Method for determining the survival prognosis of a patient suffering from pancreatic cancer

Abstract

The present invention relates to pancreatic cancer, and more particularly to the survival prognosis of a patient suffering from pancreatic cancer. The invention also aims to determine the benefit to the patient of receiving a pancreatic cancer treatment, particularly a treatment based on 5-fluorouracil. The invention also relates to a method for monitoring the efficacy of a pancreatic cancer treatment, advantageously of a treatment based on 5-fluorouracil, by implementing the method.

Description

[0001]DESCRIPTION TITLE OF THE INVENTION: METHOD FOR DETERMINING THE SURVIVAL PROGNOSIS OF A PATIENT WITH PANCREATIC CANCER TECHNICAL FIELD OF THE INVENTION The present invention relates to pancreatic cancer, and more particularly to the survival prognosis of a patient suffering from pancreatic cancer. The invention also aims to determine the ability of said patient to receive treatment for pancreatic cancer, particularly treatment based on 5-fluorouracil (5-FU). The incidence of pancreatic cancer, of which pancreatic ductal adenocarcinoma (PDAC) is the most common type, continues to increase, particularly in Western countries, and is expected to become the second most common cause of cancer-related death by 2030. Despite high prevalence and incidence rates, the survival prognosis for this disease remains poor, with an overall 5-year survival rate of less than 10%.At diagnosis, most patients with pancreatic ductal adenocarcinoma have locally advanced or metastatic cancer, and treatment options remain limited despite recent advances. Until 2011, the standard of care was gemcitabine; then came the chemotherapy regimen FOLFIRINOX (5-fluorouracil (5-FU), folinic acid, irinotecan, oxaliplatin), and in 2013, the gemcitabine plus nab-paclitaxel regimen was also introduced. These two multidrug treatments significantly improved median overall survival (OS) from 6.7 to 11.1 and 8.5 months, respectively.The limited success of treatments and the mortality rate, which remains high for some patients, underscore the need for resources to improve therapeutic targeting of patients who may prove to be good responders to 5-FU-based treatment, such as FOLFIRINOX or FOLFOX (5-fluorouracil, folinic acid, and oxaliplatin), and who would tolerate this treatment well in this indication. Treatment of pancreatic cancer with different compounds can have varying degrees of efficacy depending on the patient. However, to date, there is no way to predict the clinical benefit of the different treatments available for a given patient. There is therefore still a need for tests to select the right treatment for each patient, so as to give them the best chances of survival. It might be desirable for this test to be a test that can be performed regularly.An additional advantage would be that the said test is non-invasive. The inventors' work has made it possible to identify and select 10 genes, from among 63,494 genes, the study of whose expression level makes it possible to evaluate the survival time of a patient suffering from pancreatic cancer. Advantageously, this prediction also makes it possible to predict the chances of success of a 5-FU-based treatment and to select patients likely to respond favorably to a 5-FU-based treatment, in particular thanks to the measurement of progression-free survival, which makes it possible to know whether the patient responds favorably or not to the treatment. Thus, the study of the expression level of said genes makes it possible to provide information as to the advisability of administering a 5-FU-based treatment to a patient suffering from pancreatic cancer.One of the advantages of the invention lies in the fact that the level of expression of said genes can be assessed directly from a blood sample, advantageously whole blood from the patient, previously collected. This is particularly advantageous in the case of pancreatic cancer because it is very difficult to access the tumor cells. In addition, blood sampling (collection, stabilization and transport) can be standardized. Finally, the use of whole blood is safer than the use of a blood fraction such as peripheral blood mononuclear cells (PBMC), because it avoids handling errors related to the preparation of said fractions. By "whole blood" is meant blood with all its constituents (plasma, red blood cells, white blood cells, platelets, etc.) as opposed to "blood fraction", which corresponds to a product obtained by separation of the particular components of the blood.Peripheral blood mononuclear cells constitute an example of a blood fraction. The subject of the invention is therefore an in vitro method for establishing a survival prognosis in a patient suffering from pancreatic cancer comprising the following steps: a) measuring the level of expression of the marker genes consisting of the ten genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, in a blood sample of said patient previously taken; b) comparing the measured level of expression of the marker genes or homologous genes in step a) in said patient with a reference threshold; c) evaluating the survival time in said patient.The terms "homologous" or "same functional group" are defined herein as a polynucleotide sequence having a degree of identity of at least 80%, preferably 85%, more preferably 90%, and even more preferably 99% with the wild-type (full-length) gene sequence. In the context of this patent application, the term "functional" specifically refers to genes that belong to a homologous series, commonly referred to as a gene family, and that share the same functional group. This means that these genes have similar biological characteristics or functions, resulting in comparable reactions or behaviors in a given context, as described herein. The degree of identity refers to a sequence identity between two sequences. Identity can be determined by comparing a position in each sequence that can be aligned for comparison purposes.When an equivalent position in the sequences being compared is occupied by the same base, then the molecules are identical at that position. Various algorithms and / or alignment programs can be used to determine the homology of two sequences, including FASTA and BLAST. The method according to the invention makes it possible to establish a survival prognosis in a patient suffering from pancreatic cancer. According to the invention, steps a) to c) of the above method can be implemented on a patient suffering from pancreatic cancer, to predict or evaluate, after treatment, particularly 5-FU-based treatment, the efficacy and / or benefit of a treatment for pancreatic cancer in a patient suffering from said pathology, in particular, in terms of life expectancy.Thus, the invention also relates to an in vitro method for predicting or evaluating the efficacy and / or benefit of a treatment for pancreatic cancer in a patient suffering from said pathology, comprising the following steps: a) measuring the level of expression of the marker genes consisting of the ten genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, in a blood sample of said patient previously taken; b) comparing the measured level of expression of the marker genes or homologous genes in step a) in said patient with a reference threshold; c) evaluating the survival time in said patient. The method according to the invention is particularly suitable for predicting or evaluating the efficacy and / or benefit of a treatment for pancreatic cancer based on 5-FU.In the methods according to the invention, the reference threshold used in step c) to carry out the comparison is previously determined for the 10 genes or the homologous genes. The principle of the invention is based on the fact that the Applicant has been able to establish that the study of the level of expression of the 10 genes (MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1) or the homologous genes makes it possible to establish a prognosis of patient survival. More specifically, the Applicant established that by comparing data on the expression level of the 10 genes (MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1) or homologous genes obtained from a blood sample of said patient tested with data that it itself established for the 10 genes considered on a reference population of patients suffering from pancreatic cancer, before or during treatment, it was possible to establish a prognosis for the patient's survival and monitoring of the patient's treatment.The method according to the invention can be carried out on a blood sample from a patient, preferably on a peripheral blood sample from said patient, said blood sample being taken prior to implementing the method according to the invention. Peripheral blood is the blood which circulates through the heart, arteries, capillaries and veins. According to the invention, step a) of the method can be carried out by measuring the level of expression of the 10 genes (or homologous genes) of the group defined above. Thus according to the invention, step a) of the method can be carried out by measuring the level of expression of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes.In a first embodiment of the method according to the invention, the level of expression of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes is measured by measuring the amount of the protein encoded by said genes in the blood sample of said patient to be tested. In this case, the protein level is preferably measured using antibody-based detection methods such as immunochemistry or western blot analysis. In another embodiment of the method according to the invention, the level of expression of the genes is measured by measuring the transcription rate of said genes. This rate can be measured by measuring the amount of RNA or complementary DNA (cDNA) of said genes.In this case, the level of transcribed RNA or cDNA can be measured using nucleic acid detection methods such as quantitative PCR, DNA microarrays, hybridization with labeled probes, or lateral flow immunoassays, in particular using lateral flow strips. Preferably, in the methods according to the invention, the level of gene expression is measured by real-time quantitative PCR (qPCR) carried out on the RNA transcripts of said gene or on their cDNA. A qPCR is a PCR in which the amplified DNA is detected in real time while the polymerization reaction progresses. This detection is done by the accumulation of a fluorescent signal.This technique uses primers (sense and antisense) and a fluorescently labeled oligonucleotide probe, preferably hydrolysis probes (TaqMan), molecular beacons, dual hybridization probes (FRET), Eclipse probes, Amplifluor assays. Advantageously, said primers are specific to the flanking regions of the gene under consideration. In the case of the MCEMP1 gene, the flanking regions are located on exon 7 on chromosome 19 between nucleotides 7677090 and 7679829 (Assembly Dec. 2013, GRch38 / hg38 source UCSC). In the case of the S100A12 gene, the flanking regions are located on exon 2 and 3 on chromosome 1 between nucleotides 153373711 and 153375621 (Assembly Dec.2013, GRch38 / hg38 December 2013, source UCSC). In the case of the MMP9 gene, the flanking regions are located on exon 7 and 8 on chromosome 20 between nucleotides 46008908 and 46016561 (Assembly Dec.2013, GRch38 / hg38, source UCSC).In the case of the RACK1 gene, the flanking regions are located on exon 5 and 6 on chromosome 5 between nucleotides 181236897 and 181243906 (Assembly Dec.2013, GRch38 / hg38 December 2013, source UCSC). In the case of the DSC2 gene, the flanking regions are located on exon 9 and 10 on chromosome 18 between nucleotides 31058840 and 31102421 (Assembly Dec.2013, GRch38 / hg38 December 2013, source UCSC). In the case of the LYN gene, the flanking regions are located on exon 10 and 11 on chromosome 3 between nucleotides 188154157 and 188890671 (Assembly Dec. 2013, GRch38 / hg38 source UCSC). In the case of the LPP gene, the flanking regions are located on exon 10 and 11 on chromosome 3 between nucleotides 188154157 and 188890671 (Assembly Dec. 2013, GRch38 / hg38 source UCSC). In the case of the ARL4C gene, the flanking regions are located on exon 16 on chromosome 16 between nucleotides 399665 and 399728 (Assembly Dec. 2013, GRch38 / hg38 source UCSC).In the case of the ALDOA gene, the flanking regions are located on exon 16 on chromosome 16 between nucleotides 399665 and 399728 (Assembly Dec. 2013, GRch38 / hg38 source UCSC). In the case of the SLC8A1 gene, the flanking regions are located on exon 2 and 3 on chromosome 2 between nucleotides 40534806 and 40545781 (Assembly Dec. 2013, GRch38 / hg38 source UCSC). In an advantageous embodiment, the following primers and probes can be used to carry out the qPCR: - RNAs from the MCEMP1 gene o sense primer: GCGGCGTGTTTTCTGTCTAC (SEQ ID NO.1) o antisense primer: GGCACACTCATAATGACACAGC (SEQ ID NO.2) o Probe: AGGGCACACATGGCGACACC (SEQ ID NO.3) - RNAs from the S100A12 gene o sense primer: CCTCTCTAAGGGTGAGCTGAAG (SEQ ID NO.4) o antisense primer: GCAATGGCTACCAGGGATATG (SEQ ID NO.5) o Probe: TGCTTACAAAGGAGCTTGCAAACACCA (SEQ ID NO.6) - RNAs from the MMP9 gene o sense primer: CTTTGACAGCGACAAGAAGTGG (SEQ ID NO.7) o antisense primer: CGCCACGAGGAACAAACTG (SEQ ID NO.8) o Probe : TATCCTTGGTCCGGGCAGAAGC (SEQ ID NO.9) - RNAs issus du gene RACK1 o amorce sens: AACCCTATCCGTCTCCTGTG (SEQ ID NO.10) o amorce anti-sens: ACCGTGTTCAGATAGCCTGTG (SEQ ID NO.11SET) o AGTCCAGCCAG (SEQ ID NO.11). NO.12) - RNAs from the DSC2 gene o Amorce sense: CAGATGCCAAAACCAATGAAGG (SEQ ID NO.13) o Amorce anti-sense: TCATGGCTGATCTTGGACTAGC (SEQ ID NO.14) o Probe: ACACCAATTTGCAAGATCCTGTTGCT (SEQ ID NO. amorce sens: ATCCAACGTCCAATAAACAGCA (SEQ ID NO.16) o amorce anti-sens: AAGGCTACCACAATGTCTCCT (SEQ ID NO.17) o Probe : AGGCCAGTTCCAGAATCTCAGCTTTTACC (SEQ ID NO.18) - RNAs from the LPP gene: (SEQ ID NO.19) o amorce anti-sense: CTTGGTTATCTCCTTCAGACAGG (SEQ ID NO.20) o Probe : CACTGCTACCGATGCGAGGATTGC (SEQ ID NO.21) - RNAs issus du ARL4C gene o amorce sense: AAAGCCCTGTGGTGTATCAA (SEQ ID NO.22) o anti-sense ID NO. GCTTCCTCTGTTGGGTCAGA (SEQ ID NO.23) o Probe : TGTTTGACCTAATAATAGCCCGTTTCGTC (SEQ ID NO.23).24) - sRNAs from the ALDOA gene o sense primer: GCTTGCACTCAGAAGTTTTCTCA (SEQ ID NO.25) o antisense primer: GGAAGGTGATCCCAGTGACA (SEQ ID NO.26) o Probe: ATTGCCATGGCGACCGTCACAG (SEQ ID NO.27) - sRNAs from the SLC8A1 gene o sense primer: GTGGATCTTGGCATAACAGACAC (SEQ ID NO.28) o antisense primer: GTCATTGGCTGAGCACATTTG (SEQ ID NO.29) o Probe: CTTCCAGGCCGCTGAGCAAAGT (SEQ ID NO.30) qPCR makes it possible to determine the value of the cycle number (Cq) of a gene (Cqgene) in the patient to be tested. Cq (Cycle of quantification) is defined as the number of PCR cycles required for the fluorescent signal to cross the background noise. Cq thus makes it possible to determine the level of expression in cycle number. The Cq value obtained can then be normalized to the expression level of at least one ubiquitous gene expressed in cycle number in the same blood sample from the same patient.Said ubiquitous genes are genes which are expressed in all cells of an organism under normal and pathophysiological conditions. These genes are generally expressed at relatively constant levels. Preferably, in the methods according to the invention, in step a), in addition to the level of expression of the marker genes (Cqgene) or homologous genes, the level of expression of at least one ubiquitous gene is measured, said levels of expression being measured in number of cycle(s) (Cq, "cycle of quantification") by real-time quantitative PCR (qPCR), then the level of expression of the marker genes is normalized relative to the level of expression of at least one ubiquitous gene according to ΔCq. gène = Cq gène– Ubiquitous Cqgenein order to obtain a normalized expression level ΔCqgene for each marker gene whose expression level has been measured. Preferably, in the methods according to the invention, the normalization is carried out relative to the expression level of a ubiquitous gene, preferably, relative to the expression level of the ATP5F1A gene. In this case, the normalized expression level ΔCq gène of a marker gene is calculated by: ΔCq gène = Cq gène – Cq ATP5F1AIn the case of the ATP5F1A gene, the flanking regions are located on exon 7 and 8 on chromosome 18 between nucleotides 46084144 and 46104233 (Assembly Dec.2013, GRch38 / hg38, source UCSC). Primers and probes particularly suitable for the ATP5F1A gene can be: - RNAs from the ATP5F1A gene o sense primer: CCCAGTTGGTGAAGAGACTTAC (SEQ ID NO.31) o antisense primer: CCAGAGTAAGGAGCCAGGTAC (SEQ ID NO.32) o Probe: TACGGCCTCGGATGCTGCCC (SEQ ID NO.33) Advantageously, to carry out the qPCR, the primers, their size (preferably between 80 and 150 nucleotides), their melting temperature (Tm, preferably 60°C ± 1°C), their percentage of G and C nucleotides (GC%, preferably ~60% in 3'), their 3' and 5' self-complementarity and their stability (preferably less than 4 nucleotides), the size ranges of the product and the thermodynamic parameters (evolution of the secondary structure according to the Tm of the primers and the sodium salt concentration) are chosen to allow simultaneous detection. By "long-term survival" is meant a survival of more than 10 months, preferably more than 12 months, even more preferably more than 15 months. By "short-term survival" is meant a survival of less than 6 months, less than 5 months, or less than 3 months. Additionally, when a patient is expected to have long-term survival, this also means that they may be considered eligible for 5-FU treatment.Conversely, short-term survival of the patient indicates that a 5-FU-based treatment will have little or no benefit to the patient. Another treatment should then be considered. The Applicant's work on a reference population has led it to identify 10 genes that can be used as markers for a survival prognosis of a patient suffering from pancreatic cancer, but also to determine for these 10 genes, a reference threshold value allowing a comparison to be made. However, greater precision in the survival prognosis can be provided by measuring the expression level of the 10 genes or homologous genes. Consequently, according to the embodiment, during step a), the expression level of the 10 marker genes is measured and, during step b): i) an INDEX value is determined. gène dependent on the normalized gene expression level, defined by: INDEX gène = β coefficient of the gene * ΔCqgène Wherein the β coefficient of a given gene is as defined in Table 1 below; [Table 1] Gene β Coefficient MCEMP1 -0.00084112S100A12 -0.0036297 MMP9 -0.01867287 RACK1 0.07083326 DSC2 -0.02450139 LYN -0.0623547 LPP -0.09273414 SLC8A1 -0.00029473 ARL4C 0.05992789 ALDOA -0.01105714 Table 1: β coefficient of the 10 marker genes ii) we determine, for a given patient, an INDEX value patient equal to the sum of the INDEXES gèneof the 10 genes or homologous genes, and iii) the INDEXpatient is compared with a reference threshold previously determined for the combination of the ten genes or homologous genes. The Applicant has thus developed a system allowing a simplified comparison of the expression levels of several genes. This comparison system required the development of a coefficient, the Beta Coefficient (see Table 1 above), to weight the importance of the different genes within the system. An INDEXpatient is then calculated, corresponding to the sum of the INDEXgene of the marker genes or homologous genes whose expression level was measured in step a) of the methods according to the invention: INDEX patient = Σ INDEX gène This INDEX patientis then compared to a reference threshold value previously determined by the Applicant for the combination of the 10 marker genes. Preferably, for the combination of the 10 genes, said reference threshold value is between -0.53 and -0.47, more preferably between -0.51 and -0.49, or even more preferably equal to -0.5. This threshold of -0.5 represents the value most likely to discriminate patients according to their survival prognosis, it is established after optimization of the parameters of the Mantel-Cox model where the modeling tests different thresholds and seeks to maximize the p-value of the log-rank test associated with the tested threshold value. Thus the model optimally converged to -0.5. Thus, on the basis of the reference threshold value defined for the 10 marker genes or homologous genes, it is possible to establish the survival prognosis of the patient tested.According to a preferred embodiment of the methods according to the invention, in step a) in a blood sample previously taken from a patient to be tested, by qPCR, the level of expression in cycle number (Cqgene) of the 10 genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 and of the ubiquitous gene ATP5F1A is measured. The normalized expression level ΔCqgene of each of the 10 genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 is then calculated according to: ΔCqgene = Cqgene – CqATP5F1A An INDEXgene is then calculated for each of the genes according to: - INDEXgene = β coefficient of the gene * ΔCqgene, in which the β coefficient of a given gene is as defined in Table 2 below: [Table 2] Gene Coefficient β M. CEMP1-0.00084112S100A12 -0.0036297 MMP9 -0.01867287 RACK1 0.07083326 DSC2 -0.02450139 LYN -0.0623547 LPP -0.09273414 SLC8A1 -0.00029473 ARL4C 0.05992789 ALDOA -0.01105714 Table 2: β coefficient of the 10 marker genes The INDEXpatient is then calculated as: INDEXpatient = INDEXMCEMP1 + INDEXS100A12 + INDEXMMP9 + INDEXRACK1 + INDEXDCS2 + INDEXLYN + INDEXLPP + INDEXSLC8A1 + INDEXARL4C+ INDEXALDOA This value of INDEXpatient is then compared with the reference threshold value of the combination of the 10 marker genes, i.e. -0.5. If a patient has an INDEXpatient lower than -0.5, he or she is considered to have a long-term survival prognosis and may be considered eligible for 5-FU treatment. Conversely, if a patient has an INDEXpatient higher than -0.5, this indicates that he or she has a short-term survival prognosis and that 5-FU treatment will have little or no benefit. Another treatment should then be considered.The invention also relates to a method for monitoring the effectiveness of a treatment for pancreatic cancer by implementing the method according to the invention described above, advantageously at treatment time intervals. Those skilled in the art will easily be able to determine the treatment time intervals at which they wish to implement the method according to the invention. For example, suitable time intervals are 1 week, 2 weeks, 1 month, 2 months or 6 months. The invention also relates to the 5-FU-based treatment for its use in the treatment of pancreatic cancer in a patient with INDEX. patientless than -0.5 calculated according to the preferred embodiment described above. The present invention further relates to a DNA chip having on its surfaces, nucleic acids capable of hybridizing with the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or the homologous genes to detect the expression level of the 10 genes or the homologous genes, optionally with nucleic acids specific for a ubiquitous gene, even more preferably nucleic acids specific for the ubiquitous gene ATP5F1A. The present invention also relates to a kit for determining the survival prognosis of pancreatic cancer in a patient, comprising means for detecting the expression level of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes to detect the expression level of the 10 genes.The means for detecting the level of expression of the 10 marker genes or homologous genes may be, for example, a DNA chip according to the invention, a set of primers and a reporter such as fluorescent agents, labeled hydrolysis probes, molecular beacons, hybridization probes, and antibodies. Preferably, the kit according to the invention may comprise means for detecting the level of expression of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes. The kit may further comprise instructions for use in the in vitro method according to the invention. Finally, the invention also relates to the use of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, for the prognosis of survival of pancreatic cancer, in particular, during treatment based on 5-FU.The present invention may be better understood and other advantages and characteristics may appear on reading the following examples and the appended drawings in which: Figure 1 represents the progression-free survival curves, i.e. the duration after treatment during which the cancer does not worsen, taken from the blood samples of the 90 patients of example 1, calculated by the Kaplan-Meier method for the 2 survival groups after calculating the reference threshold value of -0.5. The group represented in gray is the set of individuals whose INDEXpatient value is lower than the reference threshold value and the group represented in black is the set of individuals whose INDEXpatient value is higher than the reference threshold value. Here the long-term survival group is the gray group. The p-value of the log-rank test "logarithmic test by rank" is indicated at the bottom of the graph: P < 0.0001.Figure 2 shows the overall survival curves, derived from the blood samples of the 90 patients in Example 1, calculated by the Kaplan-Meier method for the 2 survival groups after calculating the reference threshold value of -0.5. The group shown in gray is the set of individuals whose INDEXpatient value is lower than the reference threshold value and the group shown in black is the set of individuals whose INDEX value. patientis greater than the reference threshold value. Here the long-term survival group is the gray group. The p-value of the log-rank test is indicated at the bottom of the graph: P < 0.0001. Example 1: Identification of a gene set for pancreatic cancer survival prognosis 1.1 RNA preparation A clinical analysis was performed on 90 patients with previously untreated (at baseline) advanced pancreatic cancer (PDAC) (mean age 68.7 years; 37-88) who received a 5-FU-based regimen. These patients were from two clinical studies GemciPANC (ID NCT03599154) and BACAP (ID NCT02818829). Whole blood samples from 90 patients collected before treatment, packed in PAXgene tubes in dry ice, were received and stored at -80°C. Total RNA was extracted from the 90 whole blood samples. Transcriptome analysis (biomarker search) was conducted only on these samples. The 90 RNA samples werewere analyzed to determine their quality. RNA integrity control was performed with the Bioanalyzer 2100 (Agilent Technologies, Palo Alto, USA) using the Agilent Technologies Eukaryotic Total RNA 6000 Nano Chip. RNA quantity was monitored using a NanoDrop ND-1000 spectrophotometer (THERMO Scientific). Purified RNA was stored at -80°C. 90 whole blood RNA samples, which correspond to reference blood samples, were extracted from previously collected blood (PAXgene blood collection tubes, BD) using PAXgene Blood RNA Kit V.2 (PreAnalitix) according to the manufacturer's recommendations. Biomarker validation was performed using a COBAS platform (LC480, Roche Diagnostics) and appropriate biostatistical approaches were used to filter the best biomarkers. Table 3 below lists the 90 anonymized patients by number, independing on the clinical study (Gemcipanc or Bacap), the treatment (FOLFIRINOX OR FOLFOX), the stage of the tumor (metastatic or locally advanced) and presents for each patient the results of overall survival and progression-free survival. [Table 3] Survival Subject-free survival No. Clinical study Treatment Tumor Overall Progression (days) (days) 1 Gemcipanc Folfirinox Metastatic 875 318 2 Gemcipanc Folfirinox Metastatic 478 185 3 Gemcipanc Folfirinox Locally advanced 487 224 4 Gemcipanc Folfirinox Metastatic 116 74 5 Gemcipanc Folfirinox Locally advanced 765 665 6 Gemcipanc Folfirinox Metastatic 449 149 7 Gemcipanc Folfirinox Locally advanced 1241 381 8 Gemcipanc Folfirinox Metastatic 232 140 12 Gemcipanc Folfirinox Metastatic 249 84 13 Gemcipanc Folfirinox Metastatic 614 485 15 Gemcipanc Folfirinox Metastatic 600 317 22 Gemcipanc Folfirinox Locally advanced 1058 112 23 Gemcipanc Folfirinox Metastatic 850 358 25 Gemcipanc Folfirinox Metastatic 384 26026 Gemcipanc Folfirinox Metastatic 985 854 27 Gemcipanc Folfirinox Locally advanced 1031 464 28 Gemcipanc Folfirinox Locally advanced 563 225 31 Gemcipanc Folfirinox Locally advanced 1015 1015 32 Gemcipanc Folfirinox Locally advanced 503 503 33 Gemcipanc Folfirinox Metastatic 269 73 34 Gemcipanc Folfirinox Metastatic 996 199 35 Gemcipanc Folfirinox Metastatic 38 38 36 Gemcipanc Folfirinox Locally advanced 983 983 38 Gemcipanc Folfirinox Locally advanced 223 57 39 Gemcipanc Folfirinox Metastatic 339 99 40 Gemcipanc Folfirinox Metastatic 120 82 42 Gemcipanc Folfirinox Locally advanced 220 220 43 Gemcipanc Folfirinox Locally advanced 479 479 45 Gemcipanc Folfirinox Metastatic 176 120 49 Gemcipanc Folfirinox Locally advanced 1297 505 51 Gemcipanc Folfirinox Metastatic 187 187 52 Gemcipanc Folfirinox Metastatic 888 428 54 Gemcipanc Folfirinox Metastatic 236 236 55 Gemcipanc Folfirinox Metastatic 456 194 59 Gemcipanc Folfirinox Locally advanced 911 91160 Gemcipanc Folfirinox Metastatic 911 470 61 Gemcipanc Folfirinox Metastatic 198 175 64 Gemcipanc Folfirinox Metastatic 271 177 65 Gemcipanc Folfirinox Metastatic 268 168 68 Gemcipanc Folfirinox Metastatic 303 56 69 Gemcipanc Folfirinox Metastatic 368 217 71 Gemcipanc Folfirinox Locally advanced 337 335 73 Gemcipanc Folfirinox Metastatic 43 43 76 Gemcipanc Folfirinox Metastatic 228 54 10212 Bacap Folfirinox Metastatic 433 230 10219 Bacap Folfirinox Locally advanced 496 282 10221 Bacap Folfirinox Locally advanced 690 582 10222 Bacap Folfirinox Metastatic 39 21 10223 Bacap Folfirinox Locally advanced 588 181 10226 Bacap Folfirinox Metastatic 431 292 10235 Bacap Folfox Metastatic 24 24 10246 Bacap Folfirinox Metastatic 120 97 10253 Bacap Folfirinox Metastatic 350 171 10257 Bacap Folfirinox Metastatic 426 70 10258 Bacap Folfirinox Metastatic 200 104 10262 Bacap Folfox Metastatic 98 98 10264 Bacap Folfox Locally advanced 238 238 10266 BacapFolfirinox Metastatic 159 68 10271 Bacap Folfirinox Locally advanced 870 870 10273 Bacap Folfirinox Locally advanced 668 468 10274 Bacap Folfirinox Metastatic 459 220 10279 Bacap Folfirinox Locally advanced 551 283 10282 Bacap Folfox Metastatic 380 98 10285 Bacap Folfirinox Metastatic 405 330 10286 Bacap Folfirinox Metastatic 569 311 10287 Bacap Folfirinox Locally advanced 838 518 10288 Bacap Folfirinox Locally advanced 807 846 10289 Bacap Folfox Metastatic 26 26 10293 Bacap Folfirinox Unspecified 786 210 10294 Bacap Folfirinox Metastatic 29 29 10295 Bacap Folfirinox Locally advanced 340 209 10296 Bacap Folfirinox Metastatic 337 263 10297 Bacap Folfirinox Metastatic 773 276 10300 Bacap Folfirinox Metastatic 31 31 10302 Bacap Folfirinox Locally advanced 378 262 10304 Bacap Folfirinox Metastatic 421 398 10306 Bacap Folfirinox Locally advanced 734 734 10309 Bacap Folfirinox Locally advanced 727 727 10310 Bacap Folfirinox Metastatic 95 62 10312 BacapFolfirinox Metastatic 210 159 10316 Bacap Folfirinox Locally advanced 731 731 10319 Bacap Folfirinox Metastatic 60 60 10327 Bacap Folfirinox Metastatic 120 91 10328 Bacap Folfirinox Unspecified 332 267 10330 Bacap Folfirinox Locally advanced 248 248 10333 Bacap Folfirinox Locally advanced 623 623 10335 Bacap Folfirinox Metastatic 607 337 10336 Bacap Folfirinox Metastatic 454 299 10338 Bacap Folfirinox Metastatic 98 82 10340 Bacap Folfirinox Metastatic 432,288 Table 3: List of the 90 patients anonymized by number, according to the clinical study (Gemcipanc or Bacap), treatment (FOLFIRINOX OR FOLOFOX), tumor stage (metastatic or locally advanced) and for each patient the overall survival and progression-free survival results. 1.2. One-Step RT qPCR Validation of the targeted genes was performed by One-Step RT qPCR on a Roche Diagnostics platform. One-Step RT qPCR experiments were performed using a mixtureEvoscript RNA Probes Master (Roche Diagnostics) on a Roche Diagnostics LightCycler480 device ®according to the manufacturer's instructions. The reaction mixture was prepared as follows in a final volume of 10 µl: 2 µl of Evoscript RNA Probes Master (Roche Diagnostics), 3 µl of primer pairs and labeled hydrolysis probe (Eurogentec, final concentration 0.4 µM for primers and 0.2 µM for probe), 5 µl of RNA template (4 ng final). The One-Step RT qPCR program consists of a first step of reverse transcription of RNA into cDNA at 60°C for 15 min, followed by a pre-incubation step at 95°C for 10 min and then 45 PCR cycles (95°C for 15 seconds, 58°C for 30 seconds). Table 4 shows the primers and probes corresponding to the 10 biomarkers used for qPCR, namely MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA, SLC8A1, as well as the reference gene also called ubiquitous gene, corresponding to the ATP5F1A gene.<h2 style=";text-align:left;direction:ltr">[Table 4] Biomarker Amorce sense Amorce anti-sensory signal GCGGCGTGTTTTCTG GGCACACTCATAATG AGGGCACACATGGCGACA MCEMP TCTAC ACACAGC CC 1 (SEQ ID NO.1) (SEQ ID NO.2) (SEQ ID NO.3) CCTCTCTAAGGGTGA GCAATGGCTACCAGG TGCTTACAAAGGAGCTTGC S100A12 GCTGAAG GATATG AAACACCA (SEQ ID NO.4) (SEQ ID NO.5) (SEQ ID NO.6) CTTTGACAGCGACAA CGCCACGAGGAACA TATCCTTGGTCCGGGCAGA MMP9 GAAGTGG AACTG AGC (SEQ ID NO.7) (SEQ ID NO.8) (SEQ ID NO.9) AACCCTATCATCGTCT ACCGTGTTCAGATAG ACCTTGACCAGCTTGTCCC RACK1 CCTGTG CCTGTG AGC (SEQ ID NO.10) (SEQ ID NO.11) (SEQ ID NO.12) CAGATGCCAAAACCA TCATGGCTGATCTTG ACACCAATTTGCAAGATCA DSC2 ATGAAGG GACTAGC TCTGTTGCT (SEQ ID NO.13) (SEQ ID NO.14) (SEQ ID NO.15) ATCCAACGTCCAATA AAGGCTACCACAATG AGGCCAGTTCCAGAATCTC LYN AACAGCA TCTCCT AGCTTTTACC (SEQ ID NO.16) (SEQ ID NO.17) (SEQ ID NO.18) GTGGCTTTGGATCGA CTTGGTTATCTCCTT CACTGCTACCGATGATGCGAGG LPP GATTTCC CAGACAGG ATTGC (SEQ ID NO.19) (SEQ ID NO.20) (SEQ ID NO.(SEQ ID NO.25) (SEQ ID NO.26) (SEQ ID NO.27) GTGGATCTTGGCATA GTCATTGGCTGAGCA CTTCCAGGCCGCTGAGCAA SLC8A1 ACAGACAC CATTTG AGT (SEQ ID NO.28) (SEQ ID NO.29) (SEQ ID NO.30) CCCAGTTGGTGAAGA CCAGAGTAAGGAGC TACGGCCTCGGATGCTGCC ATP5F1 GACTTAC CAGGTAC CA (SEQ ID NO.31) (SEQ ID NO.32) (SEQ ID NO.33): Primers and probe corresponding to the 10 biomarkers used for qPCR as well as the reference gene, called the ubiquitous gene. The qPCR data were analyzed using the Delta.Cq (ΔCq) method (Livak and Schmittgen, 2001). For all target genes, the normalized ΔCq values ​​were determined by applying the formula: ΔCq = Cq (gene) – Cq (ubiquitous gene) The ubiquitous gene is ATP5F1A (NM_001001937, ATP synthase F1 subunit alpha). 1.3.Results The Mantel-Cox model (or Log-Rank test) taking into account the calculated INDEXes made it possible to determine a "reference threshold" for the combination of the 10 genes, which will make it possible to establish the survival prognosis of the tested patient. This reference threshold is -0.5 in the present example. In the present example, patients presenting an INDEX. patient below the reference threshold, -0.5 in this example, have a progression-free survival of 14.3 months compared to patients with an INDEX patient above the reference threshold, having a progression-free survival of 3.5 months (see Figure 1). Furthermore, patients with an INDEX patient below the reference threshold, -0.5 in this example, have an overall survival of 23.4 months compared to patients with an INDEX patientabove the reference threshold, having an overall survival of 7.7 months (see Figure 2). Thus, based on the reference threshold value defined for the 10 marker genes, it is possible to establish the survival prognosis of the test patient: - if the INDEX patientcalculated in the tested patient is lower than the value of the final reference threshold then the prognosis is long-term survival and - if the INDEXpatient calculated in the tested patient is higher than the value of the final reference threshold then the prognosis is short-term survival. Furthermore, the results obtained above in example 1 make it possible to predict or evaluate the efficacy and / or benefit of a treatment for pancreatic cancer in a patient suffering from said pathology based on the results obtained above, in particular thanks to the measurement of progression-free survival. Indeed, a patient with an INDEXpatient lower than the reference threshold may be considered eligible for a treatment for pancreatic cancer based on 5-FU. Conversely, if a patient has an INDEXpatient higher than the reference threshold, this indicates that he has a prognosis of short-term survival and that a treatment based on 5-FU will have little or no benefit.Another treatment should then be considered.

Claims

CLAIMS 1. An in vitro method for establishing a survival prognosis in a patient suffering from pancreatic cancer comprising the following steps: a) measuring the level of expression of the marker genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, in a blood sample of said patient previously taken; b) comparing the measured level of expression of the marker genes or homologous genes of step a) in said patient with a reference threshold; c) evaluating the survival time in said patient. 2.An in vitro method for predicting or evaluating the efficacy and / or benefit of a treatment for pancreatic cancer in a patient suffering from said pathology comprising the following steps: a) measuring the level of expression of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, in a blood sample of said patient previously taken; b) comparing the measured level of expression of the marker genes or homologous genes in step a) in said patient with a reference threshold; c) evaluating the survival time in said patient.

3. Method according to claim 2, characterized in that said treatment is a treatment based on 5-fluorouracil.

4. Method according to any one of claims 1 to 3, wherein said blood sample is a peripheral blood sample. 5.A method according to any one of claims 1 to 4, wherein the level of gene expression is measured by measuring the amount of proteins encoded by said genes present in the blood sample.

6. A method according to any one of claims 1 to 4, wherein the level of gene expression is measured by the level of transcription of the RNA or cDNA of said genes.

7. Method according to claim 6, wherein in step a), in addition to the level of expression of the marker genes (Cqgene) or homologous genes, the level of expression of at least one ubiquitous gene is measured, said levels of expression being measured in number of cycle(s) (Cq, "cycle of Quantification") by real-time quantitative PCR (qPCR), then the level of expression of the marker genes is normalized relative to the level of expression of at least one ubiquitous gene according to ΔCq gène = Cq gène– [Cq (ubiquitous gene)] in order to obtain a normalized expression level ΔCq gène for each marker gene whose expression level has been measured.

8. The method of claim 7, wherein the normalized expression level ΔCq of the marker genes or homologous genes is normalized relative to the ubiquitous gene ATP5F1A.

9. The method of claim 8, wherein, in step a), the expression level of said marker genes or homologous genes is measured and, in step b) i) an INDEXgene value dependent on the normalized expression level of the gene is determined, defined by: INDEX gène = β coefficient of the gene * ΔCq gène in which the β coefficient of a given gene is as defined below Gene Coefficient β M CEMP1 -0.00084112S100A12 -0.0036297 MMP9 -0.01867287 RACK1 0.07083326 DSC2 -0.02450139 LYN -0.0623547 LPP -0.09273414 SLC8A1 -0.00029473 ARL4C 0.05992789 ALDOA -0.01105714 ii) an INDEX value is determined for a given patient patient equal to the sum of the INDEXES gène of said genes, and iii) the INDEX is compared patient with a reference threshold previously determined for the combination of said genes.

10. Method according to claim 9, in which the expression level of the 10 marker genes is measured, the reference threshold being -0.5, an INDEXpatient less than -0.5 indicating a long-term survival prognosis.

11. Method for monitoring the effectiveness of a treatment for pancreatic cancer, advantageously a treatment based on 5-Fluorouracil, by implementing the method described in any one of claims 2 to 10, advantageously at treatment time intervals.

12. Treatments based on 5-fluorouracil for use in the treatment of pancreatic cancer in a patient with a long-term survival prognosis, determined by the method according to any one of claims 1 to 10.

13. Treatments based on 5-fluorouracil for use in the treatment of pancreatic cancer in a patient with an INDEXpatient of less than -0.5 indicating a long-term survival prognosis. patient less than -0.5, the INDEX patientbeing determined by the method according to claim 10.

14. Kit for determining the survival prognosis of pancreatic cancer in a patient, comprising means for detecting the level of expression of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes.

15. Use in an in vitro method according to claims 1 and 4 to 10, of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, for the survival prognosis of pancreatic cancer, in a patient.

16. Use in an in vitro method according to claims 2 to 10, of the genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 or homologous genes, for monitoring the effectiveness of a treatment for pancreatic cancer, advantageously of a treatment based on 5-fluorouracil in a patient.

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