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WO2018078143A1 - Moyens et procédés pour déterminer l'efficacité d'inhibiteurs anti-egfr dans une thérapie du cancer colorectal (crc) - Google Patents

Moyens et procédés pour déterminer l'efficacité d'inhibiteurs anti-egfr dans une thérapie du cancer colorectal (crc) Download PDF

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WO2018078143A1
WO2018078143A1 PCT/EP2017/077694 EP2017077694W WO2018078143A1 WO 2018078143 A1 WO2018078143 A1 WO 2018078143A1 EP 2017077694 W EP2017077694 W EP 2017077694W WO 2018078143 A1 WO2018078143 A1 WO 2018078143A1
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genes
gene
egfr
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Inventor
Marie-Laure Yaspo
Thomas Risch
Christine JANDRASITS
Hans Lehrach
Bodo Lange
Moritz SCHÜTTE
Jens Hoffmann
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Experimentelle Pharmakologie und Onkologie (epo) Berlin-Buch GmbH
Alacris Theranostics GmbH
Max Planck Gesellschaft zur Foerderung der Wissenschaften
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Experimentelle Pharmakologie und Onkologie (epo) Berlin-Buch GmbH
Alacris Theranostics GmbH
Max Planck Gesellschaft zur Foerderung der Wissenschaften
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Publication of WO2018078143A1 publication Critical patent/WO2018078143A1/fr
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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
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to a method for determining the susceptibility/responsiveness of (a) cancer cell(s), preferably (a) colorectal cancer cell(s), to the treatment with an epidermal growth factor receptor (EGFR) inhibitor. Further, the present invention relates to a method of selecting (a) cell(s), (a) tissue(s) or (a) tumor sample(s) of colorectal cancer (CRC) with susceptibility to an epidermal growth factor receptor (EGFR) inhibitor.
  • EGFR epidermal growth factor receptor
  • an in vitro method for the identification of a responder for or a subject, preferably a human patient, suffering from colorectal cancer (CRC) to an epidermal growth factor receptor (EGFR) inhibitor is disclosed.
  • the present invention also relates to a method of monitoring the efficacy of a treatment of the colorectal cancer (CRC) with an epidermal growth factor receptor (EGFR) inhibitor.
  • Colorectal cancer represents the third most frequent cancer worldwide. The five-year survival rate of patients diagnosed with metastasis is below 10%. CRC is refractory to most chemotherapeutic agents. Only fluorouracil (5-FU), irinotecan and oxaliplatin have documented responses in metastatic diseases such as colorectal cancer (CRC). Antibodies targeting the epidermal growth factor receptor (EGFR), such as cetuximab, offer therapeutic options for a fraction of metastatic colorectal cancers (CRCs) but have failed in the adjuvant setting (Nelson V.M. et al Gastrointest Oncol. 4(3) (2013), 245-252).
  • EGFR epidermal growth factor receptor
  • CRCs Colorectal cancers
  • markers for the prognosis of CRC were described; see, e.g, ⁇ et al, Targeted Oncology 9(2) (2013), 171-175; WO-A1 2009/50156; WO- A2 2016/161153; WO-A1 2009/140409; WO-A2 2013/006495; Lu et al, CMLS 67(19) (2010), 3313; Alajez, Saudi Journal of Gastroenterology 22(4) (2016), 288.
  • WO-A2 2007/025044, WO- A2 2010/145796 and WO-A1 2014/080381 disclose marker gene(s) and methods for determining the efficacy of an EGFR inhibitor such as the anti-EGFR antibody cetuximab in cancer therapy of (a) subject(s) suffering from colorectal cancer (CRC).
  • CRC colorectal cancer
  • Khambata- Ford et al. Khambata-Ford S. et al, J Clin Oncol 25 (2007), 3230-3237 describes that metastatic colorectal cancer patients with tumors that have high gene expression levels of epiregulin and amphiregulin, as well as patients with wild-type KRAS tumors are more likely to have disease control on cetuximab treatment.
  • KRAS and BRAF mutations are routinely used as predictive markers of resistance to the EGFR blockade but have low specificity since a number of wild-type tumors, i.e. patients which do not have KRAS and/or BRAF mutations also remain unresponsive (De Stefano A. et al, World J Gastroenterol 20 (2014), 9732-9743).
  • a major challenge in cancer treatment remains to select subjects/patients for specific treatment regimens based on pathogenetic and/or genetic markers in order to optimize the anti-cancer treatment outcome. It would, therefore, be helpful to know and better understand which subject(s)/patient(s) is (are) able to respond to an intended anti-cancer treatment.
  • the technical problem underlying the present invention is the provision of means and methods for the evaluation of (a) cell(s), in particular (a) cancer cell(s), (a) cancer tissue(s) or tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC), for its (their) susceptibility or responsiveness to the treatment with an anti-cancer treatment.
  • a cell(s) in particular (a) cancer cell(s), (a) cancer tissue(s) or tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC), for its (their) susceptibility or responsiveness to the treatment with an anti-cancer treatment.
  • the present invention relates to a method for determining the susceptibility or responsiveness of (a) cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject/patient suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor, comprising (a) obtaining (a) cancer cell(s), cancer tissue(s) or tumor sample(s) from a subject/patient suffering from colorectal cancer (CRC); and (b) determining the expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably determining the expression level of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 genes as shown in Table 3 ( Figure 8), even more preferably determining the expression level of 4, 5, 6, 7, 8, 9, 10, 11 or 12 genes as shown in Table 3 ( Figure 8), even more preferred the determination of the expression level of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9), or most preferred the determination of the expression level of 6, 7,
  • the present invention preferably relates to a method for determining the susceptibility or responsiveness of (a) cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject/patient suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor, said method comprising determining the expression level of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), or even more preferred determining the expression level of 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8) in said cancer cell(s), cancer tissue(s) or tumor sample(s), wherein said expression level is indicative of whether said patient is responsive or susceptible to the treatment with an EGFR inhibitor.
  • EGFR epidermal growth factor receptor
  • Also preferred in the context of the present invention is the determination of the expression level of 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7). Further, even more preferred in the context of the present invention is the determination of the expression level of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9). Most preferred in the context of the present invention is the determination of the expression level of 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9).
  • the present invention is based on the unexpected finding that by determining the expression of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably by determining 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9), it is possible to predict in a reliable manner whether or not a subject suffering from colorectal cancer (CRC) is susceptible or responsive to a treatment with an EGFR inhibitor (see Figures 4, 5, 10 and 11).
  • CRC colorectal cancer
  • the methods of the present invention allow the prediction or determination of the responsiveness or susceptibility to a treatment with an EGFR inhibitor in a subject suffering from colorectal cancer (CRC).
  • CRC colorectal cancer
  • the present invention aimed to identify one or more marker gene(s) that allow(s) the prediction of the response to an EGFR inhibitor, preferably to an anti-EGFR antibody like cetuximab, to an EGFR tyrosine kinase inhibitor such as erlotinib and gefinitib or to anti-EGFR antibody drug conjugates, independent of the KRAS, NRAS and/or BRAF mutation status in CRC patients/subjects.
  • the methods of the present invention can be applied on KRAS, NRAS and/or BRAF wild type cancer cell(s), cancer tissue(s) and/or tumor sample(s), i.e. cell(s), cancer tissue(s) and/or tumor sample(s) obtained from a patient suffering from CRC which is (are) characterized by not having (a) KRAS, BRAF and/or NRAS mutation(s) as well as on KRAS, NRAS and/or BRAF mutated samples.
  • the herein described one or more marker gene(s) allow(s) for the first time the prediction or determination of the susceptibility or responsiveness of a subject/patient suffering from CRC which do not contain (a) KRAS, BRAF and/or NRAS mutation(s), i.e. to wild type subjects/patients suffering from CRC, to the treatment with an EGFR inhibitor.
  • mini- classifiers of 12 genes (as shown in Table 3) or 16 genes (as shown in Table 4) were built which are able to identify/segregate a responder to or a subject sensitive to an EGFR inhibitor, preferably cetuximab.
  • the data of the present invention are based on the analysis of molecularly characterized 48 CRC patient-derived xenografts (PDX) by RNAseq (representing a sensitive method for measuring differences in RNA expression).
  • PDX CRC patient derived xenograft
  • T/C values Control non-treated sample
  • an EGFR- inhibitor mediated response evaluated in subjects/patients which inherently cannot have their own untreated controls, and which is evaluated by the clinical RECIST criteria (measuring tumor shrinkage after treatment) or survival data.
  • the present invention generally relates to a method of selecting (a) subject(s) suffering from colorectal cancer (CRC) with susceptibility or responsiveness to an epidermal growth factor receptor (EGFR) inhibitor, comprising the steps of: (a) determining the expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably by determining 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9), in (a) cancer cell(s), (a) cancer tissue(s) or tumor sample(s) of said subject; and (b) selecting (a) subject(s)/patient(s) suffering from colorectal cancer (CRC) characterized by a differential expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably characterized by a differential expression of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 (
  • the method may additionally comprise (i) contacting (a) cancer cell(s), (a) cancer tissue(s) or tumor sample(s) with an epiderminal growth factor receptor (EGFR) inhibitor, such as cetuximab, and (ii) evaluating susceptibility or responsiveness of said cancer cell(s), cancer tissue(s) or tumor sample(s) contacted with an epidermal growth factor receptor (EGFR) inhibitor.
  • EGFR epiderminal growth factor receptor
  • steps (i) and (ii) may be performed prior to step (a) but also after step (a) or, optionally, after step (b).
  • Said steps (i) and (ii) may in particular serve as further experimental proof that the selected subject(s) is responsive or susceptible in its viability to an EGFR inhibitor, such as cetuximab.
  • cancer cell(s), cancer tissue(s) or tumor sample(s) is not only limited to (an) isolated cell(s), (a) tissue(s), (a) tumor sample(s) and cell culture(s) from a carcinogenic tissue, preferably from colorectal cancer (CRC), but also comprises the use of (a) sample(s), i.e. (a) biological, medical or pathological sample(s) that consist of fluids such as blood, ascites, tear fluid, pleura effusion, liquor, lymph, urine, cerebral fluid, faeces or hair roots and comprise such (a) carcinogenic cell(s) or parts, fragments of carcinogenic cell(s).
  • sample(s) i.e.
  • biological, medical or pathological sample(s) that consist of fluids such as blood, ascites, tear fluid, pleura effusion, liquor, lymph, urine, cerebral fluid, faeces or hair roots and comprise such (a) carcinogenic cell(s) or parts, fragments of carcinogenic cell(s).
  • the gist of the present invention lies in the fact that a method is provided that allows the determination of the susceptibility or responsiveness of a subject suffering from colorectal cancer (CRC) for the anti-cancer or anti-proliferative treatment with an epidermal growth factor receptor (EGFR) inhibitor.
  • CRC colorectal cancer
  • EGFR epidermal growth factor receptor
  • the genes as shown in Table 1 ( Figure 6), preferably as shown in Table 3 ( Figure 8), and/or even more preferred the genes as shown in Table 4 ( Figure 9), that are differentially expressed among the cancer cell(s), cancer tissue(s), tumor tissue(s) of a subject suffering from colorectal cancer (CRC) is attributed to the response to the treatment of an epidermal growth factor receptor (EGFR) inhibitor, i.e. to the anti-EGFR antibody cetuximab.
  • EGFR epidermal growth factor receptor
  • the present invention provides a method for selecting (a) cell(s), (a) cancer tissue(s) or (a) tumor sample(s) which are susceptible or responsive to an EGFR inhibitor, but also for an in vitro method for assessing a subject suffering from colorectal cancer (CRC), i.e. a human or animal patient, for its potential susceptibility or responsiveness to an anti-cancer or anti-proliferate treatment with an EFGR inhibitor.
  • CRC colorectal cancer
  • the present invention provides not only the possibility to select (a) cell(s), (a) cancer tissue(s), (a) tumor sample(s) that are susceptible or responsive to the treatment with an EGFR inhibitor (i.e. the selection of e.g.
  • novel EGFR inhibitors may be tested or which are useful in screening methods for compounds that are suspected to function as a EGFR inhibitor) but also for a method to evaluate whether a given subject, preferably a subject suffering from colorectal cancer (CRC), is a responder or non-responder for a EGFR inhibitor treatment. Most preferably, the responsiveness of a given subject suffering from colorectal cancer (CRC) to the EGFR inhibitor cetuximab is tested.
  • CRC colorectal cancer
  • the present invention relates to a method for determining the susceptibility or responsiveness of a subject suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor (EGFR) inhibitor which comprises the step of: (a) determining the expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably by determining the expression level of 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining the expression level of 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9).
  • CRC colorectal cancer
  • EGFR epidermal growth factor
  • the gene(s) FSCN1 NCBI accession no.: NM 003088; version no.: NM_003088.3; GL347360903
  • REG4 NCBI accession no.: NM_032044; version no.: NM
  • the present invention preferably relates to a method for determining the susceptibility or responsiveness of (a) cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject/patient suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor, said method comprising determining the expression level of 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8) in said cancer cell(s), cancer tissue(s) or tumor sample(s), wherein said expression level is indicative of whether said patient is responsive or susceptible to the treatment with an EGFR inhibitor.
  • EGFR epidermal growth factor receptor
  • Also preferred in the context of the present invention is the determination of the expression level of 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8) in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7). Further, in the context of the present invention the determination of the expression level of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) is most preferred.
  • the selection method of an EGFR inhibitor responding cell or a responding subject comprises the steps of (a) obtaining (a) cell(s), (a) cancer tissue(s) or (a) tumor sample(s) from a subject/patient suffering from colorectal cancer (CRC); and (b) determining the expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably determining the expression level of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), most preferably determining the expression level of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9).
  • the method for the identification of a responder to an EGFR inhibitor or a subject sensitive to an EGFR inhibitor comprises the step of obtaining (a) cell(s), (a) cancer tissue(s) or (a) tumor sample(s) from a subject suffering from CRC with (a) differential gene expression of at least 4 genes selected from the group consisting of PIGU (NCBI accession no.: NM_080476; version no.: NM_080476.4; GI:52426746), SNRPN (NCBI accession no.: NM_003097; version no.: NM 003097.4; GI: 1011750893), FHDC1 (NCBI accession no.: NM_033393; version no.: NM_033393.2; GI: 145309323), HEATR2 (NCBI accession no.: NMJH7802; version no.: NM 017802.3; GL157388903), SLC39A2 (NCBI
  • Said differential gene expression level(s) of 4, 5, 6, 7, 8, 9, 10, 11 or 12 as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or, most preferably of 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes shown in Table 4 ( Figure 9) are indicative for susceptibility or responsiveness to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably the anti-EGFR antibody cetuximab.
  • the present invention relates in particular to a method for determining the responsiveness or susceptibility of (a) colorectal tumor cell(s), (a) colorectal cancer cell(s) or (a) colorectal cancer tissue(s) obtained from a subject suffering from colorectal cancer (CRC) to the treatment with an EGFR inhibitor, said method comprises determining the gene expression level of one or more gene(s) as shown in Table 1 ( Figure 6), preferably of 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9), in said colorectal tumor cell(s), colorectal cancer cell(s) or colorectal cancer tissue(s), wherein said gene expression level is indicative
  • Such a determination may take place on (an) individual, isolated tumor cell(s). Such an evaluation may also be carried out on biological/medical/pathological sample(s), like body fluids, isolated body tissue samples and the like, wherein said sample(s) preferably comprise cells or cell debris to be analyzed.
  • markers which can predict the outcome of an anti-cancer therapy with an EGFR inhibitor such as, e.g., with the anti-EGFR antibody cetuximab, prior to and being during treatment.
  • an EGFR inhibitor such as cetuximab
  • Subject of the present invention is a method for diagnosing a subject/patient suffering from colorectal cancer (CRC) who is to be subjected to or is being subjected to an anti-cancer treatment or an anti-proliferative treatment to assess the responsiveness or susceptibility to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to an anti-EGFR antibody such as cetuximab, prior, during, and/or after EGFR inhibitor treatment which comprises the steps of (a) detection of the gene expression level of one or more gene(s) as shown in Table 1 ( Figure 6), gene(s) more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most
  • the invention provides for the first time markers in (a) subject(s) suffering from colorectal cancer (CRC) which can predict the outcome of an anti-cancer/anti-proliferative treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably with an anti-EGFR antibody such as cetuximab, prior to the treatment with said EGFR inhibitor.
  • CRC colorectal cancer
  • the EGFR inhibitor is to be administered to a subject/patient after determination of the expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably after determination of the expression level of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably after determination of the expression level of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) in a cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from said patient/subject.
  • CRC colorectal cancer
  • marker for responsiveness to the treatment with an EGFR inhibitor and “predictor for responsiveness to the treatment with an EGFR inhibitor” can be used interchangeably and refer to (a) gene amplification(s)/expression of said gene(s), whereby the amplification/expression status is indicative for susceptibility or responsiveness to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to an anti-EGFR inhibitor such as cetuximab.
  • marker refers to measurable and quantifiable parameters (e.g. specific gene expression level, specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health and physiology-related assessments, such as a marker for predicting the response to a drug.
  • a marker is defined as a characteristic that is objectively measured and evaluated as an indicator of response and susceptibility.
  • a marker may be measured on a sample (as in the present application (a) cancer cell, (a) cancer tissue(s) or tumor sample(s) as obtained from a subject/patient suffering from CRC.
  • Markers can indicate a variety of health or disease characteristics, including the level or type of exposure to an environmental factor, genetic susceptibility, responses to exposures, or markers of subclinical or clinical disease. Thus, a simplistic way to think of markers is as indicators of disease trait (risk factor or risk biomarker), disease state (preclinical or clinical), response likelihood (prediction) or disease rate (progression). Accordingly, markers can be classified as antecedent markers (identifying the risk of developing an illness), screening markers (screening for subclinical disease), diagnostic markers (recognizing overt disease), staging biomarkers (categorizing disease severity), or prognostic markers (predicting future disease course, e.g. in response to a treatment, including recurrence). Markers may also serve as surrogate end points.
  • surrogate end points have the advantage that they may be gathered in a shorter time frame and with less expense than end points such as morbidity and mortality, which require large clinical trials for evaluation. Additional values of surrogate end points include the fact that they are closer to the exposure/intervention of interest and may be easier to relate causally than more distant clinical events.
  • An important disadvantage of surrogate end points is that if clinical outcome of interest is influenced by numerous factors (in addition to the surrogate end point), residual confounding may reduce the validity of the surrogate end point.
  • a biomarker may be a protein (including antibodies), peptide or a nucleic acid molecule (including DNA and mRNA).
  • the expression level(s) of the gene(s) as shown in Table 1 ( Figure 6), Table 2 ( Figure 7), Table 3 ( Figure 8), more preferred the expression level of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13 or 14 genes as shown in Table 3 ( Figure 8), even more preferred the expression of at least 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9), and most preferred the expression level of the genes as shown in Table 4 ( Figure 9) is (are) indicative for the susceptibility or responsiveness of (a) cell(s), (a) cancer tissue(s), or (a) tumor sample(s) to the treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to the treatment with an anti-EGFR antibody such as cetuximab.
  • the expression level of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) is indicative for the susceptibility or responsiveness of (a) cell(s), (a) cancer tissue(s), or (a) tumor sample(s) to the treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to the treatment with an anti-EGFR antibody such as cetuximab.
  • a differential gene expression level is defined herein as an expression level of the gene above or below a corresponding reference expression level.
  • the differential gene expression level is defined as the up- or down-regulation of the genes as determined in (a sample from) a subject/patient (responder) compared to the gene expression level determined in (a sample from) a reference/control subject/patient (non-responder), wherein the extent of the difference between the gene expression determined in (a sample from) a subject/patient (responder) and said reference/control gene expression is indicative of whether said subject/patient is responsive or susceptible to the treatment with an EGFR inhibitor.
  • responder refers in this context to a subject/patient which responds/is responsive/is susceptible to the treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to the treatment with an anti-EGFR antibody such as cetuximab.
  • non-responder refers in this context to a subject/patient which does not respond/is not responsive/is not susceptible to the treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to the treatment with an anti-EGFR antibody such as cetuximab.
  • RPKM read per kilo-base per million
  • a "responder” may be, for example, a subject/patient characterized by a down regulated expression level of the genes FSCNI, REG4, and/or LCN2. In particular such a patient, i.e.
  • a "non-responder" may be a subject/patient characterized by an up regulated expression level of the gene(s) FSCNl, REG4, and/or LCN2. Accordingly, the expression level(s) of the corresponding gene(s) is (are) disclosed in Table 1 ( Figure 6), Table 2 ( Figure 7), Table 3 ( Figure 8), and/or Table 4 ( Figure 9).
  • Whether (a) gene(s) is (are) differentially expressed may be also determined by using bioinformatic approaches.
  • a gene was considered differentially expressed if the False Discovery Rate (FDR) was equal or less than 1% (0.01).
  • FDR False Discovery Rate
  • different bioinformatic setups were used in order to identify differentially expressed genes.
  • the differential gene expression was determined by
  • the differential gene expression was determined by FDR ⁇ 0.01 and a dispersion of ⁇ 4.
  • the present invention also relates to a method for establishing a gene expression profile of one or more colorectal (CRC) tumor(s), the gene expression profile being indicative of response to an epidermal growth factor receptor (EGFR) inhibitor, wherein said method comprises the following steps: a) determining the expression level of 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, 40, 41 , 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71 , 72, 73, 74, 75, 76, 77, 78, 79, 80, 81 , 82, 83, 84, 85, 86, 87, 88, 89
  • a machine learning technique can be used in order to identify whether a patient is responsive or susceptible to the treatment with an EGFR inhibitor. Accordingly, in the context of the present invention a machine learning technique can be used in order to classify (a) sample(s) from a subject/patient into (a) patient(s)/subject(s) which is (are) responsive or susceptible to the treatment with an EGFR inhibitor (responder) or into (a) patient(s)/subject(s) which is (are) not responsive or susceptible to the treatment with an EGFR inhibitor (non-responder).
  • Machine learning techniques which can be used in the context of the present invention are known to the skilled person (see e.g., Larranaga, et al., Bioinform.
  • Machine learning involves training a machine learning algorithm to perform some task, rather than directly programming the system to perform the task.
  • the system observes some data, i.e. the expression level of one or more gen(s) as shown in Table 1 in (a) cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject/patient suffering from CRC, and automatically determines some structure of the data for the classification whether or not said patient(s) is (are) responsive or susceptible to the treatment with an EGFR inhibitor, such as an anti-EGFR antibody.
  • An EGFR inhibitor such as an anti-EGFR antibody.
  • One particular type of learning machine is a support vector machine (SVM).
  • SVMs are well known in the art, for example as described in (see e.g., Bennet et al., SIGKDD Explorations 2, (2000); Cortes et al, Machine Learning 20 (1995), 273-297). Additional details related to SVM-based prediction are provided below in the appended Examples. Briefly, the data set was randomly split into two respective training and independent test cohorts. Then differentially expressed genes were identified using an appropriate statistical test and a learning model was trained on the identified genes. Using this approach, the algorithm would learn to discriminate between the respective subtypes based on gene expression data in the given patient cohort. Having learned the expression features of these classes, the algorithm could recognize new samples as class members based on the expression patterns.
  • the present invention relates to a method for predicting the susceptibility or responsiveness of a patient/subject suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor comprising the step of: a) determining the expression profile of 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41 , 42, 43, 44, 45, 46, 47, 48, 49, 50, 51 , 52, 53, 54, 55, 56, 57, 58, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71 , 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 , 92,
  • the present invention relates to a method for predicting the susceptibility or responsiveness of a patient/subject suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor comprising the step of: a) determining the expression profile of 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, 40, 41 , 42, 43, 44, 45, 46, 47, 48, 49, 50, 51 , 52, 53, 54, 55, 56, 57, 58, 58, 59, 60, 61 , 62, 63, 64, 65, 66, 67, 68, 69, 70, 71 , 72, 73, 74, 75, 76, 77, 78, 79, 80, 81 , 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 ,
  • a single sample is positioned against the cohort that was used to train the classifier.
  • the training cohort is used to calculate the mean and standard deviation of expression for each gene in the expression profile.
  • the gene expression values of the single sample are normalized by calculating a z-score per gene, which is based on the mean and standard deviation values that are derived from the training cohort. If the established expression values do not follow a normal distribution, the expression values of the training cohort and the single sample need to be log-transformed before the normalization by taking the logarithm (e.g. base two).
  • the training of the SVM comprises the steps: a) establishing the gene expression profile comprising 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51 , 52, 53, 54, 55, 56, 57, 58, 58, 59, 60, 61 , 62, 63, 64, 65, 66, 67, 68, 69, 70, 71 , 72, 73, 74, 75, 76, 77, 78, 79, 80, 81 , 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, 99, 99, 100, 101 , 102, 103, 104,
  • susceptibility to an EGFR inhibitor and "responsiveness to treatment with an EGFR inhibitor” are used interchangeably in context of the present invention. Any explanations given herein in respect to “susceptibility to an EGFR inhibitor” also apply to "responsiveness to treatment with an EGFR inhibitor", mutatis mutandis, and vice versa.
  • Methods for determining the susceptibility to an EGFR inhibitor or responsiveness to the treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, are well known in the art.
  • susceptibility to an EGFR inhibitor/responsiveness to an EGFR inhibitor may be determined by contacting (a) cell(s), (a) cancer tissue(s), or (a) tumor sample(s) which are obtained from a subject, preferably a human patient, suffering from colorectal cancer (CRC) with an EGFR inhibitor and determining the viability of said cell(s), cancer tissue(s), or tumor sample(s) after contacting.
  • a cell(s), (a) cancer tissue(s), or (a) tumor sample(s) obtained from a subject, preferably a human patient, suffering from colorectal cancer (CRC) with an EGFR inhibitor and determining the viability of said cell(s), cancer tissue(s), or tumor sample(s) after contacting.
  • an evaluation/determination step may, for example, include determining the viability of the cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject, preferably a human patient, suffering from colorectal cancer (CRC) contacted with/exposed to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, or (a) colorectal cancer cell(s), colorectal cancer tissue(s) or colorectal tumor sample(s) treated with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • CRC colorectal cancer
  • cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC) described herein above may show decreased viability upon contacting/exposing/treating with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • an EGFR inhibitor preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • the cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC) may show an at least 10 %, 20 %, 30 %, 40 %, 50 %, 60 %, 70 %, 80 % and, most preferably, 90 % reduction in viability compared to reference/control cell(s), cancer tissue(s) or tumor sample(s) obtained from a patient suffering from CRC not contacted/exposed/treated with an EGFR inhibitor, preferably an anti-EGFR antibody.
  • an EGFR inhibitor preferably an anti-EGFR antibody
  • the reference/control cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC) will be identical to the cell(s), (a) cancer tissue(s) or tumor sample (s) to be tested as described herein with the only exception that the reference(s)/control(s) refer to (a) cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) that are obtained from a subject not suffering from CRC or to (a) cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) that are obtained from the subject suffering from CRC before treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, has been started.
  • an EGFR inhibitor preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR
  • cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC) contacted/exposed/treated with an EGFR inhibitor preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, and showing, for example, a decreased viability as described herein above, can be considered as being susceptible or responsible to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to an anti-EGFR antibody such as cetuximab.
  • an EGFR inhibitor preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably to an anti-EGFR antibody such as cetuximab.
  • cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) as obtained from a subject suffering from CRC treated with an EGFR inhibitor showing such a decreased viability can be considered as responsive to treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • a reduction in viability may, for example, be reflected in a decreased proliferation, such as 10 %, 20 %, 30 %, 40 %, 50 %, 60 %, 70 %, 80 % and, most preferably, 90 % reduction in proliferation compared to reference/control cancer cell(s), cancer tissue(s) or tumor sample(s) not contacted/exposed/treated with an EGFR inhibitor.
  • the decreased proliferation may be quantified, for example, by measuring the total cell volume, tissue volume or tumor sample volume using standard techniques.
  • the difference in proliferation between contacted/exposed/treated cancer cell(s), cancer tissue(s) or tumor sample(s) as obtained from a subject and corresponding references/controls as defined herein may, for example, be evaluated/determined by measuring the volume of the cancer cell(s), tissue(s) or cell culture(s) taking advantage of standard techniques.
  • Said evaluation/determination may be performed in various points in time, for example, 15 minutes, 30 minutes, 60 minutes, 2 hours, 5 hours, 18 hours, 24 hours, 2 days, 3 days, 4 days, 5 days, 6 days, 7 days, 2 weeks, 3 weeks, 4 weeks and/or more than 4 weeks after contacting/treating said cell(s), tissue(s) or tumor sample (s) with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, or exposing said cell(s), tissue(s) or tumor sample(s) to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • an EGFR inhibitor preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjug
  • said evaluation/determination may be performed repeatedly, for example, at 15 minutes, 30 minutes and 60 minutes after said contacting/exposing/treating.
  • said cell(s), tissue(s) or tumor sample(s) may be contacted/treated not only once with said EGFR inhibitor or exposed to said EGFR inhibitor but several times (e.g. 2 times, 3 times, 5 times, 10 times or 20 times) under various conditions (e.g. same concentration of inhibitor, different concentration of inhibitor, inhibitor comprised in a composition with different stabilizers, diluents, and/or carriers and the like).
  • said optionally repeated evaluation/determination may be performed after the final contacting/treating with or exposing to said EGFR inhibitor or in between said above- mentioned various contacting/exposing/treating steps.
  • the explanations given herein above with respect of the exemplarily determination/evaluation step, comprising determination the proliferation of the cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC), contacted with/exposed to an EGFR inhibitor also apply to the use of a patient derived xenograft (PDX) model of colorectal cancer (CRC).
  • PDX patient derived xenograft
  • a Patient Derived Xenograft from (a) cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from a patient suffering from said cancer, like in the present application CRC, are known to the skilled person (Fichtner et al, Eur J Cancer 40, 298-307 (2004)).
  • the Patient Derived Xenograft (PDX) models are known to be closely reflective of tumors or infections in patients for both their histopathological and genetic profiles.
  • PDX model(s) was (were) generated from tumor tissue of individuals of a population of 106 patients suffering from colorectal cancer, comprising 89 primary tumors (stages I to IV), and 27 metastases.
  • parameters of the subject may be considered as well for the prediction of the response etc.
  • Such parameters in a multivariate model may include gender, age, histological evaluation, and other markers.
  • a Cox- Proportional-Hazard regression predicts the dependent variable based on one or more independent variables. These predictors can either be measured (as e.g. level of a biomarker) or categorical data.
  • diagnostic/predictive markers only give a certain degree of sensitivity and specificity, as also outlined herein.
  • different further parameters might be considered in order to increase both, like previous response of the patient to the drug.
  • the present invention provides (a) new and superior marker(s) for predicting the response as defined herein.
  • the presence of one or more further diagnostic/predictive markers for the response is detected in the sample.
  • Compounds which may function as specific EGFR inhibitors in accordance with the present invention comprise small binding molecules such as small (organic) compounds or ligands for EGFR.
  • small molecule in the context of drug discovery is known in the art and relates to compounds having a molecular weight of less than 2,500 Daltons, preferably less than 1 ,000 Daltons, more preferably between 50 and 350 Daltons.
  • compounds which may function as EGFR inhibitor refers, e.g., to a protein, an antibody, a DNA and a RNA molecule.
  • the EGFR inhibitor is preferably an anti-EGFR antibody.
  • a number of anti-EGFR antibodies are commercially availale.
  • a number of anti-EGFR antibodies are available commercially, or are currently in clinical development.
  • Such antibodies include, but are not limited to, Vectibix® (panitumumab), Erbitux® (cetuximab), zalatumumab, nimotuzumab, and matuzumab.
  • the anti-EGFR antibodies can be selected from chimerized, humanized, fully human and single chain antibodies derived from the murine antibody 225 described in US Bl 4,943,533. Further, in the context of the present invention, the anti-EGFR antibody can be a bispecific antibody molecule that has binding specificities for EGFR and at least one different site.
  • the anti-EGFR antibodies of the present invention can be of any format selected from the group consisting of a full antibody, a F(ab)-, Fab'-SH-, Fv-, Fab'-, F(ab')2- fragment, a chimeric antibody, a CDR-grafted antibody, a fully human antibody, a bivalent antibody- construct, an antibody- fusion protein, a synthetic antibody, a bivalent antibody, a trivalent antibody, a tetravalent antibody, bivalent single chain antibody, a trivalent single chain antibody and a multivalent single chain antibody.
  • the EGFR antibody is preferably cetuximab (IMC-C225), which is a chimeric (human/mouse) IgG monoclonal antibody, also known under the tradename Erbitux®.
  • the EGFR inhibitor is the anti- EGFR antibody cetuximab.
  • Cetuximab has the CAS Registry No.: 205923-56-4.
  • Cetuximab Fab contains the Fab fragment of cetuximab, i.e., the heavy and light chain variable region sequences of murine antibody M225 (US-A1 2004/0006212) with human IgGl C HI heavy and kappa light chain constant domains.
  • the anti-EGFR antibody can be selected from the antibodies described in US-B1 6,235,883, US-B1 5,558,864 and US- Bl 5,891 ,996.
  • the anti-EGFR antibody can be, for example, AGX-EGF (Amgen Inc.) (also known as panitumumab) which is a fully human IgG2 monoclonal antibody.
  • AGX-EGF Amgen Inc.
  • panitumumab also known as panitumumab
  • the sequence and characterization of ABX-EGF which was formerly known as clone E7.6.3, is disclosed in US-B1 6,235,883.
  • the EGFR antibody can also be, for example, EMD72000 (Merck KGaA), which is a humanized version of the murine EGFR antibody EMD 55900.
  • the EGFR antibody can also be, for example: h-R3 (TheraCIM), which is a humanized EGFR monoclonal antibody; Y10 which is a murine monoclonal antibody raised against a murine homologue of the human EGFRvIII mutation; or MDX-447 (Medarex Inc.).
  • the term anti- EGFR antibody also encompasses in the context of the present invention anti-EGFR antibody drug conjugates (ADCs).
  • ADCs anti-EGFR antibody drug conjugates
  • antibody drug conjugates are encompassed by the present invention which comprise/consist of an anti-EGFR antibody linked to a cytotoxic component.
  • the EGFR inhibitor may also refer to an EGFR tyrosine kinase inhibitor. Examples of EGFR tyrosine kinase inhibitors are known in the art and include, e.g., erlotinib and/or gefinitib.
  • the EGFR-inhibitors useful in the context of the present invention may also be small molecules. Any molecule that is not a biological molecule is considered herein to be a small molecule. Some examples of small molecules include organic compounds, organometallic compounds, salts of organic and organometallic compounds, saccharides, amino acids, and nucleotides. Small molecules further include molecules that would otherwise be considered biological molecules, except their molecular weight is not greater than 450. Thus, small molecules may be lipids, oligosaccharides, oligopeptides, and oligonucleotides and their derivatives, having a molecular weight of 450 or less. It is emphasized that small molecules can have any molecular weight.
  • the anti-EGFR inhibitor may be a small molecule that inhibits the growth of tumor cells that express EGFR or a small molecule that inhibits the growth of refractory tumor cells that express EGFR. Numerous small molecules have been described as being useful to inhibit EGFR.
  • IRESSA ZD1939
  • TARCEVA 4-(substitutedphenylamino)quinozaline derivative [6,7- Bis(2-methoxy-ethoxy)-quinazolin-4-yl]-(3-ethynyl-l-phenyl)amine hydrochloride] EGFR inhibitor (see WO 96/30347).
  • TARCEVA® may function by inhibiting phosphorylation of EGFR and its downstream PI3/Akt and MAP (mitogen activated protein) kinase signal transduction pathways resulting in p27-mediated cell-cycle arrest (see Hidalgo et al., Abstract 281 presented at the 37th Annual Meeting of ASCO, San Francisco, CA, 12-15 May 2001).
  • PI3/Akt and MAP mitogen activated protein
  • small molecules are also reported to inhibit EGFR, many of which are thought to be specific to the tyrosine kinase domain of an EGFR.
  • Some examples of such small molecule EGFR antagonists are described in WO 91/116051 , WO 96/30347, WO 96/33980, WO 97/27199.
  • specific small molecule EGFR antagonists include Cl-1033 (Pfizer Inc.) or compounds thereof being optionally substituted or polysubstituted.
  • HTS high throughput screening
  • cancer cell(s), cancer tissue(s), and/or tumor sample(s) obtained from a subject, preferably a patient, suffering from colorectal cancer (CRC) for responsiveness/sensitivity to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably cetuximab.
  • CRC colorectal cancer
  • Suitable (HTS) approaches are known in the art. Screening-assays are usually performed in liquid phase, wherein for each cell/tissue/cell culture to be tested at least one reaction batch is made.
  • Typical containers to be used are micro titer plates having, for example, 384, 1536, or 3456 wells (i.e. multiples of the "original" 96 reaction vessels).
  • Robotics, data processing and control software and sensitive detectors are further commonly used components of a HTS device.
  • robot system are used which transport micro titer plates from station to station for addition and mixing of sample(s) and reagent(s), incubating the reagents, and final readout (detection).
  • HTS can be used in the simultaneous preparation, incubation, and analysis of many plates.
  • the assay can be performed in a single reaction (which is usually preferred), may, however, also comprise washing, and/or transfer steps.
  • Detection can be performed taking advantage of radioactivity, luminescence or fluorescence, like fluorescence- resonance-energytransfer (FRET), fluorescence polarisation (FP) and the like.
  • FRET fluorescence- resonance-energytransfer
  • FP fluorescence polarisation
  • the tumor samples described herein can also be used in such a context.
  • cellular assays and in vivo assays can be employed in HTS.
  • Cellular assays may also comprise cellular extracts, i.e. extracts from cells, tissues and the like.
  • cancer cell(s), cancer tissue(s) or tumor sample(s) as biological sample (in particular a sample obtained from a patient/subject suffering or being prone to suffer from colorectal cancer (CRC)), whereas in vivo assays (wherein suitable animal models are employed, e.g. the herein described mouse models) are particularly useful in the validation monitoring of the treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • an EGFR inhibitor preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • follow up assays can be performed by re-running the experiment to collect further data on a narrowed set (e.g. samples found "positive" in the first assay), confirming and refining observations.
  • a suitable readout in animal (in vivo) models is tumor growth (or respectively the complete or partial inhibition of tumor growth, and/or its remission).
  • the herein described HTS methods for the detection of copy number changes include but are not limited to sequencing technologies such as whole genome sequencing and exome sequencing.
  • the exome sequencing is a techniques for sequencing all the differentially expressed genes in a genome (known as the exome) of, e.g., extracts from cells, tissues or tumor samples obtained from a patient (responder and/or non- responder).
  • cell(s) refers to a single cell or a plurality of cells.
  • plural of cells means in the context of the present invention a group of cells comprising more than a single cell. Thereby, the cells out of said group of cells may have a similar function. Said cells may be connected cells, and/or separate cells.
  • tissue in the context of the present invention particularly means a group of cells that perform a similar function.
  • sample refers in the context of the present invention to all biological tissues, all fluids such as blood, ascites, tear fluid, pleura effusion, liquor, lymph, urine, cerebral fluid, faeces or hair roots.
  • Tissues may be, e.g. epithelial tissue, connective tissue such as bone or blood, muscle tissue such as visceral or smooth muscle and skeletal muscle, as well as nervous tissue.
  • the “sample” is collected from the patient or subjected to the method or treatment according to the invention.
  • a “tumor sample” is a sample of the tumor to be treated. Such sample may be for example taken from an excised tumor, for example, tumor tissue retrieved by surgery.
  • the cell(s), tissue(s) or tumor sample(s) to be selected comprise/are derived from or are (a) tumor cell(s), preferably (a) colorectal cancer cell(s).
  • the tumor cell(s) may, for example, be obtained from a biopsy, in particular a biopsy/biopsies from a patient/subject suffering from or being prone to suffering from colorectal cancer (CRC). It is preferred herein that said subject is a human.
  • the cancer cell(s) may be obtained from a biopsy, in particular a biopsy/biopsies from a patient/subject suffering from colorectal cancer (CRC)".
  • said tumor sample(s) or cancer cell(s) may be obtained from any biological source/organism, particularly any biological source/organism, suffering from or being prone to suffer from colorectal cancer (CRC).
  • the (tumor) cell(s) or (cancer) cell to be contacted is (are) obtained/derived from a subject, preferably a patient, suffering from colorectal cancer (CRC).
  • said tumor/cancer cell(s) may be (are) derived from an animal or mammal.
  • the meaning of the terms "animal” or “mammal” is well known in the art and can, for example, be deduced from Wehner und Gehring (1995; Thieme Verlag).
  • Non-limiting examples for mammals are even-toed ungulates such as sheep, cattle and pig, odd-toed angulates such as horses as well as carnivores such as cats and dogs.
  • DNA samples are derived from organisms that are economically, agronomically or scientifically important.
  • Scientifically or experimentally important organisms include, but are not limited to, mice, rats, rabbits, guinea pigs and pigs.
  • the tumor cell(s) may also be obtained from carnivores such as cats or dogs or, for example from primates which comprise lemurs, monkeys and apes.
  • carnivores such as cats or dogs or, for example from primates which comprise lemurs, monkeys and apes.
  • the meaning of the terms “dog, “cat”, “primate”, “lemur”, “monkey” and “ape” is known and may, for example, be deduced by an artisan from Wehner und Gehring (1995, Thieme Verlag).
  • the tumor or cancer cell(s) is (are) most preferably derived from a human being suffering from the above-mentioned colorectal cancer.
  • particular useful cells in particular tumor or cancer cells, are, accordingly, human cells. These cells can be obtained from e.g. biopsies or from biological samples but the term "cell” also relates to in vitro cultured cells.
  • the present invention relates to an in vitro method for the identification of a responder to an EGFR inhibitor or a subject sensitive to an EGFR inhibitor, said method comprising the following steps:
  • an expression of at least one of said gene(s) is indicative for a responding subject or is indicative for a sensitivity of said patient to an EGFR inhibitor.
  • the present invention relates to a method for the identification of a responder to an EGFR inhibitor or a subject sensitive to an EGFR inhibitor, said method comprising determining the gene expression of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9), whereby an expression of at least one of said gene(s) is indicative for a responding subject or is indicative for a sensitivity of said patient to an EGFR inhibitor.
  • the present invention also relates to a method of monitoring the efficacy of an EGFR inhibitor treatment of colorectal cancer (CRC) in a subject suffering from said disease comprising the steps of:
  • sample(s) may, for example, be obtained by (a) biopsy (biopsies).
  • said sample is obtained from a subject/patient suffering from colorectal cancer (CRC).
  • said sample is obtained from (a) tumor(s) and, accordingly, is (a) tumor cell(s) or (a) tumor tissue(s).
  • tumor sample(s) may be obtained from subjects/patients suffering from colorectal cancer (CRC).
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GL 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NMJ304617; version no.: NM_004617.3; GL325974483) (and/or any other gene(s) as shown in Table 3 ( Figure 8)) and (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes selected from the group consisting of ALOX5 (NCBI accession no.: NM_001320861
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) .
  • HEATR2 NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903
  • KV NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM 011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483)
  • any other gene(s) as shown in Table 3 ( Figure 8) can be combined with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 further
  • HEATR2 NCBI accession no.: NM 017802; version no.: NM_017802.3; GI:157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM 004617; version no.: NM_004617.3; GI:325974483 are preferred.
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM O 17010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483 in the context of the present invention is shown in Table 4 ( Figure 9).
  • HEATR2 NCBI accession no.: NM_017802; version no.: NMJH7802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM O 17010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GL1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) in combination with each other apply here, mutatis mutandis, to any of the remaining markers (or various combinations thereof).
  • PIGU NCBI accession no.: NM_080476; version no.: NM 080476.4; GL52426746
  • SNRPN NCBI accession no.: NM 003097; version no.: NM_ 003097.4; GI:1011750893
  • FHDC1 NCBI accession no.: NM_033393; version no.: NM_033393.2; GI: 145309323
  • HEATR2 NCBI accession no.: NM 017802; version no.: NM_ 017802.3; GI:157388903
  • SLC39A2 NCBI accession no.: NM_014579; version no.: NM_014579.3; GI:291621691
  • FYN NCBI accession no.: XM 017010650; version no.: XM 017010650; version no.: XM 017010650; version no.: XM 017010650; version no.: X
  • the gene expression/amplification status of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes selected from the group consisting of SORBSl (NCBI accession no.: XM 017015500; version no.: XM_017015500.1 ; GI: 1034566000), EREG (NCBI accession no.: NM_001432; version no.: NM_001432.2; GI: 119703747), RAMP2 (NCBI accession no.: NM 005854; version no.: NM_005854.2; GI: 118572584), GDPD5 (NCBI accession no.: NM_030792; version no.: NM_030792.6; GI: 189571656), HEATR2 (NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903
  • “Expression” refers to transcription and translation occurring within a host cell.
  • the level of expression of a DNA molecule in a host cell may be determined on the basis of either the amount of corresponding mRNA that is present within the cell or the amount of the protein encoded by the respective gene produced by the host cells. Further detail for the term "expression” within the context of the present invention can be obtained via a review of Sambrook et al. (2012), A Laboratory Manual, Fourth Edition, ISBN 978-1 -9361 13-41 -5.
  • the expression of said gene(s) is determined by determining RNA levels of the respective gene(s) or protein level(s) encoded by the respective gene(s).
  • the present invention has been exemplified by using the expression determination through determination of mRNA levels using RNA sequencing techniques. The skilled person will however acknowledge that the method may likewise be performed using different techniques and detection methods suited for determining the expression level of genes.
  • Methods for determining the expression level of a gene on the nucleic acid level, i.e. on RNA levels are known by those skilled in the art and include hybridization-based, PCR-based and sequencing-based methods, including next generation sequencing (NGS). Such methods are generally known by those skilled in the art.
  • the methods may be applied to detect the expression of one or more certain genes.
  • hybridization probes and/or primers are used to detect and/or amplify a certain nucleic acid sequence. It will be understood by the skilled person that it may be desirable to reverse transcribe the mRNA prior to detection. Reverse transcription using Reverse-Transcriptase is also commonly known (see inter alia Sambrook et al. (2012), A Laboratory Manual, Fourth Edition, ISBN 978-1-9361 13-41-5). Likewise there are kits and assays available allowing sequencing the entire genome or transcriptome. It may hence be preferred to sequence the entire transcriptome of a sample in order to gain information about the entire transcription levels. The assessment of certain expression levels, e.g.
  • RNAseq libraries may be prepared to include modifications preserving strand-specific information (Parkhomchuk D, et al., Nucleic Acids Res. 37(18) (2009), e!23). Sequencing of the so generated libraries may be performed by common methods.
  • RNAseq libraries either prepared using TruSeq RNA Sample Prep Kit v2 (Alumina, set A: RS- 122-2001 ; set B: RS- 122-2002) with modifications preserving strand- specific information or using TruSeq Stranded mRNA Sample Prep Kit (Illumina, set A: RS- 122-2101 ; set B: RS-122-2102).
  • TruSeq Stranded mRNA Sample Prep Kit Illumina, set A: RS- 122-2101 ; set B: RS-122-2102.
  • Ribo-ZeroTM Magnetic Gold Kit Epicentre, MRZG 12324
  • Sequencing (2 51 bp) was performed on HiSeq 2000/2500 instruments with v3 chemistry. In the context of the present invention the use of those kits and assays is preferred.
  • Oligonucleotide primers and probes having the desired sequence may be prepared using any suitable method, such as, for example, the phosphotri ester and phosphodiester methods or automated embodiments thereof.
  • diethylophosphoramidites are used as starting materials and may be synthesized (Beaucage et al, Tetrahedron Letters, 22 (1981), 1859-1862).
  • One method for synthesizing oligonucleotides on a modified solid support is described in US Bl 4,458,006. It is also possible to use a primer which has been isolated from a biological source (such as a restriction endonuclease digestion).
  • Preferred primers or hybridization probes have a length of from about 15-100, more preferably about 20-50, most preferably about 20-40 bases.
  • RNA reads may be first aligned to the sequences of a database to identify the gene(s). Such alignment may be for example performed against hgl 9 (Kent et al., Genome Res. 12(6) (2002), 996-1006; Kent et al, Nature. 409(6822) (2001), 860-921) using BWA (Li et al, Bioinformatics 25 (2009), 1754-1760) and SAMtools (Li et al, Bioinformatics 25 (2009), 2078-2079). Mapped reads may be annotated, e.g. using Ensembl v70.
  • Gene expression levels may then be quantified by detecting the relative amount of an RNA of a certain gene, e.g. using reads per kilobase of exon model per million mapped reads (RPKM) as a measure (see Mortazavi A. et al, Nat Methods. 5(7) (2008), 621-628).
  • RPKM per million mapped reads
  • RNA levels for example mRNA levels
  • the expression level of said gene(s) is determined by determining RNA levels by a method selected from the group consisting of hybridization based methods, PCR based methods, real-time-PCR, microarray methods, and RNA sequencing (RNAseq).
  • the expression level may, for example, be detected, assessed or evaluated by an in situ hybridization method, an in situ sequencing method, comparative genomic hybridisation and single-nucleotide polymorphism arrays.
  • exemplary in situ hybridisations are, inter alia, fluorescent in situ hybridisation (FISH), chromogenic in situ hybridisation (CISH) and silver in situ hybridisation (SISH).
  • FISH fluorescent in situ hybridisation
  • CISH chromogenic in situ hybridisation
  • SISH silver in situ hybridisation
  • the expression level of said gene(s) can be determined by the assessment, determination, detection or evaluation of the RNA levels by a method selected from the group consisting of hybridization based methods, PCR based methods, real-time-PCR, microarray methods and RNA sequencing.
  • the expression level may be determined by determining in the sample the amount of protein encoded by the gene. This may be performed using common techniques known by those skilled in the art. These techniques include immunoassays. Suitable immunoassays may be selected from the group of immunoprecipitation, enzyme immunoassay (EIA), enzyme-linked immunosorbent assays (ELISA), radioimmunoassay (RIA), fluorescent immunoassay, a cytometric bead array (CBA), a chemiluminescent assay, an agglutination assay, nephelometric assay, turbidimetric assay, a Western Blot, a competitive immunoassay, a non-competitive immunoassay, a homogeneous immunoassay a heterogeneous immunoassay, a bioassay and a reporter assay such as a luciferase assay.
  • the immunoassay is an enzyme-linked immunosorbent assay (ELISA), enzyme-
  • the present invention also relates to a method of diagnosing (colorectal cancer (CRC)) in a subject/patient suspected of suffering from colorectal cancer or suspected of being prone to suffering from colorectal cancer (CRC) comprising the steps of a) determining in a cell or tumor sample obtained from said subject/patient the gene expression or protein level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9); and b) comparing the expression or activity of said at least one marker gene determined in a) with a reference gene expression level of said one or more gene(
  • the present invention also relates to a method of monitoring the efficacy of a treatment of a colorectal cancer (CRC) in a subject/patient suffering from said cancer or being prone to suffer from said cancer comprising the steps of a) determining in (a) cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from said subject/patient the gene expression or protein level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9); and b) comparing the gene expression or protein level of said one or more marker gene(s) determined in a
  • the term "gene expression level" as used herein refers to the gene expression status as described elsewhere herein.
  • the method of monitoring the efficacy of a treatment of a cancer may comprise a step of determining in a cell or tissue sample obtained from a subject/patient suffering from colorectal cancer (CRC) (e.g.
  • the present invention also relates to a method of predicting the efficacy of a treatment of a colorectal cancer (CRC) for a subject/patient suffering from said disease comprising the steps of a) determining in (a) cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from said subject/patient the expression of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9); and b) comparing the expression of said one or more gene(s) determined in (a sample from) a reference/control subject/patient (responder and/or non-responder) in
  • the treatment of colorectal cancer may comprise the administration of an EGFR inhibitor, preferably an anti-EGFR antibody as described herein.
  • the colorectal cancer (CRC) is a malignant tumor that arises from cells of the colon or the rectum.
  • CRC is classified into hypermutated or non-hypermutated, chromosomal instable tumors. Hypermutated case show either microsatellite instability (MSI) caused by defects in the mismatch repair mechanism or mutations in POLE or POLD1.
  • MSI microsatellite instability
  • Chromosomal instable CRC is characterized by extensive chromosomal rearrangements.
  • a recent attempt to define four consensus molecular subtypes in CRC was published by Guinney et al.
  • the patient/subject suffering from colorectal cancer may be a subject/patient characterized by having a colorectal cancer (CRC) which can be classified into hypermutated, non-hypermutated, and/or chromosomal instable tumors.
  • the subject/patient suffering from colorectal cancer may be a subject/patient characterized by having a colorectal cancer (CRC) which does not have (a) KRAS, BRAS and/or NRAS mutation(s) (see Gong J. et al, J. Gastrointest. Oncol. 7 (2016), 687-704).
  • the cell(s), tissue(s) or sample(s) obtained from the patient/subject suffering from CRC is (are) characterized by not having (a) KRAS, BRAS, and/or NRAS mutation(s).
  • the cell(s), tissue(s) or sample(s) obtained from the patient/subject suffering from CRC is (are) characterized by having (a) KRAS, BRAS, and/or NRAS mutation(s).
  • cell(s), tissue(s) or tumor sample(s) obtained from the patient/subject suffering from CRC which is (are) characterized by not having (a) KRAS, BRAS, and/or NRAS mutation(s).
  • a responder to an EGFR inhibitor or a subject/patient sensitive to an EGFR inhibitor may be identified in accordance with the present method.
  • the present invention provides the possibility to recognize changes of any one of the genes shown in Table 1 ( Figure 6), more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) immediately once they occur, for example, by determining the gene expression level of said marker gene(s).
  • the assessment/evaluation/detection of the expression status of any of the above marker genes is sufficient for determining whether a subject/patient is likely to respond to or is sensitive to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, whether a (tumor) cell of a colorectal cancer is likely to respond or is responsive to treatment with an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • the assessment/evaluation/detection of the expression status of any of the above marker genes (and their combinations) is also sufficient for diagnosing sensitivity to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • the expression status alone of any of the above marker genes is indicative for a sensitivity/responsiveness to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to n anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab, and the expression level/activity of the gene products of the above marker genes need not be determined in addition to the gene expression status.
  • the present invention relates to means, methods and uses which are based on the early recognition of (an) expression change(s) of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of 4, 5, 6, 7, 8, 9, 10, 1 1 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) and/or the protein level of the respective gene(s).
  • "early” particularly means prior to (the onset of) a (complete or partial) cytogenetic or hematological response or a response measured by any imaging technique and/or to the outbreak of colorectal cancer (CRC).
  • "early" monitoring the efficacy of a therapy/treatment of said colorectal cancer may be at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 10, or at least 14 days prior to (the onset of) a (complete) cytogenetic or hematological response or a response measured by any type of imaging technique to said therapy/treatment and/or at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 10, at least 12, at least 15, or at least 18 month prior a complete cytogenetic or hematological response or a response measured by any type of imaging technique to said therapy/treatment (of the patient or control patient (responder)), wherein the longer periods are preferred.
  • "early” monitoring the efficacy of a therapy/treatment of said cancer may also be at most 1 , at most 2, at most 3, at most 4, at most 5, at most 6, at most 7, at most 10, or at most 14 days after (onset of) the therapy/treatment of said cancer, wherein the shorter periods are preferred. Most preferably, it is envisaged to already monitor the efficacy of a therapy/treatment of said cancer at the day the therapy/treatment was initiated, i.e.
  • expression of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of the expression of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional gene(s) as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) may be determined daily during the first week after initiation of the therapy/treatment, weekly during the first month of the therapy/treatment and, afterwards, monthly.
  • the reference activity/expression level may be taken at the day the therapy/treatment is initiated, from the subject/patient to be treated and/or from a corresponding reference/control subject/patient (responder/non-responder); see below.
  • "early" predicting the efficacy of a therapy/treatment of the cancer defined herein may be at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 10, or at least 14 days prior to (the onset of) a (complete) cytogenetic or hematological response to said therapy/treatment and/or at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 10, at least 12, at least 15, or at least 18 month prior a complete cytogenetic or hematological response or a response measured by any type of imaging technique to said therapy/treatment, wherein the longer periods are preferred.
  • "early" predicting the efficacy of a therapy/treatment of the cancer defined herein may also be at most 1 , at most 2, at most 3, at most 4, at most 5, at most 6, at most 7, at most 10, or at most 14 days after (onset of) the therapy/treatment of the cancer defined herein, wherein the shorter periods are preferred. Most preferably, it is envisaged to already monitor the efficacy of a therapy/treatment of said colorectal cancer (CRC) at the day the therapy/treatment was initiated, i.e.
  • CRC colorectal cancer
  • "early" predicting the efficacy of a therapy/treatment of the cancer defined herein may also be at most 1 , at most 2, at most 3, at most 4, at most 5, at most 6, at most 7, at most 10, or at most 14 days after diagnosis of the cancer, wherein the shorter periods are preferred. Most preferably, it is envisaged to already predict the efficacy of an EGFR inhibitor therapy/treatment of said colorectal cancer (CRC) at the day of diagnosis.
  • CRC colorectal cancer
  • the present invention is particularly useful for monitoring the efficacy of an EGFR inhibitor therapy/treatment of the colorectal cancer (CRC) as defined herein.
  • CRC colorectal cancer
  • the present invention is particularly useful for monitoring the efficacy of an EGFR inhibitor therapy/treatment of the colorectal cancer (CRC) as defined herein.
  • CRC colorectal cancer
  • monitoring the efficacy of a certain kind of an EGFR inhibitor therapy/treatment is regularly applied in clinical routine.
  • the skilled person is aware of the meaning of monitoring the efficacy of a certain kind of an EGFR inhibitor therapy/ treatment.
  • the meaning of the term “monitoring” encompasses the meaning of terms like "tracking", “discovering” etc.
  • monitoring the efficacy of a EGFR inhibitor therapy/treatment of colorectal cancer refers to monitoring whether a subject/patient suffering from said disease (or being prone to suffering from said cancer) responds at all to an EGFR inhibitor therapy/treatment of said disease and/or how the course of said respond is (e.g. how fast/slow the respond is and/or to what extent the respond is).
  • the present invention is further useful for predicting the efficacy of a therapy/treatment of the colorectal cancer (CRC) as defined herein.
  • CRC colorectal cancer
  • predicting the efficacy of an EGFR inhibitor therapy/treatment is highly desired in clinical routine, since it allows for preventing the disease (colorectal cancer (CRC)) and/or increasing the efficiency of an EGFR- inhibitor therapy/treatment and hence, leads to savings in cost and time and to a higher lifespan/likelihood of survival or of remission ('Genesung') of the affected patient.
  • the term "predicting the efficacy of a therapy/treatment of colorectal cancer (CRC) for a subject/patient” is used in basically the same sense like determining whether, and/or to what extent, a subject/patient exhibits susceptibility to such an EGFR inhibitor therapy/treatment, i.e. whether said subject/patient will or would respond at all to an EGFR inhibitor therapy/treatment of said disease and/or how the course of said respond will or would be (e.g. how fast/slow the respond is and/or to what extent the respond is).
  • a subject/patient exhibits susceptibility to said colorectal cancer (CRC) in accordance with this invention, when its (amplified) activity/expression level of one or more gene(s) as shown in Table 1 ( Figure 6), more preferably of (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), optionally in combination with the additional determination of (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or most preferably of (at least) 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) is differential.
  • said expression level is differential as defined herein.
  • the "predicting the efficacy of a therapy/treatment of the colorectal cancer (CRC)" in accordance with this invention may be performed after initiation of the EGFR inhibitor therapy/treatment, i.e. during the already ongoing EGFR inhibitor therapy/treatment.
  • said "predicting” may be performed during the herein described monitoring the efficacy of an EGFR inhibitor therapy/treatment of said colorectal cancer, preferably early after the beginning of said monitoring.
  • the predicting may be based on results from said monitoring obtained at a certain point in time of the ongoing EGFR inhibitor therapy/treatment.
  • said point in time is an early point in time, like, for example that point in time, when a first result from said monitoring has been obtained, hi cases where the "predicting the efficacy of an EGFR inhibitor therapy/treatment of the colorectal cancer (CRC)" as defined herein is performed during an already ongoing EGFR inhibitor therapy/treatment, it refers to the following/subsequent efficacy of said EGFR inhibitor therapy/treatment.
  • the "predicting the efficacy of an EGFR inhibitor therapy/treatment of the colorectal cancer (CRC)" may be performed (immediately) after diagnosis but, however, prior to initiation of the EGFR inhibitor therapy/treatment.
  • predicting the efficacy of an EGFR inhibitor therapy/treatment of said colorectal cancer refers to the efficacy of an EGFR inhibitor therapy/treatment which has not yet been initiated (or has been initiated substantially at the same point in time when the "predicting" was performed).
  • one non-limiting example of a healthy reference/control subject/patient is one having, e.g., (a) non-amplified, i.e. an activity/expression is not determinable/differential, HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483), and/or any other gene(s) shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_01 1515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483), and/or any other gene(s) shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GL 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483), and/or any other gene(s) shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of at least 6, 7, 8, 9, 10,
  • the reference/control subject/patient is, in one embodiment, envisaged to be a subject/patient suffering from said cancer, i.e.
  • a subject/patient having, for example, an differential activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483), and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of at least 6, 7,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI:157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483), and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17,
  • different, higher or lower means at least 1.0 fold, at least 1.5 fold, at least 2 fold, at least 2.5 fold, at least 3 fold, at least 4 fold, at least 5 fold, at least 7 fold, at least 10 fold, at least 15 fold, at least 25 fold, at least 50 fold, at least 100 fold, at least 200 fold different, higher or lower, wherein the higher values are preferred. Whether, in which direction (i.e., in which direction (i.e., in which direction (i.e.
  • HEATR2 NCBI accession no.: NM_ 017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM _011515987; version no.: XM_011515987.2; GI:1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM 004617.3; GL325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/
  • the reference/control subject/patient is subjected to the same EGFR inhibitor treatment of the colorectal cancer (CRC) as the subject/patient suffering from colorectal cancer (CRC) described and defined herein.
  • Said reference/control subject/patient may be a responder (positive reference/control) or non- responder (negative reference/control) to this treatment.
  • a subject/patient is a "responder” or “non-responder” with respect to a colorectal cancer (CRC) EGFR inhibitor treatment/therapy can be evaluated by the skilled person on the basis of his common general knowledge and/or the teaching provided herein.
  • a "responder” may be a subject/patient whose cytological/hematological parameters and/or (differential) HEATR2 (NCBI accession no.: NMJH7802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI.T 034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XMJH 1515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM 004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 additional genes
  • a "responder” may be a subject/patient not suffering from one of the herein defined resistances.
  • a “non-responder” may be a subject/patient whose cytological/hematological parameters and/or (aberrant) activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM 017802.3; GI: 157388903), 7N (NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 3
  • the patient responds to colorectal cancer (CRC) EGFR inhibitor treatment/therapy, if the activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM O 17010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM _011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NMJ304617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23
  • HEATR2 (NCBI accession no.: NM 017802; version no.: ⁇ _017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM _004617; version no.: NM__004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10, 11 ,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM 017010650; version no.: XM _017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes
  • a skilled person is readily in the position to determine whether a patient responds to colorectal cancer (CRC) EGFR inhibitor treatment/therapy by evaluation of the expression level/activity of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NMJ304617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM 004617; version no.: NM 004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes
  • one non-limiting example of a diseased reference/control subject/patient (responder and/or non-responder) suffering from a colorectal cancer (CRC) defined herein (or being prone to suffering from a susceptibility thereto) is one having an amplified HEATR2 (NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 103465471 1), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM 004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8)
  • the skilled person is aware of how a typical/desired response to a known EGFR inhibitor therapy/treatment of colorectal cancer (CRC) should proceed or is intended to proceed. Moreover, the skilled person can consider how a typical/desired response to a (unknown) EGFR inhibitor therapy/treatment of a colorectal cancer proceeds or is intended to proceed. Based on this knowledge, the means, methods and uses of this invention referring to the efficacy of an EGFR inhibitor therapy/treatment of such a cancer can, for example, also be carried out without employing (a sample of) a particular reference/control subject/patient, i.e.
  • HEATR2 NCBI accession no.: NM_017802; version no.: NMJD17802.3; GI: 157388903
  • FYN NCBI accession no.: XM_ 017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI:1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NMJD04617.3; GL325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4,
  • the subject/patient is a "responder”. If the response of a subject/patient is as fast (or even faster) than the "typical/desired response", the subject/patient is a "responder". If the response of a subject/patient is slower than the "typical/desired response", the subject/patient is a "non-responder" (when no substantial response can be seen) or "weak-responder".
  • the efficacy of a cancer treatment/therapy can be determined taking account of the change in the activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as
  • a skilled person is able to assess the efficacy of a treatment by evaluating the activity/expression level of the above marker gene(s) at various points in time during the treatment (e.g. prior to the treatment, after start of the treatment, and subsequently in intervals during the treatment).
  • a (desired) efficacy of a treatment of a cancer described herein or susceptibility thereto is indicated/predicted, when the aberrant (i.e. enhanced or decreased) activity or expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), 7N (NCBI accession no.: XM _017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GF.325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4,
  • the efficacy of a treatment of the cancer defined herein is high, when the subject/patient (to be) treated responds as fast (or even faster) and as complete as a "responder”, i.e. exhibits a "typical/desired response".
  • the efficacy of an EGFR inhibitor treatment of the colorectal cancer is high, if the patient treated shows a "typical/desired response".
  • the efficacy is high, when the activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_ 017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM 011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM 004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least
  • the efficacy of an EGFR inhibitor treatment of the colorectal cancer is low, if the patient treated does not show a "typical/desired response".
  • the efficacy is low, when the activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI:157388903), KV (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM 011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI:157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM 004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and
  • Such an "own" reference sample may be obtained prior to (or at the beginning of) the treatment/therapy, hi this specific case, the "reference/control subject/patient” would be the subject/patient to be treated itself.
  • the efficacy of the EGFR inhibitor treatment would then be assessed on the basis of how the activity or expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XMJH 1515987; version no.: XM 011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22,
  • the efficacy of an EGFR inhibitor treatment of the colorectal cancer is assessed based on the comparison of the activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or
  • different, higher or lower means at least 1.5 fold, at least 2 fold, at least 2.5 fold, at least 3 fold, at least 4 fold, at least 5 fold, at least 7 fold, at least 10 fold, at least 15 fold, at least 25 fold, at least 50 fold, at least 100 fold or at least 200 fold different, higher or lower, wherein the higher values are preferred.
  • CRC colorectal cancer
  • HEATR2 N-(NCBI accession no.: NM_017802; version no.: NM_017802.3; GI:157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 (NCBI accession no.: NM_017802; version no.: NM_0
  • a responder shows expression level/activity of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM 011515987.2; GI:1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM 004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6,
  • a responder may show reduced or increased expression level/activity of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), KV (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_ 004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (
  • CRC colorectal cancer
  • HEATR2 NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21
  • the cancer is characterised by a low expression level/activity of at least one of the marker genes and if the expression level/activity of HEATR2 (NCBI accession no.: NM_017802; version no.: NM 017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XMJH1515987; version no.: XM_011515987.2; GI: 103465471 1), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM 004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24
  • HEATR2 N-(NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM 011515987.2; GL 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NMJ304617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21
  • a reference/control sample can be obtained from a non-responder or can be obtained prior to/at the beginning of a therapy/treatment of a cancer. Accordingly, if the difference between the expression level/activity of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8,
  • a responder shows a reduced expression level/activity of HEATR2 (NCBI accession no.: NM _017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XMJ)11515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23
  • HEATR2 NCBI accession no.: NMJM7802; version no.: NMJH 7802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XMJ
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • 7N NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM 011515987.2; GI:1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10,
  • HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI:1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004 17.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10, 11 , 12,
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM 011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 68) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10, 11, 12, 13,
  • HEATR2 activity/expression level of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI:157388903), KV (NCBI accession no.: XM_ 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM _004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10, 11
  • HEATR2 activities/expression levels of HEATR2 (NCBI accession no.: NM_017802; version no.: NM 017802.3; GI:157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM__011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10,
  • Non-limiting examples of schemes of determining activities/expression levels of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM 011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8,
  • the present invention also relates to the use of a (transgenic) cell or a (transgenic) non-human animal having at least one gene marker/predictor as defined herein for screening and/or validation of an EGFR inhibitor medicament for the treatment of colorectal cancer (CRC).
  • the term "cell" as used in this context may also comprise a plurality of cells as well as cells comprised in a tissue.
  • a cell to be used may, for example, be a primary tumor cell.
  • the tumor cell or cell to be used in the screening or validation method may be obtained from samples from a (transgenic) non-human animal suffering from colorectal cancer (CRC).
  • the tumor cell or cell may also be obtained from patient samples (e.g.
  • the tumor cell or cell may be a human tumor cell.
  • such a cell to be used in the present screening or validation methods may be comprised in a tissue or tissue sample, like in a sample biopsy.
  • the used non-human animal or cell may be transgenic or non transgenic.
  • Transgenic in this context particularly means that at least one of the marker genes as described or defined herein is over- or under-expressed or has a higher or lower activity.
  • marker genes as HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), KV (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM 004617; version no.: NM_004617.3; GL325974483) and/or any
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_ 011515987; version no.: XMJ311515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483
  • any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 genes as shown in Table 2 ( Figure 7), and/or of (at least)
  • Transgenic in this context may also mean that HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) (and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7,
  • HEATR2 NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM O 17010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10, 11 ,
  • a preferred (transgenic) non-human animal or (transgenic) cell in context of the invention suffers from colorectal cancer (CRC) for the treatment of which the medicament is to be screened and/or validated.
  • CRC colorectal cancer
  • the (transgenic) non-human animal or (transgenic) cell is particularly intended to suffer from HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GL157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM 004617.3; GI:325974
  • HEATR2 NCBI accession no.: NM_017802; version no.: NM 017802.3; GI: 157388903
  • FYN NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM_011515987; version no.: XM 011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GF325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or of (at least) 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
  • transgenic non-human animal or “transgenic cell” as used herein refers to a non- human animal or cell, not being a human that comprises genetic material different from the genetic material of a corresponding wild-type animal/cell.
  • Genetic material in this context may be any kind of a nucleic acid molecule, or analogues thereof, for example a nucleic acid molecule, or analogues thereof as defined herein.
  • “Different” in this context means additional or fewer genetic material with respect to the genome of the wild-type animal/cell and/or rearranged genetic material, i.e. genetic material present at a different locus of the genome with respect to the genome of the wild-type animal/cell.
  • the (transgenic) non-human animal or (transgenic) cell is or is derived from a mammal.
  • Non-limiting examples of the (transgenic) non-human animal or derived (transgenic) cell are selected from the group consisting of a mouse, a rat, a rabbit, a guinea pig and a Drosophila.
  • the (transgenic) cell in accordance with this invention may be an animal cell, for example, a non-human animal cell.
  • human cells are envisaged to be employed as cells in context of the present invention.
  • such cell may be an embryonic stem cell (ES cell), particularly a non- human animal ES, like, for example, a mouse or rat ES cell.
  • the (transgenic) cell as described herein, particularly the ES cell, may also be used for generating the (transgenic) non-human animal as described herein.
  • the ES cell technology for generating transgenic animals is well known in the art and for example is described in Pirity et al. (Methods Cell Biol, 1998, 57:279).
  • the (transgenic) cell may be a prokaryotic or eukaryotic cell.
  • the (transgenic) cell may be a bacterial, yeast, fungus, plant or animal cell.
  • the transformation or genetically engineering of a cell with a nucleic acid construct or vector can be carried out by standard methods, as for instance described in Sambrook and Russell (2001 ), Molecular Cloning: A Laboratory Manual, CSH Press, Cold Spring Harbor, NY, USA; Methods in Yeast Genetics, A Laboratory Course Manual, Cold Spring Harbor Laboratory Press, 1990.
  • the (transgenic) non-human animal or (transgenic) cell as described or defined in context of this invention is particularly useful in methods for screening and/or validation of a medicament for the treatment of cancers as defined and described herein.
  • These screening methods may, in particular, performed in vivo using, for example, (transgenic) animals as described herein (e.g. rats, mice and the like) and/or animals comprising (a) colorectal cancer (CRC) cell(s), (a) tissue(s) or (a) cell culture(s).
  • Said (a) cell(s), (a) tissue(s) or (a) cell culture(s) may, for example, be obtained/derived from (a) colorectal cancer (CRC) tumor cell(s)/tumor(s).
  • said (a) cell(s), (a) tissue(s) or (a) cell culture(s) may be obtained from a subject/patient suffering from a CRC.
  • These in vivo screening methods may in particular comprise measuring and determining differences in tumor volume, for example, in the (transgenic) animals described herein above.
  • the present invention may relate to a method for screening and/or validation of an EGFR-inhibitor for the treatment of a colorectal cancer (CRC).
  • Said method may comprise the steps of
  • HEATR2 NCBI accession no.: NM_017802; version no.: NMJ317802.3; GI: 157388903
  • FYN NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568
  • AHCYL2 NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711
  • TM4SF4 NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with (at least) 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2
  • screening and/or validation of medicaments means, on the one hand, whether a given set of compounds comprises one or more compound(s) that can function as (a) medicament(s), and/or, on the other hand, whether (a) given compound(s) can function as (a) medicament(s). It is particularly intended that the medicaments to be screened and/or validated in context of this invention are medicaments for the treatment, prevention and/or amelioration of a cancer as defined herein.
  • the compound(s)/medicament(s) to be screened and/or validated may be administered to the non-human (transgenic) animal or cell described herein, and, afterwards (for example after a certain period of time sufficient to allow a compound to effect on a cancer as described herein), it is analyzed whether the cancer, or a symptom thereof, of said animal/cell is ameliorated.
  • the present invention also relates to an EGFR inhibitor for use in the treatment of colorectal cancer (CRC) if (a) cancer cell(s), (a) cancer tissue(s) or (a) tumor sample(s) obtained from a subject to be treated exhibits expression of at least one or more gene(s) as shown in Table 1 ( Figure 6), more preferably by determining 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9).
  • CRC colorectal cancer
  • the present invention relates to an EGFR inhibitor for use in the treatment of colorectal cancer (CRC), wherein said EGFR inhibitor is administered to the subject to be treated if (a) cancer cell(s), (a) cancer tissue(s) or tumor sample(s) obtained from the subject to be treated exhibits expression of at least one or more gene(s) as shown in Table 1 ( Figure 6), more preferably by determining 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9).
  • CRC colorectal cancer
  • the present invention also relates to a kit useful for carrying out the method or used of this invention.
  • said kit may comprise oligonucleotides or polynucleotides capable of detecting the amplification status of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GL 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM 011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM 004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) as shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8,
  • said kit may comprise (a) compound(s) required for specifically determining the amplification status of HEATR2 (NCBI accession no.: NM 017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM 017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XMJ311515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 additional genes as shown in Table 2 ( Figure 7), and/or
  • the kit (to be prepared in context) of this invention or the methods and uses of the invention may further comprise or be provided with (an) instruction manual(s).
  • said instruction manual(s) may guide the skilled person (how) to determine amplification status of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), FYN (NCBI accession no.: XM_017010650; version no.: XM_017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM_011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GI:325974483) and/or any other gene(s) shown in Table 3 ( Figure 8)
  • kit (how) to diagnose the susceptibility to an EGFR inhibitor, preferably to an EGFR tyrosine kinase inhibitor or to an anti-EGFR antibody drug conjugate, more preferably an anti-EGFR antibody such as cetuximab.
  • said instruction manual(s) may comprise guidance to use or apply the herein provided methods or uses.
  • the kit (to be prepared in context) of this invention may further comprise substances/chemicals and/or equipment suitable/required for carrying out the methods and uses of this invention.
  • such substances/chemicals and/or equipment are solvents, diluents and/or buffers for stabilizing and/or storing (a) compound(s) required for specifically determining the amplification status of HEATR2 (NCBI accession no.: NM_017802; version no.: NM_017802.3; GI: 157388903), 7N (NCBI accession no.: XM_017010650; version no.: XM 017010650.1 ; GI: 1034649568), AHCYL2 (NCBI accession no.: XM 011515987; version no.: XM_011515987.2; GI: 1034654711), TM4SF4 (NCBI accession no.: NM_004617; version no.: NM_004617.3; GL325974483) and/or any other gene(s) shown in Table 3 ( Figure 8) (optionally in combination with at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 ,
  • the present invention also relates to the use of an oligo- or polynucleotide capable of detecting the expression level(s) of one or more of the gene(s) of Table 1 ( Figure 6), more preferably by determining (at least) 4, 5, 6, 7, 8, 9, 10, 11 , or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining (at least) 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9) for predicting the susceptibility or responsiveness of a subject suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor.
  • CRC colorectal cancer
  • EGFR epidermal growth factor receptor
  • an oligo- or polynucleotide capable of detecting the expression level(s) of 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes (as shown in Figure 8) selected from the group consisting of PIGU (NCBI accession no.: NM_080476; version no.: NM_080476.4; GL52426746), SNRPN (NCBI accession no.: NM 003097; version no.: NM 003097.4; GI: 1011750893), FHDC1 (NCBI accession no.: NMJ333393; version no.: NM_033393.2; GI: 145309323), HEATR2 (NCBI accession no.: NM_017802; version no.: NM _017802.3; GI: 157388903), SLC39A2 (NCBI accession no.: NM_014579; version no.: NM_014579.3; GI:291621691), FY
  • an oligo- or polynucleotide capable of detecting the expression level(s) of 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes (as shown in Figure 9) selected from the group consisting of SORBS 1 (NCBI accession no.: XM 017015500; version no.: XM_017015500.1 ; GI: 1034566000), EREG (NCBI accession no.: NM_001432; version no.: NM_001432.2; GI: 119703747), RAMP2 (NCBI accession no.: NM_005854; version no.: NM_005854.2; GI: 118572584), GDPD5 (NCBI accession no.: NM_030792; version no.: NM_030792.6; GI: 189571656), HEATR2 (NCBI accession no.: NMJH7802; version no.: NM_017802.3
  • the oligonucleotide(s) is (are) about 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 to 100 nucleotides in length.
  • a person skilled in the art is, based on his general knowledge and the teaching provided herein, easily in the position to identify and/or prepare (a) an oligo- or polynucleotide capable of detecting one or more gene(s) as shown in Table 1 ( Figure 6), more preferably by determining 4, 5, 6, 7, 8, 9, 10, 11, or 12 genes as shown in Table 3 ( Figure 8), most preferably by determining 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 ( Figure 9).
  • the Figures show
  • Figure 1 Response to cetuximab in xenografts (PDXs): Heatmap of genes that correlate in their expression to cetuximab (Erbitux®, Merck KGaA) sensitivity.
  • PDX samples and genes are clustered using hierarchical clustering.
  • the drug sensitivity is determined by a treatment in comparison to control (T/C) (as illustrated in a continuous grey scale color code) in PDX: black - strongly responding models, grey - resistant models
  • T/C control
  • Drug sensitivity and mutation status of BRAF (V600E), NRAS and KRAS (G12, G13, Q22, Q61 , A146) are indicated as shown in the caption.
  • the sequence(s) of BRAF can be obtained from the Entrez Gene ID: 673 (Assembly: GRCh37); the sequence(s) of KRAS can be obtained from the Entrez Gene ID: 3845 (Assembly: GRCh37); and the sequence(s) of NRAS can be obtained from the Entrez Gene ID: 4893 (Assembly: GRCh37)).
  • (b) Heatmap includes genes known to be associated with cetuximab sensitivity.
  • Figure 2 12-gene mini-classifier of cetuximab response.. Support vector machine
  • SVM SVM-based machine learning
  • 12 genes i.e.
  • EPH A 4 EPH receptor 4; Entrez Gene ID: 2043, Assembly: GRCh37; (NCBI accession no.: XM_005246374; version no.: XM_005246374.2; GI: 1034612388)), PDE4D (phosphodiesterase 4D; Entrez Gene ID: 5144, Assembly: GRCh37; (NCBI accession no.: XM 017009565; version no.: XM_017009565.1 ; GI: 1034645215)), SYTL5 (synaptotagmin-like 5; Entrez
  • the drug sensitivity is indicated in a continuous color code for T/C in PDX: dark gray - strongly responding models, light gray - resistant models, (c) Respective performances of the OncoTrack (OT) mini-classifier and of the RAS/RAF mutation status in predicting cetuximab sensitivity in the following cohorts OT-PDX (OT) (cross-validation), Experimental Pharmacology and Oncology Berlin-Buch GmbH (EPO) PDX and the Gao et al, 2015 (Gao H. et ai, Nat Med 21 (2015), 1318-1325) PDX (NV).
  • the mutation status was defined by mutations in codon 12 and 13 of KRAS or detected activating mutations in KRAS, BRAF or NRAS (BRAF mutations: V600E; KRAS/NRAS mutations: G12, G13, Q22, Q61 , A146).
  • SD stable disease
  • Sensitivity, specificity and balanced accuracy were calculated based on true positive (TP), true negative (TN), false positive (FP) and false negative (FN) annotations and values >0.8 are marked in bold, (d) Same as in (c) but taking as validation cohort of 96 samples merged from OT, EPO and NV.
  • Figure 3 16-gene mini-classifier of cetuximab response. Support vector machine
  • SVM SVM-based machine learning
  • 16 genes i.e.
  • SOX2 (SRY (sex determining region Y)-box 2; Entrez Gene ID: 6657, Assembly: GRCh37; (NCBI accession no.: NM _003106; version no.: NM 003106.3; GI:325651854)), HOXD9 (homeobox 9; Entrez Gene ID: 128869, Assembly: GRCh37; (NCBI accession no.: NM_014213; version no.: NM_014213.3; GI: 194363767)), FYN (FYN oncogene related to SRC, FGR,
  • GRCh37 Assembly: GRCh37; (NCBI accession no.: XM 017015500; version no.: XM 017015500.1 ; GI: 1034566000)), EREG (epiregulin; Entrez Gene ID: 2069, Assembly: GRCh37; (NCBI accession no.: NM_001432; version no.: NM_001432.2; GI:119703747)), GDPD5 (glycerophosphodiester phosphodiesterase domain containing 5; Entrez Gene ID: 81544, Assembly: GRCh37; (NCBI accession no.: NM_030792; version no.: NM_030792.6; GI: 189571656)), PAAF1 (proteasomal ATPase-associated factor 1 ; Entrez Gene ID: 80227, Assembly: GRCh37; (NCBI accession no.: NM_025155; version no.: NM 025155.2; GI:392513657))
  • the drug sensitivity is indicated in a continuous color code for T/C in PDX: dark gray - strongly responding models, light gray - resistant models, (c) Respective performances of the OT mini-classifier and of the RAS/RAF mutation status in predicting cetuximab sensitivity in the following cohorts OT-PDX (OT) (cross-validation), EPO PDX, the Gao et al, 2015 (Gao H. et al, Nat Med 21 (2015), 1318-1325) PDX (NV) and Khambata-Ford et al, 2007 (Khambata-Ford S. et al, J Clin Oncol 25 (2007), 3230-3237) primary tumors (KF).
  • OT-PDX cross-validation
  • EPO PDX the Gao et al, 2015 (Gao H. et al, Nat Med 21 (2015), 1318-1325)
  • NV Khambata-Ford et al, 2007 (Khambata-Ford S
  • the mutation status was defined by mutations in codon 12 and 13 of KRAS or detected activating mutations in KRAS, BRAF or NRAS (BRAF mutations: V600E; KRAS/NRAS mutations: G12, G13, Q22, Q61, A146).
  • SD stable disease
  • Sensitivity, specificity and balanced accuracy were calculated based on true positive (TP), true negative (TN), false positive (FP) and false negative (FN) annotations and values >0.8 are marked in bold, (d) Same as in (c) but taking as validation cohort 164 samples merged from OT, EPO, NV and KF.
  • Figure 4 Performance of the downsized 12-gene mini-classifier. Genes with the lowest predictive power were iteratively excluded from the mini-classifier. The balanced accuracy of the downsized mini-classifier was evaluated on different data sets and plotted over the gene number, (a) OncoTrack PDX cohort, (b) Gao et al, 2015 (Gao H. et al, Nat Med 21 (2015), 1318-1325) PDX cohort. The accuracy was evaluated using the whole cohort or the cohort excluding the stable disease samples, (c) Khambata-Ford et al., 2007 ((Khambata-Ford S. et al, J Clin Oncol 25 (2007), 3230-3237) cohort of primary CRC tumors.
  • the accuracy was evaluated using the whole cohort or the cohort excluding the stable disease samples, (d) EPO PDX cohort (see also Figure 8).
  • the mini-gene classifier accuracy is stable or stays in an acceptable range, i.e. the performance of the 12-gene mini-classifier is more or less independent of the number of applied genes.
  • Figure 5 Performance of the downsized 16-gene mini-classifier. Genes with the lowest predictive power were iteratively excluded from the mini-classifier. The balanced accuracy of the downsized mini-classifier was evaluated on different data sets and plotted over the gene number, (a) OncoTrack PDX cohort, (b) Gao et al. PDX cohort. The accuracy was evaluated using the whole cohort or the cohort excluding the stable disease samples, (c) EPO PDX cohort (see also Figure 9). As is evident from Figure 5, the 16-gene mini-classifier accuracy is stable or stays in an acceptable range, i.e. the performance of the 16-gene mini- classifier is more or less independent of the number of applied genes.
  • RPKM expression level cutoff that indicates likelihood for response to cetuximab is listed in column "RPKM cutoff'.
  • Down regulated genes indicate likelihood for response to cetuximab below the cutoff.
  • Up regulated genes indicate likelihood for response to cetuximab above the cutoff.
  • logFC log 2 normalized fold change.
  • FDR false discovery rate (Benjamini-Hochberg procedure). Please see the methods for further details on setups a-d.
  • RPKM expression level cutoff that indicates likelihood for response to cetuximab is listed in column "RPKM cutoff'.
  • Down regulated genes indicate likelihood for response to cetuximab below the cutoff.
  • Up regulated genes indicate likelihood for response to cetuximab above the cutoff.
  • logFC - log2 normalized fold change.
  • FDR - false discovery rate (Benjamini-Hochberg procedure). Please see the methods for further details on setups a-d.
  • Figure 8 12-gene mini-classifier (see Table 3). Selection of cetuximab sensitivity related genes.
  • the column "EIR" expression in responders indicates if a certain gene is up or down regulated in responding PDX models compared to non-responding PDX models.
  • a RPKM (expression level) cutoff that indicates likelihood for response to cetuximab is listed in column "RPKM cutoff.
  • Down regulated genes indicate likelihood for response to cetuximab below the cutoff.
  • Up regulated genes indicate likelihood for response to cetuximab above the cutoff.
  • logFC - log2 normalized fold change.
  • FDR - false discovery rate (Benjamini-Hochberg procedure). Please see the methods for further details on setups a-d and the selection of the genes using SVM.
  • Figure 9 16-gene mini-classifier (see Table 4). Selection of cetuximab sensitivity related genes.
  • the column "EIR" expression in responders indicates if a certain gene is up or down regulated in responding PDX models compared to non-responding PDX models.
  • a RPKM (expression level) cutoff that indicates likelihood for response to cetuximab is listed in column "RPKM cutoff'.
  • Down regulated genes indicate likelihood for response to cetuximab below the cutoff.
  • Up regulated genes indicate likelihood for response to cetuximab above the cutoff.
  • logFC - log2 normalized fold change.
  • FDR - false discovery rate (Benjamini-Hochberg procedure). Please see the methods for further details on setups a-d and the selection of the genes using SVM.
  • FIG 10 Performance range of the downsized sub-signatures of the 12-gene mini- classifier (Figure 8).
  • the plot shows the upper range of the balanced accuracy for sub-signatures with a gene size of two up to eleven genes. Sub-signatures were randomly generated out of the 12-gene mini-classifier. For each gene size 120 unique sub-signatures were generated. Hyperparameter fitting and SVM training was performed on the OncoTrack PDX cohort as described. The upper bound shows the maximum of balanced accuracy. The lower bound shows the median of balanced accuracy. The small vertical line marks the 75% quartile of balanced accuracy. The balanced accuracy of the downsized sub- signatures was evaluated on different data sets and plotted over the signature size, (a) OncoTrack PDX cohort (see also Figure 8).
  • FIG 11 Performance range of the downsized sub-signatures of the 16-gene mini- classifier.
  • the plot shows the upper range of the balanced accuracy for sub- signatures with a signature size of two up to fifteen genes.
  • Sub-signatures were randomly generated out of the 16-gene mini-classifier. For each signature size 120 unique sub-signatures were generated.
  • Hyperparameter fitting and SVM training was performed on the OncoTrack PDX cohort as described.
  • the upper bound shows the maximum of balanced accuracy.
  • the lower bound shows the median of balanced accuracy.
  • the small vertical line marks the 75% quartile of balanced accuracy.
  • the balanced accuracy of the downsized sub-signatures was evaluated on different data sets and plotted over the signature size, (a) OncoTrack PDX cohort (see also Figure 9).
  • Patient cohort From a prospective CRC cohort of 106 patients a total of 116 resected tissue samples with matched blood samples, comprising 89 primary tumours (ranging from stage I to IV) and 27 metastases were collected. The tissue samples were used to generate a collection of pre-clinical patient-derived experimental models. 52 xenografts (PDX), established from 48 patient samples, were utilized for in vivo drug response testing. The genomes, exomes and transcriptomes of the donor cohort as well as of the matched untreated PDX models were sequenced.
  • PDX xenografts
  • RNA reads were aligned to hgl9 using BWA and SAMtools. Mapped reads were annotated using Ensembl v70. Gene expression levels were quantified in reads per kilobase of exon per million mapped reads (RPKM) (Mortazavi A. et al., Nat Methods. 5(7) (2008), 621 -8).
  • DNA reads were aligned to the human reference genome hgl9 using BWA (Li H. et al, Bioinformatics 25 (2009), 1754-1760) (bwa0.7.7-r441 -mem for 75/101bp, bwa0.5.9-rl6-aln for 51 bp reads).
  • BWA Li H. et al, Bioinformatics 25 (2009), 1754-1760
  • bwa0.7.7-r441 -mem for 75/101bp, bwa0.5.9-rl6-aln for 51 bp reads For xenograft (PDX) samples, the human and mouse DNA reads were deconvoluted after mapping to references from human hgl9 and mouse mm9 genome versions.
  • Somatic SNVs were detected using established pipelines based on VarScan2 (Koboldt D.C. et al., Genome Res 22 (2012), 568-576) combined with RNAseq data and functional annotation of the variants based on Ensembl v.70. Somatic indels were detected using SAMtools and Dindel (Albers C.A. et al, Genome Res 21 (2011), 961 - 973).
  • Resected tumor tissues were transplanted to immunodeficient mice (NMRI nude or NOG, Taconic, Bomholdtgard, DK- Tac:NMRI-Foxnlnu, females, 6-8 weeks at start of transplantation) using previously described methods by Fichtner et al. (Fichtner I. et al, Eur J Cancer 40 (2004), 298-307). Animal experiments were carried out in accordance with the United Kingdom Coordinating Committee on Cancer Research regulations for the Welfare of Animals and of the German Animal Protection Law and approved by the local responsible authorities. Experimental Pharmacology and Oncology Berlin-Buch GmbH (EPO) strictly follows the EU guideline European convention for the protection of vertebrate animals used for experimental and other scientific purposes.
  • mice were monitored 3 times weekly for tumor engraftment for up to 3 month. Engrafted tumors at a size of about 1 cm 3 were surgically excised and smaller fragments re-transplanted to naive NMRI nu/nu mice for further passage. Within passage 1 to 3 numerous samples were cryo-conserved (DMSO-medium) for further experiments. Tumors were passaged not more than 6 times. For confirmation of tumor histology, tumor tissue was formalin fixed and paraffin embedded (FFPE) and 5 ⁇ sections were prepared. Samples were stained according to a standard protocol for hematoxilin, eosin and Ki67 to ensure xenograft comparability to the original specimen. Cases with changed histological pattern were sent for pathological review and outgrowth of lymphoproliferative diseases was excluded. In this study, no blinding was done.
  • FFPE paraffin embedded
  • cetuximab EGFR monoclonal antibody; Erbitux®, Merck KGaA
  • EGFR monoclonal antibody Erbitux®
  • Merck KGaA EGFR monoclonal antibody
  • injection intraperitoneal injection
  • Schedule BIW (twice a week); Days: Monday and Thursday; number of cycles: 4; Dose: 30 mg/kg.
  • the injection volume was 0.1-0.2 ml/20 g body weight.
  • Treatment was continued over a period of four weeks (4 cycles) or till tumor size exceeded 1 cm 3 or animals showed loss of >15% body weight. From the first treatment day onwards the tumor volumes and body weights were recorded twice weekly. At the end of the treatment period animals were sacrificed, blood and tumor samples collected, and stored in liquid nitrogen immediately.
  • RTV relative tumor volume
  • PD Progressive Disease
  • SD Stable Disease
  • PDX xenograft samples of the 52 xenografts (PDX) that derived from one colorectal carcinoma (CRC) (150 MET1) shared highly similar global expression profiles. They were merged into one artificial single sample to avoid analysis bias by taking an average of the reads per kilobase of exon per million mapped (RPKM) (Mortazavi A, et al., Nat Methods 5 (2008), 621 -628)- values and of the T/C -values per gene or drug, i.e. cetuximab. Taking the artificial sample for 150JVIET1 into account 48 PDX were included into the drug response analysis. Drug response related gene signatures in xenografts (PDX)
  • DGE analysis using the R package edgeR (Robinson MD et al., Bioinformatics 26 (2010), 139-140) to identify signatures associated with drug, i.e. cetuximab, response results in form of T/C values for PDX: strong, moderate, minor, resistant (see the above section 6).
  • DGE analysis was applied in different setups as follows: a) combined strong+moderate vs combined minor+resistant, b) combined strong+moderate+minor vs. resistant, and c): 20 most sensitive vs. 20 least sensitive PDX. Genes were filtered by a false discovery rate (FDR) ⁇ 0.01,
  • FDR false discovery rate
  • a 12-gene classifier and a 16-gene classifier were built that predict the outcome of cetuximab treatment (response or resistance).
  • the gene signature was pre-filtered, i.e. genes that were described in US 2010/0221754 (corresponding to WO-A2 2010/145796), US 2015/0354009 (corresponding to WO- Al 2014/080381 ) and US 2012/0094863 (corresponding to WO-A2 2007/025044) as expression markers of response to cetuximab were excluded from the analysis.
  • the 16-gene mini classifier includes published genes.
  • the classifiers were validated in one, two or three external datasets (Gao H. et al, Nat Med 21 (2015), 1318-1325; Khambata-Ford S. et al., J Clin Oncol 25 (2007), 3230-3237; Pechanska P. et al, Journal of Cancer Therapy 04 (2013), 678-693). Since only 179 of 241 signature genes overlap with the provided expression data (12192 genes) of the Khambata-Ford et al, 2007 study (Khambata-Ford S. et al, J Clin Oncol 25 (2007), 3230-3237), the Khambata-Ford study was not considered for the 12-gene classifier. RPKM values were log 2 transformed and z-score normalized.
  • SVM linear support vector machine
  • SVM-RFE SVM recursive feature elimination
  • a SVM-PvFE includes following steps: 1) hyperparameter tuning, 2) train multiple SVMs on subsamples of the original training set, 3) calculate a ranking score per feature based on the trained SVMs, 4) note the relative position in the final ranking vector of m features with the lowest ranking score, 5) eliminate m features with the lowest ranking score from the feature space, 6) repeat step 1-5 until all features are ranked in the final ranking vector.
  • the hyperparameter C resis and C resp were tuned via grid search with a stratified bootstrap (C
  • the bootstrap was separately applied on the responder and resistance set with a sample size of 13 and 31 , respectively.
  • the performance of a hyperparameter set was evaluated using the F] -score.
  • For the leave-n-out resampling two and five samples of the responder and resistance set were left out from the training set, respectively.
  • the calculation of the ranking score was based on the weight vector w of a linear SVM and not w 2 as described from Duan et al.
  • the cetuximab response classifiers (12 gene classifier (including the genes: EPHA4 (EPH receptor 4; Entrez Gene ID: 2043, Assembly: GRCh37; (NCBI accession no.: XM 005246374; version no.: XM 005246374.2; GI: 1034612388)), PDE4D (phosphodiesterase 4D; Entrez Gene ID: 5144, Assembly: GRCh37; (NCBI accession no.: XM_ 017009565; version no.: XM_017009565.1 ; GI: 1034645215)), SYTL5 (synaptotagmin-like 5; Entrez Gene ID: 94122, Assembly: GRCh37; (NCBI accession no.: NMJ38780; version no.: NMJ38780.2; GI:254039641)), FYN (FYN oncogene related to SRC, FGR, YES; Entrez Gene ID: 2534, Assembly: GRCh
  • Ensembl gene identifiers were mapped to ul33av2 probeset IDs (Khambata-Ford et al., 2007) and to gene symbols (Gao et al., 2015).
  • the expression values of the external PDX cohorts were log 2 -normalized and of all three external data set were z- score transformed.
  • Four response categories were given for the Gao and Khambata- Ford data set: complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD).
  • PDX of the EPO were divided in four response categories based on given T/C values as described herein.
  • the performance of the classifier was estimated from the number of true positive (TP), false positive (FP), true negative (TN) and false negative (FN) predictions as well as the sensitivity, specificity and balanced accuracy.
  • Cross-validation on the OT PDX cohort was achieved via a 100 times repeated 10-fold cross-validation. Performance values were averaged over the repeats.
  • SD samples were excluded to determine their influence on the classifier's performance (KF: 49 samples, Gao: 32 samples).
  • KRAS wild type and all-RAS-RAF wild type samples was tested. For the KRAS wild type, mutations in codon 12 and 13 of KRAS were considered.
  • KRAS and NRAS mutations G12, G13, Q22, Q61, A146
  • BRAF mutations V600E
  • the Khambata- Ford data set provided only mutations in codon 12 and 13 of KRAS.
  • the balanced accuracy values for the gene size reduction analysis were obtained by a bootstrap cross-validation as described above. Additional information
  • a method for determining the susceptibility or responsiveness of (a) cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor, said method comprising determining the expression level of one or more gene(s) as shown in Table 1 in said cancer cell(s), cancer tissue(s) or tumor sample(s), wherein said expression level is indicative of whether said patient is responsive or susceptible to the treatment with an EGFR inhibitor.
  • CRC colorectal cancer
  • EGFR epidermal growth factor receptor
  • a method for the identification of a responder to or a subject sensitive to an EGFR inhibitor comprising determining the expression level of at least one or more gene(s) as shown in Table 1 on (a) cancer cell(s), cancer tissue(s) or tumor sample(s) from a subject suffering from colorectal cancer (CRC), whereby a expression of at least one of said genes is indicative for a responding subject or is indicative for a sensitivity of said patient to an EGFR inhibitor.
  • CRC colorectal cancer
  • a method of monitoring the efficacy of an EGFR inhibitor treatment of colorectal cancer (CRC) in a subject suffering from said disease comprising the steps of:
  • the EGFR inhibitor is selected from the group consisting of an anti-EGFR antibody, an EGFR tyrosine kinase inhibitor and an anti-EGFR antibody drug conjugate.
  • An EGFR inhibitor for use in the treatment of colorectal cancer if (a) cancer cell(s), cancer tissue(s) or tumor sample(s) obtained from a subject to be treated exhibits expression of at least one or more gene(s) as shown in Table 1 , preferably of 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 or 12 genes as shown in Table 3, more preferably of 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4.
  • the EGFR inhibitor for use according to item 10 wherein the subject to be treated has been predicted to be responsive or susceptible to the treatment with an EGFR inhibitor in a method according to any one of items 1 , 2 and 4 to 9.
  • the EGFR inhibitor for use according to item 10 or 1 1 wherein the EGFR inhibitor selected from the group consisting of an anti-EGFR antibody, an EGFR tyrosine kinase inhibitor and an anti-EGFR antibody drug conjugate.
  • a kit for predicting the susceptibility or responsiveness of a subject suffering from colorectal cancer (CRC) to the treatment with an epidermal growth factor receptor (EGFR) inhibitor comprising oligonucleotides or polynucleotides capable of detecting the expression level of one or more of the genes of Table 1 , preferably of 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 or 12 genes as shown in Table 3, more preferably of 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 genes as shown in Table 4 and optionally further comprising oligonucleotides or polynucleotides capable of detecting the expression level of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23 or 24 as shown in Table 2.
  • Use of an oligonucleotide or polynucleotide capable of detecting the expression level of one or more of the genes of Table 1 preferably of 2, 3, 4, 5, 6, 7, 8, 9,

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Abstract

La présente invention concerne un procédé de détermination de la sensibilité/réactivité de (a) cellule(s) cancéreuse(s), de préférence de (a) cellule(s) cancéreuse(s) colorectale(s), au traitement avec un inhibiteur du récepteur du facteur de croissance épidermique (EGFR). En outre, la présente invention concerne un procédé de sélection de cellule(s), de tissu(s) ou d'échantillon(s) de tumeur d'un cancer colorectal (CRC) présentant une sensibilité à un inhibiteur du récepteur du facteur de croissance épidermique (EGFR). En outre, l'invention concerne un procédé in vitro permettant l'identification d'un répondeur ou d'un sujet, de préférence un patient humain, souffrant d'un cancer colorectal (CRC) à un inhibiteur du récepteur du facteur de croissance épidermique (EGFR). La présente invention concerne également un procédé de surveillance de l'efficacité d'un traitement du cancer colorectal (CRC) avec un inhibiteur du récepteur du facteur de croissance épidermique (EGFR).
PCT/EP2017/077694 2016-10-28 2017-10-27 Moyens et procédés pour déterminer l'efficacité d'inhibiteurs anti-egfr dans une thérapie du cancer colorectal (crc) Ceased WO2018078143A1 (fr)

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WO2021077080A3 (fr) * 2019-10-18 2021-05-27 The Regents Of The University Of California Compositions et méthodes pour diagnostiquer et traiter le cancer
CN118380163A (zh) * 2024-06-21 2024-07-23 福建医科大学附属第一医院 一种用于预测药物耐药状态的方法、系统和设备

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DATABASE GENE [O] retrieved from NCBI Database accession no. NM_000239
DATABASE gene [O] retrieved from NCBI Database accession no. NM_000574
DATABASE gene [O] retrieved from NCBI Database accession no. NM_000700
DATABASE gene [O] retrieved from NCBI Database accession no. NM_001013398
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_001062
DATABASE gene [O] retrieved from NCBI Database accession no. NM_001320861
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_001394
DATABASE gene [O] retrieved from NCBI Database accession no. NM_001432
DATABASE gene [O] retrieved from NCBI Database accession no. NM_002228
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_002467
DATABASE gene [O] retrieved from NCBI Database accession no. NM_002639
DATABASE gene [O] retrieved from NCBI Database accession no. NM_002774
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_003088
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_003097
DATABASE gene [O] retrieved from NCBI Database accession no. NM_003106
DATABASE gene [O] retrieved from NCBI Database accession no. NM_003247
DATABASE gene [O] retrieved from NCBI Database accession no. NM_004184
DATABASE gene [O] retrieved from NCBI Database accession no. NM_004335
DATABASE gene [O] retrieved from NCBI Database accession no. NM_004617
DATABASE gene [O] retrieved from NCBI Database accession no. NM_005356
DATABASE gene [O] retrieved from NCBI Database accession no. NM_005531
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_005564
DATABASE gene [O] retrieved from NCBI Database accession no. NM_005854
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_006227
DATABASE gene [O] retrieved from NCBI Database accession no. NM_007350
DATABASE gene [O] retrieved from NCBI Database accession no. NM_012448
DATABASE gene [O] retrieved from NCBI Database accession no. NM_014213
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_014312
DATABASE gene [O] retrieved from NCBI Database accession no. NM_014324
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_014579
DATABASE gene [O] retrieved from NCBI Database accession no. NM_015352
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_017802
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_017866
DATABASE gene [O] retrieved from NCBI Database accession no. NM_020314
DATABASE gene [O] retrieved from NCBI Database accession no. NM_025155
DATABASE gene [O] retrieved from NCBI Database accession no. NM_030580
DATABASE gene [O] retrieved from NCBI Database accession no. NM_030762
DATABASE gene [O] retrieved from NCBI Database accession no. NM_030792
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_032044
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_033393
DATABASE GENE [O] retrieved from NCBI Database accession no. NM_080476
DATABASE gene [O] retrieved from NCBI Database accession no. NM_138780
DATABASE gene [O] retrieved from NCBI Database accession no. NM_175887
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DATABASE GENE [O] retrieved from NCBI Database accession no. XM_011515987
DATABASE GENE [O] retrieved from NCBI Database accession no. XM_017009565
DATABASE GENE [O] retrieved from NCBI Database accession no. XM_017010650
DATABASE GENE [O] retrieved from NCBI Database accession no. XM_017015500
DATABASE NCBI [O] retrieved from NCBI Database accession no. NM_017802
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WO2021077080A3 (fr) * 2019-10-18 2021-05-27 The Regents Of The University Of California Compositions et méthodes pour diagnostiquer et traiter le cancer
CN118380163A (zh) * 2024-06-21 2024-07-23 福建医科大学附属第一医院 一种用于预测药物耐药状态的方法、系统和设备

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