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EP3105346A1 - Biomarqueurs arnm prédictifs du traitement au méthotrexate (mtx) - Google Patents

Biomarqueurs arnm prédictifs du traitement au méthotrexate (mtx)

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Publication number
EP3105346A1
EP3105346A1 EP15705277.0A EP15705277A EP3105346A1 EP 3105346 A1 EP3105346 A1 EP 3105346A1 EP 15705277 A EP15705277 A EP 15705277A EP 3105346 A1 EP3105346 A1 EP 3105346A1
Authority
EP
European Patent Office
Prior art keywords
hla
drb4
mtx
responders
treatment
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP15705277.0A
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German (de)
English (en)
Inventor
Bruno STUHLMÜLLER
Karsten MANS
Thomas Häupl
Gerd-R. Burmester
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Charite Universitaetsmedizin Berlin
Original Assignee
Charite Universitaetsmedizin Berlin
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Publication of EP3105346A1 publication Critical patent/EP3105346A1/fr
Withdrawn legal-status Critical Current

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present invention relates to predictive mRNA biomarkers used in combination with HLA-DRB4 to predict treatment with MTX (methotrexate).
  • the present invention further relates to a method of predicting treatment with MTX (methotrexate), comprising the detection of the predictive mRNA biomarkers in combination with HLA-DRB4 in patient samples, wherein the patients are classified into responders or non-responders.
  • RA Rheumatoid arthritis
  • the RA occurs in the total population, depending on the ethnic group, between 0.5 to 3%. Worldwide, the annual incidence is reported to be between 0.1 to 0.5%. In Germany, about 2% of the total population (1.5 million) is affected by this disease; and every year about 100,000 new cases of illness are added. The average cost averaged by this disorder per patient is> € 23,000.
  • the 'rheumatoid factor' is a laboratory parameter in the diagnosis of many rheumatic diseases, but only occurs in about 60% of RA patients (Meyer et al., 1999).
  • the most common laboratory test used today for the diagnosis of RA is the anti-citrullm (anti-CCP) test, which has a significantly higher specificity than the RF test alone. Both test systems have a very good correlation (van Gaalen et al., 2004, Umeda et al., 2013).
  • Second, correlations with human leukocyte antigens have been shown to indicate an increased risk of RA.
  • Methotrexate is the drug of first choice in rheumatoid arthritis and is used in approximately 98% of patients immediately after initial diagnosis. In addition, MTX is also used in other autoimmune diseases and is also a common drug for chemotherapy in various cancers (see Abolmaali et al, 2013 and http://www.cancerresearchuk.org/cancer-help/about-cancer/treatment/cancer - drugs / methotrexate).
  • the object of the present invention was therefore to identify and define suitable biomarkers and to develop suitable test systems in order to enable an improved prediction of the treatment of rheumatic and other diseases.
  • MTX metalhotrexate
  • the gene (s) is (are) used in the form of its mRNA (s).
  • the following 16 genes are assigned to the "HLA-DRB4 positive patient group": ARG1, CKAP4, CRISP3, CST3, GCLM, KIAA0564, KIAA1324, LCN2, LOC654433 / PAX8-AS1, LTP, OLFM4, OSBPL1A, MMP8, SIAH1, SLC8A1 / BF223010 and SULF2.
  • HLA-DRB4-positive patient group and the “HLA-DRB4-negative patient group” herein refer to patients in whose samples the HLA-DRB4 mRNA is expressed as a selectable marker or is not expressed.
  • HLA-DRB4 mRNA is expressed as a selectable marker when a cutoff / cut-off value is reached or exceeded.
  • HLA-DRB4 mRNA is not expressed if a cut-off value is not reached.
  • signal values for the HLA-DRB4 negative patient subgroup of ⁇ 100 and> 1000 for the HLA-DRB4 positive subgroup can be defined as the cut-off value for the FILA gene expression. See, e.g. Table 4.
  • a “predictive marker” refers to a marker that allows the prediction of future expected response (in this case: response and non-response) to a drug.
  • the predictive marker allows the prediction of the course of treatment with a drug, such as MTX, already before the start of treatment The predictive marker allows this prediction for the individual patient.
  • a “predictive marker” differs in particular from a prognostic marker in that in a prognosis at least 2 measurement times are needed to classify a patient as a responder or a non-responder.
  • the patients are preferably classified into responders or non-responders.
  • Methotrexate is the drug of first choice in rheumatoid arthritis and is used in approximately 98% of patients immediately after initial diagnosis.
  • MIX is also used in other autoimmune diseases and is also a common drug for chemotherapy in various cancers (see Abolmaali et al., 2013 and http://www.cancerresearchuk.org/cancer-help/about-cancer/treatment/ cancer-drugs / methotrexate or http: //wvm.drugs.corn/monograph/methotrexate.html#r262).
  • treatment with methotrexate includes combination with biologics and MTX.
  • adalimumab Humira®
  • certolizumab certolizumab
  • golimumab Simponi®
  • infliximab Remicade®
  • rituximab such as rituximab (Rituxan®), abatacept (Orencia®), tocilizumab (Actemra® or
  • the prediction of the treatment and / or the classification of the patients before the start of treatment with MTX metalhotrexate.
  • the samples are preselected in HLA-DRB4-positive or HLA-DRB4-negative samples.
  • inflammatory, chronic inflammatory diseases, autoimmune diseases and / or tumor diseases are preferably treated.
  • the inflammatory, chronic inflammatory diseases and autoimmune diseases are preferably selected from:
  • Rheumatoid arthritis or primarily chronic polyarthritis, juvenile idiopathic arthritis, systemic lupus erythematosus (SLE), systemic sclerosis (scleroderma), polymyositis, dermatomyositis, inclusion-body myositis, psoriasis, multiple sclerosis, uveitis, Crohn's disease, Churg-Strauss disease Syndrome (CSS), Boeck's disease, ankylosing spondylitis, recurrent polychondritis, ulcerative colitis, polymyalgia rheumatica, giant cell arteritis, vasculitis.
  • the tumor diseases are preferably selected from:
  • ALL Acute lymphoblastic leukemia (ALL) (children and adults), bladder urothelial carcinoma, breast cancer, medulloblastoma, ependymoma (children and adults), non-Hodgkin's lymphoma (NHL) (children and adults), osteosarcoma (children and adults).
  • ALL Acute lymphoblastic leukemia
  • bladder urothelial carcinoma breast cancer
  • medulloblastoma medulloblastoma
  • ependymoma children and adults
  • NHL non-Hodgkin's lymphoma
  • osteosarcoma children and adults.
  • At least 50% of the mRNA biomarker genes are determined in combination with HLA-DRB4.
  • biomarker genes 50% of the biomarker genes are 16 of the 32 biomarker genes. In further embodiments, at least 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 or 32 of the 32 biomarker genes are determined, each in combination with HLA-DRB4 ,
  • biomarker genes of the HLA-DRB4 positive patient dummy are determined, in some embodiments only the biomarker genes of the HLA-DRB4 negative patient group are determined, in some embodiments the biomarker genes of both groups, the HLA DRB4-positive and HLA-DRB4-negative patient group determined (in each case in combination with HLA-DRB4).
  • the use according to the invention preferably comprises the determination of the presence of the mRNA marker / biomarker genes and their expression strength in a sample.
  • the presence of the mRNA marker / biomarker genes and their expression strength is preferably determined by means of
  • Sequence-based methods such as serial analysis of gene expression (SAGE) (such as SuperSAGE), real-time quantitative PCR (qPCR) (such as RT-qPCR), bead technology, blot, RNA or next-generation sequencing (such as IonTorrent)
  • SAGE serial analysis of gene expression
  • qPCR real-time quantitative PCR
  • blot blot
  • RNA or next-generation sequencing such as IonTorrent
  • Hybridization-based methods such as in situ hybridization, Northern blot, DNA micro and macroarrays,
  • the technologies for the investigation / determination of gene expression can be divided into hybridization-based methods and sequence-based methods.
  • hybridization-based methods are:
  • RNA is first isolated and electrophoretically separated according to size in a gel. After transfer to a membrane (blotting), the desired RNA sequence is detected by labeled probes (labeled, for example, with radioisotopes, fluorescence dyes) from complementary RNA or DNA via complementary binding. As a rule, only small numbers of sequences are examined simultaneously.
  • the amount of mRNA of a plurality of genes from cells of a culture / tissue can be determined simultaneously.
  • the mRNA is isolated and transcribed into cDNA / cRNA.
  • detection is carried out by complementary hybridization of the labeled cDNA / cRNA (labeled, for example, with radioisotopes, fluorescent dyes) with the probes of the DNA array.
  • RNA microarray techniques use Affymetrix arrays / chips such as biotin / streptavidin amplification and the dye phycoerythrin.
  • sequence-based methods are:
  • SAGE serial analysis of gene expression
  • SuperSAGE the expression of all genes of a cell can be determined very accurately by generating a short sequence piece of each transcript (the so-called "tag") and if possible many of these tags are sequenced.
  • tag a short sequence piece of each transcript
  • the advantage over microarrays is the much more accurate quantification of the transcripts, as well as the ability to identify new transcripts (e.g., non-coding ribonucleic acids such as microRNAs or antisense RNAs) and to study organisms with previously unknown genomes (preferably with SuperSAGE).
  • qPCR real-time quantitative PCR
  • PCR polymerase chain reaction
  • Dyes or special probes added to the reaction mixture are used to monitor the concentration of the product during the PCR.
  • the temporal change of the concentration makes it possible to draw conclusions about the initial concentration of the relevant nucleic acid.
  • RT-qPCR reverse transcriptase real-time qPCR
  • extended form of the multiplex qPCR is a special variant of qPCR.
  • RNA sequencing refers to the determination of the nucleotide sequence of RNA by translating the RNA into cDNA so that the DNA sequencing method can be used Gene expression, for example, how different alleles Genes are expressed to post-transcriptional modifications or for the identification of fusion genes.
  • the DNA microarray technique measures the relative activity of previously identified target genes. Sequence-based methods, such as serial analysis of gene expression (SAGE, SuperSAGE), are also used for gene expression analysis. SuperSAGE is particularly accurate because this method is not limited to previously defined genes but can measure any active gene. Since the introduction of next-generation sequencing methods (RNA-Seq), sequence-based expression analysis has become increasingly popular as it represents a digital alternative to microarrays.
  • SAGE serial analysis of gene expression
  • SuperSAGE is particularly accurate because this method is not limited to previously defined genes but can measure any active gene. Since the introduction of next-generation sequencing methods (RNA-Seq), sequence-based expression analysis has become increasingly popular as it represents a digital alternative to microarrays.
  • the sample according to the invention is preferably a patient sample, which is more preferably selected from whole blood, peripheral blood leukocytes or from purified blood cells.
  • At least one biomarker / gene is selected from the following:
  • HLA-DRB4 as a predictive biomarker for predicting treatment with MTX (methotrexate) / for predicting therapy response to MTX.
  • qPCR real-time quantitative PCR
  • At least one biomarker / gene is selected from CKAP4, CRISP3, KIAA0564, LCN2, OLFM4, MMP8, or SLC8A1 / BF223010 selected from:
  • Method of predicting MTX treatment The object is further achieved according to the invention by methods for predicting the treatment with MTX (methotrexate) / for predicting the therapy response to MTX.
  • the method according to the invention comprises the steps:
  • the patients are classified into responders or non-responders.
  • detecting in step (ii) comprises determining the presence of mRNA markers and their level of expression.
  • determining the relative level of expression of the at least one mRNA biomarker and HLA-DRB4 in step (iii) comprises comparing the level of expression with a cut-off value.
  • determining the relative level of expression of the at least one mRNA biomarker and HLA-DRB4 in step (iii) further comprises determining a Fold Change (FC).
  • the limit values or cut-off values are determined by the manufacturer of the array or chip and / or the evaluation software used (such as BioRetis, online database of BioRetis GmbH Berlin).
  • the cut-off value may be> 50
  • the amount of the regulation factor (FC) may be at least 1.5 (
  • step (iii) the expression level of the at least one mRNA biomarker and of HLA-DRB4 is compared with reference standard (s) and / or control sample (s).
  • the reference standard (s) according to the invention in step (iii) is preferably sample (s) containing one or more household gene (s), such as actin-beta (ACTB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 60S ribosomal protein PO (RPLPO).
  • ACTB actin-beta
  • GPDH glyceraldehyde-3-phosphate dehydrogenase
  • RPLPO 60S ribosomal protein PO
  • control sample (s) according to the invention in step (iii) are preferably samples of responders and / or non-responders.
  • control sample (s) according to the invention are preferably reference collectives, ie several or a plurality of samples of responders and / or non-responders.
  • control samples the 52 patient samples as described herein in the examples are used.
  • the relative expression strength of the at least one mRNA biomarker and the presence or absence of expression of HLA-DRB4 preferably results from the comparison with control sample (s) of responders and / or non-responders.
  • FC Frexacity
  • a regulation factor (FC, "Fold Orange) or an amount of the regulation factor of at least 1.5 (or>
  • the at least 70% of the individual samples / patients are preferably 60 to 100%, more preferably 70 to 100% or 70 to 90%.
  • each sample or control sample is compared with the other individual samples / control samples.
  • pairwise individual comparisons are made with all control samples (i.e., samples from known responders and / or non-responders) to classify into responders and non-responders.
  • the patients are classified as responders if in step (iii) in 60-100% (preferably at least 70%) of the pairwise comparisons the relative expression level has a value of>
  • FC is achieved at 100% of the detected mRNA biomarker.
  • the patients are classified as non-responders if in step (iii) in 60-100% (preferably at least 70%) of the pairwise comparisons the relative expression level with a reciprocal FC value of>
  • the treatment with methotrexate comprises the combination with biologics such.
  • Anti-TNF antibodies as described above
  • MTX methotrexate
  • the prediction of the treatment and / or the classification of the patients before the start of treatment with MTX metalhotrexate.
  • the sample (s) are preselected in HLA-DRB4-positive or HLA-DRB4-negative sample (s).
  • the sample is subjected to a pretreatment.
  • Such pretreatment may include:
  • Label with label e.g. Biotin.
  • detecting in step (ii) comprises determining the presence of mRNA markers and their level of expression.
  • the determination is preferably carried out by means of
  • Sequence-based methods such as serial analysis of gene expression (SAGE) (such as SuperSAGE), real-time quantitative PCR (qPCR) (such as RT-qPCR), bead technology, blot, RNA or next-generation sequencing (such as IonTorrent)
  • SAGE serial analysis of gene expression
  • qPCR real-time quantitative PCR
  • blot blot
  • RNA or next-generation sequencing such as IonTorrent
  • Hybridization-based methods such as in situ hybridization, Northern blot, DNA micro and macroarrays,
  • At least one mRNA biomarker is selected in step (ii)
  • At least one mRNA biomarker is selected from CKAP4, CRISP3, KIAA0564, LCN2, OLFM4, MMP8, or SLC8A1 / BF223010 from:
  • inflammatory, chronic inflammatory diseases, autoimmune diseases and / or tumor diseases are preferably treated.
  • the inflammatory, chronic inflammatory diseases and autoimmune diseases are preferably selected from:
  • Rheumatoid arthritis or primarily chronic polyarthritis, juvenile idiopathic arthritis, systemic lupus erythematosus (SLE), systemic sclerosis (scleroderma), polymyositis, dermatomyositis, inclusion-body myositis, psoriasis, multiple sclerosis, uveitis, Crohn's disease, Churg-Strauss disease Syndrome (CSS), Boeck's disease, ankylosing spondylitis, recurrent polychondritis, ulcerative colitis, polymyalgia rheumatica, giant cell arteritis, vasculitis.
  • the tumor diseases are preferably selected from:
  • Acute lymphoblastic leukemia (ICinder and adults), bladder urothelial carcinoma, breast cancer, medulloblastoma, ependymoma (children and adults), non-Hodgkin's lymphoma (NHL) (children and adults), osteosarcoma (children and adults).
  • ALL Acute lymphoblastic leukemia
  • bladder urothelial carcinoma breast cancer
  • medulloblastoma ependymoma
  • NHL non-Hodgkin's lymphoma
  • osteosarcoma children and adults.
  • at least 50% of the biomarker genes are determined in combination with HLA-DRB4.
  • 50% of the biomarker genes are 16 of the 32 biomarker genes.
  • only the biomarker genes of the HLA-DRB4 positive patient group are determined, in some embodiments only the biomarker genes of the HLA-DRB4 negative patient group are determined, in some embodiments, the biomarker genes of both groups, the HLA DRB4-positive and HLA-DRB4-negative patient group determined (in each case in combination with HLA-DRB4).
  • the sample according to the invention is preferably a patient sample, which is more preferably selected from whole blood, peripheral blood leukocytes or from purified blood cells.
  • kits for predicting the treatment with MTX metalhotrexate
  • MTX metalhotrexate
  • a kit according to the invention comprises:
  • Control sample (s) comprising sample (s) of respondera and / or non-responders.
  • Suitable reference standard (s) and control sample (s) are as described above.
  • the means (a) for carrying out for detecting at least one mRNA biomarker (s) are selected from
  • At least one mRNA biomarker is selected from CKAP4, CRISP3, KIAA0564, LCN2, OLFM4, MMP8, or SLC8A1 / BF223010 from:
  • the means (a) for carrying out for detecting at least one mRNA biomarker (s) in patient samples preferably comprise:
  • the object is further achieved according to the invention by the use of at least one miRNA which is selected from the following 6 miRNAs:
  • the patients are preferably classified into responders or non-responders.
  • methotrexate is the drug of choice in rheumatoid arthritis and is used in approximately 98% of patients immediately after initial diagnosis.
  • MTX is also used in other autoimmune diseases and is also a common drug for chemotherapy in various cancers (see Abolmaali et al, 2013 and http://www.cancerresearchuk.org/cancer- help / about-cancer / treatment / cancer -drugs / methotrexate or
  • treatment with methotrexate includes combination with biologics and MTX.
  • adalimumab Humira®
  • certolizumab certolizumab
  • golimumab Simponi®
  • infliximab Remicade®
  • Rituximab (Rituxan®), Abatacept (Orencia®), Tocilizumab (Actemra® or RoActemra®)
  • the prediction of the treatment and / or the classification of the patients before the start of treatment with MTX metalhotrexate.
  • the samples are preselected in HLA-DRB4-positive or HLA-DRB4-negative samples.
  • inflammatory, chronic inflammatory diseases, autoimmune diseases and / or tumor diseases are preferably treated.
  • the inflammatory, chronic inflammatory diseases and autoimmune diseases are preferably selected from:
  • Rheumatoid arthritis or primarily chronic polyarthritis, juvenile idiopathic arthritis, systemic lupus erythematosus (SLE), systemic sclerosis (scleroderma), polymyositis, dermatomyositis, inclusion-body myositis, psoriasis, multiple sclerosis, uveitis, Crohn's disease, Churg-Strauss disease Syndrome (CSS), Boeck's disease, ankylosing spondylitis, recurrent polychondritis, ulcerative colitis, polymyalgia rheumatica, giant cell arteritis, vasculitis.
  • the tumor diseases are preferably selected from:
  • ALL Acute lymphoblastic leukemia (ALL) (children and adults), bladder urothelial carcinoma, breast cancer, medulloblastoma, ependymoma (children and adults), non-Hodgkin's lymphoma (NHL) (children and adults), osteosarcoma (children and adults).
  • ALL Acute lymphoblastic leukemia
  • bladder urothelial carcinoma breast cancer
  • medulloblastoma medulloblastoma
  • ependymoma children and adults
  • NHL non-Hodgkin's lymphoma
  • osteosarcoma children and adults.
  • the use according to the invention preferably comprises the determination of the presence of the miRNA marker (s) in a sample.
  • the presence of the miRNA marker / biomarker is preferably determined by means of:
  • Sequence-based methods such as serial analysis of gene expression (SAGE) (such as SuperSAGE), real-time quantitative PCR (qPCR) (such as RT-qPCR), bead technology, blot, RNA or next-generation sequencing (eg IonTorrent)
  • SAGE serial analysis of gene expression
  • qPCR real-time quantitative PCR
  • blot blot
  • RNA or next-generation sequencing eg IonTorrent
  • Hybridization-based methods such as in situ hybridization, Northern blot, DNA micro and macroarrays,
  • Microarray analysis, quantitative PCR and / or bead-based methods are preferably used for the determination of miRNAs.
  • the sample according to the invention is preferably a patient sample, which is more preferably selected from whole blood, peripheral blood leukocytes or from purified blood cells.
  • the object is further according to the invention by methods for the prediction of
  • the method according to the invention comprises the steps:
  • detecting in step (ii) comprises determining the presence of the miRNA markers.
  • the patients are classified into responders or non-responders.
  • the patients are classified as responders if the expression among themselves to the non-responder with a FC value of at least
  • and within the comparison with the non-responder a significance of p ⁇ 0.05 occurs.
  • the patients are classified as non-responders if the expression among themselves to the non-responder with a FC value of at least
  • and within the comparison with the responder a significance of p ⁇ 0.05 occurs.
  • the treatment with methotrexate (MTX) comprises the combination with biologics such. Anti-TNF antibodies (as described above), and MTX.
  • the prediction of the treatment and / or the classification of the patients before the start of treatment with MTX metalhotrexate.
  • the sample is subjected to a pretreatment.
  • Such pretreatment may include:
  • Labeling with indirect labels e.g. Biotin, streptavidin, and / or
  • detecting in step (ii) comprises determining the presence of the miRNA markers.
  • the determination is preferably carried out by means of
  • Sequence-based methods such as serial analysis of gene expression (SAGE) (such as SuperSAGE), real-time quantitative PCR (qPCR) (such as RT-qPCR), bead technology, blot, RNA or next-generation sequencing (eg Ion Torrent),
  • SAGE serial analysis of gene expression
  • qPCR real-time quantitative PCR
  • blot blot
  • RNA or next-generation sequencing eg Ion Torrent
  • Hybridization-based methods such as in situ hybridization, Northern blot, DNA micro and macroarrays,
  • Microarray analysis and / or quantitative PCR are preferably used for the determination of miRNAs.
  • inflammatory, chronic inflammatory diseases, autoimmune diseases and / or tumor diseases are preferably treated.
  • the inflammatory, chronic inflammatory diseases and autoimmune diseases are preferably selected from:
  • RA Rheumatoid arthritis
  • SLE systemic lupus erythematosus
  • Scleroderma systemic sclerosis
  • polymyositis dermatomyositis
  • inclusion-body myositis psoriasis
  • psoriasis multiple sclerosis
  • uveitis Crohn's disease
  • Boeck's disease ankylosing spondylitis, recurrent polychondritis, ulcerative colitis, polymyalgia rheumatica, giant cell arteritis, vasculitis.
  • the tumor diseases are preferably selected from:
  • ALL Acute lymphoblastic leukemia (ALL) (children and adults), bladder urothelial carcinoma, breast cancer, medulloblastoma, ependymoma (children and adults), non-Hodgkin's lymphoma (NHL) (children and adults), osteosarcoma (children and adults).
  • ALL Acute lymphoblastic leukemia
  • bladder urothelial carcinoma breast cancer
  • medulloblastoma medulloblastoma
  • ependymoma children and adults
  • NHL non-Hodgkin's lymphoma
  • osteosarcoma children and adults.
  • the sample according to the invention is preferably a patient sample, which is more preferably selected from whole blood, peripheral blood leukocytes or from purified blood cells.
  • the reference standard / the control sample in step (iv) is preferably a reference standard consisting of household gene (s),
  • Embodiment Rheumatoid Arthritis (RA)
  • RA is usually treated immediately after diagnosis by a rheumatologist with disease-modifying anti-rheumatic drugs (DMARDs).
  • DMARDs disease-modifying anti-rheumatic drugs
  • This category also includes the conventionally used MTX, which is> 95% DMARD of choice.
  • the therapeutic success is not yet predictable and so far exists with the detectable joint destruction.
  • MTX is also used to treat other rheumatic diseases, other autoimmune diseases and the treatment of cancer.
  • the RA patient shows individual success after 3-6 weeks from the start of treatment, but only proves this after assessing the clinical parameters for determining the DAS28 change. An assessment of the response rate is certainly guaranteed only after 12-14 weeks (Quinn et al., 2005) and only reaches the maximum after about 6 months.
  • this is expressed by the preselection of HLA-DRB4 subgroups in combination with the 16 specific candidate genes for the evaluation of responders and non-responders.
  • Total genomic transcriptional analyzes are new technologies that, on the one hand, allow rapid, adapted adaptation to other molecular technologies, and have a very high priority for individualized medicine.
  • microfluidic based techniques can / will help relieve the health care system of annually increasing costs
  • these methods using whole blood as a starting material routinely accepted in the clinical trials, are well suited to providing rapid and differentiated results and to provide the physician with an effective choice of treatment for the individual patient as early as possible, with the aim of avoiding side effects (>5%;).
  • the inventors have now succeeded in developing a predictive test to estimate the future response to MTX therapy using the following predictive biomarker genes in combination with HLA-DRB4:
  • DEF4A Defensin alpha 4 (DEFA4, alias: cortico statin), which is expressed more strongly in MTX responders in the I ILADR B4 negative subgroup, has a multitude of biological functions.
  • DEF4A is described as acting for peptides with microbial and cytotoxic antiviral function for pathogen defense (Spitznagel, 1990, Wu et al., 2005).
  • DEF4A inhibits corticotropin-stimulated corticosterone production (Genz et al., 1990).
  • DEF3A has been reported by, among others, Cheok et al. (2003) as a marker contributing to the discrimination of drug responses. These findings were obtained from human leukemia cell lines in vitro.
  • the prediction marker Complement Factor-D (CFD, alias: adipsin), which is up-regulated in respondents of the HLA-DRB4 negative subgroup, functionally belongs to the trypsin family of peptidases. CFD is a component of the alternative complement pathway and is also involved in the humoral response to ward off infectious agents (Jouvin et al, 1983).
  • Transcobalamin-1 (TCN1) encodes a vitamin B12 binding protein and transfers cobalamin into the cell. Diseases that have been reported in the literature in connection with this gene are Pernicious anemia, pemicious anemia, and oral tumors. Interestingly, at the genetic level, polymorphisms within the TCN family have been described that influence MTX metabolism (Linnebank et al., 2005). Parallels between genetic and genomic findings are not yet known.
  • RNASE2 Ribonuclease-2 belongs to the ribonuclease type A family, has ribonuclease activity and binds nucleic acids. Further specified, RNASE2 is a pyrimidine-specific nuclease with also low binding affinity for uridine, cytotoxin and helminthotoxin. Another biological role of RNASE2 is in immune overreaction and in anti-parasitic defense (Yang et al., 2003; Yang et al., 2004). RNASE2 is also chemotactic for dendritic cells and is an endogenous ligand for Toll-like receptor-2 (Rosenberg 2008).
  • Transketolase-like I (TKTLI) is functionally involved in the pentose phosphate pathway and has been described to regulate the effects of MTX (Lee et al., 2008). In our own investigations, the predictive marker TKT, but not TKTL1, could be identified, which is described in the rat tumor model as an MTX predictor (Yamashita et al., 1999).
  • Peptidylglycine alpha-amidating monooxygenase (PAM), a coded enzyme capable of binding divalent copper and calcium ions, is involved in a variety of different biological functions (Prigge et al., 2000). An indirect or direct link to MTX interaction with efficacy effects is not known to date.
  • the potassium channel CNE3 belongs to the Isk family. The biological function of potassium channels is manifold. It is known that in gene model member 4 (KCNE4) in the rat model, Lee et al. (2008) show that MTX has an influence on its expression strength. 9.
  • KCNE4 gene model member 4
  • MTX has an influence on its expression strength.
  • SAG9 Sperm associated antigen-9
  • the encoded protein of SPAG9 mRNA has scaffold protein properties and structurally assembles with mitogen-activated protein kinases, thus contributing to c-Jun terminal kinase mediated sinaltransduction. SPAG9 binds to kinesin-1 and plays a role in tumor growth and development. To date, there are no connections to MTX.
  • Mitochondrial precursor Peroxiredoxin-5 (PRDX5) interacts with the peroxisome receptor 1 and has antioxidant protective functions in the normal and inflammatory tissues (Yamashita et al., 1999). Again, so far no connection with MTX is known.
  • the aquaporin-3 (AQP3) mRNA is down-regulated and encodes a protein-associated protein (Ishibashi et al., 1995), such as the
  • Wntless Wnt ligand secretion mediator has so far been largely functionally unknown. Involvement of the protein is discussed in NFkB and MAP kinase pathway (Matsuda et al., 2003). A direct and indirect connection to MTX is not known for either AQP3 or WLS.
  • the encoded GATA-binding protein-3 (GA A3) carries two GATA-type-specific zinc fingers, and is involved in the regulation of T cells in the so-called 'innate lymphoid group 3' cell development (Yagi et al. 2011, Serafini et al, 2014) and endothelial cell maturation (Umetani et al., 2001). GATA3 has been ascribed an immunosuppressive and anti-inflammatory effect (Li et al., 2013).
  • GATA3 has been described in vitro as a predictor of cytorabine hydrochloride (Ara-C), dexamethasone, methylprednisolone, mitoxantrone and rituximab treatment in tumor cell lines (US 2009/0023149 AI). It has also been described that GATA3 is a predictor of taxane insensitivity (Tominaga et al., 2012). The mRNA of GATA3 is upregulated in rat liver tumor tissue and in human breast cancer cell tissue by treatment with MTX (Belisnky et al, 2007, Gulbahce et al, 2013). However, a prediction of the efficacy of MTX does not follow from these findings. 14.
  • Eukaryotic translation initiation factor 5A encodes an mRNA-binding protein involved in translation elongation. It is also known that EIF5A plays a role in methionine metabolism and in hyposine biosynthesis (Scuoppo et al., 2012). Overexpression of EBF5A mR A in colorectal tumor tissue samples correlates with tumor severity in patients with colorectal cancer disease. EIF5A has therefore been proposed as a prognostic marker for the success of MTX-treated patients with colorectal cancer (Tunca et al., 2013, and Council Genome Database, Bioinformatics Research Center, Medical College of Wisconsin, National Heart Lung and Blood Institute (NHLBI)). ,
  • the mRNA for 'Solute carrier family' member E2_i (SLC35E2) is a new member of the 'Solute Carrier Family' and contributes to the sugar transport nucleotide.
  • the model system has shown that this transporter is involved in tumor metastasis, cellular immunity, organogenesis, and morphogenesis and in the development of connective tissue and muscle (Ishida & Kawakita 2004).
  • SLC35, as well as the other members of this gene family have transporter functionalities, including drugs, via nucleotide sugar, and are localized in the Golgi apparatus and in the endoplasmic reticulum (Nishimura et al., 2009).
  • Pathologically in animal studies of the deficiency of this gene increased tumor metastasis, as well as a disturbance of immunity, organogenesis and morphogenesis (Ishida & Kawakita 2004).
  • the upregulated mRNA of the small nucleolar RNA host gene 5 gene (SNHG5, alias: U50HG) is involved in ribosome biogenesis (Tanaka et al., 2000).
  • SNHG5 has been described as a biomarker in B-cell lymphoma, breast and prostate tumors (Dong et al., 2009, Nakamura et al, 2008, Dong et al., 2008) and is being amplified there expressed.
  • the irradiation of tumor cells leads to a counterregulation with a reduction of the mRNA expression of SNHG5 (Chaudry 2013).
  • KIAA1324 is still a functionally unknown gene. ⁇ 1 ⁇ 1324 is overexpressed in intestinal tumor cells and has been described as a diagnostic marker in epithelial intestinal tumors (US 2008/0064049 AI).
  • SIAH1 E3-ubiquitin protein ligase-1
  • the gene for E3-ubiquitin protein ligase-1 encodes a protein from the, seven in absentia homologous family (Hu et al., 1997, Nakayama et al., 2004).
  • SIAH1 plays a major role in the development of various Parkinson's diseases (Franck et al., 2006).
  • SIAH5 is regulated in conjunction with high-density lipoproteins after hypoxia and apoptosis induction via the Jun kinase pathway (Nakayama et al., 2004).
  • Cystatin-3 (CST3, alias: cystatin-C) encodes a protein that contains multiple cystatin-like sequence regions (Türk et al., 2008). CST3 is more extensively expressed in atherosclerosis (Arpegard et al, 2008), but also in diseases of the rheumatic type (Hansen et al., 2000). Hayashi et al. (2010) was able to show that an elevated serum level of Cys-C is an indicator of MTX-induced myelotoxicity in patients with RA. As with the findings of the inventors on mRNA level, especially the MTX responders, CST3 is also upregulated at the protein level of RA patients before treatment with MTX. From this it can be concluded that with MTX treatment increased myelotoxicity is to be expected also in the responders.
  • Sulfatase-2 is a heparan sulfate 6-O-endosulfatase.
  • SULF2 modulates hepatan sulfate binding by altering binding sites on cell-signaling receptors (Dai et al., 2005). Elevated expression levels of SULF1 and SULF2 are described for both tumor tissue (Wigersma et al., 1991, Nawroth et al, 2007) and inflammatory diseases such as osteoarthritis (Otsuki et al., 2008) or RA in synovial tissue (Kar et al., 1976). 5.
  • KIAA0564 (alias: Von Willebrand Factor A d omain containing 8) is functionally unknown. However, the term and other evidence suggests that von Willebrand Factor A domain containing 8 / KIAA0564 is a protein with cell adhesion properties (Reininger et al., 2006). GO annotations show that this protein has ATPase activity and ATP binding. KIAA0564 has been described in the context of diagnosis and prevention with a perspective for the prediction of therapies (WO 2002/008423 A2).
  • GCLM Glutamate-Cysteine Liquefacial Modifie
  • GCLM is important in erythrocyte survival (Foller et al., 2013) and is up-regulated in hemolytic anemia.
  • GCLM is downregulated in the MTX responders compared to the nonresponders of the HLA-DRB4 positive subgroup.
  • C AP4 The cytoskeleton-associated protein 4 (C AP4) is a transmembrane protein and is expressed in the endoplasmic reticulum. Increased expression of C AP4 has been observed in metastatic lymphoid tissue (Li et al., 2013). Functionally, CKAP4 regulates the plasminogen activating system of blood vessels (Razzaq et al., 2003). In addition, susceptibility to MTX has been reported for CKAP4 (Prigge et al., 2000) and CKAP4 has been described as a predictor of MTX in tumor disease (US 8,445,198 B2, US 2008/0292546 AI).
  • the oxysterol binding protein-like LA (OSBPL1A) is co-localized with the GTPases Rab7, Rab9 and the lysosome-associated membrane protein- ⁇ and binds phosphoinositides to endosomes and lysosomes (Johansson et al., 2005). A connection to MTX was not described.
  • the expressed gene 'Solute carrier family 8A member V acts as a sodium / calcium exchanger (Khananshvili, 2013) and GO annotations indicate that it is a cytoskeletal protein with calmodulin-binding function.
  • the transcriptional regulator (miRNA) of SLC8A1 but not SLC8A1 itself has been described as a predictor of MTX treatment in inflammatory bowel disease (WO 2009/120877 A2; WO 2011/014721 A2).
  • MTX a transcriptional regulator
  • SLC35E2 see also the Rat Genome Database, Bioinformatics Research Center, Medical College of Wisconsin, National Heart Lung and Blood Institute (NHLBI).
  • SLC8A1 has been described as a diagnostic marker for autoimmune diseases such as Systemic Lupus Erythematosus (SLE) and ANCA positive Wegener Granulomatosus (WO 2006/020899 A2).
  • the biomarker LOC654433 is a long non-coding RNA with previously unknown function.
  • Arginase 1 is a type I specific arginase that catalyzes the hydrolysis of arginine to ornithine with the elimination of urea (Ivanenkov et al., 2014).
  • Monocytes / macrophages are the major cell population expressing arginases (Murphy et al., 1998).
  • Huang et al. (2001) reported that arginase activity was significantly associated with Arginase protein expression in patients with RA.
  • Gene expression of ARG1 is enhanced in the HLA-DRB4 positive subgroup in the MTX responders. Shen et al. (2013) showed a correlation of the expression of ARG1 and the folate receptor-ß on positive Ml-type macrophages, which also express the mannose receptor. There is no direct correlation between gene expression of ARG1 and MTX.
  • Lipocalin 2 (LCN2) is expressed on neutrophils and is associated with the proteolytic enzyme gelatinase (Kjeldsen et al., 2000).
  • LCN2 is an iron trafficking protein involved in multiple processes, such as innate immunity (Zughaier et al., 2013, Landro et al., 2008), renal development, and cell migration (Paulsson et al., 2007). Bläser et al. (1995) reported that Lipocalin 2 is detectable in high amounts in the synovial fluid of patients with RA. In responders of the HLA-DRB4 positive subgroup, the mRNA encoding this enzyme is reduced.
  • CRISP3 The biomarker 'Cysteine Rich Secretory Protein' (CRISP3) has so far no biological function described.
  • a paralogue of CRISP3 is the C-type lectin domain family 18, member B (CLEC18B), which - according to GO annotation - has the ability to bind carbohydrates as a 'mannose receptor-like protein'.
  • CRISP3 interacts with 17beta-estradiol (Pfisterer et al., 1996).
  • Gene expression of CRISP3 is expressed more extensively in DHEA-stimulated human submandibular gland cells (Laine et al., 2007).
  • Gene expression of CRISP3 has been described in the context of the disease Sjögren 's syndrome (Tapinos et al., 2002).
  • CRISP3 has been described as a predictor of the treatment of prostate cancer cells (WO 2013/070088 AI).
  • Lactotransfenin (LTF, alias: lactoferrin) is a member of the transferrin gene family and is essentially expressed by neutrophils.
  • the LTF protein has heparin binding activity and has a broad functional spectrum. This includes u.a. an anti-inflammatory activity (Paulsen et al., 2002), regulation of cell growth and differentiation (Liao et al., 2012) and protection in the development of tumors (Kanwar et al., 2013).
  • LTF acts as a so-called survival factor for neutrophils in the synovial fluid (Wong et al., 2009).
  • MTX reduces expression of LTF mRNA (Oshida et al., 2011).
  • LTF has been described as a predictive gene for the treatment of ethanecept, an anti-TNF biologic, among other 43 genes.
  • the studies do not refer to the baseline gene expression before therapy alone, but were dependent on a second examination a few days after the start of therapy and therefore have no predictive, but rather a prognostic value.
  • the protein-coding Olfactomedin 4 (OLFM4) mRNA assigned to the Noelin gene family is increasingly expressed during myeloid cell development and has been described for the first time in myeloblasts (Zhang et al., 2002).
  • the protein OLFM4 is expressed in the endoplasmic reticulum, has an anti-apoptotic function and among other things promotes tumor growth (Park et al., 2012).
  • OLFM4 prevents cell growth of prostate tumor cells and has a suppressive effect on bone metastatase via the negative interaction with cathepsin D and the chemokine (CXC Motif) ligand 12 (alias: SDF-1, Berger 1988).
  • OLFM4 In systemic lupus erythematosus and inflammatory bowel disease, OLFM4 has been described as a diagnostic and prognostic marker in conjunction with other other markers (US 8,148,067 B2, US 8,148,067 B2). To date, there is no knowledge about the role and expression of OLFM4 in RA. However, in inflammatory bowel disease, OLFM4 has been described as a diagnostic biomarker and regulates autophagic processes via cathepsin-D involvement in the immune response to bacterial infections (Montero-Melendez et al., 2013). 16.
  • MMP8 matrix metalloproteinase-8
  • HLA-DRB4 positive RA subgroup The matrix metalloproteinase-8 (MMP8), the penultimate biomarker for the MTX prediction of the HLA-DRB4 positive RA subgroup, is capable of degrading type II collagen (Billinghurst et al., 1997). A connection to MTX does not exist so far
  • Figure 2 Hierarchical cluster analysis of HLA-DRB4 positive and HLA-DRB4 negative patient subgroups between responders and non-responders.
  • FIG. 1 Hierarchical cluster analysis of HLA-DRB4 positive and HLA-DRB4 negative patients Subgroups between responders and non-responders, including the moderate responder group.
  • HLA-DRB4 positive and HLA-DRB4 negative RA patient subpopulations Considering the classification into HLA-DRB4 positive and HLA-DRB4 negative RA patient subpopulations, according to the described conditions (HLA-DRB4 cut-off values, the given fold change value and the increased / decreased reference values) within the pairwise comparisons between responders and non-responders, hierarchical cluster analyzes were performed involving the moderate responders. Genesis cluster analysis was performed by log transformation followed by Pearson analysis. Again, the HLA-DRB4 negative RA patient subgroup showed a clear separation between the responders and the non-responders with a specificity and sensitivity of 100%. In the HLA-DRB4 positive RA patient subgroup, a sensitivity of 100% and a specificity of 92.9% (without consideration of the moderate responders) and 95.7% (with the moderate responders who were rated as responders) were achieved.
  • FIG. 4 Validation of Affymetrix gene selection via quantitative real-time PCR. Exemplary results of the validations, for the prediction of therapy response to MTX, are presented on quantitative real-time qPCR with triplicate evaluations (A) HLADRB4; (B) RNASE2; (C) MMP8.
  • the representation of the y-axis represents the gene expression of the individual candidate genes in relation to the applied household gene 'Ribosomal Protein Large PO' (RPLPO).
  • RPLPO Ribosomal Protein Large PO'
  • the presentation was made using a box plot method using the software SPSS.
  • the bars represent the mean, and the bars show the standard deviation within the comparisons between the MTX Responders (R), the Moderate Responders (MR) and the Non-Responders (NR).
  • the points indicate absolute deviations that are not within the defined range.
  • Figure 5 Validation of affymetrix gene selection via quantitative real-time PCR. Presented are results of the validations, for the prediction of therapy response on MTX, on quantitative real-time qPCR with triplicate evaluations.
  • the representation of the y-axis represents the gene expression of the individual candidate genes in relation to the applied household gene 'Ribosomal Protein Large PO' (RPLPO).
  • RPLPO Ribosomal Protein Large PO'
  • the presentation was made using a box plot method using the software SPSS.
  • the bars represent the median value and the bars show the standard deviation within the comparisons between the MTX Responders (R), the Moderate Respondem (MR), and the Non-Responders (NR).
  • the points indicate absolute deviations that are not within the defined range.
  • Figure 6 Validation of affymetrix gene selection via quantitative real-time PCR. Presented are results of the validations, for the prediction of therapy response on MTX, on quantitative real-time qPCR with triplicate evaluations.
  • the representation of the y-axis represents the gene expression of the individual candidate genes in relation to the applied household gene 'Ribosomal Protein Large PO' (RPLPO).
  • RPLPO Ribosomal Protein Large PO'
  • the presentation was made using a box plot method using the software SPSS.
  • the bars represent the median value and the bars show the standard deviation within the comparisons between the MTX responders (R), the moderate responders (MR) and the non-responders (NR).
  • the points indicate absolute deviations that are not within the defined range.
  • the stored and frozen PAXgene blood tubes were thawed according to the manufacturer's instructions for two hours at room temperature and the RNA using the PAXgene Blood miRNA ® Kit (PreAnalytiX) were prepared. This kit allows for both mRNA and miRNA transcriptional analysis. The amount of the purified total RNA was performed in the NanoDrop 1000 ® UV Vis Spectrophotometer (Thermo Fisher Scientific Inc., NanoDrop, Wilmington, DE, USA) and the quality check on the Bioanalyzer 2100 ® (Agilent Technologies Inc., Santa Clara, CA, USA ).
  • globin mRNA was reduced using the GLOBINclear TM kit (Life Technologies, Ambion, USA) according to the manufacturer's instructions. This was followed by synthesis of the complementary DNA (cDNA) and transcription in vitro transcription into cRNA via the Affymetrix GeneChip® 3'IVT Express kit (Affymetrix, Santa Clara, CA, USA). The amplified and biotin-labeled cRNA was then used according to the manufacturer's instructions on the GeneChip® Human Genome U133 Plus 2.0 arrays hybridized for 16 hours at 45 ° C. The washes and labeling were done in a GeneChip® Fluidics Station 450 GeneChip® using Affymetrix hybridization, washing and labeling kit. Hybridization signal readout was performed in an Affymetrix GeneChip® 3000 7G scanner, followed by normalization using the Affymetrix MAS5.0 algorithm of the Expression Console software.
  • the differential mRNA gene expression was evaluated via the BioRetis Online database (BioRetis GmbH, Berlin). This was done by pre-filtering the data according to the criteria> 70% in all group comparisons (eg R versus NR) and a fold change of> 1.5 or ⁇ -1.5.
  • the limit of signal strength, within the pairwise group comparisons (responder versus non-responder); without and with the moderate responders) was set to at least> 50 in one of the two comparison groups.
  • the data was visualized using the hierarchical clustering software Genesis 1.7.6 (Gene Expression Similarity Investigation Suite, University of Graz, Austria; Sturn et al., 2002) on log transformation and Pearson analysis. Signals, clinical data, and mutually both were determined via 1- and 2-tailed Wilcoxon Rank test using the IBM Software SPSS Statistics v.22 (Stacon, Witzenhausen, Germany).
  • qPCR quantitative real-time PCR
  • VAS Visual Analog Squares
  • HAQ Health Assessment Questionnaire
  • the following criteria were set via the database query in BioRetis (online database of BioRetis GmbH, Berlin): minimal change call with a match of> 30% increase / decrease within the group comparisons (R vs. NR) and a fold change (FC) from>
  • Amount).
  • the Analysis yielded a candidate gene of 14 genes.
  • the selection criteria of the query to identify the two HLA-DRB4 subgroup-specific genes between the group of responders and the nonresponders were at least 70% matches (increase / decrease, see Tables 2 and 3) within the pairwise single comparisons (R vs. NR) and an average fold factor (FC) of>
  • the sensitivity was 100% and the specificity 93%.
  • the moderate responders (n 4) within the non-responder group and all MTX responders clustered separately in a distinctly remote group.
  • the sensitivity was as well as the specificity at 100% each ( Figure 3A and 3B).
  • HLA-DRB4 negative subgroup and HLA-DRB4 gene sets were validated via the quantitative RT-qPCR and provided a relatively clear agreement of regulation within the respective groups (responders and non-responders). See Figure 4 with exemplary results of the validation.
  • the amount of the purified total RNA was performed in the NanoDrop 1000 ® UV Vis Spectrophotometer (Thermo Fisher Scientific Inc., NanoDrop, Wilmington, DE, USA) and the quality check on the Bioanalyzer 2100 ® (Agilent Technologies Inc., Santa Clara, CA, USA ).
  • Affymetrix-based differential expression analysis of 30 of the 32 defined biomarkers was assessed by an independent method using quantitative real-time PCR (qPCR).
  • qPCR quantitative real-time PCR
  • 2 primer assay Qiagen; Hilden, Germany
  • Power SYBR ® Green PCR Master Mix for two of the defined biomarkers, no commercial RT 2 primer assays were available at the time of the experiment.
  • the evaluation was carried out by normalizing the gene expression of the individual candidate genes in relation to the applied household gene 'Ribosomal Protein Large PO' (RPLPO).
  • QPCR runs were in a StepOne Plus ® real-time cycler (Life Technologies, Carlsbad, CA, USA) down.
  • Amplification efficiencies and efficiency-corrected delta-delta-Ct (A ⁇ Ct) values were calculated according to Fleige et al., 2006.
  • the gene sets of the FILA-DRB4 negative subgroup and the HLA-DRB4 positive subgroup were validated by quantitative RT-qPCR and provided a relatively clear agreement of regulation within the respective groups (responders and non-responders).
  • CRISP3, LCN2, MMP8, OLFM4 resulted in an average regulation factor
  • of> 3 signal; p value qPCR ⁇ 0.1; Correlation to the microarray data at least> 0.5.
  • miRNA expression profiles of n 39 patients, the two previously mentioned clinical studies, were determined.
  • the purified total RNA was processed with the Affymetrix Flash-Taq TM Biotin HSR RNA Labeling Kit (Genisphere, Hatfield, PA, USA).
  • the hybridization of the labeled samples was carried out for 16 hours at 45 ° C with miRNA 2.0 microarrays according to the manufacturer's instructions in the GeneChip® Fluidics Station 450.
  • the hybridization signals were read in the Affymetrix GeneChip® 3000 7G scanner and the normalization of the data with the post
  • the samples were washed with the miRNA QCTool software version 1.1.1.0 (Affymetrix).
  • n 7 miRNA biomarkers could be identified.
  • NCX sodium-calcium exchangers
  • CRISP-3 a protein with homology to plant defense proteins, is expressed in mouse B cells under the control of Oct2. Molecular and cellular biology 16, 6160-6168.
  • Lactoferrin is a survival factor for neutrophils in rheumatoid synovial fluid. Rheumatology 48, 39-44.
  • Table 1 Clinical and laboratory diagnostic data of RA patients before and during treatment with MTX.
  • ACPA anti-citrullinated protein antibody
  • ANA Antinuclear antibodies
  • CRP C-reactive protein
  • transcript variant 1 transcript variant 1
  • NM_001130527.2 Variant 2
  • HLA-DRB4 positive RA subgroup HLA-DRB4 negative RA subgroup
  • OSBPL1A 1.4 0.24 - 8.78 0.08-29.34 0.542 0.38 0.005 0.30 0.035 1.7
  • HLA-DRB4 1.5 0.11-3.04 0.50-5.72 0.118 0.75 0.000 0.87 0.000 0.8
  • RNASE2 -1.3 0.36 - 1.35 0.22 - 2.17 0.141 0.59 0.000 0.63 0.000 -1.8
  • affymetrix-based differential expression results of 30 of the 32 defined biomarkers was performed by an independent method using quantitative real-time PCR.
  • RPLPO served as reference gene.
  • the table contains the gene expression differences of the RT-qPCR expressed as FC, the standard error expressed as hr error, the confidence intervals expressed as C.I. and the

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Abstract

La présente invention concerne des biomarqueurs ARNm prédictifs utilisés en combinaison avec le gène HLA-DRB4 pour prédire le traitement au MTX (méthotrexate). La présente invention concerne en outre un procédé de prédiction du traitement au MTX (méthotrexate), comprenant la détection des biomarqueurs ARNm prédictifs en combinaison avec le gène HLA-DRB4 dans des échantillons de patients, et le classement des patients comme réactifs ou non réactifs.
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