWP as a control. The expression of GARP is analyzed by flow cytometry 4 days after transduction as described in supplementary materials and methods.

Analysis of cell proliferation in vitro.

The proliferation of BM-MSCs and tumor cells was analyzed using the Roche xCelligence Real-Time Cell Analyzer System (Roche Applied System, Penzberg, Germany) as previously described (Carillo-Gálvez AB et al., 2015. Stem Cell. 33:183-195). The E plates were placed on the device station in the incubator (21% O2/5% CO2 at 37°C) for continuous recording of impedance as reflected by the cell index. In some experiments, proliferation was measured as follows: 50,000 cells/well of NT and GARP++ G292, SAOS-2 and RD-ES cells were placed in a 12-well plate. When the cell cultures reached 80–90% confluency, the cells were harvested, counted, and replated at the same concentration. In some cases, 5 hours after cell plating, cells were treated with 10 μM SB431542 (Sigma-Aldrich) or 2.5 μg/ml anti-TGF-p1/2/3 Ab (11D1, R&D Systems, Minneapolis , MN).

Analysis of tumor growth in vivo.

NT, LV-CTRL, GARPKO2 and GARP++ G292 cells (4 x 106) were injected subcutaneously into NSG mice and tumor growth was measured every 6-7 days. Tumor volume was calculated using the formula: (n/6) x (a2 x b) where a and b are the values for the diameter of the smallest and largest tumor, respectively. After 2-3 months, mice were sacrificed, tumors were removed, and tumor volumes and weights were measured. Immunohistochemistry was performed on paraffin-embedded tissue sections with monoclonal antibody against human Ki-67 (MIB-1, DAKO) and an anti-Smad3 (phospho S423 S425) antibody (EP823Y, Abcam) as described in Supplementary Materials and Methods. .

Cell viability in response to etoposide and doxorubicin

Cell viability was measured using CellTiter-Blue reagent (Promega) and following the manufacturer's instructions. 10,000 plates/well of NT and GARP++ G292, SAOS-2 and RD-ES were plated into 96-well plates. 5 hours later, cells were treated with 10 μM SB431542 or 2.5 μg/ml anti-TGF-p1/2/3 Ab. CellTiter-Blue was added to the RD-ES culture after 24 hours and to the G292 and SA0S-2 cultures after 48 hours. Cells were incubated with the reagent for 4 h and fluorescence was measured at 560 nm on a Glomax multiple detection system (Promega) following the manufacturer's instructions. This experiment was also carried out in cells treated with etoposide and doxorubicin. For this, 10,000 cells/well of NT and GARP++ G292, SAOS-2 and RD-ES were plated in 96-well plates and 24 hours later, 2.5 μM of doxorubicin or different concentrations of etoposide were added to the plates: 2.5 μM, 5 μM, 10 μM, and 20 μM for RD-ES and SAOS-2 tumor cells and 10 μM, 20 μM, 40 μM, and 80 μM for G292 tumor cells. The addition and analysis of CellTiter-Blue was performed as explained above. Additionally, apoptosis was measured as described in supplementary materials and methods.

Measurement of active TGF-p

NT and GARP++ G292, SAOS-2, and RD-ES cells (40,000 cells/well) were cocultured with SMAD-binding element (SBE)-HEK293 cells (40,000 cells/well; BPS Bioscience) in assay plates. 96 wells (Sigma-Aldrich) using DMEM supplemented with 0.5% FBS. After 18 h, SBE activity was analyzed using the one-step luciferase assay system (BPS Bioscience) on a Glomax multiplex detection system (Promega) following the manufacturer's instructions.

Clonogenicity assay

NT, GARP++ SAOS-2 and RD-ES cells were seeded in 6-well plates at the following densities: 2000, 4000, 8000 and 160000 cells/well (NT) and 1000, 2000, 4000, 8000 cells/well ( GARP++), and were irradiated with 0, 2, 4 and 8 Gy, respectively, using a dose of 1.66 Gy min-1 in a L. Shepherd & associates MARK-I model 30 gamma irradiator at the Experimental Radiology Unit of the University from Granada (Spain). In some experiments, 10 μM of SB431542 was added 24 hours before irradiation. The cells were subsequently maintained in culture until the appearance of colonies that could be counted (7-9 days after irradiation). Cells were fixed and stained with crystal violet and colonies were counted (>50 cells/colony were considered for survival). The survival fraction was calculated as previously described (Franken NAP, Rodermond HM, et al., 2006, Nature protocols).

Analysis of H2AX phosphorylation

For the detection of DNA double-strand breaks (DSBs), phosphorylated H2AX (Y-H2AX) was measured by flow cytometry using the FlowCellect® Histone H2AX Phosphorylation Assay Kit (Millipore, MA, USA). To induce DSB, NT and GARP++ SAOS-2 and RD-ES tumor cells were seeded in 12-well plates (50,000 cells/well), with or without SB43154210 μM and the next day exposed to a dose of 4 Gy irradiation. After 2 hours, cells were harvested and stained for ^y -H2AX according to the manufacturer's instructions. To analyze the number of Y-H2AX foci/cells, cells were irradiated and stained for ^y -H2AX as described above and subsequently acquired on an ImageStream X Mark II imaging flow cytometer (Millipore) and analyzed using the IDEAS software (Spot Wizard).

Patients and tissue samples.

Paraffin-embedded tissues from 89 sarcoma patients who underwent resection of their tumors at the Central University Hospital of Asturias (HUCA) were studied. The samples and donor data included in this study were provided by the Biobank of the Principality of Asturias (PT17/0015/0023), integrated into the National Network of Biobanks of Spain, and were processed following standard operating procedures with approval of the Ethics and Scientific Committees. . All samples of human origin were obtained with signed informed consent. Sixty percent of the cases were men; The mean age at diagnosis was 49 years (range 2 - 89 years). Twenty-eight (31%) patients had a history of tobacco use (15 current smokers and 13 former smokers). Tumor grade was assessed in H&E-stained slides using the French Federation of Comprehensive Cancer Centers grading system (Torin, J et al.

2018. Neoplasia 20:44-56). The clinicopathological characteristics of the patients are included in Table S1. How the tissue microarray was constructed is detailed in the supplementary materials and methods.

Immunohistochemistry

Formalin-fixed, paraffin-embedded tissues were cut into 3-μm sections and dried on Flex IHC microscope slides (Dako, Glostrup, Denmark). Sections were deparaffinized with standard xylene and hydrated through graded alcohols in water. Antigen retrieval was performed using Envision Flex Target Retrieval solution, low pH (Dako, Glostrup, Denmark). Staining was performed at room temperature on an automated stainer workstation (Dako Autostainer Plus) with an anti-LRRC32/GARP antibody (Abcam #ab231214) at a 1:300 dilution using the Dako EnVision Flex visualization system (Dako Autostainer , Denmark). Counterstaining with hematoxylin was the final step. Immunostaining blinded to clinical data was scored by two independent observers using a semiquantitative scoring system based on the percentage of cells stained (1: 0%; 2: <10%; 3: 10-50%; and 4: >50%). and the intensity staining (0: no expression; 1: low intensity; and 2: high intensity). Each sample received a score value resulting from the multiplication of both scores, and the mean value in the resulting distribution was used to discriminate low- and high-expression samples.

Statistic analysis

For the in vitro experiments and the in vivo tumor growth experiment, statistical analysis was performed using GraphPad Prism software (GraphPad Software, Inc, La Jolla, CA). All data are represented as mean (SD) of at least three independent experiments unless otherwise indicated in the figure legend. Multiple comparisons of the data were performed using one-way ANOVA, followed by Bonferroni post-test. A p value <0.05 was considered significant. Experimental results distributed among the different clinical tumor groups were evaluated for significance using the χ test (with Yates correction, where appropriate). For statistical purposes, continuous variables (age, tumor size) were dichotomized, taking the mean value as the cut-off point. Survival curves were calculated using Kaplan-Meier product limit estimation. Differences between survival times were analyzed using the log-rank method and the Hazard Ratio was calculated using univariate Cox regression analysis. Multivariate Cox proportional hazards models (advanced Wald method) were used to examine the relative impact of those statistically significant variables in the univariate analysis. All statistical analyzes were carried out using the SPSS 24 software package (SPSS, IBM corp.). All tests were two-sided and p values <0.05 were considered statistically significant.

Table S1. Distribution of sarcoma cases (n=89) according to their level of GARP expression among the categories of the indicated patient and the clinicopathological parameters of the tumor. P values are shown.

Table S2. Univariate and multivariate Cox analysis.

RESULTS

GARP is expressed in several bone sarcoma cancer cell lines and its silencing blocks their proliferation

An analysis of the Cancer Cell Line Encyclopedia (CCLE) database revealed that GARP mRNA expression was predominantly found in several sarcoma cancer cell lines, including giant cell tumors, osteosarcoma, and chondrosarcoma, but also in Hodgkin and B cell lymphoma cell lines (Figure 1A). We selected three osteosarcoma cell lines with varying levels of GARP (G292, T1-73 and SAOS-2), one Ewing sarcoma cell line under GARP (RD-ES), two glioblastoma cell lines (U87, U251) and two carcinoma cell lines (HT-29, MCF-7) and compared their GARP expression with human bone marrow (BM)-derived MSCs. Our data showed that osteosarcoma cell lines G292 and T1-73 expressed similar levels of GARP compared to primary BM-MSCs, while glioma and carcinoma cell lines expressed relatively low levels of GARP mRNA (Figure 1B). We also analyzed surface GARP expression by flow cytometry which corroborated the relative levels of GARP mRNA expression (G292 > BM-MSC > T1 -73 > OSAS-2 > RD-ES) (Figure 1C). Importantly, as previously demonstrated in human ASCs [25], we found that GARP silencing (Supplementary Fig. 1) in BM-MSCs, using lentiviral vectors encoding two GARP-specific shRNAs (GARPKO1 and GARPKO2), decreased substantially their proliferative capacity compared to non-transduced (NT) and control transduced (LV-CTRL) BM-MSCs (Figure 1D). Similarly, GARP silencing in G292, T1-73, and OSAS-2 cell lines reduced their proliferative capacity compared to NT and LV-CTRL cells (Figure 1D and E) and resulted in increased killing. cell by apoptosis (Figure 1F).

GARP promotes the proliferation of bone sarcoma cell lines through the activation of TGF-p.

Next, we wanted to analyze the effect of GARP overexpression on the proliferation of bone sarcoma cells. To this end, we overexpressed GARP (GARP++) in the Ewing sarcoma cell lines G292, SAOS-2, and RD-ES using an LV encoding a codon-optimized human GARP cDNA under the control of the CMV promoter (Figure 2A). In parallel, control cells were transduced with an LV encoding enhanced green fluorescent protein (EGFP+). GARP overexpression significantly increased the proliferative capacity of all cell lines compared to NT and EGFP+ cells (Figure 2B and C). Since TGF-p is a growth factor for osteosarcoma cells [28] and GARP has been shown to promote TGF-p activation [29], we evaluated whether GARP overexpression could increase TGF-p activation. To this end, we cocultured NT and GARP++ bone sarcoma cells with a SMAD-binding element (SBE)-HEK293 TGF-p activity reporter cell line. We found that GARP overexpression significantly increased TGF-β activation by G292, SAOS-2, and RD-ES cells (Figure 2D). Blocking TGF-p signaling with SB431542 or neutralizing TGF-p using an anti-TGF-pi/2/3 antibody significantly reduced the proliferation of GARP++ cells (Figure 2F). In summary, these data show that GARP promotes the proliferation of bone sarcoma cell lines by promoting TGF-β activation.

GARP increases G292 tumor growth in vivo

To analyze whether GARP expression levels are also important for tumor growth in vivo, we injected NT, GARP++, LV-CTRL, and GARPKO2 G292 cells subcutaneously into NSG mice and followed tumor growth over time. Consistent with the in vitro data, GARP++ G292 exhibited significantly greater in vivo growth compared to NT G292, while smaller tumors were found in only 3 of 8 mice injected with GARPKO2 G292 cells (Figure 3A, B, and C). Furthermore, both the volumes and weights of GARP++ tumors isolated from euthanized mice were significantly increased compared to NT tumors (Figure 3B). In contrast, the weights and volumes of GARPKO tumors were significantly lower compared to LV-CTRL tumors (Figure 3C). We performed Ki67 immunohistochemistry to analyze the cell proliferation rate in the different tumors and found that GARP++ tumors contained a significantly higher percentage of Ki67+ cells compared to NT tumors. An opposite trend was observed between GARPKO and LV-CTRL tumors, but the difference was not statistically significant. This could be due to the fact that only three NSG mice injected with GARPKO cells G292 showed the presence of a tumor, possibly with a greater proliferative capacity. Finally, we analyzed SMAD3 activation in GARP++ and NT tumors by immunohistochemistry and observed a higher fraction of cells with high SMAD3 phosphorylation in GARP++ tumors compared to NT tumors (Figure 3F). In summary, our data show that modulation of GARP expression in G292 has profound effects on its growth in vivo, corroborating our in vitro data.

GARP-overexpressing bone sarcoma cell lines are more resistant to cell death induced by etoposide and doxorubicin, which depend on TGF-β

Previous studies on GARP in the context of cancer have focused on the inhibition of the immune response through increased activation of TGF-p, especially the induction of foxp3 Tregs [18-20]. However, no study has analyzed the effect of GARP expression on resistance to chemotherapeutic drugs or irradiation. To this end, we added different concentrations of the DNA damaging agent etoposide to the NT, EGFP and GARP++ G292, SAOS-2 and RD-ES cell lines and analyzed cell survival (CelltiterBlue) and apoptosis (7AAD/Annexin V). after 24 hours. We found that GARP overexpression increased cell survival (Figure 4A) and reduced apoptosis (Supplementary Figure S2) of all tumor cell lines in response to etoposide. Inhibition of TGF-β signaling (SB431542) or neutralization of TGF-β (1D11) significantly reversed the survival of GARP-overexpressing cells, suggesting a TGF-β-dependent mechanism (Figure 4B). Similarly, GARP++ cells were more resistant to doxorubicin-induced cell death, although to a lesser extent compared to etoposide. Again, inhibition of TGF-β signaling reversed the protective effect conferred by GARP (Figure 4C).

GARP-overexpressing sarcoma cells show reduced sensitivity to radiation-induced cell death and DNA damage

We then performed a clonogenic assay to evaluate the relative resistance of NT and GARP++ sarcoma cells to radiation-induced cell death. Pilot experiments showed that G292 did not form countable colonies, therefore experiments were performed only with the SAOS-2 and RD-ES cell lines. The SAOS-2 and RD-ES NT and GARP++ cell lines were subjected to different irradiation doses (2, 4 and 8 Gy), in the presence or absence of SB431542, and the ability of colony formation for approximately two weeks. We found that GARP++ SAOS-2 and RD-ES cells were significantly more resistant to irradiation-induced cell death compared to NT cells. Inhibition of TGF-β signaling reduced the radioresistance conferred by GARP in both cell lines (Figure 5A and B). TGF-p has been shown to protect cells against irradiation-induced DNA damage through its effect on DNA repair [30]. Therefore, we irradiated NT and GARP++ SAOS-2 and RD-ES cells, cultured with or without SB431542 for 24 hours, with 4 Gy and analyzed the induction of DNA damage as visualized by H2AX phosphorylation before and two hours after irradiation. We found that irradiation induced significantly lower levels of Y-H2AX in GARP++ cells compared to NT cells. Interestingly, we found that blocking TGF-p signaling increased the amount of DNA damage in GARP++ SAOS-2 and RD-ES cells to that of NT cells, implicating TGF-p in damage resistance. of DNA induced by irradiation (Figure 5C and RE). Finally, to better visualize DNA damage in the nuclei, we repeated irradiation of GARP++ and NT SAOS-2 and RD-ES cells, as described above, and analyzed H2AX activation using an Imagestream flow cytometer. As before, we observed that GARP++ cells were more resistant to irradiation-induced DNA damage, which was dependent on TGF-β signaling (Figure 5E and F). In summary, these data show that GARP, through its activation of TGF-β, can protect tumor cells against irradiation-induced cell death and DNA damage, suggesting that GARP could represent a therapeutic target and possibly a predictive biomarker of chemo/radioresistance of bone sarcomas.

GARP is highly expressed in human osteo, chondro and pleiomorphic sarcomas and is associated with poor survival/prognosis.

The clinical relevance of GARP expression in sarcomas is unknown. Therefore, we studied GARP expression in primary human bone sarcomas and its correlation with clinical data. We first analyzed GARP expression in cell lines derived from primary patients of two osteosarcomas (OST-3, OST-4) and one chondrosarcoma (T-CDS17) [26]. Interestingly, we found that all cell lines expressed GARP, although at variable levels (Figure 6A). OST-4 cell lines expressed GARP at a high level and GARP silencing in this cell line reduced its proliferative capacity, similar to what we observed using primary BM-MSC and bone sarcoma cancer cell lines (Figure 6B).

We next set out to analyze GARP expression in a collection of tissue microarrays, including samples from 89 patients from 10 types of sarcomas, by immunohistochemistry. We found that GARP was expressed at high levels in 43 (48%) of the sarcoma samples, including all cases of osteosarcoma and undifferentiated pleomorphic sarcoma (Figure 7A and B). None of the clinicopathological variables analyzed showed a significant correlation with the level of GARP expression (Table S1), although a trend towards higher grade (P = 0.15) and mitotic count score (P = 0.068) was observed in tumors. showing high expression of GARP (Figure 7B). Interestingly, cases expressing low levels of GARP had a significantly longer survival time than those with high expression (94 months (CI 87-100) vs 41 months (CI 28-54), respectively; HR 19; p = 0 ,0001). The 5-year survival rate was 95.5% for low expression cases and 35.3% for high expression cases (Fig. 7C). Tumor grade, tumor type, mitotic count, necrosis, and GARP expression level were included in the multivariate survival analysis. Tumor necrosis showed an independent prognostic value (p = 0.024, HR 2.643). Importantly, a trend was observed toward GARP expression having independent prognostic value (p = 0.056) (Table S2).

Finally, in a series of 11 sarcoma patients where we have responses to several first-line treatments (Figure 8A), we observed that the only two complete responders (CR) occurred in two out of four patients with low GARP levels. On the other hand, the only case in which the treatment had no effect corresponded to a patient with high levels of GARP. Despite the low number of patients, we detected a significant difference (p = 0.039) between patients with high and low GARP expression performing a dichotomous analysis of complete response versus the other response options (partial response, stable disease, and progressive disease). (Figure 8B) Therefore, these results suggest that sarcomas expressing high levels of GARP have poorer responses to antitumor treatments.

Claims (30)

1. - An in vitro method to predict or forecast the response to treatment of a sarcoma in an individual, characterized in that the method comprises measuring the GARP expression product in an isolated biological sample. 2. - The in vitro method according to claim 1, characterized in that it also comprises comparing the quantities obtained with a reference quantity. 3. - An in vitro method to predict or forecast the response to treatment of a sarcoma in an individual that comprises: a) measuring the GARP expression product in an isolated biological sample; b) compare the quantities obtained with a reference quantity; and c) include the individual in the group of individuals with a lower probability of response to treatment, when the GARP expression product is significantly higher (p < 0.05) than that of the reference sample. 4.- The in vitro method according to claim 3, characterized in that the individual is included in the group of individuals with a lower probability of response to treatment, when the GARP expression product is at least 1.3 times the expression of the reference sample. in vitro method according to claim 4, characterized in that the GARP expression product is at least 1, 5 times the expression of the reference sample. 6. - The in vitro method according to claim 4, characterized in that the GARP expression product is at least 2 times the expression of the reference sample. 7. - The in vitro method according to claim 4, characterized in that the GARP expression product is at least 2.5 times the expression of the reference sample. 8.- The in vitro method according to claim 4, characterized in that the GARP expression product is at least 3 times the expression of the reference sample. 9.- The in vitro method according to claim 4, characterized in that the GARP expression product is at least 3.5 times the expression of the reference sample. 10. - The method according to any of claims 1-9, characterized in that the determination of the GARP expression product is carried out by means of an immunoassay or immunohistochemistry. 11. - The method according to any of claims 1-10, characterized in that the determination of GARP levels is carried out using a technique selected from: immunoblot, enzyme-linked immunosorbent assay (ELISA), linear immunoassay (LIA), radioimmunoassay (RIA), immunofluorescence, x-map or protein chips . 12. - The method according to claim 11, characterized in that the determination of the GARP expression product is carried out by immunohistochemistry. 13. - The method according to any of claims 1-12, characterized in that the treatment is chemotherapy (etopoxide and doxorubicin) and/or radiotherapy. 14. - The method for predicting or forecasting the response to the treatment of a sarcoma according to claim 3, characterized in that step (a) comprises the elements and/or reagents necessary to quantify the levels of GARP in a biological sample. isolated. 15. - The method according to claim 14, characterized in that it comprises primers, probes and/or antibodies capable of quantifying the GARP expression product, and where: - the primers or primers are polynucleotide sequences of between 10 and 30 base pairs that have an identity of at least 80% with a fragment of the sequence complementary to SEQ ID NO: 1 - the probes are polynucleotide sequences of between 30 and 1100 base pairs that have an identity of at least 80% with a fragment of the sequences complementary to SEQ ID NO: 1, - the antibodies are capable of specifically binding to a region formed by the amino acid sequence SEQ ID NO: 2. 16. - The method according to claim 15, characterized in that the primers or primers have a polynucleotide sequence of between 15 and 25 base pairs. 17. - The method according to claim 15, characterized in that the primers or primers have a polynucleotide sequence of between 18 and 22 base pairs. 18. - The method according to claim 15, characterized in that the primers or primers have a polynucleotide sequence of around 20 base pairs. 19. - The method according to claims 15 to 18, characterized in that the primers or primers have an identity of at least 90% with a fragment of the sequences complementary to SEQ ID NO: 1. 20. - The method according to claims 15 to 18, characterized in that the primers or primers have an identity of at least 95% with a fragment of the sequences complementary to SEQ ID NO: 1. 21. - The method according to claims 15 to 18, characterized in that the primers or primers have an identity of at least 98% with a fragment of the sequences complementary to SEQ ID NO: 1. 22. - The method according to claims 15 to 18, characterized in that the primers or primers have 100% identity with a fragment of the sequences complementary to SEQ ID NO: 1. 23. - The method according to claims 15 to 22, characterized in that the probes are polynucleotide sequences of between 100 and 1000 base pairs. 24. - The method according to claims 15 to 22, characterized in that the probes are polynucleotide sequences of between 150 and 500 base pairs. 25. - The method according to claims 15 to 24, characterized in that the probes have an identity of at least 90% with a fragment of the sequences complementary to SEQ ID NO: 1. 26. - The method according to claims 15 to 24, characterized in that the probes have an identity of at least 95% with a fragment of the sequences complementary to SEQ ID NO: 1. 27. - The method according to claims 15 to 24, characterized in that the probes have an identity of at least 98% with a fragment of the sequences complementary to SEQ ID NO: 1. 28. - The method according to claims 15 to 24, characterized in that the probes have a 100% identity with a fragment of the sequences complementary to SEQ ID NO: 1. 29.- The method according to any of claims 14-25, wherein the antibody has the sequence SEQ ID NO:3. 30.- The method according to any of claims 14-25, where step (a) also comprises: a) a solid support that has a primary antibody attached b) a solution of the detection antibody, labeled with an enzymatic marker; and c) a reagent.