WO2018128544A1 - Biomarkers for selecting patient groups, and uses thereof. - Google Patents

Biomarkers for selecting patient groups, and uses thereof. Download PDF

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Publication number
WO2018128544A1
WO2018128544A1 PCT/NL2018/050008 NL2018050008W WO2018128544A1 WO 2018128544 A1 WO2018128544 A1 WO 2018128544A1 NL 2018050008 W NL2018050008 W NL 2018050008W WO 2018128544 A1 WO2018128544 A1 WO 2018128544A1
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tgf beta
genes
gene expression
sample
expression level
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PCT/NL2018/050008
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French (fr)
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Sun TIAN
Annuska Maria Glas
Rene Bernards
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Agendia N.V.
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Publication of WO2018128544A1 publication Critical patent/WO2018128544A1/en

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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
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • 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
    • C12Q2600/112—Disease subtyping, staging or classification
    • 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

Definitions

  • the present invention is in the field of biomarkers that stratify cancer patient groups according to activation status of the TGF beta signaling pathway and eligibility to anti-TGF beta therapy. More specifically, the invention provides gene signatures for use in such stratification.
  • TGF beta Transforming growth factor-beta
  • TGF beta plays an important role and contributes to the hallmarks of cancer, including tumor proliferation, invasion and metastasis, inflammation, angiogenesis, and escape of immune surveillance (Herbertz et al., Drug Des Devel Ther. 9:4479-4499 (2015)).
  • TGF beta signaling The physiological role of TGF beta signaling is diverse and appears to be dependent on the disease setting and cellular context. In the context of cancer, TGF beta plays contrasting roles, acting as a tumor suppressor during the first stages of tumorigenesis and as a tumor promoter during advanced stages of progression (Cantelli et al., Senwi Cancer Biol,
  • TGF beta may affect tumor proliferation directly (intrinsic effect of TGF beta signaling) or indirectly (extrinsic effect of TGF beta signaling) by inducing epithelial-mesenchymal transition (EMT), enhancing angiogenesis, counteracting antitumor immune responses, and enhancing tumor- associated fibrosis (Yingling et al., Nat Rev Drug Discov., 3(12): 1011-1022 (2004)).
  • EMT epithelial-mesenchymal transition
  • the epithelial-mesenchymal transition (EMT) is a transdifferentiation program that converts epithelial cell types into cells with mesenchymal attributes. EMT programs are activated in carcinomas, such as colorectal cancer cells, enabling them to acquire cellular traits associated with high-grade malignancy, including the ability to complete various steps of the metastatic cascade.
  • oligonucleotides (Herbertz et al., Drug Des Devel Ther. 9:4479-4499 (2015)).
  • LY2157299 alias Galunisertib
  • SMAD2 phosphorylation of SMAD2
  • the present invention solves this problem by providing a method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta signaling pathway, comprising the steps of providing a sample from a cancer patient, whereby the sample comprises gene expression products from a cancer cell of said patient, determining a gene expression level for at least five genes listed in Table 4 in said sample, comparing said determined gene expression level to a reference gene expression level of said genes in a reference sample of a cancer patient, said reference sample comprising cancer cells having an activated TGF beta signaling pathway or not an activated TGF beta signaling pathway, and typing said sample on the basis of the comparison of the determined gene expression level and the reference gene expression level.
  • cancer patient refers to a mammal, preferably a human, suffering from cancer or suspected of suffering from cancer.
  • TGF beta refers to transforming growth factor beta and includes the three TGF beta isoforms present in mammals, preferably humans, i.e. TGF beta 1, 2 and 3.
  • TGF beta signaling is associated with promotion of cell survival, induction of apoptosis, stimulation of cell proliferation, induction of differentiation, and/or initiation or resolving inflammation.
  • the biological actions of TGF beta are mediated by transforming growth factor beta (TGF beta) receptors, including type I, type II and type III receptors, which are encoded by genes TGFBRl, TFGBR2 and TFGBR3, respectively.
  • TGFBRl TGF beta type 1 receptor
  • ALK5 Activin receptor-like kinase 5
  • TGFBR2 type 2 receptor
  • TGF beta signaling pathway is used to describe the downstream signaling events attributed to TGF beta or TGF beta-like ligands, preferably events attributed to TGF beta.
  • a TGF beta ligand binds to and activates a type II TGF beta receptor.
  • the receptor recruits and forms a heterodimer with a type I TGF beta receptor and the resulting heterodimer permits phosphorylation of the type I receptor, which in turn phosphorylates and activates a member of the SMAD family of proteins.
  • a signaling cascade is triggered, which is well known to those of skill in the art, and ultimately leads to control of the expression of mediators involved in cell growth, cell differentiation, tumorigenesis, apoptosis, and cellular homeostasis, among others.
  • the term includes both the Smad- dependent (canonical) or Smad- independent (non-canonical) signaling pathway.
  • the term also covers the proteins involved in both pathways, such as, in the Smad- dependent signaling pathway, most upstream, TGF beta or TGF beta-like ligands and TGF beta receptors (including type I, type II and type III TGF beta receptors) and, more downstream, the Smad proteins (Cantelli et al., Sernin Cancer Biol,
  • activated TGF beta signaling pathway refers to an activate TGF beta signaling pathway, i.e. a TGF beta pathway that is (actively) signaling, for instance through an activated TGF beta receptor that phosphorylates downstream signaling proteins such as Smads, including Smad2 and/or Smad3, and effects transcription of TGF beta responsive genes that regulate biological effects such as proliferation and differentiation.
  • a TGF beta signaling pathway that is not active can be a TGF beta signaling pathway that is inactive.
  • TGF beta signaling is a major driver of EMT in epithelial cancers such as colorectal cancer (Cantelli et al., Semin Cancer Biol,
  • EMT epithelial cell-cell adhesion proteins
  • E-cadherin ZO- 1 and occludin
  • mesenchymal proteins like N-cadherin are upregulated.
  • This switch in gene expression is regulated by transcription factors Snail/Slug, ZEB1/2 and Twist (Cantelli et al., Semin Cancer Biol (2016)).
  • EMT also supports tumor initiation, host immunosurveillance evasion and chemoresistance.
  • a method of typing of the invention relates to typing a sample of a cancer patient for the presence or absence of an activated TGF beta signaling pathway.
  • EMT epithelial-mesenchymal transition and is a latent developmental process, involving trans differentiation of cells, preferably epithelial cells, into mesenchymal-like cells with migratory and stem cell properties.
  • typing for EMT status refers to assessing the presence or absence of an EMT phenotype.
  • an EMT phenotype is present during the process of epithelial-mesenchymal transition and/or when the mesenchymal transition is completed.
  • markers for determining EMT status include mesenchymal markers such as vimentin (VIM), S100A4 (also known as fibroblast-specific protein 1 (FSP1)), fibroblast growth factor receptor (FGFR), preferably fibroblast growth factor receptor 1 (FGFR1), fms related tyrosine kinase 1 (FLT1), fibronectin 1 (FN1), twist family bHLH transcription factor 1 or 2 (TWIST 1 or TWIST2), AXL receptor tyrosine kinase (AXL), cadherin 2 (CDH2) or transcription factor 4 (TCF4), overexpression of beta-catenin, and loss of epithelial cell adhesion molecules such as E-cadherin. Histopathological assessment of cancer tissue can additionally be performed to determine EMT status.
  • VIM vimentin
  • FSP1 fibroblast-specific protein 1
  • FGFR fibroblast growth factor receptor
  • FLT1 fibroblast growth factor receptor 1
  • FLT1 fm
  • the ability to identify tumors that have not undergone EMT, or that not have an activated TGF beta signaling pathway, may help to identify cancer patients that are not likely to benefit from treatment with inhibitor of the TGF beta signaling pathway.
  • the cancer patient suffers from a solid tumor. More preferably, the subject suffers from a solid tumor having the propensity to develop an EMT phenotype, including carcinomas and non-epithelial cancers.
  • An example of a non-epithelial cancer having the propensity to develop an EMT phenotype is glioblastoma.
  • carcinomas in the context of the invention are squamous cell carcinomas, adenocarcinomas, transitional cell carcinomas and basal cell carcinomas. Specific examples of carcinomas are colorectal cancer, breast cancer and melanoma.
  • the cancer in said patient is colorectal cancer.
  • the stage of said cancer is preferably stage I, stage II, stage III or stage IV, more preferably stage II or stage III.
  • the skilled person is aware of the methods and means for determining the stage of a cancer. Practitioners commonly use the American Joint Committee on Cancer's (AJCC's) TNM system to describe the stage of a cancer and assign on the basis of said results a cancer stage grouping ranging from stage 0-4.
  • AJCC's American Joint Committee on Cancer's
  • a tissue sample from a cancer patient comprising gene expression products from a cancer cell of said patient can be obtained in numerous ways, as is known to a person skilled in the art.
  • a tissue sample can be obtained directly from the individual, for example by removal of a biopsy from the tumor.
  • said sample is obtained from a tumor after removal of the tumor from a patient.
  • Said sample is preferably obtained from the tumor within two hours after removal, more preferably within 1 hour after removal.
  • tissue sample Before a tissue sample is obtained from a removed tumor, said tumor is preferably cooled and stored at about 0 -8°C.
  • the sample can be freshly prepared from cells or a tissue sample at the moment of harvesting, or they can be prepared from samples that are stored at -70°C until processed for sample preparation.
  • tissues or biopsies can be stored under conditions that preserve the quality of the protein or RNA. Examples of these preservative conditions are fixation using e.g. formaline and paraffin embedding, RNase inhibitors such as RNAsin (Pharmingen) or RNasecure (Ambion), aquous solutions such as RNAlater (Assuragen;
  • a sample from a colorectal cancer patient may be fixated in formalin, for example as formalin-fixed paraffin-embedded (FFPE) tissue.
  • FFPE formalin-fixed paraffin-embedded
  • the sample is an FFPE sample.
  • gene expression product refers to an expression product of a gene and includes gene expression products such as RNA, including mRNA. Also included in this term are complementary nucleic acids derived from a gene expression product, such as cDNA and cRNA.
  • the gene expression product in a sample from a cancer patient is RNA.
  • the gene expression level for at least five genes listed in Table 4 is determined. More preferably, the gene expression level of at least 10, 11, 12, 13, 14, 15, 16, 17, 1 8, 19, 20, 21 ,22 ,23, 24 or 25 genes of Table 4 is determined.
  • the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl and MRC2 is determined.
  • the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl, MRC2, RBMS1, CYTH3, CALD1, PREXl and ZNF469 is determined. Even more preferably, the gene expression level of at least genes TRIB2, VIM, TIMP2,
  • the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl, MRC2, RBMS1, CYTH3, CALD1, PREXl, ZNF469, AHR, ITPRIPL2, PTRF, CYB5R3, FERMT2 is determined. Even more preferably, the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl, MRC2, RBMS1, CYTH3, CALD1, PREXl, ZNF469, AHR, ITPRIPL2, PTRF, CYB5R3, FERMT2, NR3C1, RAP IB, IL6ST, RGAG4 and STOM is determined. Most preferably, the gene expression level of all genes listed in Table 4 is determined.
  • the gene expression level is determined for a set of genes selected from the genes listed in Table 1.
  • the set of genes selected from the genes listed in Table 1 preferably contains at least the first 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 rank-ordered genes of Table 1.
  • the set of genes selected from the genes listed in Table 1 contains at least 80, 85, 90, 95 or 100 genes of Table 1.
  • the set of genes selected from the genes listed in Table 1 contain all genes listed in Table 1.
  • the gene expression level is determined for a set of genes selected from the genes listed in Table 2.
  • the set of genes selected from the genes listed in Table 2 preferably contains at least the first 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 rank-ordered genes of Table 2.
  • the set of genes selected from the genes listed in Table 2 contains at least 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 genes of Table 2.
  • the set of genes selected from the genes listed in Table 2 of genes contains all genes listed in Table 2.
  • the gene expression level is preferably in addition, in a method of typing according to the invention.
  • the set of genes selected from the genes listed in Table 3 preferably contains at least the first 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 rank- ordered genes of Table 3.
  • the set of genes selected from the genes hsted in Table 3 contains at least 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 genes of Table 3.
  • the set of genes selected from the genes listed in Table 3 contains all genes listed in Table 3.
  • the gene expression level is determined for at least two sets of genes selected from different tables as indicated in the previous paragraph.
  • the gene expression level may be determined for (i) a set of genes selected from the genes listed in Table 1 and a set of genes selected from the genes listed in Table 2, (ii) a set of genes selected from the genes listed in Table 1 and a set of genes selected from the genes listed in Table 3, and (iii) a set of genes selected from the genes listed in Table 2 and a set of genes selected from the genes listed in Table 3.
  • the gene expression level is determined for (i) a set of genes selected from the genes listed in Table 1, a set of genes selected from the genes listed in Table 2, and a set of genes selected from the genes listed in Table 3.
  • the sets of genes are preferably as indicated in the previous paragraph.
  • a method of typing of the invention can also be performed with all genes listed in Tables 1-3.
  • a method for typing according to the invention is preferably a method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta 1, 2 or 3 signaling pathway, or in other words, an activated TGF beta signaling pathway attributable to TGF beta 1, 2 or 3.
  • the gene expression level of at least 10 genes of Table 4 is determined.
  • the gene expression level of at least 12 genes of Table 4 is determined.
  • the gene expression level of at least 15 genes of Table 4 is determined.
  • Methods to determine gene expression levels of genes are known to a skilled person and include, but are not limited to, Northern blotting, quantitative PCR, microarray analysis and RNA sequencing. It is preferred that said gene expression levels are determined simultaneously. Simultaneous analyses can be performed, for example, by multiplex qPCR, RNA sequencing procedures, and microarray analysis. Microarray analysis allow the simultaneous determination of gene expression levels of expression of a large number of genes, such as more than 50 genes, more than 100 genes, more than 1000 genes, more than 10.000 genes, or even whole-genome based, allowing the use of a large set of gene expression data for normalization of the determined gene expression levels in a method of the invention.
  • Microarray-based analysis involves the use of selected biomolecules that are immobilized on a solid surface, an array.
  • a microarray usually comprises nucleic acid molecules, termed probes, which are able to hybridize to gene expression products. The probes are exposed to labeled sample nucleic acid, hybridized, and the abundance of gene expression products in the sample that are complementary to a probe is determined.
  • the probes on a microarray may comprise DNA sequences, RNA sequences, or copolymer sequences of DNA and RNA.
  • the probes may also comprise DNA and/or RNA analogues such as, for example, nucleotide analogues or peptide nucleic acid molecules (PNA), or combinations thereof.
  • the sequences of the probes may be full or partial fragments of genomic
  • a probe is to be specific for a gene expression product of a gene as listed in Tables 1-7.
  • a probe is specific when it comprises a continuous stretch of nucleotides that are completely complementary to a nucleotide sequence of a gene expression product, or a cDNA product thereof.
  • a probe can also be specific when it comprises a continuous stretch of nucleotides that are partially complementary to a nucleotide sequence of a gene expression product of said gene, or a cDNA product thereof.
  • Partially means that a maximum of 5% from the nucleotides in a continuous stretch of at least 20 nucleotides differs from the corresponding nucleotide sequence of a gene expression product of said gene.
  • the term complementary is known in the art and refers to a sequence that is related by base-pairing rules to the sequence that is to be detected. It is preferred that the sequence of the probe is carefully designed to minimize nonspecific hybridization to said probe. It is preferred that the probe is, or mimics, a single stranded nucleic acid molecule.
  • the length of said complementary continuous stretch of nucleotides can vary between 15 bases and several kilo bases, and is preferably between 20 bases and 1 kilobase, more preferred between 40 and 100 bases, and most preferred about 60 nucleotides.
  • a most preferred probe comprises about 60 nucleotides that are identical to a nucleotide sequence of a gene expression product of a gene, or a cDNA product thereof.
  • probes comprising probe sequences as indicated in Tables 1-3 and 5-7 can be employed.
  • the gene expression products in the sample are preferably labeled, either directly or indirectly, and contacted with probes on the array under conditions that favor duplex formation between a probe and a complementary molecule in the labeled gene expression product sample.
  • the amount of label that remains associated with a probe after washing of the microarray can be determined and is used as a measure for the gene expression level of a nucleic acid molecule that is
  • the determined gene expression level can be normalized for differences in the total amounts of nucleic acid expression products between two separate samples by comparing the level of expression of a gene that is known not to differ in expression level between samples. If samples for use in a method of the invention are FFPE samples, it is possible to use an FFPE normalization template.
  • gene expression levels are determined by microarray analysis.
  • Another preferred method for determining gene expression levels is by sequencing techniques, preferably next- generation sequencing (NGS) techniques of RNA samples. Sequencing techniques for sequencing RNA have been developed. Such sequencing techniques include, for example, sequencing-by-synthesis.
  • NGS next- generation sequencing
  • Sequencing-by-synthesis or cycle sequencing can be accomplished by stepwise addition of nucleotides containing, for example, a cleavable or photobleachable dye label as described, for example, in U.S. Patent No. 7,427,673 ; U.S. Patent No. 7,414, 116 ; WO 04/018497 ; WO 91/06678 ; WO 07/123744 ; and U.S. Patent No. 7,057,026 .
  • pyrosequencing techniques may be employed.
  • Pyrosequencing detects the release of inorganic pyrophosphate (PPi) as particular nucleotides are incorporated into the nascent strand (Ronaghi et al., Analytical Biochemistry 242(l):84-9 (1996); Ronaghi, M. Genome Res. 11(1):3- 11 (2001);
  • released PPi can be detected by being immediately converted to adenosine triphosphate (ATP) by ATP sulfurylase, and the level of ATP generated is detected via lucifer ase -p ro prise d p hotons .
  • ATP adenosine triphosphate
  • Sequencing techniques also include sequencing by ligation techniques.
  • Such techniques use DNA ligase to incorporate oligonucleotides and identify the incorporation of such oligonucleotides and are inter alia described in U.S. Patent No 6,969,488 ; U.S. Patent No. 6, 172,218 ; and U.S. Patent No. 6,306,597.
  • Other sequencing techniques include, for example, fluorescent in situ sequencing
  • Sequencing techniques can be performed by directly sequencing RNA, or by sequencing a RNA-to-cDNA converted nucleic acid library. Most protocols for sequencing RNA samples employ a sample preparation method that converts the RNA in the sample into a double-stranded cDNA format prior to sequencing.
  • the reference sample is preferably a sample, such as an RNA sample, isolated from a tissue of a healthy individual, or isolated from a cancerous growth of a cancer patient, preferably a colorectal cancer patient.
  • said reference sample is indicative of, or known to have, an activated or not activated TGF beta signaling pathway.
  • the activation status of the TGF beta signaling pathway of said sample has been determined.
  • the reference sample can be an RNA sample from a cancerous growth of a cancer patient, such as a colorectal cancer patient, having an EMT phenotype or not having an EMT phenotype.
  • the reference sample may comprise an RNA sample from a relevant cell line or mixture of cell lines.
  • the RNA from a cell line or cell line mixture can be produced in-house or obtained from a commercial source such as, for example, Stratagene Human Reference RNA.
  • Another preferred reference sample comprises RNA isolated and pooled from normal adjacent tissue from cancer patients.
  • said reference sample is a pooled RNA sample that is isolated from tissue comprising cancer cells from multiple individuals suffering from cancer, preferably colorectal cancer, more preferably stage 2 and/or 3 colorectal cancer, and which cancer cells either have (i) an activated or not activated TGF beta signaling pathway, or (ii) are positive or negative for EMT status. It is preferred that said sample is pooled from more than 10 individuals, more preferred more than 20 individuals, more preferred more than 30 individuals, more preferred more than 40 individuals, most preferred more than 50 individuals.
  • the reference gene expression level is a template, preferably a profile template, indicative of an activated, or not activated, TGF beta signaling pathway.
  • suitable profile templates are the gene expression level templates of (i) a colorectal cancer of which the TGFB1 mRNA level is in the highest 20% percentile and the TGFBR1 and TGFBR2 mRNA level is not in the lowest 20% percentile, calculated on the basis of a group of colorectal cancer patients, preferably a group of at least 10, 30, 40, 50, 100, 200 or 300 colorectal cancer patients, (ii) a colorectal cancer of which the TGFB2 mRNA level is in the highest 20% percentile and the TGFBRl and TGFBR2 mRNA level is not in the lowest 20% percentile, calculated on the basis of a group of colorectal cancer patients, preferably a group of at least 10, 30, 40 ,50, 100, 200 or 300 colorectal cancer patients, or (iii) a colorectal cancer of
  • a number of different coefficients can be used for determining a correlation between the gene expression level in a sample from a cancer patient and a profile template.
  • Preferred methods are parametric methods which assume a normal distribution of the data.
  • One of these methods is the Pearson product- moment correlation coefficient, which is obtained by dividing the covariance of the two variables by the product of their standard deviations.
  • Preferred methods comprise cosine-angle, un-centered correlation and, more preferred, cosine correlation (Fan et al., Con,/ ' Proc IEEE Eng Med Biol Soc. 5:4810-3 (2005)).
  • a similarity score is a measure of the average correlation of gene expression levels of a set of genes in a sample from a cancer patient and a profile template. Said similarity score can, but does not need to be, a numerical value between +1, indicative of a high correlation between the gene expression level of the set of genes in a sample of said cancer patient and said profile template, and - 1, which is indicative of an inverse correlation.
  • a threshold can be used to differentiate between samples having an activated TGF beta signaling pathway or that are positive for EMT status, and samples not having an activated TGF beta signaling pathway or that are negative for EMT status.
  • Said threshold is an arbitrary value that allows for discrimination between samples from patients without an activated TGF beta signaling pathway, and samples of patients with an activated TGF beta signaling pathway. If a similarity threshold value is employed, it is preferably set at a value at which an acceptable number of patients with an activated TGF beta signaling pathway would score as false negatives, and an acceptable number of patients without an activated TGF beta signaling pathway would score as false positives.
  • a similarity score is preferably displayed or outputted to a user interface device, a computer readable storage medium, or a local or remote computer system.
  • a method of typing of the invention further comprises determining a stage of the cancer. The staging of a cancer is generally based on the size of the cancer and on whether the cancer has spread to lymph nodes or other areas of the body.
  • MSI MicroSateUite Instabl
  • MSS MicroSateUite Stable
  • a sample of a cancer patient is preferably additionally typed for microsateUite stability status. This is preferably performed by the steps of: - providing a sample from a cancer patient, whereby the sample comprises RNA expression products from a cancer cell of said patient; - determining a gene expression level for DUSP18 and at least one further gene listed in Table 5 or Table 6; - comparing said determined gene expression level of said at least two genes to a gene expression level of said genes in a reference sample; and - typing said sample on the basis of the comparison of the determined gene expression level and the gene expression level of said genes in a reference sample.
  • the sample used can be (part of) the same sample on the basis of which a cancer patient is typed for the presence or absence of an activated TGF beta signaling pathway.
  • Preferred combinations of genes to be used in typing for MSI status are selected from Table 5 and/or 6 and are provided by DUSP18 and SMCR7L, more preferred DUSP18, SMCR7L and CEP68, more preferred DUSP18, SMCR7L, CEP68 and UNKL, more preferred DUSP18, SMCR7L, CEP68, UNKL and
  • KCNK5 more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5 and RNF43, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43 and RPL22L1, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1 and AXIN2, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2 and TNNC2, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, and ATP9A, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, and ATP9A, more preferred DUSP18,
  • the reference sample can be a sample as described in WO 2012/087144 A2, for instance on page 16 and 17 of WO 2012/087144 A2.
  • EGFR Epidermal Growth Factor Receptor
  • a sample of a cancer patient is preferably additionally typed for the presence or absence of activating mutations in the EGFR pathway, more preferably for the presence or absence of one or more activating mutations in BRAF. This is preferably performed by the steps of: - providing a sample from a cancer patient, whereby said sample comprises gene expression products from a cancer cell of said patient;
  • the sample used can be (part ol) the same sample on the basis of which a cancer patient is typed for the presence or absence of an activated TGF beta signaling pathway and/or microsatellite stability status.
  • a preferred set of genes to additionally type for activating mutations in the EGFR pathway comprises at least 2 of the genes listed in Table 7, more preferably at least 5 of the genes listed in Table 7, more preferably at least 10 of the genes listed in Table 7. More preferably such a set of genes comprises at least 20 of the genes listed in Table 7, more preferably at least 30 of the genes listed in Table 7, more preferably at least 40 of the genes listed in Table 7.
  • a most preferred set of genes comprises all genes listed in Table 7.
  • WO 2012/044167 A2 and/or the PIK3CA mutation gene signature in Table 3 of WO 2012/044167 A2 can be used to complement the typing for activating mutations in the EGFR pathway.
  • a preferred set of genes comprises at least 2 of the genes listed in Table 1 and/or Table 3, more preferably at least 5 of the genes listed in Table 1 and/or Table 3, more preferably at least 10 of the genes listed in Table 1 and/or Table 3. More preferably such a set of genes comprises at least 20 of the genes listed in Table 1 and/or Table 3, more preferably at least 30 of the genes listed in Table 1 and/or Table 3, more preferably at least 40 of the genes listed in Table 1 and/or Table 3.
  • a most preferred set of genes comprises all genes listed in Table 1 and/or Table 3 depicted in WO 2012/044167 A2.
  • the additional typing for activating mutations in the EGFR pathway may further comprise determining the expression level of EREG, and AREG. Over- expression of any one of these markers, preferably all two markers, compared to the level of expression of that marker in a reference sample from a patient not having an activating mutation in the EGFR pathway, was found to be indicative for a likeliness to respond to anti-EGFR therapy.
  • the invention also relates to a method for comparing gene expression levels, comprising the steps of: - providing a sample from a cancer patient, the sample comprising gene expression products from a cancer cell of said patient; - determining a gene expression level for at least five genes listed in Table 4; - comparing said determined gene expression level to a reference gene expression level of said genes in a reference sample.
  • inhibitor of the TGF beta signaling pathway refers to a therapeutic compound of any type, including small molecule-, proteins, antibody-, antisense-, small interfering RNA-, or microRNA-based compounds, that inhibit block, counteract or antagonize signaling, preferably stimulatory signaling, in the TGF beta signaling pathway.
  • such an inhibitor is an inhibitor of TGF beta receptor mediated signaling, also referred to as an inhibitor of TGF beta receptor activity, which includes therapeutic compounds that (i) inhibit or block natural TGF beta from binding to a TGF beta receptor and forming an active signaling complex, or (ii) inhibit TGF beta receptor mediated signaling by binding to a TGF beta receptor either extracellularly or intracellularly and blocking signaling through said TGF beta receptor.
  • Therapeutic compound LY2157299 alias Galunisertib
  • LY2157299 alias Galunisertib
  • an inhibitor of the TGF beta signaling pathway abrogates signaling or activation of the canonical TGF beta signaling pathway.
  • a preferred inhibitor is a specific or selective inhibitor of TGF beta 1, 2 or 3. Depending on which TGF beta isoform the activation is attributed to, therapy with an inhibitor of a specific TGF beta isoform can be assigned.
  • Non-limiting examples of inhibitors of the TGF beta signaling pathway are (i) TGF beta inhibitors such as antisense oligonucleotides counteracting TGF beta 1, 2 and/or 3 synthesis, TGF beta 1, 2 and/or 3-neutralizing antibodies, and soluble TGF beta receptors, (ii) TGF beta receptor inhibitors such as a competitive TGF beta receptor antagonist, including TGF beta muteins, that block or dampen TGF beta(agonist)-mediated signaling by competing for TGF beta receptor binding sites, anti-TGF beta receptor monoclonal antibodies that prevent ligand-receptor interaction, and TGF beta receptor kinase inhibitors, (iii) inhibitors of SMAD proteins, or (iv) a combination of such inhibitors.
  • TGF beta inhibitors such as antisense oligonucleotides counteracting TGF beta 1, 2 and/or 3 synthesis, TGF beta 1, 2 and/or 3-neutralizing antibodies, and soluble TGF beta receptors
  • TGF beta inhibitors selected from the group formed by, or consisting of, fresolimumab (originator: Cambridge Antibody Technology) which binds to and inhibits TGF beta 1, 2 and 3; trabedersen (originator: Antisense Pharma) which is an antisense oligonucleotide targeting TGF beta 2; and disitertide (originators: Digna Biotech; University of Navarra) which is a peptidic TGF beta 1 inhibitor specifically designed to block TGF beta 1-receptor interaction; Lucanix (originator: NovaRx Corporation) which is a TGF beta 2 inhibitor; and/or FANGTM Vaccine (originator: Gradalis) which is a TGF beta 1 and 2 inhibitor; and/or TGF beta receptor inhibitors selected from the group formed by, or consisting of, LY2157299 (alias Galunisertib; originator: Eli Lilly); TEW 7197 (Origin
  • PF-03446962 alias Ascrinvacumab; originator: Pfizer
  • LY3022859 alias IMC TR1; originator: ImClone Systems
  • ⁇ 26894 alias the inhibitor is LY2157299.
  • the therapy assigned is preferably an inhibitor of that specific TGF beta isoform.
  • the invention also provides a method for assigning a standard-of-care therapeutic agent to a cancer patient, comprising the steps of: - assigning a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, to a cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention.
  • a standard-of-care therapeutic agent is a therapeutic compound, or combination of such compounds, that is/are considered by medical practitioners as appropriate, accepted, and/or widely used for a certain type of patient, disease or clinical circumstance.
  • NCCN National Comprehensive Cancer Network
  • NCCN GUIDELINES NCCN Clinical Practice Guidelines in Oncology
  • Standard-of-care cancer therapy may include chemotherapy, radiation therapy, hormonal therapy and/or targeted cancer therapy such as immunotherapy and tyrosine-kinase inhibition therapy.
  • MSI-like samples by a methods of the invention, which samples were typed as MSS samples by standard methods (IHC/ PCR), is of high clinical relevance. It is preferred that colorectal cancer patients with stage 2 MSI-like colorectal cancer are not assigned, and not treated, with 5-FU but with an alternative standard-of-care therapeutic agent.
  • a cancer patient typed as being positive for MSI status (MSI-high) is assigned, and treated with, an immunotherapeutic agent such as a PD- 1 or PD-Ll inhibitor.
  • a preferred PD-1 or PD-Ll inhibitor is selected from the group formed by, or consisting of, nivolumab (originators Medarex and Ono Pharmaceutical.; CAS number 946414-94-4);
  • pembrolizumab (originators Merck & Co and The Leukemia & Lymphoma Society; CAS Number 1374853-91-4); JS001 (originator Shanghai Junshi Biosciences); TSR- 042 (originator AnaptysBio; developer Tesaro, Inc.); Pidilizumab (CT-011,
  • the PD-1 or PD-L1 inhibitor is the PD-L1 inhibitor atezolizumab.
  • a sample of a cancer patient is additionally typed for the presence or absence of one or more activating mutations in the EGFR pathway, it is possible to further assign treatment on the basis of the result of typing obtained.
  • a sample of such a patient is typed as having one or more activating mutations in the EGFR pathway, preferably therapy is assigned which allows for inhibition of EGFR pathway at the level of the activating mutation or downstream of that pathway.
  • therapy is assigned which allows for inhibition of BRAF or inhibition of signaling mediators downstream in the BRAF signaling pathway.
  • Preferred inhibitors of the BRAF signaling pathway are selected from the group formed by, or consisting of, PLX- 4032 (alias vemurafenib; CAS number 918504-65-1), dabrafenib (CAS number 1195765-45-7), sorafenib (originator: Onyx Pharmaceuticals and University of Kentucky; CAS number 284461-73-0), PLX-4720 (originator: Plexxikon), GDC-0879 (CAS number 905281-76-7), MLN2480 (alias TAK-580; originator: Biogen personal; Sunesis Pharmaceuticals), R05126766 (originator: Chugai Pharmaceutical), RAF265 (Originator: Novartis) and AZ 628 (CAS number 878739-06-1).
  • PLX- 4032 alias vemurafenib; CAS number 918504-65-1
  • dabrafenib CAS number 1195765-45-7
  • a cancer patient typed as having one or more activating mutations in the EGFR pathway is assigned, or treated with, a vinca alkaloid.
  • a preferred vinea alkaloid is vinorelbine.
  • the present invention further provides an inhibitor of the TGF beta signaling pathway for use in the treatment of a cancer patient typed as having an activated TGF beta signaling pathway according to a method for typing of the invention.
  • the invention also relates to a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, for use in the treatment of cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention.
  • the invention further relates to a use of an inhibitor of the TGF beta signaling pathway in the manufacture of a medicament for treating a cancer patient typed as having an activated TGF beta signaling pathway according to a method for typing of the invention.
  • the invention also relates to a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, in the manufacture of a medicament for treating a cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention.
  • the invention provides a method for treating a cancer patient, comprising the steps of: - administering a therapeutically effective amount of an inhibitor of the TGF beta signaling pathway to a cancer patient typed as having an activated TGF beta signaling pathway according to a method for typing of the invention.
  • the invention also relates to a method for treating a cancer patient, comprising the steps of: - administering a therapeutically effective amount of a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, to a cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention
  • FIG. 3A-C show the heatmaps of the TGF beta 1, 2 and 3 signatures
  • Figure 5 shows the prognostic power of the gene signature of Table 4 in stage 2 and stage 3 colorectal cancer patients. It follows from Figure 5 that with a gene signature of the invention it is possible to prognosticate cancer patients for survival. It also follows from Figure 5 that cancer patients having an activated TGF beta signaling pathway have worse survival parameters than cancer patients not having an activated TGF beta signaling pathway.
  • Figure 6 shows the prognostic value of a random combination of genes from the TGF beta signature as listed in Table 4 for identifying an activated or non- activated TGF beta signaling pathway.
  • the plot is based on gene expression products from samples of stage 2 and 3 colorectal cancer patients.
  • the plot shows that any combination of about 15 genes from Table 4 has prognostic power ( ⁇ 0.05) in samples of stage 2 and 3 colorectal cancer patients.
  • CD 14 GATCCAAGACAGAATAATGAATGGACTCAAACTGCCTTGGCTTCAGGGGAGTCCCGTCAG HD_8pack_Dx_0608 8.04E- -13
  • NM_004850 R0CK2 TATATAAATACACAG AGTTTG GTATG ATATTTAAATACATCATCTG G CCAGG CATGGTG G 1, .69E- • 11 -0.36345
  • NM_004665 VNN2 A AAG AG CCTGG GTGTTTG G GTCAG ATAAATG AAG ATCAAACTCCAG CTCCAG CCTCATTT 2, .44E- -09 0.421704
  • Table 7 Genes of gene signature for determining activating mutations in EGFR pathway.
  • the first step in developing the signatures was to define the initial stratification of activation/non- activation of TGF beta signaling groups.
  • TGFBR1, TGFBR2 The mRNA level of TGF beta receptors (TGFBR1, TGFBR2), at least when present at low levels, is functionally relevant. Therefore, mRNA level of TGF beta ligands (TGFB1, TGFB2, TGFB3), and mRNA levels of TGF beta receptors (TGFBR1, TGFBR2), were both used for the initial stratification of activation/non- activation of TGF-beta signaling groups (Table 8).
  • TGFB2, and TGFB3 displayed activated TGF beta signaling.
  • the mRNA level of TGFB1, TGFB2, TGFB3 alone was found not sufficient to predict TGFB signaling and a TGFB signaling-induced phenotype. This follows from the fact that there is low concordance between the TGF beta 1, 2 or 3 signature, and high mRNA levels of TGFbeta I, 2, or 3, respectively (Table 9). Therefore, relying on IHC stain of any single TGF beta protein alone is unlikely to work.
  • Table 8 Initial stratification of the activation/non- activation of TGF beta signaling grou s.
  • the survival curves, hazard ratios and p- values of log-rank test are shown in Figure 4.
  • the p-values of the survival analysis of individual TGFBeta signatures and three their combinations are all significant (p ⁇ 0.05).

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Abstract

The invention relates to a method for typing a sample of a cancer patient for an activated or non-activated TGF beta signaling pathway, comprising the steps of providing a sample from a cancer patient, whereby the sample comprises gene expression products from a cancer cell of said patient, determining a gene expression level for at least five genes listed in Table 4, comparing said determined gene expression level to a reference gene expression level of said genes in a reference sample of a cancer patient, said reference sample comprising cancer cells having an activated or non-activated TGF beta signaling pathway, and typing said sample on the basis of the comparison of the determined gene expression level and the reference gene expression level.

Description

Title: Biomarkers for selecting patient groups, and uses thereof. FIELD OF THE INVENTION
The present invention is in the field of biomarkers that stratify cancer patient groups according to activation status of the TGF beta signaling pathway and eligibility to anti-TGF beta therapy. More specifically, the invention provides gene signatures for use in such stratification.
STATE OF THE ART
Transforming growth factor-beta (TGF beta) signaling regulates a wide range of biological processes, for instance in ontogeny and in tumorigenesis. In
tumorigenesis, TGF beta plays an important role and contributes to the hallmarks of cancer, including tumor proliferation, invasion and metastasis, inflammation, angiogenesis, and escape of immune surveillance (Herbertz et al., Drug Des Devel Ther. 9:4479-4499 (2015)).
The physiological role of TGF beta signaling is diverse and appears to be dependent on the disease setting and cellular context. In the context of cancer, TGF beta plays contrasting roles, acting as a tumor suppressor during the first stages of tumorigenesis and as a tumor promoter during advanced stages of progression (Cantelli et al., Senwi Cancer Biol,
dx.doi.org/10.1016/]. semcancer.2016.08.009, (2016)). This can be explained by the fact that while some tumors develop TGF beta-inactivating mutations and progress in a TGF beta-independent manner, others accumulate mutations in tumor suppressor genes that operate downstream of TGF beta signaling. Cancer cells that acquire these mutations gain an advantage, as they can employ the wide range of pro-tumorigenic effectors downstream of TGF beta stimulation.
TGF beta may affect tumor proliferation directly (intrinsic effect of TGF beta signaling) or indirectly (extrinsic effect of TGF beta signaling) by inducing epithelial-mesenchymal transition (EMT), enhancing angiogenesis, counteracting antitumor immune responses, and enhancing tumor- associated fibrosis (Yingling et al., Nat Rev Drug Discov., 3(12): 1011-1022 (2004)). The epithelial-mesenchymal transition (EMT) is a transdifferentiation program that converts epithelial cell types into cells with mesenchymal attributes. EMT programs are activated in carcinomas, such as colorectal cancer cells, enabling them to acquire cellular traits associated with high-grade malignancy, including the ability to complete various steps of the metastatic cascade.
In the past years, the pharmaceutical industry has focused research efforts in the development of drugs that block TGF beta signaling in cancer patients. Multiple pharmacological approaches are under investigation, ranging from vaccines, small molecules, monoclonal antibodies, and antisense
oligonucleotides (Herbertz et al., Drug Des Devel Ther. 9:4479-4499 (2015)). One promising candidate is LY2157299 (alias Galunisertib), of Eli Lilly, which is currently researched for application in a wide array of solid tumors and operates by inhibition the TGF beta receptor I kinase and thereby the phosphorylation of SMAD2, the latter being a downstream signaling mediator in the TGF beta signaling pathway.
There is a need in the art for methods that predict treatment response, and thereby eligibility to such treatment, associated with administration of inhibitors of TGF beta signaling in cancer patients. This would allow for a distinction between patient groups that benefit from treatment with such an inhibitor, and patient groups that do no benefit from treatment with such an inhibitor.
It is an aim of this invention to provide gene signatures that allow for the selection of cancer patient populations that respond effectively to inhibitors of TGF beta signaling.
The present invention solves this problem by providing a method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta signaling pathway, comprising the steps of providing a sample from a cancer patient, whereby the sample comprises gene expression products from a cancer cell of said patient, determining a gene expression level for at least five genes listed in Table 4 in said sample, comparing said determined gene expression level to a reference gene expression level of said genes in a reference sample of a cancer patient, said reference sample comprising cancer cells having an activated TGF beta signaling pathway or not an activated TGF beta signaling pathway, and typing said sample on the basis of the comparison of the determined gene expression level and the reference gene expression level.
It was found that with a method of the invention it is now possible to determine whether cancer patients have an activated TGF beta signaling pathway. This provides for a new clinical setting wherein cancer therapy can be personalized on the basis of molecular typing of activation status in the TGF beta signaling pathway. Unexpectedly, the inventors were able to distinguish three gene signatures, based on the three different TGF beta isoforms, that are indicative of an activated TGF beta signaling pathway. This provides for subtyping in activation of the TGF beta signaling pathway, i.e. subtyping whether the activation is based on, or attributable to, TGF beta ligands 1, 2 or 3. Stratification for the presence or absence of an activated TGF beta signaling pathway provides for intelligent treatment- decision making, as is elaborated on herein below.
The term "cancer patient" refers to a mammal, preferably a human, suffering from cancer or suspected of suffering from cancer.
The term "TGF beta", as used herein, refers to transforming growth factor beta and includes the three TGF beta isoforms present in mammals, preferably humans, i.e. TGF beta 1, 2 and 3. TGF beta signaling is associated with promotion of cell survival, induction of apoptosis, stimulation of cell proliferation, induction of differentiation, and/or initiation or resolving inflammation. The biological actions of TGF beta are mediated by transforming growth factor beta (TGF beta) receptors, including type I, type II and type III receptors, which are encoded by genes TGFBRl, TFGBR2 and TFGBR3, respectively. Biological effects are inter alia mediated by a receptor complex of the TGF beta type 1 receptor (TGFBRl, also referred to as Activin receptor-like kinase 5 (ALK5)) and type 2 receptor (TGFBR2), which receptors comprise a serine/threonine protein kinase. Receptor activation leads inter alia to phosphorylation of Smad proteins, which translocate to the nucleus for effecting expression of mediators involved in any of the aforementioned biological effects.
The term "TGF beta signaling pathway", is used to describe the downstream signaling events attributed to TGF beta or TGF beta-like ligands, preferably events attributed to TGF beta. For example, in one signaling pathway a TGF beta ligand binds to and activates a type II TGF beta receptor. The receptor recruits and forms a heterodimer with a type I TGF beta receptor and the resulting heterodimer permits phosphorylation of the type I receptor, which in turn phosphorylates and activates a member of the SMAD family of proteins. A signaling cascade is triggered, which is well known to those of skill in the art, and ultimately leads to control of the expression of mediators involved in cell growth, cell differentiation, tumorigenesis, apoptosis, and cellular homeostasis, among others. The term includes both the Smad- dependent (canonical) or Smad- independent (non-canonical) signaling pathway. The term also covers the proteins involved in both pathways, such as, in the Smad- dependent signaling pathway, most upstream, TGF beta or TGF beta-like ligands and TGF beta receptors (including type I, type II and type III TGF beta receptors) and, more downstream, the Smad proteins (Cantelli et al., Sernin Cancer Biol,
dx.doi.org/10.1016/j.semcancer.2016.08.009, (2016)).
The term "activated TGF beta signaling pathway", as used herein, refers to an activate TGF beta signaling pathway, i.e. a TGF beta pathway that is (actively) signaling, for instance through an activated TGF beta receptor that phosphorylates downstream signaling proteins such as Smads, including Smad2 and/or Smad3, and effects transcription of TGF beta responsive genes that regulate biological effects such as proliferation and differentiation. A TGF beta signaling pathway that is not active, can be a TGF beta signaling pathway that is inactive.
TGF beta signaling is a major driver of EMT in epithelial cancers such as colorectal cancer (Cantelli et al., Semin Cancer Biol,
dx.doi.org/10.1016/j.semcancer.2016.08.009, (2016)). During EMT, expression of epithelial cell-cell adhesion proteins such as E-cadherin, ZO- 1 and occludin is downregulated, while mesenchymal proteins like N-cadherin are upregulated. This switch in gene expression is regulated by transcription factors Snail/Slug, ZEB1/2 and Twist (Cantelli et al., Semin Cancer Biol (2016)). EMT also supports tumor initiation, host immunosurveillance evasion and chemoresistance.
It was established that activation of a TGF beta signaling pathway in cancer cells can be indicative for EMT status. Thus, in a method of typing of the invention, the phrase "typing a sample of a cancer patient for the presence or absence of an activated TGF beta signaling pathway" can be used interchangeably with the phrase "typing a sample of a cancer patient for EMT status" - which status can be positive or negative - or, in other words, "typing a sample of a cancer patient for the presence or absence of EMT". However, preferably, a method of typing of the invention relates to typing a sample of a cancer patient for the presence or absence of an activated TGF beta signaling pathway.
The term "EMT", as used herein, refers to epithelial-mesenchymal transition and is a latent developmental process, involving trans differentiation of cells, preferably epithelial cells, into mesenchymal-like cells with migratory and stem cell properties. In the context of the invention, typing for EMT status refers to assessing the presence or absence of an EMT phenotype. Preferably, an EMT phenotype is present during the process of epithelial-mesenchymal transition and/or when the mesenchymal transition is completed. The skilled person is aware of markers for determining EMT status, which include mesenchymal markers such as vimentin (VIM), S100A4 (also known as fibroblast-specific protein 1 (FSP1)), fibroblast growth factor receptor (FGFR), preferably fibroblast growth factor receptor 1 (FGFR1), fms related tyrosine kinase 1 (FLT1), fibronectin 1 (FN1), twist family bHLH transcription factor 1 or 2 (TWIST 1 or TWIST2), AXL receptor tyrosine kinase (AXL), cadherin 2 (CDH2) or transcription factor 4 (TCF4), overexpression of beta-catenin, and loss of epithelial cell adhesion molecules such as E-cadherin. Histopathological assessment of cancer tissue can additionally be performed to determine EMT status.
The ability to identify tumors that have not undergone EMT, or that not have an activated TGF beta signaling pathway, may help to identify cancer patients that are not likely to benefit from treatment with inhibitor of the TGF beta signaling pathway.
Preferably, in a method of typing of the invention, the cancer patient suffers from a solid tumor. More preferably, the subject suffers from a solid tumor having the propensity to develop an EMT phenotype, including carcinomas and non-epithelial cancers. An example of a non-epithelial cancer having the propensity to develop an EMT phenotype is glioblastoma. Examples of carcinomas in the context of the invention are squamous cell carcinomas, adenocarcinomas, transitional cell carcinomas and basal cell carcinomas. Specific examples of carcinomas are colorectal cancer, breast cancer and melanoma. Preferably, the cancer in said patient is colorectal cancer. The stage of said cancer is preferably stage I, stage II, stage III or stage IV, more preferably stage II or stage III. The skilled person is aware of the methods and means for determining the stage of a cancer. Practitioners commonly use the American Joint Committee on Cancer's (AJCC's) TNM system to describe the stage of a cancer and assign on the basis of said results a cancer stage grouping ranging from stage 0-4.
A tissue sample from a cancer patient comprising gene expression products from a cancer cell of said patient can be obtained in numerous ways, as is known to a person skilled in the art. In a method of the invention, a tissue sample can be obtained directly from the individual, for example by removal of a biopsy from the tumor. Preferably, said sample is obtained from a tumor after removal of the tumor from a patient. Said sample is preferably obtained from the tumor within two hours after removal, more preferably within 1 hour after removal.
Before a tissue sample is obtained from a removed tumor, said tumor is preferably cooled and stored at about 0 -8°C. The sample can be freshly prepared from cells or a tissue sample at the moment of harvesting, or they can be prepared from samples that are stored at -70°C until processed for sample preparation. Alternatively, tissues or biopsies can be stored under conditions that preserve the quality of the protein or RNA. Examples of these preservative conditions are fixation using e.g. formaline and paraffin embedding, RNase inhibitors such as RNAsin (Pharmingen) or RNasecure (Ambion), aquous solutions such as RNAlater (Assuragen;
US06204375), Hepes-Glutamic acid buffer mediated Organic solvent Protection Effect (HOPE; DE 10021390), and RCL2 (Alphelys; WO04083369), and non-aquous solutions such as Universal Molecular Fixative (Sakura Finetek USA Inc.;
US7138226). Alternatively, a sample from a colorectal cancer patient may be fixated in formalin, for example as formalin-fixed paraffin-embedded (FFPE) tissue. Preferably, the sample is an FFPE sample.
The term "gene expression product", as used herein, refers to an expression product of a gene and includes gene expression products such as RNA, including mRNA. Also included in this term are complementary nucleic acids derived from a gene expression product, such as cDNA and cRNA. Preferably, the gene expression product in a sample from a cancer patient is RNA. In a method of typing of the invention, the gene expression level for at least five genes listed in Table 4 is determined. More preferably, the gene expression level of at least 10, 11, 12, 13, 14, 15, 16, 17, 1 8, 19, 20, 21 ,22 ,23, 24 or 25 genes of Table 4 is determined. Preferably, the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl and MRC2 is determined. More preferably, the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl, MRC2, RBMS1, CYTH3, CALD1, PREXl and ZNF469 is determined. Even more preferably, the gene expression level of at least genes TRIB2, VIM, TIMP2,
PLEKHOl, MRC2, RBMS1, CYTH3, CALD1, PREXl, ZNF469, AHR, ITPRIPL2, PTRF, CYB5R3, FERMT2 is determined. Even more preferably, the gene expression level of at least genes TRIB2, VIM, TIMP2, PLEKHOl, MRC2, RBMS1, CYTH3, CALD1, PREXl, ZNF469, AHR, ITPRIPL2, PTRF, CYB5R3, FERMT2, NR3C1, RAP IB, IL6ST, RGAG4 and STOM is determined. Most preferably, the gene expression level of all genes listed in Table 4 is determined.
Alternatively, in a method of typing according to the invention, the gene expression level is determined for a set of genes selected from the genes listed in Table 1. The set of genes selected from the genes listed in Table 1 preferably contains at least the first 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 rank-ordered genes of Table 1. Alternatively, the set of genes selected from the genes listed in Table 1 contains at least 80, 85, 90, 95 or 100 genes of Table 1.
Most preferably, the set of genes selected from the genes listed in Table 1 contain all genes listed in Table 1. Alternatively, or in addition to the set of genes selected from the genes listed in Table 1, preferably in addition, in a method of typing according to the invention, the gene expression level is determined for a set of genes selected from the genes listed in Table 2. The set of genes selected from the genes listed in Table 2 preferably contains at least the first 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 rank-ordered genes of Table 2. Alternatively, the set of genes selected from the genes listed in Table 2 contains at least 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 genes of Table 2. Most preferably, the set of genes selected from the genes listed in Table 2 of genes contains all genes listed in Table 2. Alternatively, or in addition to the set of genes selected from the genes listed in Table 1 and/or Table 2, preferably in addition, in a method of typing according to the invention, the gene expression level is
determined for a set of genes selected from the genes listed in Table 3. The set of genes selected from the genes listed in Table 3 preferably contains at least the first 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 rank- ordered genes of Table 3. Alternatively, the set of genes selected from the genes hsted in Table 3 contains at least 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 genes of Table 3. Most preferably, the set of genes selected from the genes listed in Table 3 contains all genes listed in Table 3.
Preferably, in a method of typing of the invention, the gene expression level is determined for at least two sets of genes selected from different tables as indicated in the previous paragraph. In other words, the gene expression level may be determined for (i) a set of genes selected from the genes listed in Table 1 and a set of genes selected from the genes listed in Table 2, (ii) a set of genes selected from the genes listed in Table 1 and a set of genes selected from the genes listed in Table 3, and (iii) a set of genes selected from the genes listed in Table 2 and a set of genes selected from the genes listed in Table 3. Most preferably, the gene expression level is determined for (i) a set of genes selected from the genes listed in Table 1, a set of genes selected from the genes listed in Table 2, and a set of genes selected from the genes listed in Table 3. The sets of genes are preferably as indicated in the previous paragraph.
A method of typing of the invention can also be performed with all genes listed in Tables 1-3.
One of the advantages of the invention is that three different gene signatures are provided, which, although having overlap in genes, allow for attributing the activation in the TGF beta pathway to a specific TGF beta ligand, i.e. TGF beta 1, 2 or 3. A method for typing according to the invention is preferably a method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta 1, 2 or 3 signaling pathway, or in other words, an activated TGF beta signaling pathway attributable to TGF beta 1, 2 or 3. Preferably, in a method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta 1 signaling pathway, the gene expression level of at least 10 genes of Table 4 is determined. Preferably, in method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta 2 signaling pathway, the gene expression level of at least 12 genes of Table 4 is determined. Preferably, in method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta 3 signaling pathway, the gene expression level of at least 15 genes of Table 4 is determined.
Methods to determine gene expression levels of genes are known to a skilled person and include, but are not limited to, Northern blotting, quantitative PCR, microarray analysis and RNA sequencing. It is preferred that said gene expression levels are determined simultaneously. Simultaneous analyses can be performed, for example, by multiplex qPCR, RNA sequencing procedures, and microarray analysis. Microarray analysis allow the simultaneous determination of gene expression levels of expression of a large number of genes, such as more than 50 genes, more than 100 genes, more than 1000 genes, more than 10.000 genes, or even whole-genome based, allowing the use of a large set of gene expression data for normalization of the determined gene expression levels in a method of the invention.
Microarray-based analysis involves the use of selected biomolecules that are immobilized on a solid surface, an array. A microarray usually comprises nucleic acid molecules, termed probes, which are able to hybridize to gene expression products. The probes are exposed to labeled sample nucleic acid, hybridized, and the abundance of gene expression products in the sample that are complementary to a probe is determined. The probes on a microarray may comprise DNA sequences, RNA sequences, or copolymer sequences of DNA and RNA. The probes may also comprise DNA and/or RNA analogues such as, for example, nucleotide analogues or peptide nucleic acid molecules (PNA), or combinations thereof. The sequences of the probes may be full or partial fragments of genomic
DNA. The sequences may also be in vitro synthesized nucleotide sequences, such as synthetic oligonucleotide sequences.
In the context of the invention, a probe is to be specific for a gene expression product of a gene as listed in Tables 1-7. A probe is specific when it comprises a continuous stretch of nucleotides that are completely complementary to a nucleotide sequence of a gene expression product, or a cDNA product thereof. A probe can also be specific when it comprises a continuous stretch of nucleotides that are partially complementary to a nucleotide sequence of a gene expression product of said gene, or a cDNA product thereof. Partially means that a maximum of 5% from the nucleotides in a continuous stretch of at least 20 nucleotides differs from the corresponding nucleotide sequence of a gene expression product of said gene. The term complementary is known in the art and refers to a sequence that is related by base-pairing rules to the sequence that is to be detected. It is preferred that the sequence of the probe is carefully designed to minimize nonspecific hybridization to said probe. It is preferred that the probe is, or mimics, a single stranded nucleic acid molecule. The length of said complementary continuous stretch of nucleotides can vary between 15 bases and several kilo bases, and is preferably between 20 bases and 1 kilobase, more preferred between 40 and 100 bases, and most preferred about 60 nucleotides. A most preferred probe comprises about 60 nucleotides that are identical to a nucleotide sequence of a gene expression product of a gene, or a cDNA product thereof. In a method of the invention, probes comprising probe sequences as indicated in Tables 1-3 and 5-7 can be employed.
To determine the gene expression level when micro- arraying, the gene expression products in the sample are preferably labeled, either directly or indirectly, and contacted with probes on the array under conditions that favor duplex formation between a probe and a complementary molecule in the labeled gene expression product sample. The amount of label that remains associated with a probe after washing of the microarray can be determined and is used as a measure for the gene expression level of a nucleic acid molecule that is
complementary to said probe.
The determined gene expression level can be normalized for differences in the total amounts of nucleic acid expression products between two separate samples by comparing the level of expression of a gene that is known not to differ in expression level between samples. If samples for use in a method of the invention are FFPE samples, it is possible to use an FFPE normalization template.
Preferably, gene expression levels are determined by microarray analysis.
Another preferred method for determining gene expression levels is by sequencing techniques, preferably next- generation sequencing (NGS) techniques of RNA samples. Sequencing techniques for sequencing RNA have been developed. Such sequencing techniques include, for example, sequencing-by-synthesis.
Sequencing-by-synthesis or cycle sequencing can be accomplished by stepwise addition of nucleotides containing, for example, a cleavable or photobleachable dye label as described, for example, in U.S. Patent No. 7,427,673 ; U.S. Patent No. 7,414, 116 ; WO 04/018497 ; WO 91/06678 ; WO 07/123744 ; and U.S. Patent No. 7,057,026 . Alternatively, pyrosequencing techniques may be employed.
Pyrosequencing detects the release of inorganic pyrophosphate (PPi) as particular nucleotides are incorporated into the nascent strand (Ronaghi et al., Analytical Biochemistry 242(l):84-9 (1996); Ronaghi, M. Genome Res. 11(1):3- 11 (2001);
Ronaghi, M. et al., Science 281:5375, 363 (1998); U.S. Patent No. 6,210,891 ; U.S. Patent No. 6,258,568 ; and U.S. Patent No. 6,274,320. In pyrosequencing, released PPi can be detected by being immediately converted to adenosine triphosphate (ATP) by ATP sulfurylase, and the level of ATP generated is detected via lucifer ase -p ro duce d p hotons .
Sequencing techniques also include sequencing by ligation techniques.
Such techniques use DNA ligase to incorporate oligonucleotides and identify the incorporation of such oligonucleotides and are inter alia described in U.S. Patent No 6,969,488 ; U.S. Patent No. 6, 172,218 ; and U.S. Patent No. 6,306,597. Other sequencing techniques include, for example, fluorescent in situ sequencing
(FISSEQ), and Massively Parallel Signature Sequencing (MPSS).
Sequencing techniques can be performed by directly sequencing RNA, or by sequencing a RNA-to-cDNA converted nucleic acid library. Most protocols for sequencing RNA samples employ a sample preparation method that converts the RNA in the sample into a double-stranded cDNA format prior to sequencing.
In a method of typing of the invention, the reference sample is preferably a sample, such as an RNA sample, isolated from a tissue of a healthy individual, or isolated from a cancerous growth of a cancer patient, preferably a colorectal cancer patient. Preferably, said reference sample is indicative of, or known to have, an activated or not activated TGF beta signaling pathway. In other words, the activation status of the TGF beta signaling pathway of said sample has been determined. In the same manner, the reference sample can be an RNA sample from a cancerous growth of a cancer patient, such as a colorectal cancer patient, having an EMT phenotype or not having an EMT phenotype. The reference sample may comprise an RNA sample from a relevant cell line or mixture of cell lines. The RNA from a cell line or cell line mixture can be produced in-house or obtained from a commercial source such as, for example, Stratagene Human Reference RNA. Another preferred reference sample comprises RNA isolated and pooled from normal adjacent tissue from cancer patients.
Even more preferably, said reference sample is a pooled RNA sample that is isolated from tissue comprising cancer cells from multiple individuals suffering from cancer, preferably colorectal cancer, more preferably stage 2 and/or 3 colorectal cancer, and which cancer cells either have (i) an activated or not activated TGF beta signaling pathway, or (ii) are positive or negative for EMT status. It is preferred that said sample is pooled from more than 10 individuals, more preferred more than 20 individuals, more preferred more than 30 individuals, more preferred more than 40 individuals, most preferred more than 50 individuals.
Typing of a sample can be performed in various ways. In one method, a coefficient is determined that is a measure of a similarity or dissimilarity of a sample with a previously established reference gene expression level - of the target genes - that is specific to a certain cell type, tissue, disease state or any other interesting biological or clinical interesting samples group. Such a reference gene expression level can be referred to as a profile template. Typing of a sample can be based on its (dis)similarity to a single profile template or based on multiple profile templates. In the invention, the profile templates are representative of samples that (i) have an activated or not activated TGF beta signaling pathway, or (ii) are positive or negative for EMT status.
Preferably, the reference gene expression level is a template, preferably a profile template, indicative of an activated, or not activated, TGF beta signaling pathway. Examples of suitable profile templates are the gene expression level templates of (i) a colorectal cancer of which the TGFB1 mRNA level is in the highest 20% percentile and the TGFBR1 and TGFBR2 mRNA level is not in the lowest 20% percentile, calculated on the basis of a group of colorectal cancer patients, preferably a group of at least 10, 30, 40, 50, 100, 200 or 300 colorectal cancer patients, (ii) a colorectal cancer of which the TGFB2 mRNA level is in the highest 20% percentile and the TGFBRl and TGFBR2 mRNA level is not in the lowest 20% percentile, calculated on the basis of a group of colorectal cancer patients, preferably a group of at least 10, 30, 40 ,50, 100, 200 or 300 colorectal cancer patients, or (iii) a colorectal cancer of which the TGFB3 mRNA level is in the highest 20% percentile and the TGFBRl and TGFBR2 mRNA level is not in the lowest 20% percentile, calculated on the basis of a group of colorectal cancer patients, preferably a group of at least 10, 30, 40 ,50, 100, 200 or 300 colorectal cancer patients.
A number of different coefficients can be used for determining a correlation between the gene expression level in a sample from a cancer patient and a profile template. Preferred methods are parametric methods which assume a normal distribution of the data. One of these methods is the Pearson product- moment correlation coefficient, which is obtained by dividing the covariance of the two variables by the product of their standard deviations. Preferred methods comprise cosine-angle, un-centered correlation and, more preferred, cosine correlation (Fan et al., Con,/' Proc IEEE Eng Med Biol Soc. 5:4810-3 (2005)).
Said correlation with a profile template is used to produce an overall similarity score for the set of genes that are used. A similarity score is a measure of the average correlation of gene expression levels of a set of genes in a sample from a cancer patient and a profile template. Said similarity score can, but does not need to be, a numerical value between +1, indicative of a high correlation between the gene expression level of the set of genes in a sample of said cancer patient and said profile template, and - 1, which is indicative of an inverse correlation. A threshold can be used to differentiate between samples having an activated TGF beta signaling pathway or that are positive for EMT status, and samples not having an activated TGF beta signaling pathway or that are negative for EMT status. Said threshold is an arbitrary value that allows for discrimination between samples from patients without an activated TGF beta signaling pathway, and samples of patients with an activated TGF beta signaling pathway. If a similarity threshold value is employed, it is preferably set at a value at which an acceptable number of patients with an activated TGF beta signaling pathway would score as false negatives, and an acceptable number of patients without an activated TGF beta signaling pathway would score as false positives. A similarity score is preferably displayed or outputted to a user interface device, a computer readable storage medium, or a local or remote computer system. A method of typing of the invention further comprises determining a stage of the cancer. The staging of a cancer is generally based on the size of the cancer and on whether the cancer has spread to lymph nodes or other areas of the body.
Additionally typing a sample for microsateUite stability (MicroSateUite Instabl (MSI) or MicroSateUite Stable (MSS) status
In a method of typing of the invention, a sample of a cancer patient is preferably additionally typed for microsateUite stability status. This is preferably performed by the steps of: - providing a sample from a cancer patient, whereby the sample comprises RNA expression products from a cancer cell of said patient; - determining a gene expression level for DUSP18 and at least one further gene listed in Table 5 or Table 6; - comparing said determined gene expression level of said at least two genes to a gene expression level of said genes in a reference sample; and - typing said sample on the basis of the comparison of the determined gene expression level and the gene expression level of said genes in a reference sample.
The sample used can be (part of) the same sample on the basis of which a cancer patient is typed for the presence or absence of an activated TGF beta signaling pathway.
The advantages of typing for microsateUite stability status are extensively described in WO 2012/087144 A2, the content of which is incorporated by reference herein. Additionally typing a sample of a patient for MSI status provides for valuable information regarding predicted response to anti-cancer therapy and allows for intelligent treatment decision-making. The gene signature referred to in Tables 5 and 6 of the present application is identical to the gene signature of Tables 4 and 5 of WO 2012/087144 A2.
Preferred combinations of genes to be used in typing for MSI status are selected from Table 5 and/or 6 and are provided by DUSP18 and SMCR7L, more preferred DUSP18, SMCR7L and CEP68, more preferred DUSP18, SMCR7L, CEP68 and UNKL, more preferred DUSP18, SMCR7L, CEP68, UNKL and
KCNK5, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5 and RNF43, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43 and RPL22L1, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1 and AXIN2, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2 and TNNC2, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, and ATP9A, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, ATP9A and VAV3, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, ATP9A, VAV3 and QPRT, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, ATP9A, VAV3, QPRT and PLAGL2, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, ATP9A, VAV3, QPRT, PLAGL2, and C13orfl8, more preferred DUSP18, SMCR7L, CEP68, UNKL, KCNK5, RNF43, RPL22L1, AXIN2, TNNC2, ATP9A, VAV3, QPRT, PLAGL2, C13orfl8 and
ARID3A. A combination of genes from genes selected from Table 5 and/or 6 may be combined with MLHl (NM_000249), which is downregulated in MSI patients when compared to MSS patients. It is also possible to determine gene expression levels for all genes listed in Table 5 and/or 6, optionally complemented with MLHl (NM_000249).
In the context of typing for MSI status, the reference sample can be a sample as described in WO 2012/087144 A2, for instance on page 16 and 17 of WO 2012/087144 A2.
Any specific embodiments relating to method steps for typing for MSI status in WO 2012/087144 A2 are incorporated herein by way of reference.
It is to be understood that the method steps relating to the additional typing for MSI status can be supplemented with any embodiments discussed hereinbefore for the typing for the presence or absence of an activated TGF beta signaling pathway.
Additionally typing a sample for activating mutations in. the Epidermal Growth Factor Receptor (EGFR) pathway.
In a method of typing of the invention, a sample of a cancer patient is preferably additionally typed for the presence or absence of activating mutations in the EGFR pathway, more preferably for the presence or absence of one or more activating mutations in BRAF. This is preferably performed by the steps of: - providing a sample from a cancer patient, whereby said sample comprises gene expression products from a cancer cell of said patient;
- determining a gene expression level for at least two genes listed in Table 7;
- comparing said determined gene expression level of said at least two genes to a gene expression level of said genes in a reference sample;
- typing said sample on the basis of the comparison of the determined gene expression level and the gene expression level of said genes in a reference sample.
The sample used can be (part ol) the same sample on the basis of which a cancer patient is typed for the presence or absence of an activated TGF beta signaling pathway and/or microsatellite stability status.
The advantages of typing for the presence or absence of activating mutations in the EGFR pathway are described in WO 2012/044167 A2, the contents of which are incorporated by references herein. Additionally typing a sample of a patient for activation in the EGFR pathway provides for valuable information regarding predicted response to anti-cancer therapy and allows for intelligent treatment decision making. The gene signature referred to in Table 7 is identical to the gene signature of Table 2 of WO 2012/044167 A2.
A preferred set of genes to additionally type for activating mutations in the EGFR pathway comprises at least 2 of the genes listed in Table 7, more preferably at least 5 of the genes listed in Table 7, more preferably at least 10 of the genes listed in Table 7. More preferably such a set of genes comprises at least 20 of the genes listed in Table 7, more preferably at least 30 of the genes listed in Table 7, more preferably at least 40 of the genes listed in Table 7. A most preferred set of genes comprises all genes listed in Table 7.
In addition, the KRAS mutation gene signature described in Table 1 of
WO 2012/044167 A2 and/or the PIK3CA mutation gene signature in Table 3 of WO 2012/044167 A2 can be used to complement the typing for activating mutations in the EGFR pathway. For the KRAS mutation gene signature and the PIK3CA mutation gene signature, a preferred set of genes comprises at least 2 of the genes listed in Table 1 and/or Table 3, more preferably at least 5 of the genes listed in Table 1 and/or Table 3, more preferably at least 10 of the genes listed in Table 1 and/or Table 3. More preferably such a set of genes comprises at least 20 of the genes listed in Table 1 and/or Table 3, more preferably at least 30 of the genes listed in Table 1 and/or Table 3, more preferably at least 40 of the genes listed in Table 1 and/or Table 3. A most preferred set of genes comprises all genes listed in Table 1 and/or Table 3 depicted in WO 2012/044167 A2.
The additional typing for activating mutations in the EGFR pathway may further comprise determining the expression level of EREG, and AREG. Over- expression of any one of these markers, preferably all two markers, compared to the level of expression of that marker in a reference sample from a patient not having an activating mutation in the EGFR pathway, was found to be indicative for a likeliness to respond to anti-EGFR therapy.
Any specific embodiments related to method steps for typing for activating mutations in the EGFR pathway in WO 2012/044167 A2 are
incorporated herein by way of reference.
It is to be understood that the method steps relating to the additional typing for activating mutations in the EGFR pathway can be supplemented with any embodiments discussed hereinbefore for the typing for the presence or absence of an activated TGF beta signaling pathway.
Methods for comparing gene expression levels
The invention also relates to a method for comparing gene expression levels, comprising the steps of: - providing a sample from a cancer patient, the sample comprising gene expression products from a cancer cell of said patient; - determining a gene expression level for at least five genes listed in Table 4; - comparing said determined gene expression level to a reference gene expression level of said genes in a reference sample.
On the basis of the compared gene expression levels, it is possible to type a subject for the presence or absence of an activated TGF beta signaling pathway.
It is to be understood that the method steps relating to a method for comparing gene expression levels as described in this section can be supplemented with any embodiments discussed hereinbefore for the typing for the presence or absence of an activated TGF beta signaling pathway.
Treatment based on the. result of a method of typing of the. in ven tion. A method of typing of the invention allows for intelligent treatment decision-making. A method for typing of the invention allows for the selection of patient groups that are eligible for treatment with an inhibitor of the TGF beta signaling pathway, and for the selection of patient groups that are eligible for treatment with a standard-of-care therapeutic agent other than an inhibitor of the TGF beta signaling pathway. Therefore, the invention provides a method for assigning an inhibitor of the TGF beta signaling pathway to a cancer patient, comprising the steps of: -assigning an inhibitor of the TGF beta signaling pathway to a cancer patient typed as having an activated TGF beta signaling pathway according to a method of typing of the invention.
The term "inhibitor of the TGF beta signaling pathway" as used herein, refers to a therapeutic compound of any type, including small molecule-, proteins, antibody-, antisense-, small interfering RNA-, or microRNA-based compounds, that inhibit block, counteract or antagonize signaling, preferably stimulatory signaling, in the TGF beta signaling pathway. Preferably, such an inhibitor is an inhibitor of TGF beta receptor mediated signaling, also referred to as an inhibitor of TGF beta receptor activity, which includes therapeutic compounds that (i) inhibit or block natural TGF beta from binding to a TGF beta receptor and forming an active signaling complex, or (ii) inhibit TGF beta receptor mediated signaling by binding to a TGF beta receptor either extracellularly or intracellularly and blocking signaling through said TGF beta receptor. Therapeutic compound LY2157299 (alias Galunisertib), of Eli Lilly, is an example of a therapeutic compound that binds to the TGF beta receptor type I and inhibits its kinase activity, thereby specifically downregulating phosphorylation of SMAD2 and abrogating activation of the canonical pathway. Preferably, an inhibitor of the TGF beta signaling pathway abrogates signaling or activation of the canonical TGF beta signaling pathway. Because the invention allows for attributing activation in the TGF beta signaling pathway to a specific TGF beta isoform, a preferred inhibitor is a specific or selective inhibitor of TGF beta 1, 2 or 3. Depending on which TGF beta isoform the activation is attributed to, therapy with an inhibitor of a specific TGF beta isoform can be assigned.
Non-limiting examples of inhibitors of the TGF beta signaling pathway are (i) TGF beta inhibitors such as antisense oligonucleotides counteracting TGF beta 1, 2 and/or 3 synthesis, TGF beta 1, 2 and/or 3-neutralizing antibodies, and soluble TGF beta receptors, (ii) TGF beta receptor inhibitors such as a competitive TGF beta receptor antagonist, including TGF beta muteins, that block or dampen TGF beta(agonist)-mediated signaling by competing for TGF beta receptor binding sites, anti-TGF beta receptor monoclonal antibodies that prevent ligand-receptor interaction, and TGF beta receptor kinase inhibitors, (iii) inhibitors of SMAD proteins, or (iv) a combination of such inhibitors.
Preferred inhibitors of the TGF beta signaling pathway are TGF beta inhibitors selected from the group formed by, or consisting of, fresolimumab (originator: Cambridge Antibody Technology) which binds to and inhibits TGF beta 1, 2 and 3; trabedersen (originator: Antisense Pharma) which is an antisense oligonucleotide targeting TGF beta 2; and disitertide (originators: Digna Biotech; University of Navarra) which is a peptidic TGF beta 1 inhibitor specifically designed to block TGF beta 1-receptor interaction; Lucanix (originator: NovaRx Corporation) which is a TGF beta 2 inhibitor; and/or FANG™ Vaccine (originator: Gradalis) which is a TGF beta 1 and 2 inhibitor; and/or TGF beta receptor inhibitors selected from the group formed by, or consisting of, LY2157299 (alias Galunisertib; originator: Eli Lilly); TEW 7197 (Originator: Ewha Womans
University); PF-03446962 (alias Ascrinvacumab; originator: Pfizer); LY3022859 (alias IMC TR1; originator: ImClone Systems); and ΚΪ26894. Preferably, the inhibitor is LY2157299.
If a sample of cancer patient is typed as having an activated TGF beta signaling pathway, and the activation is attributable to a specific TGF beta isoform, the therapy assigned is preferably an inhibitor of that specific TGF beta isoform.
The invention also provides a method for assigning a standard-of-care therapeutic agent to a cancer patient, comprising the steps of: - assigning a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, to a cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention. These patient groups are likely not to benefit from administration of an inhibitor of the TGF beta signaling pathway, and therefore alternative therapy is to be assigned. As used herein, a "standard-of-care therapeutic agent" is a therapeutic compound, or combination of such compounds, that is/are considered by medical practitioners as appropriate, accepted, and/or widely used for a certain type of patient, disease or clinical circumstance. Standard-of-care therapies for different types of cancer are well known by persons of skill in the art. For example, the National Comprehensive Cancer Network (NCCN) publishes the NCCN Clinical Practice Guidelines in Oncology (NCCN GUIDELINES) that provide detailed up- to-date information on standard-of-care therapies for a wide variety of cancers.
For example, standard-of-care therapy for patients suffering from colorectal cancer include surgery, and chemotherapy such as administration of 5- fluorouracil (5-FU), 5-FU-semustine, 5-FU-leucovorin, capecitabine or oxaliplatin.
Standard-of-care cancer therapy may include chemotherapy, radiation therapy, hormonal therapy and/or targeted cancer therapy such as immunotherapy and tyrosine-kinase inhibition therapy.
In embodiments where a sample of a cancer patient is additionally typed for MSI status, it is possible to further assign treatment on the basis of the result of typing obtained. Although MSI cancers are associated with favorable prognosis, there is evidence that patients with MSI colorectal cancers respond differently to fluorouracil -based chemotherapy compared to patients with micros atellite stable (MSS) colorectal cancers. Especially patients with stage 2 MSI colorectal cancers may be harmed by treatment with 5-FU. It is therefore recommended to test for MSI in all stage 2 colon cancer patients, and not to prescribe 5-FU to MSI-high patients with stage 2 colon cancer. Therefore, the identification of MSI-like samples by a methods of the invention, which samples were typed as MSS samples by standard methods (IHC/ PCR), is of high clinical relevance. It is preferred that colorectal cancer patients with stage 2 MSI-like colorectal cancer are not assigned, and not treated, with 5-FU but with an alternative standard-of-care therapeutic agent. Preferably, a cancer patient typed as being positive for MSI status (MSI-high) is assigned, and treated with, an immunotherapeutic agent such as a PD- 1 or PD-Ll inhibitor. A preferred PD-1 or PD-Ll inhibitor is selected from the group formed by, or consisting of, nivolumab (originators Medarex and Ono Pharmaceutical.; CAS number 946414-94-4);
pembrolizumab (originators Merck & Co and The Leukemia & Lymphoma Society; CAS Number 1374853-91-4); JS001 (originator Shanghai Junshi Biosciences); TSR- 042 (originator AnaptysBio; developer Tesaro, Inc.); Pidilizumab (CT-011,
MDV9300; originator CureTech); AMP-224 (originator Amplimmune); REGN2810 (originator Regeneron Pharmaceutical); JNJ-63723283 (originator Janssen
Research & Development); PDR001 (originator Novartis); BGB-A317 (originator BeiGene); SHR- 1210 (originator Jiangsu Hengrui Medicine Co); MEDI068 or AMP- 514 (Astra Zeneca/Medimmune); Atezolizumab (originators Genentech and
University Medical Center Groningen; CAS number 1380723-44-3); Durvalumab (originator Medlmmune); BMS-936559 (alias MDX-1105; originator Medarex); LY3300054 (originator Eli Lilly); Avelumab (alias MSB0010718C; originators EMD Serono and Merck KGaA); KN035 (originator Alphamab); CA-170 (originator Aurigene Discovery Technologies) and SHR- 1210 (originator Jiangsu Hengrui Medicine Co.). More preferably, the PD-1 or PD-L1 inhibitor is the PD-L1 inhibitor atezolizumab.
In embodiments where a sample of a cancer patient is additionally typed for the presence or absence of one or more activating mutations in the EGFR pathway, it is possible to further assign treatment on the basis of the result of typing obtained. If a sample of such a patient is typed as having one or more activating mutations in the EGFR pathway, preferably therapy is assigned which allows for inhibition of EGFR pathway at the level of the activating mutation or downstream of that pathway. For activating mutations in BRAF, therapy is assigned which allows for inhibition of BRAF or inhibition of signaling mediators downstream in the BRAF signaling pathway. Preferred inhibitors of the BRAF signaling pathway are selected from the group formed by, or consisting of, PLX- 4032 (alias vemurafenib; CAS number 918504-65-1), dabrafenib (CAS number 1195765-45-7), sorafenib (originator: Onyx Pharmaceuticals and University of Kentucky; CAS number 284461-73-0), PLX-4720 (originator: Plexxikon), GDC-0879 (CAS number 905281-76-7), MLN2480 (alias TAK-580; originator: Biogen Idee; Sunesis Pharmaceuticals), R05126766 (originator: Chugai Pharmaceutical), RAF265 (Originator: Novartis) and AZ 628 (CAS number 878739-06-1).
Alternatively, a cancer patient typed as having one or more activating mutations in the EGFR pathway is assigned, or treated with, a vinca alkaloid. A preferred vinea alkaloid is vinorelbine. In embodiments described herein that relate to assigning treatment, it is to understood that also methods of treatment form part of the invention, wherein a therapeutically effective amount of the assigned medicament is administered to a cancer patient that is typed according to methods described herein.
The present invention further provides an inhibitor of the TGF beta signaling pathway for use in the treatment of a cancer patient typed as having an activated TGF beta signaling pathway according to a method for typing of the invention. The invention also relates to a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, for use in the treatment of cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention.
The invention further relates to a use of an inhibitor of the TGF beta signaling pathway in the manufacture of a medicament for treating a cancer patient typed as having an activated TGF beta signaling pathway according to a method for typing of the invention. The invention also relates to a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, in the manufacture of a medicament for treating a cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention.
In the same manner, the invention provides a method for treating a cancer patient, comprising the steps of: - administering a therapeutically effective amount of an inhibitor of the TGF beta signaling pathway to a cancer patient typed as having an activated TGF beta signaling pathway according to a method for typing of the invention. The invention also relates to a method for treating a cancer patient, comprising the steps of: - administering a therapeutically effective amount of a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, to a cancer patient typed as not having an activated TGF beta signaling pathway according to a method for typing of the invention
The term "therapeutically effective amount" refers to a quantity of a specified agent sufficient to achieve a desired effect in a subject being treated with that agent. Ideally, a therapeutically effective amount of an agent is an amount sufficient to inhibit or treat the disease or condition without causing a substantial cytotoxic effect in the subject. The therapeutically effective amount of an agent will be dependent on the subject being treated, the severity of the affliction, and the manner of administration of the therapeutic agent. Preferably, the term refers to (i) an amount sufficient to inhibit, block or counteract signaling - or activation - in the TGF beta signaling pathway, and/or (ii) an amount sufficient to treat cancer. It is within the knowledge and capabilities of the skilled practitioner to determine therapeutically effective dosage regimens.
The term "administering", as used herein, refers to the physical introduction of an agent or therapeutic compound to a cancer patient, using any of the various methods and delivery systems known to those skilled in the art. The skilled person is, per cancer and agent for administration, aware of suitable methods for administration and dosage forms. Administration of small molecules described herein can be performed by non-parenteral administration such as by oral and enteral administration. Preferred route of administration for protein- based agents such as antibodies is by parenteral administration, including intravenous, intramuscular, subcutaneous, intraperitoneal, spinal or other parenteral routes of administration, executed inter alia by injection or infusion in the form of a solution. Administering can be performed, for example, once, a plurality of times, and/or over one or more extended periods of time. The content of publications mentioned herein are incorporated herein by reference.
For the purpose of clarity and a concise description, features are described herein as part of the same or separate embodiments, however, it will be appreciated that the scope of the invention may include embodiments having combinations of all or some of the features described.
FIGURE LEGENDS
Figure 1 shows the prognostic value of a random combination of genes from the TGF beta 1-3 signatures as listed in Tables 1-3 for identifying an activated or non- activated TGF beta signaling pathway. The plot is based on gene expression products from samples of stage 2 and 3 colorectal cancer patients. The plot shows that any combination of 20 genes of the TGF beta 3 signature, or any combination of 60 genes of TGF beta 2 signature, or any combination of 85 genes of the TGF beta 1 signature has prognostic power (<0.05) in samples of stage 2 and 3 colorectal cancer patients.
Figure 2 shows in the upper panel the response to chemotherapy (treated and untreated) in a group of colorectal cancer patients typed as having an activated TGF beta signaling pathway (treated, n=22; and untreated, n=20). Therapy showed no benefit in the TGF beta activated group, and it even appeared to result in decreased survival in terms of higher regional recurrence and distant metastasis as compared to the untreated patient group. In the lower panel, the response to chemotherapy of the TGF beta non-activated colorectal cancer patient group is shown (treated, n=73; untreated, n=46). Therapy arguably showed a little benefit in the TGF beta non-activated group. From this graph it follows that cancer patients with an activated TGF beta signaling pathway tend not to benefit from chemotherapy. TGF beta activation (TGFBeta activated group) is correlated with an EMT phenotype, and tumors with an EMT phenotype generally do not benefit from chemotherapy.
Figure 3A-C show the heatmaps of the TGF beta 1, 2 and 3 signatures,
respectively. Black bars on the upper row of each heatmap indicate the mRNA level of the tumor sample and indicate an initial stratification of activated TGFB signaling.
Figure 4 shows the prognostic power of the gene signatures of the invention in stage 2 and stage 3 colorectal cancer patients, for identifying TGF beta activation status and distinguishing patient groups for survival, i.e. regional recurrence and distant metastasis. Shown is (a) TGF beta 1 signature (Table 1), (b) TGF beta 2 signature (Table 2), (c) TGF beta 3 signature (Table 3), (d) a combination of all three signatures, wherein TGF beta activation is defined by any one positive prediction of TGFBl, TGFB2 or TGFB3 signature, (e) any combination of two out of three signatures, and (f) all three signatures. All p-values are <0.05.
Figure 5 shows the prognostic power of the gene signature of Table 4 in stage 2 and stage 3 colorectal cancer patients. It follows from Figure 5 that with a gene signature of the invention it is possible to prognosticate cancer patients for survival. It also follows from Figure 5 that cancer patients having an activated TGF beta signaling pathway have worse survival parameters than cancer patients not having an activated TGF beta signaling pathway.
Figure 6 shows the prognostic value of a random combination of genes from the TGF beta signature as listed in Table 4 for identifying an activated or non- activated TGF beta signaling pathway. The plot is based on gene expression products from samples of stage 2 and 3 colorectal cancer patients. The plot shows that any combination of about 15 genes from Table 4 has prognostic power (<0.05) in samples of stage 2 and 3 colorectal cancer patients.
Table 1: TGF beta 1 signature.
Rank
order Gene Probe sequence Transcript ID P-value
1 TGFB1 C AACTATTG CTTCAG CTCCACG G AG AAG AACTG CTG CGTG CG G C AG CTGTACATTG ACTT HD_8pack_Dx_2906 1.49E- ■25
2 BASP1 TTCAGTCAACTTTACCAAGAAGTCCTGGATTTCCAAGATCCGCGTCTGAAAGTGCAGTAC HD_8pack_Dx_0344 1.59E- -14
3 VASH1 GTTGTACTAGACTTTGTTCAGGCTGTTCTCATCTCAGTATTGCCCCTTCCTTTCACTTTC HD_8pack_Dx_3213 4.72E- ■14
4 PECAM1 TTC AAAG G CTTGTAGTTTTG G CTAGTCCTTGTTCTTTG G A AATAC AC AGTG CTG ACCAG A NM_000442 4.69E- ■12
5 VAMP5 CTGCAGCAGCGTTCAGACCAACTCCTGGATATGAGCTCAACCTTCAACAAGACTACACAG NM_006634 2.73E- -15
6 TRIB2 ACG G CTTTTCTATTG CTGTATG AT AC AG A ACTCTTTTG G CAT AA AT ATTTGTGTTCCC AG HD_8pack_Dx_3092 2.30Ε· -12
7 KCTD12 CAGAGGCATGCATTTACATATGTTGCCCTAATTACCATTTGATGATCATAAATACAAGTG NM_138444 1.22E- -11
8 VIM TGATTAAGACGGTTGAAACTAGAGATGGACAGGTTATCAACGAAACTTCTCAGCATCACG NM_003380 2.23E- -12
9 PPP1R12A GTATAAGATGTTAGATTCTGTAATCTTCACATTCATTTTAGCAGGTACTGAGTGATGCTG NM_002480 6.22E- ■12
10 TIMP2 GTTGAAAGTTGACAAGCAGACTGCGCATGTCTCTGATGCTTTGTATCATTCTTGAGCAAT HD_8pack_Dx_3011 6.22E- -14
11 AYTL2 CAGTAAGTACGGGAAAAAATGTTTACTAACTTCCTCAGAGATTCGTGATACGCGTTTCTC HD_8pack_Dx_0334 3.20Ε· -12
12 SERTAD1 GTCATAGCTTGGGCTGTTCCTTCTCTGATACGGGAAGAGACCCCAATCAGATTTTTCAAA NM_013376 2.39E- -13
13 PIM1 GCCTGCTGGTTTTATCTGAGTGAAATACTGTACAGGGGAATAAAAGAGATCTTATTTTTT NM_002648 1.43E- -14
14 PLEKH01 CGGGTTGGACAGACTCTTATCTCCGTGTTGCTGGATAAAGCTTTTTTATTTACCTCAATC NM_016274 6.71E- -13
15 CD 14 GATCCAAGACAGAATAATGAATGGACTCAAACTGCCTTGGCTTCAGGGGAGTCCCGTCAG HD_8pack_Dx_0608 8.04E- -13
16 MRC2 ATGTGAACATGGACTCGAAGACATGGCCCTTTCTCTGTAGTTGATTTTTTAAATGTGCCA NM_006039 6.48E- -12
17 RBMS1 GAGGGGAAATCTGCTGCTAGAAATGTCTGAACTAAGTGCCATACTCGTCTGGGTAAGATT NM_016836 9.82E- -12
18 TNFSF12 CCTCCCTTGAGAATTCCCTGTGGATTTTTAAAACAGATATTATTTTTATTATTATTGTGA HD_8pack_Dx_3881 9.04E- -13
19 CYTH3 GATGGCTGTCAGAGCTCTTGCAGATACTGTGTTCACTAAATAAAAATCACATGTATTGTT NM_004227 4.65E- -12
20 CALD1 CCATGCTGTGAAATAGAGACTTTTCTACTGATCATCATAACTCTGTATCTGAGCAGTGAT HD_8pack_Dx_0554 6.04E- -12
21 LILRB2 ACTTGATTCTGCAGTCGAAATAACTAATATCCCTACATTTTTTAATTAAAGCAACAGACT NM_005874 2.44E- -12
22 PREX1 CAAAGAAAGGTATGTTGTCTAACAGGGGACCAACAGAAGGTAGTATTGACAACTGTTCCC NM_020820 1.05E- -12
23 CAPN2 AG A AGTTCTTATAG AA AG G ACACAAGTTTGTTTCCTG G CTTTACCTTG G G AA AATG CTAG HD_8pack_Dx_3906 7.74E- -12
24 HIF1A TAAGCATTGTGAAGGAAGATTAATATAGCCAAATAACTAGAGTGATCAGTTCTACCAGAG HD_8pack_Dx_1319 6.00E-■13
25 RFT 1 TTTATCATGTGTATATCGTCCAGAAAGTATTAAGGCTTTAGGTAGATGCAACTGGCGAAC NM_015150 1.29E- ■11
26 ZNF469 G G G G CCCTG AG GTTGTACTGTAA ACATCATAGTG ACTTGTCTTTTC A AATATATTCCCAC NM_001127464 1.36E- -12
27 MRC2 GGTGCGACAGCGTGGGACAATGTGAACATGGACTCGAAGACATGGCCCTTTCTCTGTAGT HD_8pack_Dx_1876 9.79E- -12
28 AHR CTGTTG G ACGTC AG CAAGTTCACATG G AG G CATTG ATG CATG CT ATTCACAATTATTCCA NM_001621 7.80E- -15
29 ITGB2 GCCAATTTATTTACATTTAAACTTGTCAGGGTATAAAATGACATCCCATTAATTATATTG NM_000211 5.28E- -15
30 ITPRIPL2 TTCGTTTTCTCTTG CAG GTTG G AGT AA ATTTG C ACTTTG A ATC ATGTGG GTC ATTTG GG G NM_001034841 2.47E- -14
31 PTRF CTTGGGGAACCTCTCACGTTGCTGTGTCCTGGTGAGCAGCCCGACCAATAAACCTGCTTT NM_012232 1.17E- -11
32 TGFBR1 GAATAGGATTGCTCTCACATTAAAGATAGTTACTTCAATTTGAAGGCTGGATTTAGGGAT HD_8pack_Dx_4439 8.74E- -12
33 DNAJB4 TTCTTTTGAGGGTTCATTAAATTGCATGAATAGAGACGGGTCAAATAAATAGGCAAAAGG NM_007034 9.25Ε· -12
34 CYB5R3 AGTGACCTCGACGTTGCCTTTAGACTACAGTTGTGTTAGCCTCTTGCGTATTGGCTTTTT NM_007326 9.48E- -14
35 CRY2 AGATGGTTGCAGGCAAAATGCACTTTATAGAGATTTTCTATTGCTGGGAAGGTGTGTTTC NM_021117 1.47E- -12
36 LAPTM4A TGCAGAGGCAAGAAAAATATTTGACATTGTGACTTGACTGTGGAAGATGATGGTTGCATG NM_014713 1.29E- -11
37 RHBDF2 AGTAACGCTAACTTTGTACGGACGATGTCTCATGGATTAAATAATATTCTTTATGGCAGT HD_8pack_Dx_2456 8.54E- -12
38 DEGS1 ACTGCTGAATCCTGTACAGCCTTACTCATAAATAAAGTACTTACTGAATTTCCACCATTC NM_003676 1.40E- -11
39 AIMKRD44 G CTG C AAG ATACG GTCATG AG TTTTG ATTAAC ACCTT AATAACC AG CG G AG CTG AC ACA NM_153697 6.59E- -12
40 SIDT2 TCTTTTCTCAGAGCGTCTCCATGCTATGGTTGCATTTCCGTTTTCTATGAATGAATTTGC NM_001040455 9.88E- -12
41 AHNAK ATTTCCAGCACTTTAATGGCCAATTAACTGAGAATGTAAGAAAATTGATGCTGTACAAGG NM_001620 3.55E- -12
42 PANX1 GAATTGAGGCCATTTGGGAAGAAAATTCTAGCACTGGTGGAGAATTATAGAATAAAGATT NM_015368 7.16E- -12
43 SNX1 TCTCGGGTGACTCAATATGAAAGGGACTTCGAGAGGATTTCAACAGTGGTCCGAAAAGAA HD_8pack_Dx_3706 4.10E- -12
44 SLC2A3 ACTGGATGAAATAACTCCTTCTTGTAGTAGTCTCATTACTTTTGAAGTAATCCCGCCACC NM_006931 6.16E- -13
45 S1PR3 GCTGCAGAGAAACTATGCATTAGGTCTCTTTTCAATTAGAAACCTTTACTATTTCCAATG NM_005226 4.35E- -13
46 UGCG AATGGTTTTGTGCAGTGAACAACACATGGCGAGGTACTAACTGAGAAACTTTTTCATGCT ENST00000374279 7.40E- -13
47 FERMT2 GAGAGGTGGATTACCAGTATTGTTCAATAATCCATGGTTCAAAGACTGTATAAATGCATT NM_001134999 3.46E- -13
48 PPP1R9B TGTATATAATATATATATGTATGTATTGTTCCCGGTTTTGTACGGACCATGCCCTCTGTC NM_032595 3.58E- -12
49 TIMP2 TGCTTTGTATCATTCTTGAGCAATCGCTCGGTCCGTGGACAATAAACAGTATTATCAAAG NM_003255 5.76Ε· -12
50 DLC1 TTTGGATATCAGTGTTCCTCATGAAGATATACATGGATATTCAATTTTGATGGCTTCCAG NM_182643 5.49E- -14
51 ADPRH G G G G A AG AG AT AAACTTT ATG C AT AAC ATTAG G GTAA ATC AATA AAG ATG GTCTG AC ACA NM 001125 4.74E- -14
52 YPEL3 GAGCAGCCAGAAGTACAAAGAGGGGAAGTACATCATTGAACTCAACCACATGATCAAAGA NM. _031477 1.37E-■11
53 DENND5A CGGGATGTGTCATCGTGCCAAATACCACATTTCCTGTTGGCACAGTTTCACAGAAGTAAA NM. _015213 1.86E- ■13
54 MYCBP2 TGAACAGGAAATGAGAGCATCTCCCAAAATAAGTCGAAAATGTGCTAATAGACACACCAG NM. ,015057 8.54E- -14
55 GM2A G AGTTCTG G G CTC ATTTG AAG CCTG G A ATAG C A AT AAATCTTTTT AACTTG CG G ACAGTT NM. _000405 1.16E- -11
56 KIDINS220 TGTTATCGTTTTAACATAGCTCATTTATGTAGAATGAATTCTGGTGGTTTACCCCAAGTC NM. _020738 4.15E- •12
57 N0TCH2 GGCCCCCACTAATAAGTGGTACTATGGTTACTTCCTTGTGTACATTTCTCTTAAAAGTGA NM. _024408 1.40E- -11
58 RUNX2 GCCCAGAATCCAGGTTAATACATGGAAACACGAAGCATTAGCAAAAGTAATAATTATACC NM. _004348 2.51E- -13
59 LAIR1 G G G G C AGTTG CT AATTT AGTT TAG G CA AACGTG G AC ACATTAA ATTCTCCTACA AACCC NM. _002287 1.89E- -12
60 FAM114A1 AGGTCCTTAACCCCATGATCAGTAGTGTATTGTTAGAGGGCTGCAACAGTACAACGTACA NM. ,138389 1.03E- -11
61 CHD3 CTGTCCTGATCCCCTCTTCTGTATCAGGTTTATTGGTTGTACATATAAATTATACTTTCC NM. ,001005271 1.52E- -11
62 CFH TTGGATTAATTTGTGAAAATGTAATTATAAGCTGAGACCGGTGGCTCTCTTCTTAAAAGC NM. ,000186 5.68E- -12
63 CD68 G G GT ACCCTTATTTCCTCG AC ACG C A ACTG G CTCA AAG AC A ATGTT ATTTTCCTTCCCTT HD_8pack_Dx_3486 1.57E- -11
64 OPTN AACACTGGACCAGCTGTAAAAGTAAACAGTGTGTTTATGCATTGAGATACTAAAGCATTT NM. ,001008211 7.01E- -13
65 PLD2 CTGCTGACAGACACTAACTTTGTATCCGTTCAATAAGCATTTCATAAATAAAGGTGTAGA NM. ,002663 1.26E- -11
66 CCM2 TCAGAGACCTT AAA AAGAAGTTTACTGCAATGTGAAT AATTT AATCTCTGGTTGCCAAGC NM. ,001029835 3.52E- -13
67 PREX1 TGTCTAACAGGGGACCAACAGAAGGTAGTATTGACAACTGTTCCCGCTTCTACTAAAAAA HD_8pack_Dx_2290 1.06E- -11
68 SERPING1 GACAACATTTGATCCCAAGAAAACCAGAATGGAACCCTTTCACTTCAAAAACTCAGTTAT NM. ,000062 1.54E- -12
69 NR3C1 GTGAAAATGGGTTGGTGCTTCTAACCTGATGGCACTTAGCTATCAGAAGACCACAAAAAT NM. ,001018077 7.23E- -12
70 Clorf54 AGAAGGCTGCTATGACTCTTTGGATGGGAGTCTGGCAAGAGGAAATTGGAAGATAAAATA NM. ,024579 4.12E- -14
71 RNF138P1 TGCTAAGTGATCTAGTTGGCTGCTATTACACCTTAGAAATTGAGTTTACACACACACACA NR_ 001575 5.58E- ■12
72 SBN02 CG CCTG CG GTTTCTATGTATTTAT AG C AAGTTCTG ATGTAC ATATGTA AAG G ACTTTTTT NM. ,014963 1.06E- -11
73 SLC38A10 CTTGCAGTGACTCAGAATGATAATTATTATGACTGTTTATCGATGCTTCCCACAGTGTGG NM. ,001037984 4.24E- -13
74 ATL3 AGCTCAATAGCATCTTAACGTGAAGATCAAACAAGAACACAACAAGCCCCTACTGATTTC NM. ,015459 2.35E- -13
75 MTMR9L CAAAAGTACTGAGGGTCTTAAGTTTGAAGTGTCCAAAGTATAGGGAGGTCTCAATAATAA NR_ 026850 2.58E- -14
76 RAP1B GTG GTG C AATTTTGTATA ACTTAG CATC AGTAGTTCAATAA ATTTG GATTG CC ATG C AAG HD_8pack_Dx_2413 4.89E- ■12
77 CLK3 CAGAAAGCACAGATTTGACCCAAGCTATTTATATATTGTAAAGTTATAATAAAGTGTTTC NM. ,003992 8.72Ε· -12
78 PMP22 TGTG CCTCCA AG G ACTGTCTG G C AATG ACTTGTATTG G CCACCAACTGTAG ATGTATAT A NM. ,000304 1.81E- -12
79 RANBP9 G C ACCG C AC ATTTTTCAG GTTTTG A AAGTTGTAGTAATG GTGTA ATATCAA AT AAAG C AC NM 005493 1.76E- -12
80 ATP2B4 ATCCCCAAGTGAAATATGTTGCGGTAGAGATGGAATGTATAAAATCCGCCAGTAGTGTGA NM..001001396 8.38E-■14
81 PTPRC GTTGTTGTAAAGATCAACCAGCACAAAAGATGTCCAGATTACATCATTCAGAAATTGAAC NM. .002838 3.85E- ■15
82 LOC387763 ATG G CTG AAG G CATTTATTTAACG ATCTTTTTACCTG G ATATGTCTGTG AG G CTCCTG A A NM. .001145033 3.75E- -12
83 NAB2 CACCTATCTGAGCAGTTAGAGCGTCTTTCTTTTCAGATTGTGTACAGTAGATTATTTATT NM. .005967 1.07E- -11
84 IL6ST CTGGAAAACAAACCATTTTACTATTCCTAAGGAGCAATATACTATCATAAACAGAACAGC NM. .175767 4.60E- -14
85 RGAG4 ATAAG AAG CTG CTCTGTATGCTA AAG CTTTCTCTCCTC AATA AAA AT ATAAAG G GTGTGT NM. .001024455 7.33E- -12
86 DBN 1 TTGGGAAAATATCACTTTGTATTCTCTGTCCAGGGCTTCAGATATTTTGCACGAATTTTA NM. .080881 2.47E- -12
87 STOM GGGTGACATTTGTAACATTTCCTCTTTGAGACTCTGAGTTCACCTAGAGAAGTCTAAGCA M. .198194 2.44E- -12
88 ZBTB2 TTAGTATTCATCCTCCAGGTGTCTTACTTCAGAATGCATCCTTTGAGATTATGTCCACTT NM. .020861 1.23E- ■12
89 STAT2 TCCTGTTC AG AAAG G G G CTCTTCTG AG C AG AA ATG G CTAATA AACTTTGTG CTG ATCTG G NM. .005419 1.80E- -11
90 L NA TGTG G CAGTG GTTTTG G C A AACG CTAAAG AG CCCTTG CCTCCCCATTTCCCATCTG CA CC NM. .170707 6.81E- -14
91 A_32_P5086 CTGGGAAAGAAAGCTGTTATGCTTAGACTTCTCTAGGTGAACTCAGAGTCTCAAAGAGGA A_32_P5086 2.64E- -12
92 EISiTPDl TGGTTACTTCTGTAGACAAAAGAATAATGCTACTTAATCAGGCTTTCTGTGTGACAAGAA M. .001776 1.38E- -12
93 SLC38A6 ACTCATCATTTTTGATTGGATTAATAAATAAAAGAAATATTTTCCTACTTCTTACAAGAA NM. .153811 2.60E- -12
94 TFE3 GAAGCTTGGAGGAGGGTTGTAAAAGCATATTGTACCCCCTCATTTGTTTATCTGATTTTT HD_8pack_Dx_4438 1.44E- -12
95 BTN3A1 AGGCCACACTTGATAAATCATGGGGAACAGATGTGTTCCACCCAACAAATGTGATAAGTG NM. .007048 3.41E- -12
96 LY96 TGAAGCTATTTCTGGGAGCCCAGAAGAAATGCTCTTTTGCTTGGAGTTTGTCATCCTACA NM. .015364 4.33E- -13
97 ENST00000366784 TGTAATTTGTAATTCTTTAGTTTTCAAGAGGGACTCTACATGTTTCCTTGTGATGATGGC ENST00000366784 1.34E- -11
98 SPARC CCACATACCTAGATCTCCAGATGTCATTTCCCCTCTCTTATTTTAAGTTATGTTAAGATT NM. .003118 5.93E- -12
99 PDLI 7 ACACCTGCTTCGTCTGTGCGATATGTCAGATCAACCTGGAAGGAAAGACCTTCTACTCCA NM. .005451 8.76E- -12
100 ICAM 1 GAAATACTGAAACTTGCTGCCTATTGGGTATGCTGAGGCCCACAGACTTACAGAAGAAGT NM. .000201 3.02E- -12
101 RASSF4 AAGCCTTTGCGAAACTATGCAACAGTTTACATCAGTCATGTGAAGTATTTGTCTAAAACA NM. .032023 4.99E- -12
102 MSN GGAATTGTGGGGCAATCTATTAATAGCTGCCTTAAAGTCAGTAACTTACCCTTAGGGAGG NM. .002444 6.48E- -13
103 CIS G CCTTG CTAG AG GTAG AGTTTG ATCATAG A ATTGTG CTG GTCATAC ATTTGTG GTCTG AC NM. .001734 2.68E- -12
104 C5AR1 TCTCAAAAGTTCTTTGGGACAAAACAGAAGTCCATGGAGTTATCTAAGCTCTTGTAAGTG NM. .001736 4.87E- -12
105 LAT2 CCCAGAGGGACCTTGAGTCAGAAATGTTGCCAGAAAAAGTATCTCCTCCAACCAAAACAT NM. .032464 1.53E- -12
106 ABCA1 CCAAAGAGCCATGTGTCATGTAATACTGAACCACTTTGATATTGAGACATTAATTTGTAC NM. .005502 5.29E- -13
107 IGFBP7 ACCTCCAGAATATTATTAGTCTGCATGGTTAAAAGTAGTCATGGATAACTACATTACCTG NM 001553 5.95E- -14
CTCACAACGAACTGGCTGATAGTGGAATACCTGGAAATTCTTTCAATGTGTCATCCCTGG HD_8pack_Dx_1742 7.78E-12 TGGCTGAGATGATACCCGACCCTCTAGGGAAATTCTTAGAGTAACTTCTAGGAAATGTCA NR_003491 2.16E-12 G CTTATG AA ATGTCATTTAAAGTTCACTT TTG AG CATCA ATAAA AAG G G A AG CTGTGTG NM 024692 1.01E-13
Table 2: TGF beta 2 signature.
Rank
order Gene Probe sequence Transcript ID P-value
1 COL4A2 TTA A AG G CA AAACTGTG CTCTTTAT ΓΑ AAA AACACTG ATAATC AC ACTG CG GTAG GTC HD_8pack_Dx_0710 4.46E- •23
2 RNF220 GTCTGTATATTCTATACAAAGGTACTTGTCCTTTCCCTTTGTAAACTACATTTGACATGG HD_8pack_Dx_4081 1.27E- -20
3 TGFB2 TGTATTTTGATGACCAATTACGCTGTATTTTAACACGATGTATGTCTGTTTTTGTGGTGC NM_001135599 9.06E- -32
4 NC0R2 TTCG ATGCGTATTCTGTG G CCG CC ATTTG CG C AG G GTG GTG GTATTCTGTC ATTTACACA HD_8pack_Dx. _1946 4.23Ε· -21
5 AP2M1 CTTCATTTTGTACACGTGTGACTTCGTCCAGTTACAAACCCAATAAACTCTGTAGAGTGG NM_004068 2.90E- -29
6 TRIB2 ACG G CTTTTCTATTG CTGTATG AT AC AG A ACTCTTTTG G CAT AA AT ATTTGTGTTCCC AG HD_8pack_Dx_ .3092 1.83E- -21
7 DCN C ATCCACCTTCAG ATGTGTCT ACGTG CG CTCTG CCATTCAACTCG G AAACTATAAGTAAT HD_8pack_Dx_ 0829 1.45E- -20
8 VIM TGATTAAGACGGTTGAAACTAGAGATGGACAGGTTATCAACGAAACTTCTCAGCATCACG NM_003380 1.32E- -21
9 Clorfl64 TGTGATGCTGTGTCTGTATATTCTATACAAAGGTACTTGTCCTTTCCCTTTGTAAACTAC HD_8pack_Dx. _0472 1.72E- -23
10 TIMP2 GTTGAAAGTTGACAAGCAGACTGCGCATGTCTCTGATGCTTTGTATCATTCTTGAGCAAT HD_8pack_Dx_ _3011 3.98E- -24
11 HISPPD1 GTATGTAAGTTTTCTGTTTGTGAAAATGTAGTTAATGTACTCACTGTGGAGGTCATAAGG NM_015216 6.89E- -22
12 IGFBP7 TTGATGCCTTACATGAAATACCAGTGAAAAAAGGTGAAGGTGCCGAGCTATAAACCTCCA HD_8pack_Dx_ .1410 3.67Ε· -23
13 PLEKH01 CGGGTTGGACAGACTCTTATCTCCGTGTTGCTGGATAAAGCTTTTTTATTTACCTCAATC NM_016274 2.50E- -27
14 ARPC5 TG CCCTGTG G GTAG C ATCTGTTTCTCTCAG CTTTG CCTTCTTG CTTTTTCAT ATCTGT AA NM_005717 9.26E- -21
15 DCN AGCATAAGTACATCCAGGTTGTCTACCTTCATAACAACAATATCTCTGTAGTTGGATCAA HD_8pack_Dx_ 0828 2.33E- -21
16 RAP1B GTG GTG C AATTTTGTATA ACTTAG CATC AGTAGTTCAATAA ATTTG GATTG CC ATG C AAG HD_8pack_Dx_ .2413 1.20E- -28
17 SEPT11 TGCATATATCACTAGTGCCAAGACATAAAGCGGGGGAAAATATATTTTTACCCAAACATT NM_018243 2.18E- -33
18 MRC2 ATGTGAACATGGACTCGAAGACATGGCCCTTTCTCTGTAGTTGATTTTTTAAATGTGCCA NM_006039 1.42E- -25
19 MYLK GGTAAATGAGAACACTACAACTGTAGTCAGCTCACAATTTTTAAATAAAGGATACCACAG HD_8pack_Dx_ .1924 2.73E- -22
20 RBMS1 GAGGGGAAATCTGCTGCTAGAAATGTCTGAACTAAGTGCCATACTCGTCTGGGTAAGATT NM_016836 5.07Ε· -24
21 PBX1 ATGATACTAACACGGTGTAGGTTTTACAGTCTCCTAATTTGTACTGGTAATGCATATTCC NM_002585 7.79E- -21
22 CYTH3 GATGGCTGTCAGAGCTCTTGCAGATACTGTGTTCACTAAATAAAAATCACATGTATTGTT NM_004227 3.28E- -31
23 SERF2 ACCCCTTCCCAGTGTTTTTTATTCCTGTGGGGCTCACCCCAAAGTATTAAAAGTAGCTTT HD_8pack_Dx_ .2623 1.11E- -20
24 RPS6KA2 GATGGGTGGCCACTGTACAGATATTTATTACGCTTTCCAGACTTTCTGAATAGA I 1 1 1 1 1 NM..021135 1.78E- -23
25 C3orfl0 CCCCCACTTGGCTTGAAGGGACATTTTCAGAC 1 1 1 1 CTTTCTGTCACTTGGAGTGTCTAT NM. .018462 6.78E- -23
26 HTRA1 CCGAAGTTGCCTCTTTTAGGAATCTCTTTGGAATTGGGAGCACGATGACTCTGAGTTTGA HD_8pack_Dx_1383 1.02E- -20
27 CALD1 CCATGCTGTGAAATAGAGAC 1 1 1 1 CTACTGATCATCATAACTCTGTATCTGAGCAGTGAT HD_8pack_Dx_0554 2.92E- -24
28 PLDN CCCTCATACATTCGTCTGA I 1 1 I AGC I 1 1 AAGA 1 GAGAA 1 GC 1 1 1 1 1 ACACATTTAA NM_ .012388 7.67E- -25
29 PREX1 CAAAGAAAGGTATGTTGTCTAACAGGGGACCAACAGAAGGTAGTATTGACAACTGTTCCC NM. .020820 5.30E- -21
30 HTRA3 AAGGGGCATTTGTGAGCTTTGCTGTAAATGGATTCCCAGTGTTGCTTGTACTGTATGTTT HD_8pack_Dx_1384 5.23E- -24
31 TM4SF1 GACCACGAGGAAATACCCTCAAAACTAACTTGTTTACAACAAAATAAAGTATTCACTACC NM .014220 5.94E- -21
32 CTNS GATGCGAATTAGTAAAAGCTAAATTCAAAAGTAGAATGGGCATCTCCAAAGAGTACGATA NM. .004937 1.27E- -21
33 FBLN 1 G G AATG G CTG G G ATTTCTCG G C ACTCTGC ATC ATCC ATL 1 1 1 1 CTTATAGGTGGGAAAAT NM. .006486 5.04E- -23
34 YPEL5 GGGACAGAACTGCTGGGTTGTC 1 1 1 1 I CCATGTAACTTAAGCATAGTAATATAAATAAAG NM. .001127401 3.54E- -28
35 ZN F469 GGGGCCCTGAGGTTGTACTGTAAACATCATAGTGACTTGTC I 1 1 1 CAAATATATTCCCAC NM. .001127464 1.90E- -22
36 CXCR5 1 1 1 I C I 1 1 1 1 A AT AAA AAG G CACCTATAAA ACAG GTC AATACAGTAC AG GCAGCACAGAG NM. .032966 3.00E- -22
37 MRC2 G GTG CG ACAG CGTG G G ACA ATGTG AACATG G ACTCG AAG ACATG G CCCTTTCTCTGTAGT HD_8pack_Dx_1876 3.87E- -24
38 AH R CTGTTG G ACGTC AG CA AGTTC AC ATG G AG G C ATTG ATG CATG CT ATTCAC A ATTATTCCA NM. .001621 7.25E- -22
39 ITPRIPL2 TTCG I 1 1 I C I C I I GCAGGTTGGAGTAAATTTGCACTTTGAATCATGTGGGTCATTTGGGG NM. .001034841 8.04E- -28
40 DST AGGAAAAGTTTAACATGAACTAACATTTCTGCACTGTAACGTGCCGGGCACACACTAAAC NM. .015548 1.52E- -21
41 DPP8 CATGCTCAAAATCAAATGATACATATTCCTGAGAGACCCAGCAATACCATAAGAATTACT NM. .130434 8.97E- -21
42 CLC 6 CTTTGGAACTTGGGAGTTCTCATTGTAACCCTAACATGTGAGAATAAAATGTCTTCTGTC NM. .001286 4.07E- -22
43 MARS G G CTC AT AG A AAGTCACTTTAATAG AT AG G G AC AGT AATA A AT AA ATGTACA ATCTCTAT NM. .004990 1.57E- -22
44 PTRF CTTGGGGAACCTCTCACGTTGCTGTGTCCTGGTGAGCAGCCCGACCAATAAACCTGCTTT NM. .012232 5.35Ε· -25
45 RAP IB C AACTACTTTG AG GTGG CCAA ATGTA AACTAA AAG CCTTAATTAAAGTG GTG CAA 1 I M G NM. .015646 4.19E- -24
46 MAP1B CCTGTTTCCATTTGAAAGGAACTGTAAGCTTTTATCTTTTAACCAACTGAACAATACACC NM. .005909 3.34E- -24
47 CDC2L2 GCAGCCGTGGTAGTAGCTGTCTATGATTCTTGCTCAGCAAAGTAAAATAAATGTTAAATA AB007916 3.01E- -22
48 CYB5R3 AGTGACCTCGACGTTGCCTTTAGACTACAGTTGTGTTAGCCTCTTGCGTATTGGC 1 1 1 1 1 NM. .007326 1.25E- -27
49 SPOCK1 C 1 1 1 1 1 CTCAAAGTCACTGATGTTTGTTCCTGTTAAATGTATAGCATTGTAATGAGAGCC HD_8pack_Dx_2794 1.34E- -20
50 NOTCH4 CACTGCTATCGCTATTTAAGAACCCTAAATCTGTCACCCATAATAAAGCTGATTTGAAGT NM. .004557 4.66E- -23
51 ENST00000369739 TGGTGCCTAAGAGAGCTATATATATACACATGTAAAGTCCATTG 1 1 1 1 1 ATTGTCCTGAG ENST00000369739 5.49E- -21
52 BCAR1 GAAGAACCTGAAGAACTATTTTTCGTTATTGGTTTTCCAATCATTTGACTAAGAGTCTCC NM. _014567 2.72E- -28
53 RHOQ G GTG GTTC AC ATTA AAGT ATC ATG G CCTTATGT ATG CTC AAATG G A ATCTT ATGTA ACTT NM. _012249 1.20E- -20
54 PPP1R12C GGGGGAGAAGGTATTTTCGAGATAAAGCACAGGCACCACAAATAAAAGTCGTGAAGTTGC NM. _017607 2.69E- -21
55 DEGS1 ACTGCTGAATCCTGTACAGCCTTACTCATAAATAAAGTACTTACTGAATTTCCACCATTC NM. .003676 3.83E- -21
56 TMEM175 GTTCTTG CGTG G CCTG GTTTTATTTTCATTGTG A AATATCATG CTCTTATTTCAGTC TC NM. .032326 1.78E- -21
57 SIDT2 TCTTTTCTCAGAGCGTCTCCATGCTATGGTTGCATTTCCGTTTTCTATGAATGAATTTGC NM. .001040455 2.69E- -22
58 PHC3 GGGTCTGGATGGAAGATTAGTGGGCCTACAGGATCATTTATTTATATTGTTTATATTACA NM. .024947 1.95E- -20
59 PANX1 GAATTGAGGCCATTTGGGAAGAAAATTCTAGCACTGGTGGAGAATTATAGAATAAAGATT NM. .015368 1.88E- -20
60 S1PR3 GCTGCAGAGAAACTATGCATTAGGTCTCTTTTCAATTAGAAACCTTTACTATTTCCAATG NM. .005226 4.95E- -28
61 FERMT2 GAGAGGTGGATTACCAGTATTGTTCAATAATCCATGGTTCAAAGACTGTATAAATGCATT NM. .001134999 3.06E- -27
62 PXDN GTTTGCACTTTGTAATGATGCCTTTCAGTTCAAATAAATGGGTCACATTTTCAAATGGAG NM. .012293 5.40E- -24
63 LPP GTGACTGATCTAGTTTTCTCAGCTGTATGCAAAGTAATCTTTCAAAGACTAGGTTAAGAT NM. .005578 1.40E- -23
64 TTBK2 ACATATGTG CTTT TGTTTG ACCTTGTGTTTG CTG CCA A ACCTAATAC AGTTG AATTG G G NM. .173500 1.71E- -21
65 TRIP12 TTTG CTGTGTG A AATTTAAA AAAG G G ATGTTTTTCCAG G CTG G AACA ATAA ATGTG G CTG NM. .004238 1.37E- -20
66 NIDI CAGATTTGTACAAGTATTGGATGATTCCTTGAGTTTACAGCTGTACAAATAGTGTGGAAA NM. .002508 9.62E- -21
67 LUM CTCACAACGAACTGGCTGATAGTGGAATACCTGGAAATTCTTTCAATGTGTCATCCCTGG HD_8pack_Dx_1742 2.66E- -23
68 GJC1 TGCTCAGGGCCTTGTCTCTAGGAAGATTTTGTCAATTCCAAATACAGTTTTGAAGATTCA NM. .005497 5.83E- -21
69 MAP3K1 CCAG G G CTTA AG G G CT AACTTCT ATT AG C ACCTT ACTGTGTA AG C AA ATGTTAC A AA AA A NM. .005921 4.11E- -26
70 TIMP2 TGCTTTGTATCATTCTTGAGCAATCGCTCGGTCCGTGGACAATAAACAGTATTATCAAAG NM. .003255 8.18E- -31
71 JDP2 GGGGTGCATTTCCATCCTTGTAAACCCTTCATAGTACTCAGTCCTGTATCGCTCAGTAAA NM. .130469 3.30E- -23
72 ADPRH GGGGAAGAGATAAACTTTATGCATAACATTAGGGTAAATCAATAAAGATGGTCTGACACA NM. .001125 1.15E- -20
73 PDLI 5 GAGAGCCTTCTCAGACATGAAGCAAGGGAAACATACTGAATAGTTTTACACAAATTTGAT NM. .006457 9.86E- -23
74 CALD1 TTCCTTGTTTACTGGTTTGACTATAATTCTCTGTTATCTTTACGAGGTAAAACTGCAAGC NM. .033138 1.73E- -23
75 ZFP36L1 CACACATTAAGATGAATGTAATTATTATTCCTCTTGCTGGTCACTACCGTCGCTTTCTAT NM. .004926 1.43E- -20
76 C6orf62 TCCTTTGGAGTAAAACTAGTGCTTACCAGTTTCCAATTGTATTTAGCTTCTGGTTGGAAT NM. .030939 3.59E- -21
77 NUCKS1 AAGCAAACCATTGTATGTGTAAGTGTTTAAGTTACCTTTTTGTCTATTGGTCTCTTTGCC NM. .022731 8.82E- -22
78 SMARCC2 C AAG GTTCTATTAACC ACTTCTA AG G GTACACCTCCCTCCAA ACTACTG CATTTTCTATG NM. .139067 3.48E- -21
79 TMEM30A CCCATGCACCATTCAGTAAACATAAAAATCACAATTCTGCTAATGTCATTTGGAACTTCA NM 018247 3.62E- -24
80 PPIC TAAAAATCAAACCGTCACCCTTTAGTTTGCTTGAACTTTAGTAAACCACCTGCTTAGGGA NM_ _000943 6.10E-27
81 MTR TTATTCAGTAGTGGAAATGAGTGAACTACAGCTATACCTCACAATAAGAATGAATCTCAG NM. _000254 1.08E-20
82 RAB12 CTTGAGTGTTGTGGTATGAAAAGCATTGTGGTCTTTCTACACTAATGAAGTGCAAATAAA NM. _001025300 3.54E-24
83 TCF4 AGACGCATCGAATCACATGGGACAGATGTAAAAGGGTCCAAGTTGCCACATTGCTTCATT NM. _003199 4.90E-22
84 ZC3H 14 GATTAATGCAAAAGGGGTAATAAAGACTGCAACATTCTCAGGACCAAATTAAACTGCTAA M _024824 7.49E-22
85 NCRNA00201 CTGTTG G AAG AG ACA AAATGTG ACTTG GTTCATA ATAAAG CA AG AATTATTT ACTCTCG G R_ 026778 4.17E-24
86 CIS TGTAG ATGTCCCTTGTAG CC ACTTCTG C A AC A ATTTC ATTG GTG GTT ACTTCTG CTCCTG NM. _201442 2.20E-23
87 COL6A1 ATAGTGATGTGTTCGACGTTTTATCAAAGGCCCCCTTTCTATGTTCATGTTAGTTTTGCT NM _001848 1.25E-22
88 CD63 TC AG CCTCCTC ATCTG G G G G AGTG G AATAGTATCCTCC AG GTTTTTCA ATT AA ACG G ATT HD_8pack_Dx_0622 2.772
89 MAP3K3 TG C AGTG C AAAG CC AG G CC AGTGTTGCG C ATT ACTTACAATA AA AG G G ATC ATTTATATC NM. _203351 2.10E-23
90 MGRN 1 C AG ATG G G CTCATCGTTG GTTCGTTTTTACTGTATATTT ATAGTA ATAAA ATC ATG C AG C NM. _015246 1.90E-22
91 COL3A1 ACTTCAACACTCTTTATGATAACAACACTGTGTTATATTCTTTGAATCCTAGCCCATCTG NM. _000090 2.28E-24
92 C20orfl94 ATTTACCTTGGTAATCGAGATGTCATGCTAAGGACCAATAAACTATCACTGAACAAGCAA NM. _001009984 9.60E-31
93 TUBB6 AAG CCTG AAATTGTG CCGTGTTG CCTTATATG AATATG CAGTATG G G ACTTTG A AATAAT NM. _032525 1.20E-25
94 PREX1 TGTCTAACAGGGGACCAACAGAAGGTAGTATTGACAACTGTTCCCGCTTCTACTAAAAAA HD_8pack_Dx_2290 7.27E-22
95 SERINC1 CAGGTCAGAAGAATGATGGAATGTTTTAGAATAAACTCCTGCTTATAGTATACTACACAG NM. _020755 3.34E-21
96 OPTN AACACTGGACCAGCTGTAAAAGTAAACAGTGTGTTTATGCATTGAGATACTAAAGCATTT NM. _001008211 1.93E-20
97 CCM2 TCAGAGACCTTAAAAAGAAGTTTACTGCAATGTGAATAATTTAATCTCTGGTTGCCAAGC NM. _001029835 3.01E-23
98 SEC13 ATGTTC A AATCTATTTTG G GTCATTTTTATGTACCTTTG G GTTCAG G CATTATTTG G GG G NM. _183352 1.00E-24
99 DSTN GCTAGGACACCTGTGGTATCTTTAATTGTATCTCCTTCAGAAGTTTGCTTCTTATGGTAT NM. _001011546 5.84E-21
100 SPON2 GCGGTTTCGGAAGCGTCAGTGTTTCCATGTTATGGATCTCTCTGCGTTTGAATAAAGACT NM. _012445 2.48E-32
101 YTHDF3 CCAAACTCACCATTTGGTCCTCTTTAATCTTTGAGGGTTTCAATAAAAATTGTTCACTCA NM. _152758 4.56E-21
102 NR3C1 GTGAAAATGGGTTGGTGCTTCTAACCTGATGGCACTTAGCTATCAGAAGACCACAAAAAT NM. _001018077 1.52E-25
103 LUC7L3 G ACTAAGTG G G ATTTC ATTTTTACAACTCTG CTCTACTTAG CCTTTG G ATTTAG AAGTAA NM. _016424 1.38E-21
104 MGP T ACTG AAATACATAG G CTTATATACAATG CTTCTTTCCTGTATATTCTCTTGTCTG GCTG NM. _000900 1.71E-24
105 Clorfl52 TCT ATC ATTCCG CGTTTG G G CT ATTACG A AG A AACTATC ATG AG C ATCC AT ACGTG G C AG NR_ 003242 3.66E-21
106 ARHGAP1 CCAGTGTTCACATTCACACTTAATGACTTCCTTGGCACCAATCATGTATTTCACCGTTTG NM. _004308 5.20E-29
107 YLPM1 CTAGGATTAAAAACAATAAACTTTCATGATAAAGCCGATGAGATTCATGGGCTATACAGC NM 019589 1.10E-20
108 SBN02 CG CCTG CG GTTTCTATGTATTTAT AG C AAGTTCTG ATGTAC AT ATGTA AAG G ACTTTTTT NM_ _014963 1.72E- -24
109 C5orf24 GTCCATTTATTAGGTTAAAGTTGACCCATTCAGTGTAAAAATAACCATAGTGTGTGAGCT NM. _001135586 4.76E- -26
110 PLAT TGAACAACTAGGCTTCAGCATATTTATAGCAATCCATGTTAGTTTTTACTTTCTGTTGCC NM. _000930 8.50E- -22
111 ATL3 AGCTCAATAGCATCTTAACGTGAAGATCAAACAAGAACACAACAAGCCCCTACTGATTTC NM. _015459 9.93E- -21
112 THY1 TTATG G C ATCTC ATTG AG G AC AA AG A AA ACTG CAC AATAA AACC A AG CCTCTG G AATCTG M _006288 4.83E- -33
113 TXLNA C AG CCAG G G ACTTG ATTTTG ATGTATTTTA AACC AC ATTAAATA AAG AGTCTGTTG CCTT NM. _175852 1.47E- -20
114 PSMD4 G C ACG G AATATAGG GTTAG ATGTGTGTT ATCTGTA ATC ATTATAG CCT AA ATA A AG CTTG NM. _002810 2.63E- -21
115 PCBP4 AG G G G CCCAGTTCTC AG CAG CAG ACACTCTGTAC AGTTTTTTCAATCCCTGTTTTTG AAT NM. _033010 4.37E- -22
116 LOC399959 TATGTGACTTTGTCATATGTTCCTAACCCCCAATAAAAGCAATGTTGCATCAACTGTGAA NR_ 024430 1.06E- -22
117 BNIP2 GTGCTGTTTTGGATAACACGTTTGTTACAAGCATTTAAACTGTTTCATTTGGTAGTACCT NM. _004330 1.18E- -23
118 CBX6 GTGTCATTCGTGACTTTTTTGTAAAGAAGTTGTGTTTTCAGAGGTGATTTTATGACAGGA NM. _014292 2.78E- -21
119 MFAP4 A AATT AC ACCTG G AGTC AG GTG CAG AAG G G AACCTTGTATTTC AC AG G CCTC ATTTTG AT NM. _002404 9.20E- -23
120 IL6ST CTGGAAAACAAACCATTTTACTATTCCTAAGGAGCAATATACTATCATAAACAGAACAGC NM. _175767 1.00E- -23
121 RGAG4 ATAAG A AG CTG CTCTGTATGCTAAAG CTTTCTCTCCTC A ATAAA AATATA AAG G GTGTGT NM. _001024455 6.51E- -21
122 STOM GGGTGACATTTGTAACATTTCCTCTTTGAGACTCTGAGTTCACCTAGAGAAGTCTAAGCA NM. _198194 1.58E- -24
123 TRIM8 GGGCAGTTTGATCACTGATCGAGTAAGGAATGACCTTTAGATTGTGCGACTTTTGTTTTT NM. _030912 3.49E- -22
124 MXRA7 TGGCTTGGATCTCTGTATTCAGCCTTTGTTCAGTCCAATAAACTTTGAGTAGATGATCTC NM. _001008529 5.12E- -30
125 PHF2 TCGTGGCTATTAAAGTGTTTTATTTCCCAATTCATATTACTCTTGTATCGAGTCCATGAG NM. _005392 1.20E- -20
126 A_32_P5086 CTGGGAAAGAAAGCTGTTATGCTTAGACTTCTCTAGGTGAACTCAGAGTCTCAAAGAGGA A_32_P5086 3.11E- -25
127 RTN4 ATTTTACTTTGTTGCAGATAGTCTTGCCGCATCTTGGCAAGTTGCAGAGATGGTGGAGCT NM. _020532 5.35E- -23
128 GPX8 TAACTCCTGATCATCTTACAGCAGACATAACAACAGAGTGTTAGAGACTGGAATAAATAT NM. _001008397 5.69Ε· -21
129 CREB3L2 CAGCAGTGTTTAAATCTAAATACGTTGTGAGTCTGTTATCTGTCCTATCGCGTTTTTTAA NM. _194071 1.99E- -21
130 SIN3B G G G G CTTGTCCTTCCTTTG CAG CTGTTTTG A ATGT AGTTTTCCTTTTCT ATTTATTTG C A NM. _015260 1.66E- -26
131 NDST1 CCTTCCTCCATTAATGTACAATCTCGAACTAACTGCTAATAAAGTGGGGTTCTGTTTGTA NM. _001543 3.81E- -29
132 TSHZ3 TTTGGTTGTTGACAATGAAGCACCATTATGTGACTCTTCATATAACCCTTTTTTCTACGG NM. _020856 8.85E- -26
133 PALM ACGAGGCCCCCGATGTTCTTGATTTTCCCAGAGAAGCAAATAAACAGCGTGAACAGCCCC NM. _002579 2.25E- -21
134 APP CAGGATGATTGTACAGAATCATTGCTTATGACATGATCGCTTTCTACACTGTATTACATA NM. _000484 1.17E- -21
135 SPARC CCACATACCTAGATCTCCAGATGTCATTTCCCCTCTCTTATTTTAAGTTATGTTAAGATT NM 003118 1.61E- -32
136 MGP GGGTCAAAGGAGAGTCAACATATGTGATTGTTCCATAATAAACTTCTGGTGTGATACTTT NM. _000900 4.49E-21
137 MRVI1 GCATTGAACTGTAGAGTGTCACATACCTGAGTTTGAAAATAAAAGCACATTTCCAAACCT NM. ,001100163 3.11E-25
138 ARPC5 GCAAACTGGTGCAGAAATTCTATAAACTCTTTGCTGTTTTTGATACCTGCTTTTTGTTTC NM. _005717 2.53E-23
139 NFE2L1 GTTCTCTTTGCCATAAAGACTCCGTGTAACTGTGTGAACACTTGGGATTTTTCTCCTCTG NM. .003204 4.04E-21
140 ZEB1 CATCATGGTCA I 1 1 I C I A I 1 1 1 1 1 ACCAGACTCCCATCTCACAATAAAATGCATCAACA M. .001128128 4.68E-21
141 IGFBP7 ACCTCCAGAATATTATTAGTCTGCATGGTTAAAAGTAGTCATGGATAACTACATTACCTG NM. .001553 3.40E-34
142 STAT5B GCAGAGTTACAGTCACAAAGTTGTGTA 1 1 1 1 ATGTTACAATAAAGCCTTCCTCTGAAGGG NM. .012448 1.37E-24
143 CLIP4 GCTTATGAAATGTCATTTAAAGTTCACTTCTTGAGCATCAATAAAAAGGGAAGCTGTGTG NM. .024692 7.58E-27
144 DKK3 GGTAATTGTAGGGCGAGGATTATAAATGAAATTTGCAAAATCACTTAGCAGCAACTGAAG NM 015881 7.60E-21
Table 3: TGF beta 3 signature.
Rank
order Gene Probe sequence Transcript ID P-value
1 MEG3 TTCC AA AG C AC AG G G CTTGG CG CACCCCACTGTG CTCTCAATA AATGTGTTTCCTGTCTT HD_8pack_Dx_1810 1.68E- •16
2 C0L1A1 GGTGGGAGGAAGCAAAAGACTCTGTACCTATTTTGTATGTGTATAATAATTTGAGATGTT _000088 1.42E- •15
3 SLC39A13 AAGTGGCCATCGAGAGGTCTGGATGGTTTTATAGCAACTTTGCTGTGATTCCGTTTGTAT NM_152264 1.11E- ■15
4 ADAM12 AATCTTGGTTTGCCTTCCAGAAAACAAAACTGCATTTCACTTTCCCGGTGTTCCCCACTG HD_8pack_Dx_0069 6.47E- ■16
5 DCN TATTTGACTTTATGCTAGAAGATGAGGCTTCTGGGATAGGCCCAGAAGTTCCTGATGACC NM_133507 3.35E- -24
6 L0XL1 TG AG ATG C A AC ATTC ACT AC AC AG GTCG CT ACGTTFCTG CA AC AA ACTG C AA AATTGTCC NM_005576 2.89E- -17
7 PECAM1 TTCAAAGGCTTGTAGTTTTGGCTAGTCCTTGTTCTTTGGAAATACACAGTGCTGACCAGA _000442 1.18E- •15
8 FN1 TACAACCAGTATTCTCAGAGATACCATCAGAGAACAAACACTAATGTTAATTGCCCAATT HD_8pack_Dx_1148 3.54E- -17
9 CRISPLD2 GCTACCAACACTTACCCTGTGTTTAAAAAGATCTTGTACCAAGCCAACGGCGTTCCTGGC HD_8pack_Dx_0752 2.98E- ■16
10 TRIB2 ACG G CTTTTCTATTG CTGTATG ATACAG A ACTCTTTTG G CATA AATATTTGTGTTCCCAG HD_8pack_Dx_3092 1.89E- -19
11 DCN CATCCACCTTCAGATGTGTCTACGTGCGCTCTGCCATTCAACTCGGAAACTATAAGTAAT HD_8pack_Dx_0829 7.15E- -25
12 VIM TGATTAAGACGGTTGAAACTAGAGATGGACAGGTTATCAACGAAACTTCTCAGCATCACG NM_003380 1.77E- -21
13 KLF9 AAGAAGAAAGCCCTTCACCATTGTGGAATGATGCCCTGGCTTTAAGGTTTAGCTCCACAT NM_001206 7.21E- -18
14 ClOorflO TGTGTTTTCTCTGGAGATAGAATGTAAACCATATTAAAAGGAAAAAGTTTCAGACAAGCA NM_007021 4.43E- -20
15 TIMP2 GTTG AAAGTTG AC AAG CAG ACTG CG C ATGTCTCTG ATG CTTTGTATCATTCTTG AG CAAT HD_8pack_Dx_3011 1.90E- -22
16 PLXDC2 GAAGGCTTTATTGTATCAGAGCAGTGCTAAAATTTCTAGGACAGAACAACACCAGTACTG NM_032812 2.93E- -17
17 IGFBP7 TTG ATG CCTTACATG AA AT ACCAGTG A AAA AAG GTG AAG GTG CCG AG CTATAAACCTCC A HD_8pack_Dx_1410 2.63E- •18
18 PIM1 GCCTGCTGGTTTTATCTGAGTGAAATACTGTACAGGGGAATAAAAGAGATCTTATTTTTT NM_002648 7.84Ε· •16
19 PLEKH01 CGGGTTGGACAGACTCTTATCTCCGTGTTGCTGGATAAAGCTTTTTTATTTACCTCAATC NM_016274 1.60E- -19
20 TGFB3 GTCTG G G ATT AAG G G CA AATCTATTACTTTTG CAA ACTGTCCTCTACATCA ATT AACATC HD_8pack_Dx_2908 1.27E- -27
21 DCN AGCATAAGTACATCCAGGTTGTCTACCTTCATAACAACAATATCTCTGTAGTTGGATCAA HD_8pack_Dx_0828 1.76E- -25
22 RAP1B GTG GTG C A ATTTTGT AT AACTT AG C ATCAGT AGTTC A AT AA ATTTG G ATTG CC ATG C AAG HD_8pack_Dx_2413 3.00E- -16
23 SEPT11 TG C ATATATCACTAGTG CC AAG ACATA AAG CG G G G G AA AATATATTTTT ACCCAA ACATT NM 018243 1.78E- -18
24 MRC2 ATGTGAACATGGACTCGAAGACATGGCCCTTTCTCTGTAGTTGATTTTTTAAATGTGCCA N _006039 2.14E-■22
25 PTGIS TTGTTATGCCTTGCTATTTTAATAAAGATTCTATTTTCGTATAACATTGTCAAGTGGAAA NM_000961 4.11E- •19
26 RBMS1 GAGGGGAAATCTGCTGCTAGAAATGTCTGAACTAAGTGCCATACTCGTCTGGGTAAGATT N _016836 1.25E- -21
27 CYTH3 G ATG G CTGTCAG AG CTCTTG CAG AT ACTGTGTTC ACT AAATA AA AATC AC ATGTATTGTT NM_004227 3.21E- -21
28 RPS6KA2 GATGGGTGGCCACTGTACAGATATTTATTACGCTTTCCAGACTTTCTGAATAGATTTTTT N _021135 3.31E- -17
29 IGFBP4 GAAAAATCTCATTCCCAGAGTCAGAGGAGAAGAGACATGTACCTTGACCATCGTCCTTCC HD_8pack_Dx_4217 5.43Ε· -18
30 HTRA1 CCGAAGTTGCCTCTTTTAGGAATCTCTTTGGAATTGGGAGCACGATGACTCTGAGTTTGA HD_8pack_Dx_1383 7.99E- -23
31 CALD1 CCATGCTGTGAAATAGAGACTTTTCTACTGATCATCATAACTCTGTATCTGAGCAGTGAT HD_8pack_Dx_0554 2.58E- -15
32 HTRA3 AAG G G G C ATTTGTG AGCTTTG CTGTA AATG G ATTCCC AGTGTTG CTTGTACTGT ATGTTT HD_8pack_Dx_1384 1.40E- -15
33 PLDN CCCTCATACATTCGTCTGATTTTGAGCTTGTAAGATGAGAACTGCTTTTTACACATTTAA N _012388 5.52E- -16
34 PREX1 CAAAGAAAGGTATGTTGTCTAACAGGGGACCAACAGAAGGTAGTATTGACAACTGTTCCC N _020820 1.29E- -16
35 HIF1A TAAGCATTGTGAAGGAAGATTAATATAGCCAAATAACTAGAGTGATCAGTTCTACCAGAG HD_8pack_Dx_1319 8.22E- -16
36 CYP1B1 CTGTGTTTATATGGAAGAAAGTAAGGTGCTTGGAGTTTACCTGGCTTATTTAATATGCTT NM_000104 1.36E- -17
37 FBLN1 GGAATGGCTGGGATTTCTCGGCACTCTGCATCATCCATCTTTTCTTATAGGTGGGAAAAT N _006486 1.12E- -23
38 CYBRD1 CCCTCATTTTTTGGATAGTCACCAGACCGCAATGGAAACGTCCTAAGGAGCCAAATTCTA N _024843 7.41E- -17
39 YPEL5 G G G AC AG A ACTG CTG G GTTGTCTTTTTCCATGTAACTTAAG CATAGTAATAT AAATA AAG N _001127401 3.57E- -16
40 ZNF469 GGGGCCCTGAGGTTGTACTGTAAACATCATAGTGACTTGTCTTTTCAAATATATTCCCAC N _001127464 2.39E- -19
41 Contig54847_RC TGTG GTATATGTGTG CAA AT AAG G AC ATT ATG A AG CTTA A AT ATG G AATGTCTCTTG G AC HD_8pack_Dx_4499 5.66E- -20
42 MRC2 GGTGCGACAGCGTGGGACAATGTGAACATGGACTCGAAGACATGGCCCTTTCTCTGTAGT HD_8pack_Dx_1876 1.42E- -20
43 CTSF CCTCTCCATGTCCAGGAAACTTGTAACCACCCTTTTCTAACAGCAATAAAGAGGTGTCCT HD_8pack_Dx_0791 7.60E- -17
44 AHR CTGTTGGACGTCAGCAAGTTCACATGGAGGCATTGATGCATGCTATTCACAATTATTCCA N _001621 1.61E- -16
45 AEBP1 ACAGTAGAGACCTACACAGTGAACTTTGGGGACTTCTGAGATCAGCGTCCTACCAAGACC N _001129 3.89Ε· -16
46 ITPRIPL2 TTCGTTTTCTCTTGCAGGTTGGAGTAAATTTGCACTTTGAATCATGTGGGTCATTTGGGG NM_001034841 9.58E- -18
47 CSPG2 GAGGCGCTGATCCCTAAAATGGCGAACATGTGTTTTCATCATTTCAGCCAAAGTCCTAAC HD_8pack_Dx_0767 2.86E- -17
48 PTRF CTTG G G G A ACCTCTC ACGTTG CTGTGTCCTG GTG AG CAG CCCG ACC AATA AACCTG CTTT NM_012232 1.51E- -20
49 GGT5 TCCCACCCTCTCGATCTGTATATCCTCCAGTCCAAGATTAAAGAGGCGGACTGTGGCCTG N _001099781 3.55E- -18
50 GLIl ATGTATAGTCTGTATACGTTTTGAGGAGAAATTTGATAATGACACTGTTTCCTGATAATA N _005269 6.78Ε· -16
51 MAP1B CCTGTTTCCATTTGAAAGGAACTGTAAGCTTTTATCTTTTAACCAACTGAACAATACACC N 005909 5.91E- -20
52 DNAJB4 TTCTTTTGAGGGTTCATTAAATTGCATGAATAGAGACGGGTCAAATAAATAGGCAAAAGG N _007034 8.51E-■18
53 CYB5R3 AGTGACCTCGACGTTGCCTTTAGACTACAGTTGTGTTAGCCTCTTGCGTATTGGCTTTTT NM_007326 2.09E- ■17
54 SP0CK1 CTTTTTCTCAAAGTCACTGATGTTTGTTCCTGTTAAATGTATAGCATTGTAATGAGAGCC HD_8pack_Dx_2794 8.45E- •16
55 RHOQ G GTG GTTCACATTAA AGTATC ATG G CCTTATGTATG CTCAA ATG G AATCTTATGT AACTT NM_012249 9.81E- ■16
56 CLDN11 ACTGATGGTGCATTTTATTCTTGAAGTGAAATCTGTGCAATAAAATAACAGACTGTCTGC N _005602 3.08E- •17
57 FBLN5 GGGAACCCTGGGAGTAGCTAGTTTGC ITGCGTACACAGAGAAGGCTATGTAAACAAA N _006329 6.76E- •17
58 UGCG AATGG1 GTGCAGTGAACAACACATGGCGAGGTACTAACTGAGAAACT TCATGCT ENST00000374279 3.25E- ■16
59 FERMT2 GAGAGGTGGATTACCAGTATTGTTCAATAATCCATGGTTCAAAGACTGTATAAATGCATT NM_001134999 9.72E- ■20
60 PXDN GTTTGCACTTTGTAATGATGCCTTTCAGTTCAAATAAATGGGTCACATTTTCAAATGGAG NM_012293 3.14E- ■16
61 GRASP GGGGTGGGGACAGCACAGACTGTTCCACCGTTGTGCATATTGTTGCTTCTGAACCACAAA N _181711 4.18E- •16
62 SHANK3 GTTTGGAGTCTGGACTAAGCTCCATCCACGTCACTCACAAGTTTCTGTTTATATTTCTAG N _001080420 3.79E- •16
63 AEBP1 CATTCCCCTTCACAACAGTAGAGACCTACACAGTGAACTTTGGGGACTTCTGAGATCAGC HD_8pack_Dx_0087 6.44E- ■17
64 LUM CTCACAACGAACTGGCTGATAGTGGAATACCTGGAAATTCTTTCAATGTGTCATCCCTGG HD_8pack_Dx_1742 5.37E- ■23
65 EFEMP2 TTTGGATAAGCCCTAGTAGTTCCCTGGGCCTGTTTTTCTATAAAACGAGGCAACTGGACT N _016938 7.51E- •20
66 TIMP2 TGCTTTGTATCATTCTTGAGCAATCGCTCGGTCCGTGGACAATAAACAGTATTATCAAAG N _003255 9.96E- •25
67 CALD1 TTCCTTGTTTACTGGTTTGACTATAATTCTCTGTTATCTTTACGAGGTAAAACTGCAAGC N J 3138 2.79E- •17
68 ZFP36L1 CACACATTAAGATGAATGTAATTATTATTCCTCTTGCTGGTCACTACCGTCGCTTTCTAT N _004926 6.86E- ■16
69 VCAN ACTTCCTGTGCCTTTCCTATCACCTCGAGAAGTAATTATCAGTTGGTTTGGATTTTTGGA NM_004385 8.07E- ■16
70 MTR TTATTCAGTAGTGGAAATGAGTGAACTACAGCTATACCTCACAATAAGAATGAATCTCAG N _000254 7.52E- •16
71 CPXM2 TTATCTTGCAAGAAAAAAGTATGTCTCACTTTTTGTTAATGTTGCTGCCTCATTGACCTG NM_198148 3.82E- ■17
72 TCF4 AGACGCATCGAATCACATGGGACAGATGTAAAAGGGTCCAAGTTGCCACATTGCTTCATT N _003199 4.47E- •18
73 L CD1 AGGAGCAGGCTGGGATCCCAACTATCGCTTGTTGCCTCTTTTTCAAGTGGAATTTGAATT N _014583 2.77E- ■16
74 THY1 TGCCTGAAGACCCCAGATGTGAGGGCACCACCAAGAATTTGTGGCCTACCTTGTGAGGGA HD_8pack_Dx_3007 5.09E- ■17
75 ACTA2 ATCATGAAGTGTGATATTGACATCAGGAAGGACCTCTATGCTAACAATGTCCTATCAGGG HD_8pack_Dx_0063 7.28E- ■17
76 CIS TGTAGATGTCCCTTGTAGCCACTTCTGCAACAATTTCATTGGTGGTTACTTCTGCTCCTG NM_201442 5.42E- ■20
77 COL6A1 ATAGTGATGTGTTCGACGTTTTATCAAAGGCCCCCTTTCTATGTTCATGTTAGTTTTGCT N _001848 1.02E- •18
78 LAIR1 GGGGCAGTTGCTAATTTAGTTCTAGGCAAACGTGGACACATTAAATTCTCCTACAAACCC N _002287 6.00E- •17
79 MAP3K3 TG C AGTG CAA AGCCAG G CC AGTGTTG CG C ATTACH AC AATAAAAG G G ATCATTT ATATC N 203351 1.63E- ■16
80 EFEMP1 AGGCAGCCATCATAACCATTGAATAGCATGCAAGGGTAAGAATGAGTTTTTAACTGCTTT N _004105 1.09E- -21
81 LOC387763 ACCTGGATATGTCTGTGAGGCTCCTGAAAGGAGACAAATAAAGTCAATATATTTGCACAA HD_8pack_Dx_1672 2.84E- ■17
82 COL16A1 TGGATGAAAGACTCCGTTGGGAATAAATGGCCAAAGCTTATAGGACTCTGTGACAGGTTG N _001856 1.47E- -16
83 CFH TTGGATTAATTTGTGAAAATGTAATTATAAGCTGAGACCGGTGGCTCTCTTCTTAAAAGC NM_000186 4.11E- -17
84 COL3A1 ACTTCAACACTCTTTATGATAACAACACTGTGTTATATTCTTTGAATCCTAGCCCATCTG N _000090 6.13E- •20
85 C20orfl94 ATTTACCTTGGTAATCGAGATGTCATGCTAAGGACCAATAAACTATCACTGAACAAGCAA N _001009984 1.80E- •20
86 TUBB6 AAGCCTGAAATTGTGCCGTGTTGCCTTATATGAATATGCAGTATGGGACTTTGAAATAAT NM_032525 5.25E- -21
87 PREX1 TGTCTAACAGGGGACCAACAGAAGGTAGTATTGACAACTGTTCCCGCTTCTACTAAAAAA HD_8pack_Dx_2290 1.40E- -16
88 THBS2 GGTCTATTTGTCTTCTCTCAAGAAATGGTCTATTTCTCAGACCTCAAGTACGAATGCAGA NM_003247 3.97E- ■16
89 KLF2 GAGACAGGTGGGCATTTTTGGGCTACCTGGTTCGTTTTTATAAGATTTTGCTGGGTTGGT N _016270 1.93E- -16
90 SPON2 G CG GTTTCG G AAG CGTC AGTGTTTCCATGTT ATG G ATCTCTCTG CGTTTG AATA AAG ACT N _012445 1.60E- -17
91 NR3C1 GTGAAAATGGGTTGGTGCTTCTAACCTGATGGCACTTAGCTATCAGAAGACCACAAAAAT N _001018077 1.78E- ■20
92 A_32_P138178 AGATTTGCCCTTAATCCCAGACAGTATGAGATACAATTCTGGGACTTTGTCTTCGTAACC A_32_P138178 1.07E- ■24
93 MGP TACTG A AATAC AT AG G CTT ATATACA ATG CTTCTTTCCTGTATATTCTCTTGTCTG G CTG N _000900 9.33E- -27
94 JAM2 GCCTTGGTGTATGCTATGCTCAGAGGAAAGGCTACTTTTCAAAAGAAACCTCCTTCCAGA HD_8pack_Dx_1479 1.13E- -15
95 ARHGAP1 CCAGTGTTCACATTCACACTTAATGACTTCCTTGGCACCAATCATGTATTTCACCGTTTG N _004308 1.16E- -15
96 WTIP GCTCCACGACAAAAGGACAAGATTTGACTTAAATTAAGTTTTTCCCTTGAGGATATTTTC N _001080436 2.83E- ■16
97 Clorf54 AGAAGGCTGCTATGACTCTTTGGATGGGAGTCTGGCAAGAGGAAATTGGAAGATAAAATA NM_024579 1.15E- -16
98 KCTD12 GCTACTGTTTTCCTTCCTGTGTGTGAAGTAATGAATCATTGATTATGTGACTTGTTATGT N _138444 2.67E- -18
99 THBS2 CCACTGAAACCCTGCACTTAGCTAGAACCTCATTTTTAAAGATTAACAACAGGAAATAAA NM_003247 2.17E- -17
100 CDR1 ATGGATTTCCTGGAAGACGTGGATTTTCCTGGAAGATCTGGATTTGGTGGAAGACCAGTA N _004065 2.52E- -17
101 MTMR9L CA AAAGTACTG AG G GTCTTA AGTTTG AAGTGTCCAA AGTAT AG G G AG GT TCAATA ATAA NRJD26850 9.03Ε· •16
102 THY1 TTATGGCATCTCATTGAGGACAAAGAAAACTGCACAATAAAACCAAGCCTCTGGAATCTG NM_006288 6.32E- ■24
103 PRRX1 G ATTTGTAG G GTACTTG G CAG GTTAAATTA AACCAG A AG AG GTG ACTTA ATAA A AAAG G G NM_006902 1.66E- ■17
104 PMP22 TGTGCCTCCAAGGACTGTCTGGCAATGACTTGTATTGGCCACCAACTGTAGATGTATATA NM_000304 5.82E- ■16
105 LOC399959 TATGTGACTTTGTCATATGTTCCTAACCCCCAATAAAAGCAATGTTGCATCAACTGTGAA NR_024430 1.56E- -21
106 LOC387763 ATGGCTGAAGGCATTTATTTAACGATCTTTTTACCTGGATATGTCTGTGAGGCTCCTGAA N _001145033 1.70E- -18
107 SFRP2 ATAACCTACATCAACCGAGATACCAAAATCATCCTGGAGACCAAGAGCAAGACCATTTAC HD_8pack_Dx_4405 1.16E- -15
108 PDLIM3 AA AC AT AC ACTT AG CTATG1 FGCAACTCT fGGGGCTAG C A AT A ATG AT ATTT A A A M..014476 4.04E-■17
109 FNDC1 TCACAGGGTGAAAGAGATGGCAAATGGAGTACGTCAGTCTTCCAAAGAACACCAGAATCT NM_ .032532 1.25E- ■17
110 IL6ST CTGGAAAACAAACCATTTTACTATTCCTAAGGAGCAATATACTATCATAAACAGAACAGC N . .175767 6.62E- •16
111 RGAG4 AT AAG AAG CTG CTCTGTATG CTA A AG CTTTCTCTCCTCAATA AAA ATATA AAG G GTGTGT NM. .001024455 2.32E- ■18
112 DBN1 TTG G G AAA ATATCACTTTGTATTCTCTGTCCAG G G CTTCAG ATATTTTG CACG AATTTTA N . .080881 4.22E- •18
113 STOM GGGTGACATTTGTAACATTTCCTCTTTGAGACTCTGAGTTCACCTAGAGAAGTCTAAGCA N . .198194 1.51E- •15
114 AR CX2 CTGAATTGACAGTAAACCTGTCCATTATGAATGGCCTACTGTTCTATTATTTGTTTTGAC NM. .014782 1.80E- ■19
115 MXRA7 TGGCTTGGATCTCTGTATTCAGCCTTTGTTCAGTCCAATAAACTTTGAGTAGATGATCTC M. .001008529 1.11E- ■21
116 STAT2 TCCTGTTCAGAAAGGGGCTCTTCTGAGCAGAAATGGCTAATAAACTTTGTGCTGATCTGG NM. .005419 3.87E- ■17
117 ITPRIPL2 GTAGAAGGATGTGGCTTTTAGAGAAGTCCAGTAGAAGAAGCAAGAACTAGCTGCAGGGAA NM. .001034841 5.44E- •16
118 A_32_P5086 CTGGGAAAGAAAGCTGTTATGCTTAGACTTCTCTAGGTGAACTCAGAGTCTCAAAGAGGA A_32_P5086 1.56E- •16
119 GPX8 TAACTCCTGATCATCTTACAGCAGACATAACAACAGAGTGTTAGAGACTGGAATAAATAT NM. .001008397 1.84E- ■19
120 CXCL12 GTG ACATTTCC ATG C ATAA ATG CG ATCCAC AG A AG GTCCTG GTG GTATTTGTAACTTTTT M. .199168 5.22E- ■19
121 STON1 GAATTCATGGGTAGATGATTTGTGCAGATCTGAATTTAAGAACATTTCCTTTTTCTGTGG NM. .006873 2.56E- •17
122 NDST1 CCTTCCTCC ATTA ATGT AC A ATCTCG A ACTA ACTG CT AATAA AGTG G G GTTCTGTTTGT A NM. .001543 3.59E- •16
123 TSHZ3 TTTGGTTGTTGACAATGAAGCACCATTATGTGACTCTTCATATAACCCTTTTTTCTACGG NM. .020856 6.92E- •17
124 PALM ACGAGGCCCCCGATGTTCTTGATTTTCCCAGAGAAGCAAATAAACAGCGTGAACAGCCCC NM. .002579 7.91E- ■19
125 A_24_P918527 TTCCAAACACAAGCAGAGTCTCCTTGGAGGTGACATGGATATGGGCAACCCAGGAACCCT A_24_P918527 2.14E- ■16
126 SPARC CCACATACCTAGATCTCCAGATGTCATTTCCCCTCTCTTATTTTAAGTTATGTTAAGATT NM. .003118 8.95E- •28
127 MGP GGGTCAAAGGAGAGTCAACATATGTGATTGTTCCATAATAAACTTCTGGTGTGATACTTT NM. .000900 3.45E- ■27
128 CIS GCCTTGCTAGAGGTAGAGTTTGATCATAGAATTGTGCTGGTCATACATTTGTGGTCTGAC NM. .001734 4.53E- •19
129 CCDC80 AAAGTAGTTCATCTAGGAAACTGTCCTGGGAACCAAACTTCTGATTTCTTTTGCAACCCT NM. .199511 7.28E- ■20
130 MGC24103 TGGACATTTCTTTGTCTGAGGATATATCTTGGCAGTACAGGATTTCTTCAGACGTGGCTC BC020879 7.45E- ■16
131 ABCA1 CCAAAGAGCCATGTGTCATGTAATACTGAACCACTTTGATATTGAGACATTAATTTGTAC NM. .005502 9.76E- ■17
132 C3 TCCCGTCGTGCGTTGGCTCAATGAACAGAGATACTACGGTGGTGGCTATGGCTCTACCCA NM. .000064 1.64E- ■17
133 FMNL3 ATGTG G G G G CCC ACTTTTTTGTAC ATGT ACC ACCTCCCTTTCCTCTTACTGT AC AT AA AC NM. .175736 2.39E- •15
134 IGFBP7 ACCTCCAGAATATTATTAGTCTGCATGGTTAAAAGTAGTCATGGATAACTACATTACCTG NM. .001553 5.30E- •26
135 TGFB3 TCCTCT AC ATC AATT AAC ATCGTG G GTC ACTACAG G G AG A AAATCC AG GTCATG C AGTTC NM 003239 1.94E- ■33
136 STAT5B GCAGAGTTACAGTCACAAAGTTGTGTATTTTATGTTACAATAAAGCCTTCCTCTGAAGGG NM_012448
137 CRISPLD2 CAAAGCATCCCACTCAAGGGAGACTTGAAACTTCCAGTGTGAGTTGACCCCATCATTTAA NMJB1476
138 CLIP4 G CTTATG AAATGTC ATTTAAAGTTCACTTCTTG AG CATCAAT AAAA AG G G AAG CTGTGTG NM_024692
139 NNMT CTGCTGTGAAAGAGGCTGGCTACACAATCGAATGGTTTGAGGTGATCTCGCAAAGTTATT NM 006169
Table 4: Preferred set of 25 genes, each individually present in all three TGF beta signatures (Tables 1-3).
Gene
TRIB2
VIM
TIMP2
PLEKHOl
MRC2
RBMSl
CYTH3
CALDl
PREXl
ZNF469
AHR
ITPRIPL2
PTRF
CYB5R3
FERMT2
NR3C1
RAP IB
IL6ST
RGAG4
STOM
SPARC
CIS
IGFBP7
LUM
CLIP4 Table 5: Genes of 41 genes signature for determining micros ate llite stability status.
Transcript ID Gene Probe sequence Pvalue Difference*
AK098417 ARIH2 ACTAGGATATAAACTCTTTGAGATAGAGGTCCATATTTTTTCTTTACCTAACAGCACCTG 0 -0.46097
N _152511 DUSP18 CTCCmCTGTGCACAGCACTTTATTGmCA GTACTCTTCCAAAAAGTTACCCTGTG 0 -0.40082
NM_000249 MLH1 TGTGGGATGTGTTCTTCTTTCTCTGTATTCCGATACAAAGTGTTGTATCAAAGTGTGATA 0 -0.50737
AK057088 NUDT3 ACCAGAGAAATAATAGGTATTTGTTAGACCTGAGTGTACATTTCACATGTTATCCTTCAC 0 -0.45415
BC018720 PTCD2 GACCTCTTAGGCTTGGTGTGAGGATGAAATGAGATAGGGAATATAAAGCAAGCAGATAGT 0 -0.40303
N _019008 SMCR7L CAAGGATTTCTTATGGTGGTTTCAGTTTCATTTGCATAAAGGTATTGAGAGGGAACAAAA 0 -0.45347
NR_002323 TUG1 TATCATTCGTCTTCTTTTCCAAACTACACATCACTGTATGACTCAACCAGTAGCAGTTAT 0 -0.36182
NM_015147 CEP68 TTACTTTCTTGGCTAACCAGTTTCTTAGAAGAAAATGTGTCAGGGACTTGGGGATCTACA 2.22 E-19 -0.41459
ENST00000399461 RPL13P5 ATTCCCATCGGCAATGTCTACAAGGAGAAAGCCAGAGTCATCGCTGACTAGGAGGAAAAC 1.33E-18 -0.39194
NM_001038707 CDC42SE1 GGGGTCTCATTAGCTTTGCAACAGGAAACATCCTGTTTTATTATGGTAGTGGGGTCAGGA 2.00E-18 0.350333
N _023076 UNKL AGCAGAGGGGATCCAACGTCAGAGCTTTTAGAATTACTTTTTTAAGCAGCTGTCTTCTGG 2.22E-18 -0.38905
IMM_020770 CGN CGAAGGGCTGAGCTCAGATGAGGAATTCGACAGTGTCTACGATCCCTCGTCCATTGCATC 6.77E-18 -0.42231
N _139067 S ARCC2 CAAGGTTCTATTAACCACTTCTAAGGGTACACCTCCCTCCAAACTACTGCATTTTCTATG 5.46E-17 -0.33021
HD_8_MaP3.0_121 EGFR GTTTGCACAGTTCTAGACACGATAAATACATGTGAAATCACACAACTCAGAAAATGTCCC 7.22E-17 -0.57738
THC2657554 KCNK5 CTGTCTCCAGGTAGGTGGACCAGAGAACTTGAGCGAAGCTCAAGCCTTCTCAACTCAAGG 4.07E-16 -0.50507
NM_004892 SEC22B GTTTTTGATGGCCTTTTAAACAAGACTCCAGTATGTGAAGGTTAATTGCTGTGCTCCACA 5.44E-16 0.235386 HD_8_ColoP1.0_15K_02960 PLAGL2 AGTAAGCATACTGAAGTGAGTTCGGGTACTGAGTGCAGGATAAAGCTATTCTTATCCTTT 9.09E-16 -0.55932
N _017763 RNF43 GGCAGAATTACAGCTGAGCGGGGACAACAAAGAGTTCTTCTCTGGGAAAAGTTTTGTCTT 1.33E-15 -0.51758
THC2669975 IM P2L TGTCATTCTGAAAACATCCTATGCGATGGAATGGAGAAGGAAGTGATGACTCAGAGTGTG 1.60E-15 -0.67274
BC010934 ZBTB20 TTGAAGTTGGAAATCCAAGGGGAATCTAAAACCGACCAGATGTTTCTGCTGCTGGAAAGG 2.09E-15 -0.58235
N _001099645 RPL22L1 ATTGGCTTCGAGTGGTTGCATCTGACAAGGAGACCTACGAACTTCGTTACTTCCAGATTA 2.10E-15 0.646235
A 022319 CAPN1 TGGGCATTGCAGTAGGTACCAGTGAGAAAAAAGGGGAAAATCTGCATATTGAGTATTTAT 2.16E-15 -0.47643
NM_003898 SYNJ2 AGTCAAAGAAGCAGGGGAAAAGTAAGCTCCTCCAAAGTTGCTTGCAGTGCTGGAAATAGA 3.04E-15 -0.31603
IMM_004655 AXIN2 TTCCTGGAGAGGGAGAAATGCGTGGATACCTTAGACTTCTGGTTTGCCTGCAATGGATTC 3.22E-15 -0.63995
N _003279 TNNC2 GACTTCGACGAGTTCCTGAAGATGATGGAGGACGTGCAGTAAGGAGTGGACAGTCGCCTC 3.94E-15 -0.9326
NM 152713 STT3A ATTG G CTG GTCAG G ATATACAAG GTAAAG G ACCTG G ATAATCG AG GCTTGTCAAG G ACAT 4.06E-15 0.273671
BG114486 QPRT AGAGACACTGGGCTGGCCTAGACACTGCCTTTGGTGATACCCTAAACCAAAGGGGCCAGT 5.12E-■15 -0.71233
ΝΜ_006113 VAV3 CATATACTTTGTCTTGCCTGTATGCAGCCCTTGTGTAATATGGTGAATTAGAGTGGTATT 6.06E- •15 -0.76354
HD_8_ColoP1.0_ _15K_ .01341 RPL15 GAGTGGTAAGATTTTATTGTGTCAAACGACTGCATTAGTTGTGTTTTGTTATTATGGCAG 7.52E- ■15 -0.5011
HD_8_ColoP1.0_ _15K _02438 C13orfl8 TTAACAAGGAGCTAGCCAAACTTCTCTGAGAGTTTGAGGAGGTAGCCTGAGAGGATCATT 8.45 E- ■15 -0.76906
BC035247 BC035247 GTGGAGGACACTTCAATCTAAAGTGATCTTAAAGGAGGAGTAGTAGGATTTGAAGATGAA 8.62E- ■15 -0.4553
BC043603 FA 44A GTTATTCGTATTCAACAAGTGGAA 1 1 1 1 1 ACTTTGCTGTTCTCAGAAACCCATGAATCTG 1.24E- ■14 0.490717
N _017583 TRIM44 GGACTTCCTTGCTTTTCTCTACTTCCAAATCACAATTTCTTACAACCAAGCTTTGTGCTC 1.37E- •14 -0.23311
BX427767 BX427767 CAACTTGAATTTGATCCCATAAAGTCAGGCATCAGGAAGCCATTCAGAATTTTTCACCCT 1.81E- -14 -0.32189
NM_006045 ATP9A TGTGATGACACACATATGATCTTTCGTGTTTCTGAGCGACTCTACTTTCATTGTTTGCCA 2.13E- •14 -0.46116
HD_8_ColoP1.0_ _15K_ .01048 SSH2 GTTCACAAAAACACCTAGTAGGTATTCAGTTCATATTGGAATGAATGAGAAAATGAGCAG 2.14E- ■14 -0.50851
BX119435 BX119435 AAGAACTTTGGAAGAGATCAGCTGGAAATATATCTCATTTATTTTATGAATAAATATGAA 2.83E- ■14 -0.70285
AK026351 PRKAR2A CCTGTCTTGACTGCTGACGTTCCTCAATGATTCTATTGTCTA I 1 1 1 ATGGGAAGCAGCCT 2.84E- ■14 -0.26461
BC010544 BC010544 GGCAAATGTAAACTCAGCCTTTCATTCATGACGTGTGAAATTTCAGTTTCTCTGGAGTTT 3.43E- ■14 -0.59557
NM_007122 USF1 ACAATG ACGTG CTTCG ACAACAG GTG G AAG ATCTTAAAAACA AG AATCTG CTG CTTCG AG 3.68E- -14 0.39099
HD_8_ColoP1.0_ _15K_ .02428 ARID3A GTGTGAAATTTCAGTTTCTCTGGAGTTTGTCAGACGGCGTGGGAACCACGCCTGAAACTC 4.57Ε· ■14 -0.61897
Table 6: Genes of 63 genes ! signature for determining micros atellite stability status.
Transcript ID Gene Probe sequence Pvalue Difference*
N _152511 DUSP18 CTCCTTTCTGTGCACAGCACTTTATTGTTACAAAGTACTCTTCCAAAAAGTTACCCTGTG 0 -0.46097
N _019008 S CR7L CAAG G ATTTCTTATG GTG GTTTC AGTTTCATTTG CATAAAGGTATTG AG AG GG AACAA AA 0 -0.40303
NM_015147 CEP68 TTACTTTCTTGGCTAACCAGTTTCTTAGAAGAAAATGTGTCAGGGACTTGGGGATCTACA 2. .22E- 19 -0.41459
NM_023076 UNKL AGCAGAGGGGATCCAACGTCAGAGCTTTTAGAATTACTTTTTTAAGCAGCTGTCTTCTGG 2. .22E- 18 -0.38905
HD_8_ColoP1.0 KCNK5 CTGTCTCCAGGTAGGTGGACCAGAGAACTTGAGCGAAGCTCAAGCCTTCTCAACTCAAGG 2, .75E- 16
-0.50952 _15K_01129
N _017763 NF43 GGCAGAATTACAGCTGAGCGGGGACAACAAAGAGTTCTTCTCTGGGAAAAG 1 1 1 1 GTCTT 1, .33E- ■15 -0.51758
N _001099645 RPL22L1 ATTGGCTTCGAGTGGTTGCATCTGACAAGGAGACCTACGAACTTCGTTACTTCCAGATTA 2, .10E- ■15 0.646235
NMJ304655 AXIN2 TTCCTGGAGAGGGAGAAATGCGTGGATACCTTAGACTTCTGGTTTGCCTGCAATGGATTC 3. .23E- 15 -0.63995
NM_ 003279 TNNC2 GACTTCGACGAGTTCCTGAAGATGATGGAGGACGTGCAGTAAGGAGTGGACAGTCGCCTC 3, .96E- 15 -0.9326
BX427767 GGA2 CAACTTGAATTTGATCCCATAAAGTCAGGCATCAGGAAGCCATTCAGAATTTTTCACCCT 1. .85E- ■14 -0.32189
NM_006045 ATP9A TGTGATGACACACATATGATCTTTCGTGTTTCTGAGCGACTCTACTTTCATTGTTTGCCA 2. .14E- ■14 -0.46116
NM_ 006113 VAV3 TTGCCAACCCTGGTATGCTGGAGCAATGGAAAGATTGCAAGCAGAGACCGAACTTATTAA 1. .61E- 13 -0.60949
NM_020717 SHR00M4 TGCCAGGTTTAACCACTCATAGCAACAAGAC 1 1 1 1 ACCCAGAGACCAAAACCTATAGACC 1. .85E- •13 -0.54502
NM_006887 ZFP36L2 AGCAAAAAAGTCGAACTTTTTCTGTTGAACAAAATATTCACAACAGGGCAGTTGTGATAC 3. .17E- •13 -0.3543
IMM_005170 ASCL2 CTGCTGGAGGGACACTGCTGGCAAACGGAGACCTATTTTTGTACAAAGAACCCTTGACCT 5. .95E- •13 -0.62015
NM_014298 QPRT CTGTCAGGGCTGACTTCACCTCTGCTCATCTCAGTTTCCTAATCTGTAAAATGGGTCTAA 6, .82E- •13 -0.58565
HD_8_ColoP1.0
-0.62286 _15K_01983 SHR00M2 GTGGTCATTTTGATGATATGTGTGTAAAATGTGAATAATCCAATTGGTGTCTGTACTCAG 7, 5Ε- 13
NM_002657 PLAGL2 AGAGAAAAGTACAAGACAGAAATCTTCTAGCACTTTGTAAACACAGTGAATAACCTCTTG 9. .50E- •13 -0.38368
IMM_000273 GPR143 ATATTCCTCAGACTCAACAATTCTTGTTCTTTAGAACTGTGTTCTCACCTTCCCAACACT 2. .13E- •12 -0.6543
HD_8_ColoP1.0
-0.33734 _15K_02115 Unknown GTGCAATTTGGCAGACAAGTTGGTGAAAGGTAAGTTGTCTCCAGAGATTTCAATCAGGGA 4. .36E- 12
BC000986 BC000986 TCAGCTTTGGAACTCCTCAGCCCTGAGTTTGGTCTTTAGTCGCCTCTGAGAACTTTAATT 6, Ό7Ε-■12 -0.3653
N _001533 HNRIMPL CTCCTAATTAGGTGCCTAGGAAGAGTCCCATCTGAGCAGGAAGACATTTCTCTTTCCTTT 6, J6E- 12 0.196249
HD_8_ColoP1.0
-0.63733 _15K_01307 GGT7 AAAGAAGATATCGAATAACTTGGAAAAATGGGTACTTAGTGCGGTGGCAAAAGCCAAACA 7. .31E- •12
N _001429 EP300 TTTTTGAATCTTTCGTAGCCTAAAAGACAATTTTCCTTGGAACACATAAGAACTGTGCAG 9, .14E- 12 -0.23177
N _015515 KRT23 TTTCCTACTGCAGCCTTCAGATTCTCATCATTTTGCATCTA i l l ! GTAG CC AATAAAACT 9, .42E- ■12 -0.93864
N _175887 PRR15 TGTTAAACTACAAAACTGTACAGCCTA 1 1 1 1 AGTGTGGACTATTAAAACCCTTGCACTGT 1, .15E- ■11 -0.38293
HD_8_ColoP1.0
-0.54546 _15K_02495 EPDR1 TCTAGATGCTTCTACTGTTATGTTTTATCTGCCCATTTATCTTTCTTAGTTACCAGGAGA 1, .67E- •11
NM_004850 R0CK2 TATATAAATACACAG AGTTTG GTATG ATATTTAAATACATCATCTG G CCAGG CATGGTG G 1, .69E- •11 -0.36345
NM_006242 PPP1R3D TTGTTTTGCAAAGGCCCAAGTCCTCCTGCTAGGAAAAGCTTTTGCATGTGTCCTGAATGT 3 .26E- ■11 -0.30692
N _080752 ZSWIM3 TGTGAGAGTTTAAAGTGGGCAGGACATACTAGGGTTTAGCA I 1 1 1 AGCCAATGTCTTCCT 5, .53E- ■11 -0.35386
N _025113 C13orfl8 TGTGTC GGAAAGGGCTTTATTTGTGAATTTTGCCAGAATACGACTGTCATCTTCCCAT 8, .37E- ■11 -0.57206
N _001009185 ACSL6 AAACAAATAGAAGAGCTTTACTCAATCTCCATGTGAAGTTCAAGGAAAGTTCTTCTCAGT 9, .67E- ■11 -0.86449
BC107798 TN NT1 TCCGAGCGTAAGAAGCCTCTGGACATTGACTACATGGGGGAGGAACAGCTCCGGGAGAAA 1. .13E- 10 0.625506
NM_ 003811 TN FSF9 CTGGAGTCTACTATGTCTTCTTTCAACTAGAGCTGCGGCGCGTGGTGGCCGGCGAGGGCT 1. .24E- 10 0.351198
NM_033342 TRIM7 CGTAAC ATACCAGTTAG GG CCTG CG G AAG CATCTTGTAATG G AAC ACATTACTATTTCTG 2. .04E- •10 0.84181
NM_006408 AGR2 CTCCTCAATCTGGTTTATGAAACAACTGACAAACACCTTTCTCCTGATGGCCAGTATGTC 2. .21E- •10 0.616835
HD_8_ColoP1.0
-0.4694 _15K_01105 S0RBS1 CCATCGCTGTTTGACATAACCTCCTGATTCTATTATTGTCACAGCATTAACCTCCACAGT 2. .89E- 10
NM_017896 C20orfll TGTGGTACCTTTGTACATGTTTGATTCTGTATTCTTTATTCCAGTGTGGCATATGTGCCC 3. .47E- 10 -0.23281
N _006769 LM04 TGCCTTCATCTCAGATTTGTTCATCACAGGTGGATCCCATGTGTCTTCAGTAGACAAGTC 3, .71E- 10 0.346863
NM_003270 TSPA 6 ACGTTGCATTGTTGTGGTGTCACCGATTATAGAGATTGGACAGATACTAATTATTACTCA 4. .34E- •10 -0.32381
HD_8_ColoP1.0
-0.35376 _15K_01438 DIDOl TTAGTGTTGCATCTGATTTTCAGGTGTACATTTATTTTTGACTGGGCAGATAGGGGATTT 5, .32E- ■10
NM_016407 C20orf43 GCTTTAAAAAGGATGGATTTCAAATACACTGTGCCCACTAGAAGCTTCGAAGGGCCTCGT 6. 3Ε- 10 -0.19523
N _001815 CEACA 3 AAAGTCAGATCTTGTGAATGAAGAAGCAACTGGACAGTTCCATGTATACCAAGAAAATGC 7, .15E- -10 -0.35011
N _014183 DYIMLRB1 ACACTGAAGCGACTGCAGAGCCAGAAGGGAGTGCAGGGAATCATCGTCGTGAACACAGAA 7, .92Ε· -10 -0.18116
NM_006558 HDRBS3 ATGATGAACAGAGTTATGATTCCTATGATAACAGCTATAGCACCCCAGCCCAAAGTGGTG 8. .15E- -10 -0.29656
NM_001098722 GNG4 CAAACTCCATCCAGTACATTCTTTCTTCTTTCATGAAAGAGCTTGAGTTGGATGTAAATA 9. .41E- -10 -0.7322
NM_ 005224 ARID3A CAGCTGCCCATGAGCATTCGGATCAACAGCCAAGCCTCCGAAAGCCGCCAGGACTCTGCT 9, .61E- -10 -0.36692
AK025743 LOC157860 G G GGTTTAG GGTCG AG CTGTTCCTG ATGTTTATCG G AG ACTG G G ATCA AAG CTATCCAG G 1. .31E- -09 -0.35981
NM_004963 GUCY2C CAGCTGAATACCACAGACAAGGAGAGCACCTATTTTTAAACCTAAATGAGGTATAAGGAC 1. .39E- -09 -0.43427
NM_015338 ASXL1 AATAGGGTTGTCTTTCCTATGAAAATGCCATCTGTAGACCTTGTGAGTCAGCCGTCCAGA 1. .87E- -09 -0.23183
NM_004665 VNN2 A AAG AG CCTGG GTGTTTG G GTCAG ATAAATG AAG ATCAAACTCCAG CTCCAG CCTCATTT 2, .44E- -09 0.421704
NM_024698 SLC25A22 TTTTTTCTTTTGAAGAGTTTTAAGAAGTTGTAACTTTTTGTGTCTTGTCATGTCAGAGAA 2 .44E- -09 0.194785
N _001040167 LFNG AAGCGAATGATAAGGGAAAAGTTCTCAGGGAATTGAAGTGTTGTTGCTATGGTGACGTCC 2, .47E- -09 -0.29768
N _153256 C10orf47 AAGATCTCAGGGTAGGGAAAAACCAGTGAATGAGGTTACACAGCAGGAAAAGAACCGGTT 2, .57E- -09 -0.35659
N _014574 STRN3 CTGTACTGGATGTGAACTGAGCGTATATCTGTTTTTAGGTGTCTTTAAGCCAATGTGGAG 2, .80Ε· -09 0.340281
NM_004363 CEACA 5 AGTTCTCTTTATCG CCA AAATCACG CCAAATAATAACG GG ACCTATG CCTGTTTTGTCTC 3. 8Ε- -09 -0.39052
NM_ 001003652 SMAD2 AAACAGCACTTGAGGTCTCATCAATTAAAGCACCTTGTGGAATCTGTTTCCTATATTTGA 3, .16E- -09 0.216501
NM_ 001024847 TGFBR2 GACATCTCGCTGTAATGCAGTGGGAGAAGTAAAAGATTATGAGCCTCCATTTGGTTCCAA 5, .52E- -09 -0.19635
BC006795 MDM2 A AC AGTTAACAG G ATG CAG AC ATG G CAG AG GTTTCCTAAAA ATCTC ATTATCTATA ACC A 9. .91E- -09 0.305677
AF531436 FBX034 CTCATGGCGGAATTAGAAGAACTAGAACAGGAGGAACCAGACAAGAATTTGCTGGAAGTC 1. .22E- -08 -0.24946
NM_014553 TFCP2L1 GATGGTGGGCTAAATTTTAATTCTCAAAAGTGTAGGAGGCTAATATTGTCTTCTAAGTTC 1, .34E- -08 -0.40512
NM_003202 TCF7 CCCAGAAAACCTCCAGTAGTGGACAACAGGTTTTCACCATAGCCTACGTTAACCCATTTT 1, .36E- -08 -0.32239
THC2669157 0IT3 CAGCAAATGTACTAATTTACACTGTCACTGTATACTTCTCCCTATAACCTTGTAAGTGTT 1, .58E- -08 -0.87831
Table 7: Genes of gene signature for determining activating mutations in EGFR pathway.
Figure imgf000050_0001
Figure imgf000051_0001
EXAMPLES
Example 1: Development of the TGF beta gene signatures
Gene expression data of 451 colorectal cancer FFPE samples from 7 different medical centers were profiled on DX2 44K array (amid 32627), a proprietary array based on Agilent full genome microarray. Normalization was performed with 461 colon normalization genes with their FFPE normalization template.
The first step in developing the signatures was to define the initial stratification of activation/non- activation of TGF beta signaling groups.
Experimental evidence showed that an inactivated mutation on TGF beta receptor TGFBR2 reduced the signaling level of the TGF beta pathway and failed to induce epithelial mesenchymal transition (Pino et al., Gastroenterology 138: 1406-1417 (2010)).
The mRNA level of TGF beta receptors (TGFBR1, TGFBR2), at least when present at low levels, is functionally relevant. Therefore, mRNA level of TGF beta ligands (TGFB1, TGFB2, TGFB3), and mRNA levels of TGF beta receptors (TGFBR1, TGFBR2), were both used for the initial stratification of activation/non- activation of TGF-beta signaling groups (Table 8).
The second step was to perform 500 rounds of 10-fold cross validation to train 3 signatures, one for TGFB1 signaling, TGFB2 signaling and TGFB3 signaling. In the cross validation procedure, genes with a median difference less than 1.25 fold change were removed. Genes were ranked by their occurrence frequency, and a cutoff was chosen at the 20% percentile of scores, consistent with the percentile used in the initial stratification. The optimal number of genes, performance and heatmap of the 3 gene signatures are shown in Table 9 and Figure 3. The total percentage of tumors predicted to have an activated TGF beta signaling pathway, whereby prediction is performed by the TGF beta 1, 2 and 3 signatures, is 37.9%.
It should be noted that not all tumors with high mRNA levels of TGFB1,
TGFB2, and TGFB3 displayed activated TGF beta signaling. In other words, the mRNA level of TGFB1, TGFB2, TGFB3 alone was found not sufficient to predict TGFB signaling and a TGFB signaling-induced phenotype. This follows from the fact that there is low concordance between the TGF beta 1, 2 or 3 signature, and high mRNA levels of TGFbeta I, 2, or 3, respectively (Table 9). Therefore, relying on IHC stain of any single TGF beta protein alone is unlikely to work. Table 8. Initial stratification of the activation/non- activation of TGF beta signaling grou s.
Figure imgf000053_0001
Table 9. Performance of the TGF beta gene signatures.
Figure imgf000054_0001
Example 2: Correlating the TGF beta gene signatures with known biomarkers of mesenchimal phenotypes.
The Loboda EMT signature (Loboda et al, BMC Medical Genomics, 4:9 (2011)) and Agendia C subtype FFPE signature (trained on FFPE data; see WO2012/087144A) were read out on the 451 colorectal cancer FFPE samples described in Example 1. As is described in WO2012/087144A, C-type colorectal cancer patients have a poor prognosis with a 5-year Distant Metastasis Free Survival (DMFS) rate of about 58%. By using 420 stage 2 and stage 3 colorectal tumor samples, correlations between the 3 TGF beta gene signatures and the Loboda EMT signature and Agendia C subtype signature were established (Table 10).
As is shown in Table 10, single gene mRNA level of TGF beta 1, TGF beta 2 and TGF beta 3, do not result in correlations with scores from the Loboda EMT signature and Agendia C subtype FFPE signature. This suggests that single gene mRNA levels of TGFB 1, TGF beta 2 and TGF beta 3 can not reliably be used to determine an activated TGFB signaling pathway/EMT phenotype.
Table 10. Correlation to EMT signature and C-type signature indicates that TGF beta 1-3 gene signatures tend to identify mesenchymal phenotypes.
Figure imgf000056_0001
Example 3: Prognostic power of TGF beta gene signatures
Within the samples set of 451 patients, 420 patients had stage 2 or stage 3 tumors. The event end points used in the evaluation of prognosis was defined either by event type (1) regional recurrence or (2) distant metastasis. 24 tumors with event type (3) cancer related death and (4) local recurrence were removed. However, tumors showing event type (1) or (2), regardless whether event type (3) or (4) occurred, were included. In total, the prognostic value of the three TGF beta gene signatures was evaluated in these 396 stage 2 and stage 3 colorectal cancer patients. The survival analysis of individual TGF beta signatures and three different combinations of them were performed and the results are as displayed in Figure 4: (4a) TGFbeta activation defined only by TGFBl signature, (4b) TGFbeta activation defined only by TGFB2 signature, (4c) TGFbeta activation defined only by TGFB3 signature, (4d) TGFbeta activation defined by any one positive prediction of TGFBl, TGFB2 or TGFB3 signature, (4e) TGFbeta activation defined by any combination of two positive predictions of TGFBl, TGFB2 or TGFB3 signature, (41) TGFbeta activation defined by all three positive predictions of TGFBl, TGFB2 and TGFB3 signature. The survival curves, hazard ratios and p- values of log-rank test are shown in Figure 4. The p-values of the survival analysis of individual TGFBeta signatures and three their combinations are all significant (p<0.05). When TGFbeta activation is defined by any combination of two positive predictions of TGFBl, TGFB2 or TGFB3 signature, the p-value is the most significant (Figure 4e, p=0.0021).
It follows from Figure 4 that with a gene signature of the invention it is possible to prognosticate cancer patients for TGF beta activation status and survival.
A set of 25 core genes are shared by TGFBl signature, TGFB2 signature and TGFB3 signature (Table 4). By using these 25 core genes set as general TGFbeta signature, and a cutoff chosen at the 20% percentile of scores, consistent with the percentile used in the initial stratification, prognostication based on the 25 core genes set was tested. TGFbeta activation was defined only by any combination of two positive predictions of the TGFBl signature, TGFB2 signature or TGFB3 signature. As is shown in Figure 5, the 25 core gene set showed significant prognostic value (HR=2.77 P<0.0001) in these 396 stage 2 and stage 3 patients.
Example 4: Prediction of chemotherapy response of TGF beta gene signatures
Within the samples set of 451 patients, 179 patients had stage 3 tumors. 18 tumors with event type (3) cancer related death and (4) local recurrence were removed. However, tumors showing event type (1) or (2), regardless of whether event type (3) or (4) occurred, were included. The predictive value of chemotherapy response of the three TGF beta gene signatures was evaluated in the remaining 161 stage 3 colorectal cancer patients.
TGFbeta activation was defined by any combination of two positive predictions of the TGFBl, TGFB2 or TGFB3 signatures. With this definition and within these 161 stage 3 patients, 42 patients had TGFBeta activation (no chemotherapy treatment = 20, chemotherapy treated = 22) and 119 patients had TGFB non- activation (no chemotherapy treatment = 46, chemotherapy treated = 73). Figure 2 shows that in the TGFBeta activation group of 42 stage 3 patients, chemotherapy does not result in any benefit, while in the TGFBeta inactivation group of 119 stage 3 patients, a tendency of benefiting from chemotherapy is observed, although the p- value is not significant. These results agree with the notion that TGFBeta activation can lead to chemotherapy resistance.

Claims

Claims
1. A method for typing a sample of a cancer patient for the presence or absence of an activated TGF beta signaling pathway, comprising the steps of:
- providing a sample from a cancer patient, whereby the sample comprises gene expression products from a cancer cell of said patient;
- determining a gene expression level for at least five genes listed in Table 4;
- comparing said determined gene expression level to a reference gene expression level of said genes in a reference sample; and
- typing said sample for the presence or absence of an activated TGF beta signaling pathway on the basis of the comparison of the determined gene expression level and the reference gene expression level.
2. The method according to claim 1, further comprising determining a stage of the cancer.
3. The method according to claim 1 or claim 2, comprising determining the gene expression level for at least 15 genes, preferably all 25 genes, listed in Table 4.
4. The method according to any one of the previous claims, comprising determining the genes expression level of all genes listed in Table 1, 2 and/or 3.
5. The method according to any one of the previous claims, comprising determining the genes expression level of all genes listed in Tables 1 and 2, Tables 1 and 3, or Tables 2 and 3.
6. The method according to any one of the previous claims, wherein a gene expression level is determined for all genes listed in Tables 1-3.
7. The method according to any one of the previous claims, wherein the sample is formalin- fixed, paraffin-embedded (FFPE).
8. The method according to any one of the previous claims, wherein the cancer patient is a colorectal cancer patient.
9. The method according to any one of claims 1-8, wherein a sample of said cancer patient is additionally typed for microsatellite stability status, preferably by performing the steps of:
- determining a gene expression level for DUSP18 and at least one further gene listed in Table 5 or Table 6;
- comparing said determined gene expression level of said at least two genes to a gene expression level of said genes in a reference sample;
- typing said sample on the basis of the comparison of the determined gene expression level and the gene expression level of said genes in a reference sample.
10. The method according to claim 9, wherein the at least one further gene is SMCR7L.
11. The method according to any one of claims 1- 10, wherein a sample of said cancer patient is additionally typed for the presence or absence of one or more activating mutations in the EGFR pathway, preferably by performing the steps of:
- determining a gene expression level for at least two genes listed in
Table 7;
- comparing said determined gene expression level of said at least two genes to a gene expression level of said genes in a reference sample;
- typing said sample on the basis of the comparison of the determined gene expression level and the gene expression level of said genes in a reference sample.
12. The method according to claim 11, wherein the method is for typing said sample for the presence or absence of one or more activating mutations in BRAF.
13. A method for assigning an inhibitor of the TGF beta signaling pathway to a cancer patient, comprising the steps of: -assigning an inhibitor of the TGF beta signaling pathway to a cancer patient typed as having an activated TGF beta signaling pathway according to a method of any one of claims 1-8.
14. A method for assigning a standard-of-care therapeutic agent to a cancer patient, comprising the steps of:
- assigning a standard-of-care therapeutic agent, other than an inhibitor of the TGF beta signaling pathway, to a cancer patient typed as not having an activated TGF beta signaling pathway according to a method of any one of claims 1-7.
15. An inhibitor of the TGF beta signaling pathway for use in the treatment of a cancer patient typed as having an activated TGF beta signaling pathway according to a method of any one of claims 1-8.
PCT/NL2018/050008 2017-01-06 2018-01-08 Biomarkers for selecting patient groups, and uses thereof. WO2018128544A1 (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020234482A1 (en) * 2019-05-21 2020-11-26 Universität Zürich MAPKi RESISTANCE SIGNATURES
CN112342295A (en) * 2019-08-06 2021-02-09 中山大学孙逸仙纪念医院 Tumor marker for detecting human colorectal cancer and application thereof
WO2021063972A1 (en) * 2019-09-30 2021-04-08 Fundació Institut De Recerca Biomèdica (Irb Barcelona) Cthrc1 as biomarker for a tgfbeta-activated tumor microenvironment

Citations (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1991006678A1 (en) 1989-10-26 1991-05-16 Sri International Dna sequencing
US6172218B1 (en) 1994-10-13 2001-01-09 Lynx Therapeutics, Inc. Oligonucleotide tags for sorting and identification
US6204375B1 (en) 1998-07-31 2001-03-20 Ambion, Inc. Methods and reagents for preserving RNA in cell and tissue samples
US6210891B1 (en) 1996-09-27 2001-04-03 Pyrosequencing Ab Method of sequencing DNA
US6258568B1 (en) 1996-12-23 2001-07-10 Pyrosequencing Ab Method of sequencing DNA based on the detection of the release of pyrophosphate and enzymatic nucleotide degradation
US6274320B1 (en) 1999-09-16 2001-08-14 Curagen Corporation Method of sequencing a nucleic acid
US6306597B1 (en) 1995-04-17 2001-10-23 Lynx Therapeutics, Inc. DNA sequencing by parallel oligonucleotide extensions
DE10021390A1 (en) 2000-05-03 2001-11-15 Juergen Olert Protection solution for fixing samples for paraffin embedding, comprising amino acids and sugars, eliminates the need for aldehyde crosslinkers and retains protein structures
WO2004018497A2 (en) 2002-08-23 2004-03-04 Solexa Limited Modified nucleotides for polynucleotide sequencing
WO2004083369A2 (en) 2003-03-12 2004-09-30 Institut Claudius Regaud Tissue binding composition
US6969488B2 (en) 1998-05-22 2005-11-29 Solexa, Inc. System and apparatus for sequential processing of analytes
US7057026B2 (en) 2001-12-04 2006-06-06 Solexa Limited Labelled nucleotides
US7138226B2 (en) 2002-05-10 2006-11-21 The University Of Miami Preservation of RNA and morphology in cells and tissues
WO2007123744A2 (en) 2006-03-31 2007-11-01 Solexa, Inc. Systems and devices for sequence by synthesis analysis
US7414116B2 (en) 2002-08-23 2008-08-19 Illumina Cambridge Limited Labelled nucleotides
WO2012044167A2 (en) 2010-09-28 2012-04-05 Agendia N.V. Methods and means for typing a sample comprising cancer cells based on oncogenic signal transduction pathways
WO2012087144A2 (en) 2010-12-23 2012-06-28 Agendia N.V. Methods and means for molecular classification of colorectal cancers
WO2013079309A1 (en) * 2011-11-28 2013-06-06 Fundació Privada Institució Catalana De Recerca I Estudis Avançats Methods and kits for the prognosis of colorectal cancer
US20130165337A1 (en) * 2011-12-22 2013-06-27 Aveo Pharmaceuticals, Inc. Identification of multigene biomarkers
WO2014058317A1 (en) * 2012-10-10 2014-04-17 Stichting Het Nederlands Kanker Instituut-Antoni van Leeuwenhoek Ziekenhuis Methods and means for predicting resistance to anti-cancer treatment

Patent Citations (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1991006678A1 (en) 1989-10-26 1991-05-16 Sri International Dna sequencing
US6172218B1 (en) 1994-10-13 2001-01-09 Lynx Therapeutics, Inc. Oligonucleotide tags for sorting and identification
US6306597B1 (en) 1995-04-17 2001-10-23 Lynx Therapeutics, Inc. DNA sequencing by parallel oligonucleotide extensions
US6210891B1 (en) 1996-09-27 2001-04-03 Pyrosequencing Ab Method of sequencing DNA
US6258568B1 (en) 1996-12-23 2001-07-10 Pyrosequencing Ab Method of sequencing DNA based on the detection of the release of pyrophosphate and enzymatic nucleotide degradation
US6969488B2 (en) 1998-05-22 2005-11-29 Solexa, Inc. System and apparatus for sequential processing of analytes
US6204375B1 (en) 1998-07-31 2001-03-20 Ambion, Inc. Methods and reagents for preserving RNA in cell and tissue samples
US6274320B1 (en) 1999-09-16 2001-08-14 Curagen Corporation Method of sequencing a nucleic acid
DE10021390A1 (en) 2000-05-03 2001-11-15 Juergen Olert Protection solution for fixing samples for paraffin embedding, comprising amino acids and sugars, eliminates the need for aldehyde crosslinkers and retains protein structures
US7427673B2 (en) 2001-12-04 2008-09-23 Illumina Cambridge Limited Labelled nucleotides
US7057026B2 (en) 2001-12-04 2006-06-06 Solexa Limited Labelled nucleotides
US7138226B2 (en) 2002-05-10 2006-11-21 The University Of Miami Preservation of RNA and morphology in cells and tissues
US7414116B2 (en) 2002-08-23 2008-08-19 Illumina Cambridge Limited Labelled nucleotides
WO2004018497A2 (en) 2002-08-23 2004-03-04 Solexa Limited Modified nucleotides for polynucleotide sequencing
WO2004083369A2 (en) 2003-03-12 2004-09-30 Institut Claudius Regaud Tissue binding composition
WO2007123744A2 (en) 2006-03-31 2007-11-01 Solexa, Inc. Systems and devices for sequence by synthesis analysis
WO2012044167A2 (en) 2010-09-28 2012-04-05 Agendia N.V. Methods and means for typing a sample comprising cancer cells based on oncogenic signal transduction pathways
WO2012087144A2 (en) 2010-12-23 2012-06-28 Agendia N.V. Methods and means for molecular classification of colorectal cancers
WO2013079309A1 (en) * 2011-11-28 2013-06-06 Fundació Privada Institució Catalana De Recerca I Estudis Avançats Methods and kits for the prognosis of colorectal cancer
US20130165337A1 (en) * 2011-12-22 2013-06-27 Aveo Pharmaceuticals, Inc. Identification of multigene biomarkers
WO2014058317A1 (en) * 2012-10-10 2014-04-17 Stichting Het Nederlands Kanker Instituut-Antoni van Leeuwenhoek Ziekenhuis Methods and means for predicting resistance to anti-cancer treatment

Non-Patent Citations (10)

* Cited by examiner, † Cited by third party
Title
CANTELLI ET AL., SEMIN CANCER BIOL, 2016
FAN ET AL., CONF PROC IEEE ENG MED BIOL SOC, vol. 5, 2005, pages 4810 - 3
HERBERTZ ET AL., DRUG DES DEVEL THER, vol. 9, 2015, pages 4479 - 4499
HERBERTZ ET AL., DRUG DES DEVEL THER., vol. 9, 2015, pages 4479 - 4499
LOBODA ET AL., BMC MEDICAL GENOMICS, vol. 4, 2011, pages 9
PINO ET AL., GASTROENTEROLOGY, vol. 138, 2010, pages 1406 - 1417
RONAGHI ET AL., ANALYTICAL BIOCHEMISTRY, vol. 242, no. 1, 1996, pages 84 - 9
RONAGHI, M. ET AL., SCIENCE, vol. 281, no. 5375, 1998, pages 363
RONAGHI, M., GENOME RES., vol. 11, no. 1, 2001, pages 3 - 11
YINGLING ET AL., NAT REV DRUG DISCOV., vol. 3, no. 12, 2004, pages 1011 - 1022

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020234482A1 (en) * 2019-05-21 2020-11-26 Universität Zürich MAPKi RESISTANCE SIGNATURES
CN112342295A (en) * 2019-08-06 2021-02-09 中山大学孙逸仙纪念医院 Tumor marker for detecting human colorectal cancer and application thereof
WO2021063972A1 (en) * 2019-09-30 2021-04-08 Fundació Institut De Recerca Biomèdica (Irb Barcelona) Cthrc1 as biomarker for a tgfbeta-activated tumor microenvironment

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