METHOD FOR DETERMINING THE SURVIVAL PROGNOSIS OF A PATIENT WITH PANCREATIC CANCER

Abstract

The present invention relates to pancreatic cancer, and more particularly to the survival prognosis of a patient with pancreatic cancer. The invention also aims to determine the benefit of such a patient receiving treatment for pancreatic cancer, particularly treatment with 5-fluorouracil. The invention further relates to a method for monitoring the effectiveness of pancreatic cancer treatment, advantageously 5-fluorouracil treatment, by implementing the method.

Description

Title of the invention: METHOD FOR DETERMINING THE SURVIVAL PROGNOSIS OF A PATIENT WITH PANCREATIC CANCER TECHNICAL FIELD OF THE INVENTION

[0001] The present invention relates to pancreatic cancer, and more particularly to the survival prognosis of a patient suffering from pancreatic cancer.

[0002] The invention also aims to determine the capacity of said patient to receive treatment for pancreatic cancer, particularly treatment based on 5-fluorouracil (5-FU).

[0003] The incidence of pancreatic cancer, of which pancreatic ductal adenocarcinoma (PDAC) is the most common type, continues to rise, 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 a 5-year overall 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 FOLFIRINOX chemotherapy regimen (5-fluorouracil (5-FU), folinic acid, irinotecan, oxaliplatin), and in 2013, the gemcitabine plus nab-paclitaxel regimen was also introduced.These two multi-drug treatments significantly improved median overall survival (OS) from 6.7 to 11.1 and 8.5 months, respectively.

[0004] The limited success of the treatments and the mortality rate which remains high for a proportion of patients underline the need for resources to improve the therapeutic targeting of patients who could 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.

[0005] Treatment of pancreatic cancer with different compounds may have varying degrees of effectiveness depending on the patient. However, to date, there is no way to predict the clinical benefit of the different available treatments on a given patient.

[0006] There is therefore still a need for tests to enable the right treatment to be selected for each patient, in order to give them the best chance of survival.

[0007] It might be desirable for said test to be one that can be performed regularly. An additional advantage would be for said test to be non-invasive.

[0008] The work of the inventors has made it possible to identify and select 10 genes, 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.

[0009] 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 making it possible to know whether the patient responds favorably or not to the treatment.

[0010] Thus, the study of the level of expression of said genes makes it possible to provide information regarding the advisability of administering a 5-FU-based treatment to a patient suffering from pancreatic cancer.

[0011] One of the advantages of the invention lies in the fact that the level of expression of said genes can be evaluated directly from a blood sample, advantageously whole blood from the patient, previously taken.

[0012] This is particularly advantageous in the case of pancreatic cancer because it is very difficult to access the tumor cells.

[0013] Furthermore, blood sampling (collection, stabilization and transport) can be standardized.

[0014] 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 are an example of a blood fraction.

[0015] 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 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 expression level of the marker genes or homologous genes in step a) in said patient with a reference threshold; (c) assess the survival time in said patient.

[0016] The term "homolog" is 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. 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. 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 for determining the homology of two sequences, including FASTA and BLAST.

[0017] The method according to the invention makes it possible to establish a survival prognosis in a patient suffering from pancreatic cancer.

[0018] 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 a treatment, particularly a 5-FU-based treatment, the efficacy and / or the benefit of a treatment for pancreatic cancer in a patient suffering from said pathology, in particular, in terms of life expectancy.

[0019] 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 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 expression level of the marker genes or homologous genes in step a) in said patient with a reference threshold; (c) assess the survival time in said patient.

[0020] The method according to the invention is particularly suitable for predicting or evaluating the efficacy and / or benefit of a 5-FU-based treatment for pancreatic cancer.

[0021] 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.

[0022] The principle of the invention is based on the fact that the Applicant was 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 of the homologous genes makes it possible to establish a prognosis of survival of the patient. More specifically, the Applicant established that by comparing data on the expression level of the 10 genes (MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARUC, 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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 quantity of the 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.

[0028] Preferably, in the methods according to the invention, the level of expression of the genes is measured by real-time quantitative PCR (real-time quantitative polymerase chain reaction or 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.

[0029] 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, Am-plifluor assays. Advantageously, said primers are specific to the flanking regions of the gene in question.

[0030] 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).

[0031] 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).

[0032] 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).

[0033] 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).

[0034] 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).

[0035] In the case of the LYN gene, the flanking regions are located on the exon on chromosome 16 between nucleotides 399665 and 399728 (Assembly Dec. 2013, GRch38 / hg38 source UCSC).

[0036] 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).

[0037] In the case of the ARL4C gene, the flanking regions are located on the exon on chromosome 16 between nucleotides 399665 and 399728 (Assembly Dec. 2013, GRch38 / hg38 source UCSC).

[0038] In the case of the ALDOA gene, the flanking regions are located on the exon on chromosome 16 between nucleotides 399665 and 399728 (Assembly Dec. 2013, GRch38 / hg38 source UCSC).

[0039] 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).

[0040] In an advantageous embodiment, the following primers and probes can be used to carry out the qPCR: - RNAs from the MCEMP1 gene • forward primer: GCGGCGTGTTTTCTGTCTAC (SEQ ID NO. 1) • antisense primer: GGCACACTCATAATGACACAGC (SEQ ID NO. 2) • Probe: AGGGCACACATGGCGACACC (SEQ ID NO. 3) - RNAs from the S100A12 gene • forward primer: CCTCTCTAAGGGTGAGCTGAAG (SEQ ID NO. 4) • antisense primer: GCAATGGCTACCAGGGATATG (SEQ ID NO. 5) • Probe: TGCTTACAAAGGAGCTTGCAAACACCA (SEQ ID NO. 6) - RNAs from the MMP9 gene • forward primer: CTTTGACAGCGACAAGAAGTGG (SEQ ID NO. 7) • antisense primer: CGCCACGAGGAACAAACTG (SEQ ID NO. 8)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: TATCCTTTGGTCCGGGCAGAAGC (SEQ ID NO. 9)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> -RNAs are from the RACK1 gene<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amor ses: AACCCTATCATCGTCTCCTGTG (SEQ ID NO. 10)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Amorce anti-sens: ACCGTGTTCAGATAGCCTGTG (SEQ ID NO. 11)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: ACCTTGACCAGCTTGTCCCAGC (SEQ ID NO. 12)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> - RNAs are the origin of the DSC2 gene<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amor ses: CAGATGCCAAAACCAATGAAGG (SEQ ID NO. 13)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Amorce anti-sens: TCATGGCTGATCTTGGACTAGC (SEQ ID NO. 14)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: ACACCAATTTGCAAGATCATCTGTTGCT (SEQ ID NO. 15)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> -RNAs are the source of the LYN gene.<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amor ses: ATCCAACGTCCAATAAACAGCA (SEQ ID NO. 16)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amorce anti-sense: AAGGCTACCACAATGTCTCCT (SEQ ID NO. 17)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: AGGCCAGTTCCAGAATCTCAGCTTTTACC (SEQ ID NO. 18)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> -RNAs are the origin of the LPP gene.<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Amorce sense: GTGGCTTTGGATCGAGATTTCC (SEQ ID NO. 19)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Amorce anti-sens: CTTGGTTATCTCCTTCAGACAGG (SEQ ID NO. 20)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr">• Sonde: CACTGCTACCGATGCGAGGATTGC (SEQ ID NO. 21)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> -RNAs are the origin of the ARL4C gene<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amor ses: AAAGCCCTGTGGTGTATCAA (SEQ ID NO. 22)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Amorce anti-sens: GCTTCCTCTGTTGGGTCAGA (SEQ ID NO. 23)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: TGTTTGACCTAATAATAGCCCGTTTCGTC (SEQ ID NO. 24)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> -RNAs are the origin of the ALDOA gene.<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amor ses: GCTTGCACTCAGAAGTTTTCTCA (SEQ ID NO. 25)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Amorce anti-sens: GGAAGGTGATCCCAGTGACA (SEQ ID NO. 26)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: ATTGCCATGGCGACCGTCACAG (SEQ ID NO. 27)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> -RNAs are from the gene SLC8A1<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amor ses: GTGGATCTTGGCATAACAGACAC (SEQ ID NO. 28)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • amorce anti-sense: GTCATTGGCTGAGCACATTTG (SEQ ID NO. 29)<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> • Sonde: CTTCCAGGCCGCTGAGCAAAGT (SEQ ID NO. 30)<h2 style=";text-align:left;direction:ltr">

[0041] qPCR makes it possible to determine the value of the cycle number (Cq) of a gene (Cqgene) in the patient to be tested. The Cq ("Cycle of quantification") is defined as the number of PCR cycles required for the fluorescent signal to cross the background noise. The Cq thus makes it possible to determine the level of expression in cycle number.

[0042] The obtained Cq value can then be normalized relative to the expression level of at least one ubiquitous gene expressed in cycle number in the same blood sample from the same patient. So-called ubiquitous genes are genes that are expressed in all cells of an organism under normal and pathophysiological conditions. These genes are generally expressed at relatively constant levels.

[0043] 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 ACqgene Cqgene Cqgene ubiquitous in order to obtain a normalized ACqgene expression level for each marker gene whose expression level was measured.

[0044] Preferably, in the methods according to the invention, the normalization is carried out with respect to the level of expression of a ubiquitous gene, preferably with respect to the level of expression of the ATP5F1A gene. In this case, the normalized expression level ACqgened of a marker gene is calculated by: ACqgene CQgene — CqATP5FlA

[0045] In 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).

[0046] Particularly suitable primers and probes for the ATP5F1A gene may be: - RNAs from the ATP5F1A gene • forward primer: CCCAGTTGGTGAAGAGACTTAC (SEQ ID NO. 31) • antisense primer: CCAGAGTAAGGAGCCAGGTAC (SEQ ID NO. 32) • Probe: TACGGCCTCGGATGCTGCCC (SEQ ID NO. 33)

[0047] 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.

[0048] 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.

[0049] By "short-term survival" is meant a survival of less than 6 months, less than 5 months, or less than 3 months.

[0050] Furthermore, when a patient is expected to have long-term survival, this also means that he or she may be considered eligible for 5-FU treatment. Conversely, short-term survival of the patient indicates that 5-FU treatment will provide little or no benefit to the patient. Another treatment should then be considered.

[0051] The Applicant's work on a reference population led it to identify 10 genes that could be used as markers for a survival prognosis for a patient suffering from pancreatic cancer, but also to determine for these 10 genes, a reference threshold value allowing a comparison to be made.

[0052] However, greater precision in the survival prognosis can be provided by measuring the expression level of the 10 genes or homologous genes. Therefore, according to the embodiment, during step a), the expression level of the 10 marker genes is measured and, during step b): i) an INDEXgene value is determined depending on the normalized expression level of the gene, defined by: INDEXgene = coefficient [3 of the gene * ACqgene Wherein the coefficient [3 of a given gene is as defined in Table 1 below; [Tables 1] Gene Coefficient [3 MCEMP1 -0.00084112 S100A12 -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: coefficient [3 of the 10 marker genes ii) for a given patient, we determine an INDEXpatient value equal to the sum of the INDEXgene of the 10 genes or homologous genes, and iii) the TNDEXpatient is compared with a reference threshold previously determined for the combination of ten genes or homologous genes.

[0053] 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), making it possible to weight the importance of the different genes within the system.

[0054] 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: INDEXpatient = S INDEXgene

[0055] This INDEXpatient is then compared to a reference threshold value previously determined by the Applicant for the combination of the 10 marker genes.

[0056] 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.

[0057] 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 converged optimally to -0.5.

[0058] 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.

[0059] 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 ACqgene of each of the 10 genes MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and SLC8A1 is then calculated according to: ACqgene CQgene — CqATP5FlA

[0060] An INDEXgene is then calculated for each of the genes according to: - INDEXgene = coefficient [3 of the gene * ACqgene, in which the coefficient [3 of a given gene is as defined in Table 2 below: [Tables 2] Gene Coefficient [3 MCEMP1 -0.00084112 S100A12 -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: coefficient [3 of the 10 marker genes

[0061] LTNDEXpatient is then calculated as: INDEXpatient = INDEXMC£Mp7 + INDEXs / WM / 2 + INDEXMMP9 + INDEX^^y + INDEX dcs2 + INDEXlyjV + INDEXlff + INDEXSLCW + INDEXW7C+ INDEXaldoa

[0062] This INDEXpatient value is then compared with the reference threshold value of the combination of the 10 marker genes, i.e. -0.5.

[0063] If a patient has an INDEXpatient of less than -0.5, they are considered to have a long-term survival prognosis and may be considered eligible for 5-FU treatment. Conversely, if a patient has an INDEXpatient of greater than -0.5, this indicates that they have a short-term survival prognosis and that 5-FU treatment will provide little or no benefit. Another treatment should then be considered.

[0064] 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.

[0065] A person skilled in the art will easily be able to determine the treatment time intervals at which he wishes 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.

[0066] The invention also relates to the 5-FU-based treatment for its use in the treatment of pancreatic cancer in a patient having an INDEXpatient of less than 0.5 calculated according to the preferred embodiment described above.

[0067] 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 homologous genes to detect the expression level of the 10 genes or homologous genes, optionally with nucleic acids specific for a ubiquitous gene, even more preferably nucleic acids specific for the ubiquitous gene ATP5F1 A.

[0068] The present invention also relates to a kit for determining the prognosis of survival 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 to detect the level of expression of the 10 genes.

[0069] 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.

[0070] 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.

[0071] The kit may further comprise instructions for use in the in vitro method according to the invention.

[0072] 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.

[0073] The present invention may be better understood and other advantages and characteristics may appear on reading the following examples and the attached drawings in which:

[0074] [Fig.l] 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 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 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.

[0075] [Fig.2] represents the overall survival curves, taken 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 lTNDEXpatient value is lower than the reference threshold value and the group shown in black is the set of individuals whose lTNDEXpatient 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 is indicated at the bottom of the graph: P < 0.0001.

[0076] Example 1: Identification of a set of genes for the prognosis of survival of pancreatic cancer 1.1 Preparation of RNA

[0077] 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 derived from two clinical studies GemciPANC (Id. NCT03599154) and BACAP (Id. NCT02818829). Whole blood samples from 90 patients collected before treatment, packaged in PAXgene tubes in dry ice were received and stored at -80°C.

[0078] Total RNA was extracted from the 90 whole blood samples. Transcriptome analysis (biomarker search) was conducted only on these samples.

[0079] The 90 RNA samples were 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. The RNA quantity was monitored using a NanoDrop ND-1000 spectrophotometer (THERMO Scientific). The purified RNAs were stored at -80°C.

[0080] 90 whole blood RNA samples, which correspond to blood samples from reference, 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.

[0081] Biomarker validation was done using a COBAS platform (LC480, Roche Diagnostics) and appropriate biostatistical approaches were used to filter the best biomarkers.

[0082] Table 3 below lists the 90 anonymized patients by number, according to the clinical study (Gemcipanc or Bacap), the treatment (FOLFIRINOX OR FOLFOX), the stage of the tumor (metastatic or locally advanced) and presents for each of the patients the results of overall survival and progression-free survival. [Tables 3] Subject No. Clinical Study Treatment Tumor Overall Survival (days) Progression-Free Survival (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 384 260 26 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 911 911 60 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 Folfox 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 Bacap Folfirinox 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 Folfirinox 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 Bacap Folfirinox 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 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

[0083] 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 an Evoscript RNA Probes Master mix (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 the primers and 0.2 μM for the probe), 5 μl of RNA template (4 ng final). The One-Step RT qPCR program consists of an initial 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).

[0084] Table 4 indicates 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. [Tables 4] <h2 style=";text-align:left;direction:ltr">Biomar queur Amorce sens Amorce anti-sens Sonde MCEM PI GCGGCGTGTTTTCT GTCTAC GGCACACTCATAA TGACACAGC AGGGCACACATGGCGA CACC (SEQ ID NO. 1) (SEQ ID NO. 2) (SEQ ID NO. 3) S1OOA1 2 CCTCTCTAAGGGT GAGCTGAAG GCAATGGCTACCA GGGATATG TGCTTACAAAGGAGCT TGCAAACACCA (SEQ ID NO. 4) (SEQ ID NO. 5) (SEQ ID NO. 6) MMP9 CTTTGACAGCGAC AAGAAGTGG CGCCACGAGGAAC AAACTG TATCCTTGGTCCGGGCA GAAGC (SEQ ID NO. 7) (SEQ ID NO. 8) (SEQ ID NO. 9) RACK1 AACCCTATCATCG TCTCCTGTG ACCGTGTTCAGAT AGCCTGTG ACCTTGACCAGCTTGTC CCAGC (SEQ ID NO. 10) (SEQIDNO. 11) (SEQ ID NO. 12) DSC2 CAGATGCCAAAAC CAATGAAGG TCATGGCTGATCT TGGACTAGC ACACCAATTTGCAAGA TCATCTGTTGCT (SEQ ID NO. 13) (SEQ ID NO. 14) (SEQ ID NO. 15) LYN ATCCAACGTCCAA TAAACAGCA AAGGCTACCACAA TGTCTCCT AGGCCAGTTCCAGAAT CTCAGCTTTTACC (SEQ ID NO. 16) (SEQ ID NO. 17) (SEQIDNO. 18) LPP GTGGCTTTGGATC GAGATTTCC CTTGGTTATCTCCT TCAGACAGG CACTGCTACCGATGCG AGGATTGC (SEQ ID NO. 19) (SEQ ID NO. 20) (SEQ ID NO.21) ARL4C AAAGCCCTGTGGT GTATCAA GCTTCCTCTGTTG GGTCAGA TGTTTGACCTAATAATA GCCCGTTTCGTC (SEQ ID NO. 22) (SEQ ID NO. 23) (SEQ ID NO. 24) ALDO A GCTTGCACTCAGA AGTTTTCTCA GGAAGGTGATCCC AGTGACA ATTGCCATGGCGACCG TCACAG (SEQ ID NO. 25) (SEQ ID NO. 26) (SEQ ID NO. 27) SLC8A 1 GTGGATCTTGGCA TAACAGACAC GTCATTGGCTGAG CACATTTG CTTCCAGGCCGCTGAG CAAAGT (SEQ ID NO. 28) (SEQ ID NO. 29) (SEQ ID NO. 30). ATP5F IA CCCAGTTGGTGAA GAGACTTAC CCAGAGTAAGGA GCCAGGTAC TACGGCCTCGGATGCT GCCC (SEQ ID NO. 31) (SEQ ID NO. 32) (SEQ ID NO. 33) Table 4: Primers and probes corresponding to the 10 biomarkers used for qPCR as well as the reference gene, called the ubiquitous gene.

[0085] The qPCR data were analyzed using the Delta.Cq (ACq) method (Livak and Schmittgen, 2001). For all target genes, the normalized ACq values ​​were determined by applying the formula: ACq = Cq (gene) - Cq (ubiquitous gene) The ubiquitous gene is ATP5F1A (NM_001001937, ATP synthase Fl subunit alpha). 1.3. Results

[0086] 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 patient tested. This reference threshold is -0.5 in the present example.

[0087] In the present example, patients with an INDEXpatient below the reference threshold, -0.5 in the present example, have a progression-free survival of 14.3 months compared to patients with an INDEXpatient above the reference threshold, having a progression-free survival of 3.5 months (see [Fig.l]).

[0088] Furthermore, patients with an INDEXpatient lower than the reference threshold, -0.5 in the present example, have an overall survival of 23.4 months compared to patients with an INDEXpatient higher than the reference threshold, having an overall survival of 7.7 months (see [Fig.2]).

[0089] Thus, on the basis of the reference threshold value defined for the 10 marker genes, it is possible to establish the survival prognosis of the test patient: - if the INDEXpatient calculated 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 final reference threshold value then the prognosis is short-term survival.

[0090] 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 presenting 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 presents an INDEXpatient higher than the reference threshold, this indicates that he has a prognosis for short-term survival and that a treatment based on 5-FU will not present or little 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. A 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 expression of the genes is measured by measuring the amount of the 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 expression of the genes is measured by the level of transcription of the RNA or cDNA of said genes.

7. A method according to claim 6, wherein in step a), in addition to the

8.

9. level of expression of marker genes (Cqgene) or homologous genes, the level of expression of at least one ubiquitous gene is measured, said expression levels 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 ACqgene = Cqgene - [Cq (ubiquitous gene)] in order to obtain a normalized ACqgene expression level for each marker gene whose expression level was measured. The method of claim 7, wherein the normalized expression level ACq of the marker genes or homologous genes is normalized relative to the ubiquitous gene ATP5F1A. Method according to claim 8, in which, during step a), the level of expression of said marker genes or homologous genes is measured and, during step b) i) we determine an INDEXgene value dependent on the normalized expression level of the gene, defined by: INDEXgene = coefficient [3 of the gene * ACqgene in which the coefficient [3 of a given gene is as defined below Gene Coefficient [3 MCEMP1 -0.00084112 S100A12 -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) for a given patient, an INDEXpatient value equal to the sum of the INDEXgene of said genes is determined, and iii) the INDEXpatient is compared with a reference threshold previously determined for the combination of said genes.

10. The method of claim 9, wherein 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. 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.

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