WO2015144854A1 - Procédé permettant de prédire les résultats chez un patient et une réponse thérapeutique du cancer colorectal métastatique - Google Patents

Procédé permettant de prédire les résultats chez un patient et une réponse thérapeutique du cancer colorectal métastatique Download PDF

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WO2015144854A1
WO2015144854A1 PCT/EP2015/056649 EP2015056649W WO2015144854A1 WO 2015144854 A1 WO2015144854 A1 WO 2015144854A1 EP 2015056649 W EP2015056649 W EP 2015056649W WO 2015144854 A1 WO2015144854 A1 WO 2015144854A1
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ctc
therapy
genes
patients
blood sample
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Miguel Abal Posada
Rafael LÓPEZ LÓPEZ
Jorge BARBAZÁN GARCÍA
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Fundacion Ramon Dominguez
Servizo Galego de Saude SERGAS
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Fundacion Ramon Dominguez
Servizo Galego de Saude SERGAS
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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
    • C12Q2600/118—Prognosis of disease development
    • 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 invention relates to the field of the diagnostic methods performed out of the body to determine if a therapy is appropriate for a particular individual.
  • the present invention refers to a method for determining both the outcome of patients suffering from metastatic colorectal cancer and the effectiveness of the administered therapy.
  • Colorectal cancer represents the fourth leading cancer-related death cause worldwide (Jemal et al., 201 1 ), mainly due to the presence of metastasis, fact that significantly reduces survival rates. Cancer dissemination starts with primary tumors shedding malignant cells into the circulation and those Circulating Tumor Cells (CTCs) can form a distant metastasis when reaching an appropriate target organ (Nguyen et al., 2009).
  • CTC detection and quantification has shown to be a predictive prognostic factor in different tumor types, including colorectal.
  • CTC count is increasingly being incorporated to clinical trials as a non-invasive, fast and high sensitive patient monitoring technique, what has favoured the development of several different CTC quantification methods in the last years.
  • FDA American Food and Drug Administration
  • CTCs of epithelial origin CD45-, EpCAM+, and cytokeratins 8, 18+ and/or 19+
  • mCRC metastatic colorectal cancer
  • the CellSearch ® system makes use of ferrofluid nanoparticles with antibodies that target epithelial cell adhesion antigens in order to enrich the samples in CTCs, which are magnetically separated from the bulk of other cells in the blood.
  • CTCs which are magnetically separated from the bulk of other cells in the blood.
  • different studies have shown that the presence of 3 or more CTCs per 7,5 ml of blood in mCRC patients predicted poor patient outcome at baseline, e.g. before treatment (Cohen et al., 2008; Cohen et al., 2009).
  • CTCs Molecular characterization of CTCs is becoming more relevant in colorectal cancer patients, achieving similar, or even better CTC detection rates, strengthening CTC prognostic value in mCRC and opening a new way for personalized patient treatment, based on CTC characteristics (Gervasoni et al., 2008; Barbazan et al., 2012a; Lagoudianakis et al., 2009).
  • CTC characteristics For example, KRAS, BRAF, EGFR or PIK3CA mutational statuses in CTCs can be analysed, providing relevant information.
  • CTC profiling has become a promising source of information, providing with hundreds of CTC markers for detection and prognosis and also potential therapeutic targets, and importantly contributing to the actual knowledge of the process of metastatic dissemination (Barbazan et al., 2012b; Smirnov et al., 2005).
  • the group of the present inventors reported a method for detection of CTCs from mCRC patients that combines immune- enrichment (based on magnetic beads covered with anti-EpCAM antibodies), optimal purification of RNA from very low cell numbers, and the selection of accurate PCR probes for assessing the expression level of GAPDH and VIL (as CTC detection markers) normalized to CD45 (a marker specific to leukocytes).
  • a logistic model based on said markers is also presented, which model can be used as prognosis tool to determine progression-free survival in mCRC.
  • the model was complemented with a gene expression study of mCRC patients (Barbazan et al., 2012b), that resulted in 410 genes that characterized the CTC population. Comparison between primary carcinomas and lung and liver metastases further involved the CTC-genes in the promotion of metastasis. The correlation of CTC- gene expression with clinical parameters demonstrated detection and prognosis significance.
  • the list of validated genes with diagnostic and prognostic value included, among others, CLU and TIMP1 , which are associated with cell death and anti-apoptotic activity, and TLN1 , which is associated with cell adhesion.
  • TGF i , APP, CD9, ITGB5, LIMS1 , RSU1 , VCL and BMP6 were also among the validated genes with diagnostic and prognostic value. Prognosis of patients' outcome might be an important information, but the selection of the appropriate therapy for each individual and the assessment of the effectiveness or non-effectiveness of the administered therapy is an important goal, in order to stop it for those patients who are only suffering toxicity-derived adverse effects and to change to a more appropriate therapy as soon as possible. It is important to keep in mind that not all tumors respond to the same therapies, even though their classification and morphological appearance are similar; difficulties to choose the appropriate therapy results in more than 50% cancer patients not receiving an efficient treatment.
  • Cancer staging is the process of determining the extent to which a cancer has developed by spreading.
  • Contemporary practice is to use an overall stage grouping that consists of assigning a number from I- IV to a cancer, with I being an isolated cancer and IV being a cancer which has spread to other organs, mainly if new occurrences of the disease (metastasis) have generated from the organ or part of organ of the primary tumor to another non-adjacent organ or part.
  • TNM staging system a system of classification of malignant tumors that describes the extent of a person's cancer taking into account three parameters:
  • TNM TNM is developed and maintained by the Union for International Cancer Control (UlCC) (https://www.uicc.org/) and by the American Joint Committee on Cancer (AJCC) (http://cancerstaqinq.org/About/what-is-the- ajcc/Paqes/whatisajcc.aspx). UlCC and AJCC staging systems were unified into a single staging system in 1987. Nevertheless, most of the common tumors have their own TNM classification system. In the case of colorectal cancer (American Joint Committee on Cancer: AJCC Cancer Staging Manual. 6 th ed. New York, NY, Springer, 2002, pp 1 13-124), the following classification criteria are followed:
  • TX Primary tumor cannot be assessed
  • T1 Tumor invades submucosa
  • T2 Tumor invades muscularis
  • T3 Tumor invades through the muscularis basement into the subserosa, or into nonperitonealized tenuic or perirectal tissues
  • T4 Tumor directly invades other organs or structures, and/or perforates visceral peritoneum
  • N1 Metastasis in 1 to 3 regional lymph nodes
  • Stage IV colorectal cancer corresponds with the situation of any T, any N,
  • Performance Status refers to the general condition and the activities that a patient can perform.
  • Performance Status classification is based on scales and criteria used by doctors and researchers to assess how a patient's disease is progressing, assess how the disease affects the daily living abilities of the patient, and determine appropriate treatment and prognosis. It is a common practice to use the ECOG Performance Status, of the Eastern Cooperative Oncology Group, (publicly available, for instance, on the web site: http://ecoq.dfci.harvard.edu/qeneral/perf stat.html), reported by Oken and coworkers (Oken et al., 1982). According to such classification, patients are graded as follows:
  • Stage I a localized tumor
  • Stage II and III patients with localized disease
  • Chemotherapy is administered to those patients, usually based on clinical criteria without prognostic value.
  • Stage IV colorectal cancer is the most advanced cancer stage. Also termed metastatic colorectal cancer (mCRC), stage IV CRC is characterized by the presence of tumor dissemination to nearby lymph nodes and other parts of the body, like the liver, lungs or ovaries. When the cancer has reached this stage, surgery is generally used for relieving or preventing complications as opposed to curing the patient of the disease. When disseminated disease to the liver and/or lungs is restricted enough, and after having demonstrated chemosensitiviy to adjuvant therapies, surgery might be applied to remove metastatic lesions.
  • mCRC metastatic colorectal cancer
  • chemotherapy is considered the main treatment.
  • stage IV cancer that cannot be surgically removed, chemotherapy, radiation therapy, or both may be used to relieve, delay or prevent symptoms.
  • chemotherapy radiation therapy, or both may be used to relieve, delay or prevent symptoms.
  • survival rates strongly decrease, with a high number of patients dying after several months due to the presence of disseminated disease.
  • Chemotherapy standard treatment is mainly based in the use of fluoropyrimidines (fluorouracil or capecitabine), either in monotherapy or combined with oxaliplatin/irinotecan and targeted drugs (Bevacizumab, Panitumumab or Cetuximab) (Cunningham et al., 2010).
  • fluoropyrimidines fluorouracil or capecitabine
  • oxaliplatin/irinotecan and targeted drugs Bevacizumab, Panitumumab or Cetuximab
  • Some combinations receive specific names, such as FOLFOX (leucovorin, 5-fluorouracil and oxaliplatin), FOLFIRI (leucovorin, 5-fluorouracil and irinotecan) or FOLFOXIRI (leucovorin, 5-fluorouracil, oxaliplatin and irinotecan).
  • a predictive factor is a measurement that is associated with response or lack of response to a particular therapy, while response can be defined using any of the clinical endpoints commonly used in clinical trials.
  • the necessity and difficulty of identifying suitable predictive factors for a given therapy is more clear if it is taken into account that the fact of being a prognostic factor or marker (a measurement that is associated with clinical outcome in the absence of therapy) does not imply that a molecule or gene also has a predictive value.
  • CT colonography also known as computerized tomographic colonography, virtual colonoscopy or CT scan
  • CT scan has emerged in the last decade as an alternative to colonoscopy, due to its better safety profile, although it is not commonly accepted as the reference technique, because it is considered to be less reliable than colonoscopy.
  • CT scan consists of a series of detailed pictures of areas inside the body, taken from different angles, created by a computer linked to an x-ray machine.
  • CT examination is usually performed 3 months after the beginning of the treatment, which means that, when patients are non responders to therapy, a long time has been wasted administering a therapy that results finally to be not effective, increasing the risk for the patient to be aggravated the disease instead of getting an alleviation of the condition.
  • KRAS mutation status (bearing the wild type gene or an exon 2-mutated gene) have shown to be effective for stratification of patients receiving anti-EGFR therapy (Lievre et al., 2008), and serum biomarkers like CA-125 and, specially, carcinoembrionic antigen (CEA) are also an indicative tool for treatment effectiveness in mCRC patients (Aldulaymi et al., 2010), but none of them are conclusive as markers for therapy monitoring.
  • KRAS in particular lacks prognostic value by itself.
  • CTCs have been proposed not only as a baseline predictive factor for patient outcome, but also as an indicator of therapy effectiveness, since changes in CTC count along treatment predicted therapy response in different tumor types and usually earlier than current approaches (Hartkopf et al., 201 1 ; Hayes et al., 2006; Saad et al., 2012), thus allowing the separation of patients who are benefiting from the therapy from those who do not.
  • CTC changes in mCRC Matsusaka et al., 201 1 ; Tol et al., 2010
  • most data having emerged from breast cancer studies as breast cancer is the tumor type most investigated in the field of CTC research.
  • EMT epithelial to mesenchymal transition
  • E-cadherin proteins that are characteristic of mesenchymal cells (for example, vimentin, fibroblast-specific protein-1 , SNAI1 (Snail) and SNAI2 (Slug), nuclear ⁇ - catenin and stromelysin-3) as well as for the lost of epithelial markers such as, for instance, E-cadherin; some functional evidences are the relapse and metastasising capacity observed in regressed tumors after spontaneous induction of SNAI1 , as well as the change of phenotype and invasive behaviour resulting from the manipulation of E-cadherin expression. In fact, downregulation of E-cadherin expression is one of the common endpoints of EMT-inducing signalling pathways, other common endpoint being the expression of EMT associated genes.
  • E-cadherin repressors including zinc-finger factors (Snail, Slug, Zeb1 and Zeb2) and class I and II bHLH factors (E47 and Twist (Twist 1 and Twist2)), but Peinado and coworkers consider that it remains unsolved whether the different repressors may participate in silencing E-cadherin in different types of tumors or at defined stages of tumor progression (Peinado et al., 2005).
  • EMT markers have been related with cancer progression and with primary colorectal cancer progression in particular, such as the ZEB (Zinc Finger E- Box-Binding Homeobox) family of transcription factors, particularly ZEB1 and ZEB2, which repress E-cadherin promoter, are often cited together in relation to EMT and cancer progression.
  • ZEB1 has been implicated in EMT in human colorectal cancer (Xiong et al., 2012).
  • Tumor cells undergoing EMT have been shown to gain, among other attributes, drug resistance abilities.
  • mesenchymal cell expressing low E-cadherin levels have been related to EGFR kinase inhibitors resistance in Non- Small Cell Lung Cancer (NSCLC) (Witta, 2006), or to monoclonal anti-EGFR antibodies (Cetuximab) in the case of colorectal cancer, as mesenchymal cells can regulate AKT activation, one of the main targets for these therapies, through EGFR-independent pathways like Integrin Linked Kinase (ILK) (Laure et al., 2005).
  • NSCLC Non- Small Cell Lung Cancer
  • ILK Integrin Linked Kinase
  • WO12149014A1 discloses a method of identifying patients with cancer who may benefit from treatment with a pharmaceutical composition comprising a compound that inhibits tumor cells from undergoing an epithelial to mesenchymal transition, which comprises measuring the expression levels of a list of 88 genes in a tumor sample, calculating what they call the EMT gene signature (EMTGS) and identifying the patients benefiting from the therapy as those with an EMTGS value similar to a reference value corresponding to cells of a mesenchymal phenotype.
  • EMT gene signature EMT gene signature
  • the list of 88 genes includes many genes well known for being related to the EMT process such as vimentin, TWIST 1 , SNAI1 , SNAI2, ZEB1 and ZEB2.
  • the method should be able to classify the patients as responders and non-responders to the therapy prior to the current methods such as CT tomography, in order to have reliable data to consider the possibility of stopping the administration of the drugs that are only causing adverse effects to non-responding patients and, if possible, to replace it for another one as soon as possible.
  • the present invention provides a solution to said problem.
  • the present invention provides a panel of markers with predictive value for therapy effectiveness monitoring in mCRC patients, each marker individually being capable of allowing the assessment of therapy effectiveness by comparison of their levels before therapy start and after the first (or subsequent) therapy cycle and even, in terms of overall survival, being capable of allowing the assessment of therapy effectiveness simply by determining its level at a moment of therapy cycle and comparing it with a reference value.
  • the present invention also provides a qPCR-based multimarker CTC detection panel for outcome prediction before treatment and for therapy effectiveness monitoring in mCRC patients, by using a combination of the above mentioned intestine-specific epithelial markers and EMT transcripts, which combination means an improvement for therapy effectiveness monitoring because diminish the probability of false positive results.
  • the present invention relates to a method for determining the effectiveness of a therapy administered to a subject suffering from metastatic colorectal cancer (mCRC) and/or the outcome of said subject that comprises the steps of:
  • low-CTC if the expression level of the selected gene in CTCs is low or, when more than one gene of the above mentioned set of genes is being analysed, if the expression level in CTCs of more than a half of said analysed genes is low;
  • high-CTC if the expression level of the selected gene in CTCs is high or, when more than one gene of the above mentioned set of genes is being analysed, if the expression level in CTCs of at least one half of said analysed genes is high;
  • non responder to the therapy, if the subject is "high-CTC" for the analysed follow-up blood sample, and ii. "responder” to the therapy, if the subject is "low-CTC" for the analysed follow-up blood sample;
  • steps b) to f) predicting the outcome of the subject at a time point of therapy course by classifying the subject as a "high risk” subject when the blood sample taken at that time point is "high-CTC", and as a "low risk” subject when the blood sample taken at that time point is "low-CTC".
  • step d) needs not to be carried out, being possible to classify the subject as “responder” or “non responder” according to the classification of the expression level of the gene as “low” or “high”, respectively. That alternative way of classification is also encompassed by the scope of the present invention.
  • the gene or each one of the genes selected for carrying out the steps of the method of the invention is also referred as an "analysis gene” and the group of genes selected for carrying out the steps of the method of the present invention are also called “the set of analysed genes” or "the panel of analysed genes”.
  • the expression level in CTCs of only one gene of set of genes of the group of GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 is to be determined and used for carrying out the other steps of the method of the invention, it is preferred that it is selected between LOXL3 and ZEB2, more preferably LOXL3.
  • more than a gene of the group of GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 is included in the set of analysed genes, that is, it is a preferred embodiment of the present invention that one wherein the expression level in CTCs at least two, three, four, five, six or all the seven genes of the group of GADPH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 is determined and classified in step b) and c), and the analysed blood sample and, subsequently, the subject are both classified according to the expression level of said genes in the CTCs of said blood sample in steps d) and e) and, when carried out, in step f) and/or g). Even when the expression level of more than one of said genes is determined and used for classifying the blood sample and the subject at the moment of taking that blood sample, it is preferred that LOXL3 or ZEB2 or both of them are
  • LOXL3 and VI L1 are among the selected genes for carrying out the method of the invention. More particular embodiments are those where LOXL3, VI L1 and CLU are selected when the expression level of at least three genes is determined or where LOXL3, VIL1 , CLU and GAPDH are selected when at least four genes of the group of GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 are used for determining their expression levels and carrying out with them the method of the present invention.
  • Another preferred embodiment of the method of the present invention is that one wherein at least six genes of the group of GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 are included in the set of analysed genes, as in Examples 1 to 4 of the present application.
  • the selected genes can be GAPDH, VIL1 , TIMP1 , CLU, LOXL3 and ZEB2, as in Example 2, or the seven genes of the group, GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2, as in Example 3 of the present application.
  • the set of analysed genes can also be GAPDH, VIL1 , CLU, TLN1 , LOXL3 and ZEB2, or, GAPDH, VIL1 , TIMP1 , TLN1 , LOXL3 and ZEB2.
  • GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 are included in the set of analysed genes and particularly, when the set of analysed genes are GAPDH, VIL1 , TIMP1 , CLU, LOXL3 and ZEB2, or GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2, the blood sample to be classified in step c) will be classified as "low-CTC" when the expression level of at least four genes of the set of analysed genes is low, and "high-CTC" when the expression level of three or more genes of the set of analysed genes is high.
  • a previous blood sample is taken from the subject before the administration of the therapy cycle that is already administered when the first follow-up sample is taken (for instance, when the first follow-up sample is taken after having administered therapy cycle 1 , said previous blood sample will be the baseline sample, that is, a blood sample taken before the start of the therapy.
  • a preferred embodiment of the method of the invention is that wherein steps b) to e) (assessment and classification of the expression level of selected CTC genes, classification of the blood sample as "high-CTC” or “low-CTC” and assessment of therapy effectiveness) , and optionally, step f) (repeating steps b) to e) in follow-up samples subsequent to the first follow-up blood sample) are carried out in said previous blood sample; optionally, additionally or alternatively to steps b) to e), step g) (prediction of the outcome of the subject at the time point of the therapy course when said previous blood sample has been taken) can be carried out in said blood sample.
  • step f) of confirmation is carried out when the subject is "low-CTC" for the follow-up blood sample considered in step d) and "high-CTC" for the immediately previous sample (for instance, “low-CTC” for the sample taken before administering therapy cycle 2, the first follow-up sample, but "high-CTC” for the sample taken before therapy start, the baseline sample).
  • That confirmatory step has the aim of confirming that the subject is indeed responding to the administered therapy and detecting a possible change in the response. Of course, this confirmatory step can be repeated as many times as it is considered advisable, to obtain a new assessment of therapy effectiveness in different time points along the therapy course.
  • any embodiment which comprises taking at least a blood sample previous to the first follow-up blood sample to use such previous blood sample to carry out step g) (alternatively to steps b) to f) or additionally to them) for predicting the outcome of the patient, which can be a particularly preferred embodiment when said previous sample is the baseline blood sample and it is use for predicting the outcome of the patient before the start of the therapy.
  • the administered therapy in evaluation is chemotherapy, particularly the most common one for mCRC patients, that one comprising the administration of at least one fluoropyrimidine (fluorouracil or capecitabine) alone or in combination with oxaliplatin or irinotecan and/or with anti-EGFR or anti-VEGF antibodies.
  • the first follow-up sample may be the sample taken before administering therapy cycle 2, and will be normally taken 4 weeks after the start of therapy, which might be an alternative way of defining the moment of taking the sample.
  • the second follow-up sample can be (and it is preferred to be) the sample taken before administering the next therapy cycle, before therapy cycle 3, so the time point when it is taken can be normally alternatively defined as 16 weeks after the start of therapy.
  • the expression level of each gene is normalized with regard to the expression level of a reference gene.
  • the reference gene is a lymphocyte-specific gene, such as CD45, which allows to take into account possible leukocytes that may have contaminated the sample.
  • each blood sample is enriched in CTCs, to decrease the noise of the sample and the risk of non-specific results. It is particularly preferred to separate CTCs from other components of the original sample by applying any immunoaffinity technique based on the use of specific antibodies against a membrane antigen present in CTCs, such as anti-EpCAM antibodies, since EpCAM is specific of cells of epithelial origin.
  • the use of a system that facilitates separation of CTCs from other blood components by magnetic means, such as the use of magnetic beads covered with an anti-EpCAM antibody is particularly preferred because, apart from the ease of application, a good level of purification can be obtained so that CTCs can be considered to become isolated from the rest of the original sample components.
  • the expression level of each gene in a sample can be also assessed by different techniques, all of them compatible with the above-mentioned embodiments of the method of the present invention, such as determination of the levels of the protein expressed by the gene.
  • mRNA messenger RNA
  • the cutoff value that allows the classification of the expression level of each gene as high or low can be selected depending on particular circumstances in the application of the method.
  • a possibility is using the 75% percentile value of the expression level of the gene resulting from a statistical study of blood samples taken from mCRC patients at the time point of therapy course wherein the blood sample to be classified has been taken.
  • the particular value can be that used in the Examples of the present application or, preferably, one resulting from a broader study.
  • the method of the present invention is compatible with any other method of assessment of therapy response, and can be combined, complemented or confirmed by any of said methods, such as imaging techniques as, for instance, CT tomography, or monitoring techniques based on the determination of levels of certain biomarkers in serum, such as CA-125 or CEA.
  • imaging techniques as, for instance, CT tomography
  • monitoring techniques based on the determination of levels of certain biomarkers in serum such as CA-125 or CEA.
  • the embodiments of the method wherein the assessment is complemented with the results of an imaging technique such as CT colonography and/or with a monitoring technique based on the determination of a biomarker in serum such as CA-125 or CEA are also encompassed by the scope of the present invention.
  • Fig.1 Relative gene expression values for LOXL3 (left panel) and ZEB2 (right panel) transcripts obtained by qPCR, normalized to 40 cycles and this value to the 40-Cq value for CD45 [(40-Cq target)-(Cq CD45)], in whole blood samples enriched in CTCs.
  • Fig. 2 Kaplan Meier survival analysis for baseline (panels A and B) and 4- week follow up (panels C and D). Progression Free Survival (panels A and C) and Overall Survival (panels B and D) curves are shown, based on the number of patients at risk depending on the time from baseline blood drawn in months (X- axis). Grey lines correspond to the results of patients classified as High-CTC, whereas darker lines correspond to patients classified as Low-CTC by using the panel including 7 markers.
  • Fig. 3 Patient classification according to markers evolution (Panel A) and Kaplan Meier survival analysis of the patients according to their classification based on evolution of 7 markers in CTCs: Progression Free Survival (PFS) (panel B) and Overall Survival (OS) (panel C) curves for responders (R: Dark Grey lines) and non responders (NR: light grey lines).
  • PFS Progression Free Survival
  • OS Overall Survival
  • R Dark Grey lines
  • NR light grey lines
  • Fig. 4 Kaplan Meier survival analysis for baseline (panels A and B) and 4- week follow up (panels C and D). Progression Free Survival (panels A and C) and Overall Survival (panels B and D) curves are shown, based on the number of patients at risk depending on the time from baseline blood drawn in months (X- axis). Grey lines correspond to the results of patients classified as High-CTC, whereas darker lines correspond to patients classified as Low-CTC by using the panel including 7 markers.
  • Fig. 5 Patient classification according to markers evolution (Panel A) and Kaplan Meier survival analysis of the patients according to their classification based on evolution of 7 markers in CTCs: Progression Free Survival (PFS) (panel B) and Overall Survival (OS) (panel C) curves for responders (R: Dark Grey lines) and non responders (NR: light grey lines).
  • PFS Progression Free Survival
  • OS Overall Survival
  • R Dark Grey lines
  • NR light grey lines
  • Fig. 6 Comparison of therapy response-based patient classification between CTC-marker levels variation along treatment and first computed tomography evaluation.
  • PFS Progression Free Survival
  • OS Overall Survival
  • SD Stable Disease
  • PR Partial Response
  • PD Progressive Disease
  • R Responder
  • NR Non-Responder
  • the present invention provides a multimarker panel for CTC detection, based on gene expression quantification, that includes tissue specific (intestine-specific epithelial markers) and EMT related CTC markers, for the effective prediction of patient outcome before therapy but, more importantly, also for the early prediction of treatment effectiveness in mCRC patients.
  • tissue specific intestine-specific epithelial markers
  • EMT related CTC markers for the effective prediction of patient outcome before therapy but, more importantly, also for the early prediction of treatment effectiveness in mCRC patients.
  • Human mCRC patients are the preferred subjects for applying the invention.
  • the method of the present invention is based on the results of a study, carried out by the present inventors, whose main endpoints were the evaluation of the expression levels of selected mRNA transcripts in CTCs as predictors of Progression Free Survival (PFS) and Overall Survival (OS) at baseline, and at follow-up as a therapy-response monitoring tool.
  • PFS Progression Free Survival
  • OS Overall Survival
  • the markers selected for the study, as well as their identification numbers according to NCBI database Entrez Gene or RefSeq Gene I D for http://www.ncbi.nlm.nih.gov/aene/) and HUGO Gene Nomenclature Committee resources (HGNC ID, for http://www.qenenames.org/), and their genome location in the human genome according to the last available version in the Ensembl Genome Browser database (http://www.ensembl.orq/Homo sapiens/Info/Index), are as follows:
  • HGNC ID HGNC:4141 ; location: Chromosome 12: 6,643,093- 6,647,537 forward strand, Ensembl: ENSG000001 1 164, version: ENSG000001 1 1640.10).
  • VIL1 Villin 1
  • CTC-marker specific of intestinal origin (RefSeq Gene ID: 7429, updated on 22 March 2014; HGNC I D: HGNC:12690; location: Chromosome
  • TIMP1 Tissue Inhibitor of Metalloproteinase 1
  • CRC specific CTC gene (RefSeq Gene I D: 7076, updated on 24 March 2014; HGNC ID: HGNC:1 1820; location: Chromosome X: 47,441 ,712-47,446, 188 forward strand; Ensembl: ENSG00000102265, version: ENSG00000102265.7).
  • CRC specific CTC gene (Included in late phases of the study, as an optional gene) (RefSeq Gene ID: 7094, updated on 22 March 2014; HGNC ID: HGNC:1 1845; location: Chromosome 9: 35,696,945-35,732,392 reverse strand; Ensembl: ENSG00000137076, version: ENSG00000137076.14).
  • Lymphocyte-specific gene used as reference gene. (RefSeq Gene ID: 5788, updated on 22 March 2014; HGNC ID: HGNC:9666; location: Chromosome 1 : 198,607,801 -198,726,545 forward strand.; Ensembl: ENSG00000081237, version: ENSG00000081237.14)
  • NCBI reference sequence of the mRNAs encoded by each gene is indicated in Table 2 (see preliminary sections of the Examples); specifically, the transcript variant or variants that can be detected by the probes used in the Examples of the present application are indicated in said Table, as well as the proteins that can be translated from said transcripts.
  • the group of the present inventors had also reported the diagnostic and prognostic value of TIMP1 , CLU and TLN1 (Barbazan et al., 2012b), but its combination with GAPDH and VIL1 in the previous design model had not been suggested. Moreover, no genes with predictive value for assessing the effectiveness of therapies administrated to mCRC patients had been reported by the group of the present inventors.
  • the set of markers includes two genes previously associated to the induction of EMT-like aggressive cancer phenotypes, LOXL3 and ZEB2.
  • each of the seven markers individually has a predictive value for the response to the administered therapy, both for predicting PFS and OS for the patients undergoing the treatment to assess, particularly when the classification as responders and non responders to the therapy is made by comparing a first follow-up sample with a previous sample, specially a baseline sample taken before therapy start, and confirmed in a second follow-up sample taken in a moment of the therapy course subsequent (when at least one more or more than one additional therapy cycle has been administered) to the moment when the first follow-up sample was taken.
  • Example 1 all markers show a significant correlation with the other six additional markers, not only when the baseline blood sample (the sample taken before therapy start) is considered, but also for the first follow-up sample (taken approximately 4 weeks after therapy start, when the therapy cycle 1 has been administered) and the second follow-up sample (taken approximately 16 weeks after therapy start, once therapy cycle 2 has been administered and before therapy cycle 3). Therefore, it is expectable that combinations of said seven markers might also have a predictive value for the patients undergoing therapy.
  • the method of the present invention encompasses the assessment of therapy response by analysing the expression level in CTCs of at least one of the genes of the group of GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 and its comparison with a reference value (for instance, the 75% percentile cutoff value), considering responders to the therapy those subjects having values lower than said cutoff value in the time point of therapy course when the analysed blood sample has been taken.
  • a reference value for instance, the 75% percentile cutoff value
  • the method of the present invention can be carried out determining only one marker or determining only (or at least) two, three or four markers.
  • Such regression analysis shows that LOXL3 is the marker whose contribution is more important in the model and, for that reason, it is the preferred marker when the method of the invention is to be carried out with only one marker, and it is one of the markers that, preferable, should be included in any combination of markers.
  • the preferred combinations of set of markers for determining and analysing their expression levels are:
  • the embodiments of the method of the invention based on the combination of a set of markers in a model, instead of being based on the results obtained for an individual marker, diminish the probability of type I errors, that is, false positives.
  • the six-gene panel based on GAPDH, VIL1 , TIMP1 , CLU, LOXL3 and ZEB2 considered in Examples 1 to 3 of the present invention significantly reduced the probability of type I error and increased the reliability of the analysis when working with relatively small patients cohorts.
  • the embodiments of the method of the present invention based on the combination of several markers of the group of GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 are preferred, particularly those based on six of said markers or on the seven markers.
  • TIMP1 is a CTC-marker specific of intestin origin, just as TIMP1 and CLU, and its diagnostic and prognostic value for mCRC is similar to that of said genes according to previous works of the group of the present inventors (Barbazan et al., 2012b), in the models based on the combinations of six markers, it is considered that TIMP1 or CLU can be replaced by TLN1 , particularly in the model applied in Examples 1 to 3, which is discussed below.
  • Example 3 shows that the present inventors appear to have surprisingly arrived at an appropriate combination of markers that allow good patient stratification before therapy start and also therapy response monitoring. And it is particular surprising because the predictive value of the method of the present invention seems not to arise simply from the inclusion of EMT markers in the set of analysed genes.
  • EMT markers have predictive value when their levels are assessed in CTCs of epithelial origin, not even when the protein products of the genes under study are all factors inducing E-cadherin silencing (LOXL2, ZEB1 , E47, SNAIL1 , SNAIL2, TWIST1 ), just like LOXL3 and ZEB2.
  • SNAIL1 the gene encoding Snail, which is a protein involved in E-cadherin silencing where several networks regulating EMT converge, did not give rise to statistically significant results in order to predict the response treatment in terms of Progression Free Survival (PFS) and Overall Survival (OS).
  • PFS Progression Free Survival
  • OS Overall Survival
  • ZEB1 a gene encoding a transcription factor closely related to ZEB2 and frequently mentioned together with ZEB2 (or encompassed by the common denomination ZEB) as a factor with similar involvement in the EMT process.
  • ZEB1 a gene encoding a transcription factor closely related to ZEB2 and frequently mentioned together with ZEB2 (or encompassed by the common denomination ZEB) as a factor with similar involvement in the EMT process.
  • one of the advantages of the method of the present invention is the short numbers of markers (six in the basic design of the method, preferably normalized to a seventh one, CD45) that are enough for good monitoring of treatment response; and indeed, as commented in Example 1 , each of said seven markers has predictive value by itself and can be used individually.
  • markers six in the basic design of the method, preferably normalized to a seventh one, CD45
  • each of said seven markers has predictive value by itself and can be used individually.
  • the sample needed for carrying out the method disclosed in WO12149014A1 must be a tumor sample.
  • the study giving rise to the method of the present invention has been carried out with mCRC patients receiving the standard treatment for mCRC patients, and the samples taken to the patients are blood samples, easier to obtain and well admitted by most patients.
  • Another important advantage of the method of the present invention is the early moment during therapy course when the effectiveness of therapy is evaluated.
  • One of the main objectives in this study was to analyze how CTC- marker variations could predict therapy response. This evaluation should be done as soon as possible, as those treatment-refractory patients will not have any beneficial effect but they will be affected by chemotherapy-derived toxicity. Routinely, evaluation of tumor evolution is performed approximately three months after treatment onset, and during this time some patients may progress without being detected, dying before first CT evaluation in worst cases. Variations in the analyzed CTC-markers between baseline and 4-week follow up, effectively predicted PFS and OS outcome, generating a model that early classifies responding and non responding patients after only one chemotherapy cycle.
  • the method of the present invention is compatible with any other assessment methods, particularly with imaging techniques such as CT tomography and/or with the determination of the level of other biomarkers, for instance in serum, such as CA-125 or CEA.
  • imaging techniques such as CT tomography
  • the method of the present application can be seen as complementary to such techniques or any other similar ones, which can be used to confirm the assessment.
  • Example 4 wherein the results obtained by the method of the present invention were compared with the results derived from CT colonographies performed on the same patients, not only confirm the validity of the method of the present invention as a reliable tool for assessing mCRC patients' response to an administered therapy well before the CT colonographies are performed, but they also indicate that the present method seems to be more reliable, because it gives rise to a better classification of a group of patients as responders or non responders than said imaging technique when their PFS and OS values were taking into account.
  • CTC multimarker panel a set of genes whose expression levels are measured on CTCs. For that reason, normalizing the expression levels obtained with regard to the expression levels of a non-CTC gene, such as CD45, is highly recommendable in order to avoid signals coming from other possible cells remaining after CTC enrichment, such as lymphocytes.
  • CTCs circulating tumor cells
  • epithelial CTC specific transcripts combined with EMT- markers might improve CTC detection rates, compared for example with CellSearch ® , as a broader range of cellular subtypes could be identified.
  • the method of the present invention allows the stratification of patients prior to treatment by means of the quantification of CTC markers in the baseline sample. Then, it may allow the use of more or less aggressive therapies based on marker levels before the beginning of a systemic treatment line.
  • the present invention provides a method which can be regarded as an early prognostic test, useful in the clinical setting for mCRC patients undergoing therapy.
  • a multicenter study including a larger number of patients should be advisable, that would allow to obtain more accurate results about the reference cutoff values for marker expression levels or possible circumstances that could make advisable to use values different from the 75% percentile value as reference value.
  • the data provided in the present application are useful orientative tools in that sense.
  • T and N relates to TNM staging system
  • Tumor burden, metastasis location and therapy response were evaluated by standard imaging procedures (computed tomography, CT) by a specialized radiologist. Following RECIST 1 .1 guidelines (Eisenhauer et al., 2009), disease progression was defined as an increase in the number of metastatic lesions, growth of pre-existing distant tumors in more than 20% of the initial size, or both. Patients who died during the follow-up period without being evaluated by CT, were also considered as progression events, having verified that death was disease-related. Eight healthy controls, matched for age and sex with patients, were included for the validation of LOXL3 and ZEB2 as CTC markers.
  • RNAIater ® solution RNAIater ® solution at -80 S C until further processing.
  • RNA was extracted with a methodology optimized for low concentration samples (Qiamp Viral, Qiagen) and cDNA was synthesized using SuperScriptlll polymerase (Life Technologies). To optimize target detection, samples were first preamplified (PreAmp Master Mix kit, Life Technologies).
  • MRNA levels of CD45, GAPDH, VIL1 , TIMP1 , CLU, TLN1 , LOXL3 and ZEB2 genes were quantified by quantitative Real- Time PCR using hydrolysis probes chemistry (Life Technologies) in a StepOne plus thermocycler (Life Technologies). Probe characteristics are detailed in Table 2, as well as the mRNA reference sequence (accession in GenBank, http://www.ncbi.nlm.nih.gov/qenbank/. wherein the last digit indicates the version of the referenced sequence) corresponding to the specific mRNA variant detected by each probe, and the reference sequence corresponding to the protein translated from each of said transcripts:
  • PFS Progression Free Survival
  • OS Overall Survival
  • Prognostic groups for each analysis point were set based on CTC marker levels, and single patients were included into low or high- CTC groups if marker levels were, respectively, below or above cutoff, defined as the 75% percentile for each independent marker. That means that, for each marker and time point, 25% of the patients were classified as high-CTC, whereas the remaining 75% were included in the low-CTC group.
  • Kaplan-Meier (KM) and univariate and multivariate COX regression survival analysis were used to study associations between marker levels and PFS/OS. Differences between controls and patients for LOXL3 and ZEB2 were analyzed using Mann-Whitney non- parametric t test. Spearman correlation test was used to evaluate differences in CD45 expression between runs. All statistic tests were performed with SPSSv20.0 and GraphPad prism v5 software, and considered significant when p ⁇ 0.05.
  • GAPDH and VIL1 were chosen as they have been previously validated as CTC detection markers in a previous work from the group of the present inventors (Barbazan et al., 2012a). GAPDH was used as a housekeeping gene, detecting all cell types present in the sample, and VIL1 as a specific intestinal origin CTC-marker.
  • CD45 gene expression (a lymphoid cell marker) was used as a reference gene to normalize CTC-markers expression levels, minimizing the noise produced by the presence of non-specifically isolated cells in the sample.
  • the usefulness of CD45 as a normalizer had been previously validated (Barbazan et al., 2012a;
  • TLN1 was also added to the study as a seventh marker, also as a CRC specific CTC gene coming from the same global gene expression profiling study as
  • VIL1 Low 12.54 10.07-15.00 ⁇ 0.001 24.38 20.71-28.05 ⁇ 0.001
  • TIMP1 Low 12.69 10.25-15.12 ⁇ 0.001 24.50 20.72-28.28 ⁇ 0.001
  • VIL1 Low 12.14 9.92-14.36 0.017 23.85 20.13-27.57 ⁇ 0.001
  • TIMP1 Low 11.96 9.79-14.22 0.066 23.29 19.62-26.96 0.015
  • TLN1 Low 11.87 9.60-14.15 0.090 23.16 19.43-26.88 0.022
  • the present inventors generated a simple model for the combination of markers in one single value for each analysed patient.
  • markers were selected, namely GAPDH, VIL1 , TIMP1 , CLU, LOXL3, ZEB2.
  • GAPDH GAPDH
  • VIL1 VIL1
  • TIMP1 TIMP1
  • CLU CLU
  • LOXL3 LOXL3
  • ZEB2 LOXL3
  • Baseline CTC-marker model 50 3.39 (1.68-6.83) 0.001 2.96 (1.44-6.09) 0.003
  • CEA Carcinoembrionic antigen
  • ECOG Eastern Cooperative Oncology Group
  • PS Performance Status
  • Low-CTC ⁇ Responder (R) Responders group included patients that had been previously included in the low-CTC group both at baseline and at 4 weeks, based on marker levels. Patients that changed from the low-CTC group at baseline to the high-CTC one at 4 weeks, and those being at the high-CTC one in both time points, were classified as non-responders. Patients changing from the high-CTC group at baseline to the low-CTC one at 4 weeks, were preventively included in the group of non responders and a third confirmatory sample was drawn before cycle 5 of chemotherapy (approximately 16 weeks from baseline). If those patients were corroborated as low-CTC by the CTC-marker model, they were reclassified as responders. They continued as non-responders if they came back to the high-CTC group at the 16-week follow-up.
  • Table 9 shows the data represented in Fig. 3.
  • CEA Carcinoembrionic antigen
  • ECOG Eastern Cooperative Oncology Group
  • PS Performance Status
  • mets metastasis
  • R Responder patient group
  • NR Non responders patient group *Most significant prognostic factor in Cox multivariate analysis
  • EMT EMT
  • prognostic or predictive value EMT markers
  • the assays described in Examples 1 and 2 were performed with a group of six well-known EMT markers (LOXL2, ZEB1 , E47, SNAIL1 , SNAIL2, TWIST1 ) in 20 patients with mCRC (a random subset of the 50 patients whose demographic data are shown in Table 1 ), in the samples taken from said patients before and during the treatment (4 weeks and 16 weeks after beginning the treatment). A possible correlation between the expression levels of said genes and response to treatment was evaluated.
  • TIMP1 talin 1
  • CI Confidence Interval
  • CEA Carcinoembrionic antigen
  • ECOG Eastern Cooperative Oncology Group
  • PS Performance Status
  • Fig. 5A patients were classified as responders and non- responders following the same criteria used in Example 2 (see Table 8). Using the model including 7 markers (TLN1 included), KM survival analysis for responders and non-responders was performed.
  • Figs. 5B and 5C respectively, show the results obtained for PFS and OS.
  • CEA Carcinoembrionic antigen
  • ECOG Eastern Cooperative Oncology Group
  • PS Performance Status
  • mets metastasis
  • R Responder patient group
  • NR Non responders patient group *Most significant prognostic factor in Cox multivariate analysis
  • TLN1 as a seventh marker in the model does not change the tendencies and variation directions shown with the 6-marker model, but the difference between the groups are considerably increased.
  • Adding TLN1 to the six marker model initially tested improves the effectiveness of the classification method. For instance, if the multivariate Cox proportional harzard regression (HR) analyses corresponding to the six-marker (see Table 7) and seven-marker (see Table 13) models are compared, it can be observed that the HR value for the OS changes from 5.10 in the six marker model (without TLN1 ) to 9.67 in the seven-marker model (with TLN1 ).
  • HR Cox proportional harzard regression
  • PS ECOG is the most important variable, the most significant factor; however, once TLN1 is included in the model, the model itself becomes the most significant variable. And that is the case when the model is prepared with the data obtained both from the baseline sample and from the 4- week follow-up sample.
  • the 6-marker model can be regarded as a useful tool to predict therapy response and to take decisions in connection with the maintenance of the administered therapy or the change to a different one; the 7-marker model, in turn, increases the reliability of the method.
  • the possible predictive value of each individual marker in said version of the model was assessed, that is, when the classification as responder or non responder is taken after considering the gene expression levels not only in the CTCs of the first follow-up sample but also in at least a second follow-up sample (in this case, the 16-weeks follow-up sample), particularly for those patients that were high-CTC at baseline and low- CTC after administering the first therapy cycle (4 weeks after therapy start).
  • each marker showed to have predictive value for the therapy response, both for predicting PFS and OS.
  • TIMP1 R 12.6 (10.3-14.9) 0.005 24.6 (20.9-28.2) 0.0004
  • any combination of the seven markers provides a predictive value for therapy response, at least from an experimental and statistical point of view. Therefore, apart from the six- and seven-marker models discussed above, other alternative models for assessing therapy response based on different combinations of markers (two, three, four, five, or six of the seven markers of the method of the present invention) may also be used for assessing therapy effectiveness and can be considered comprised within the scope of the present invention.
  • classifying the blood sample as "low-CTC” if the expression level in CTCs of more than a half of the selected analysed genes is low, and "high-CTC” if the expression level in CTCs of at least one half of the selected analysed genes is high.
  • LOXL3 is one of the preferable options.
  • good combinations could be:
  • CT colonography was performed three months after the beginning of the therapy.
  • the assessment of the response obtained from the CT colonography images and with the seven CTC- marker model was compared.
  • Fig. 6B and Fig. 6C show the results of a survival analysis performed in order to compare the terms corresponding to PFS (Fig. 6B) and OS (Fig. 6C) for the three groups of patients. Both survival studies are especially meaningful.
  • the members of the group classified as non-responders by both techniques are those with the worst prognosis, and those classified as responders by both techniques are those with best prognosis.
  • those patients classified as responders according to the CT results and as non responders using the CTC marker model exhibit significantly lower PFS and OS values (approximately 5 months of PFS and 10 of OS) than the members of the group classified as responders by both techniques.
  • Gervasoni A Monasterio Munoz RM, Wengler GS, Rizzi A, Zaniboni A, Parolini O.
  • Hayes DF Circulating Tumor Cells at Each Follow-up Time Point during Therapy of Metastatic Breast Cancer Patients Predict Progression-Free and Overall Survival. Clinical Cancer Research. 2006;12:4218-24. Hou HWH, Warkiani MEM, Khoo BLB, Li ZRZ, Soo RAR, Tan DS-WD, Lim W-TW,
  • Circulating tumor cells as a surrogate marker for determining response to chemotherapy in Japanese patients with metastatic colorectal cancer.

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Abstract

L'invention concerne un procédé permettant de prédire les résultats chez un patient et une réponse thérapeutique du cancer colorectal métastatique. Le procédé est basé sur la détection du niveau d'expression d'un panel de gènes exprimés dans des cellules tumorales circulantes (CTC) épithéliales (GAPDH, VIL1, TIMP1, CLU, LOXL3, ZEB et TLN1), de préférence normalisés au CD45 ou d'un autre gène non exprimé dans les cellules CTC, et la comparaison de l'évolution desdits niveaux dans des échantillons sanguins prélevés à différents moments dans le temps chez des patients souffrant d'un cancer colorectal métastatique et subissant une thérapie. Les échantillons sont classés en fonction des niveaux d'expression d'au moins l'un desdits gènes ou, de préférence, d'une combinaison de six (GAPDH, VIL1, TIMP1, CLU, LOXL3, ZEB) ou sept gènes, en une forte ou une faible concentration de cellules CTC, le changement à une classification faible ou le maintien de la classification à un niveau faible indiquant l'efficacité de la thérapie. Le procédé est facile à mettre en œuvre et peut être effectué précocement au cours de la thérapie, ce qui permet de prendre plus tôt des décisions concernant la poursuite de l'administration de la thérapie de l'administration à des patients qui ne répondent pas au traitement.
PCT/EP2015/056649 2014-03-26 2015-03-26 Procédé permettant de prédire les résultats chez un patient et une réponse thérapeutique du cancer colorectal métastatique Ceased WO2015144854A1 (fr)

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