METHOD FOR DETERMINING THE SURVIVAL PROGNOSIS OF A PATIENT SUFFERING FROM PANCREATIC CANCER
20180105881 ยท 2018-04-19
Inventors
Cpc classification
G01N33/6872
PHYSICS
C12Q2600/106
CHEMISTRY; METALLURGY
G01N2800/52
PHYSICS
A61P35/00
HUMAN NECESSITIES
International classification
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 suitability of said patient to receive a treatment for pancreatic cancer, in particular a treatment with gemcitabine. The invention also concerns a method for monitoring the effectiveness of a treatment for pancreatic cancer, and advantageously a treatment with gemcitabine, by implementing the method.
Claims
1. In-vitro method for establishing a survival prognosis for a patient suffering from pancreatic cancer, comprising the following steps: a) measuring the level of expression of at least one marker gene selected from the group constituted by the NME4, ITPR3, SESN3, ARL4C and RPLP1 genes or homologous genes, in a blood sample taken previously from said patient; b) comparing the level of expression measured for the marker gene(s) selected in step a) in said patient against a reference threshold; c) evaluating the survival time for said patient.
2. In-vitro method for predicting or evaluating the efficacy and/or benefit of treatment of pancreatic cancer in a patient suffering from said pathology, comprising the following steps: a) measuring the level of expression of at least one marker gene selected from the group constituted by the NME4, ITPR3, SESN3, ARL4C and RPLP1 genes or homologous genes, in a blood sample taken previously from said patient; b) comparing the level of expression measured for the marker gene(s) selected in step a) in said patient against a reference threshold; c) evaluating the survival time for said patient.
3. Method according to claim 2, characterized in that said treatment is treatment with gemcitabine.
4. Method according to any one of claims 1 to 3, characterized in that in step a) the level of expression of at least two genes is measured, advantageously of 3, more advantageously of 4, and preferably of 5 genes.
5. Method according to any one of claims 1 to 4, in which said blood sample is a sample of peripheral whole blood.
6. Method according to any one of claims 1 to 5, in which the level of expression of the gene or genes is measured by measuring the quantity of the protein or proteins encoded by said gene that is/are present in the blood sample.
7. Method according to any one of claims 1 to 5, in which the level of expression of the gene or genes is measured from the transcription level of the RNA or cDNA of said gene.
8. Method according to claim 7, in which, in step a), besides the level of expression of a marker gene (Ct.sub.gene) or of each gene of a combination of at least 2 marker genes, the level of expression of at least one ubiquitous gene is measured, said levels of expression being measured as number of cycle(s) (Ct, cycle threshold) by real-time quantitative PCR (qPCR), then the level of expression of the marker gene(s) is normalized with respect to the level of expression of the at least one ubiquitous gene according to
?Ct.sub.gene=Ct.sub.gene?[(mean value of the)Ct(ubiquitous gene(s))] to obtain a normalized level of expression ?Ct.sub.gene for each marker gene the level of expression of which has been measured.
9. Method according to claim 8, in which the normalized level of expression ?Ct of a marker gene or of each gene of a combination of at least two marker genes is normalized with respect to two ubiquitous B2M and GAPDH genes.
10. Method according to claim 9, in which, in step a), the level of expression of a single marker gene is measured and, in steps b) and c), the reference thresholds (S.sub.ref) of a given gene are: TABLE-US-00015 Gene S.sub.ref NME4 3.1864 ITPR3 6.4014 SESN3 3.6262 ARL4C 2.6286 RPLP1 6.3748 normalized level of expression ?Ct of NME4 greater than 3.1864 and/or normalized level of expression ?Ct of ITPR3, SESN3, ARL4C and/or RPLP1 less than 6.4015, 3.6262, 2.6286 and 6.3748 respectively indicating a prognosis of long-term survival.
11. Method according to claim 9, in which, in step a), the level of expression of a combination of at least two marker genes is measured and, in step b), for each gene the expression of which has been measured i) a value INDEX.sub.gene is determined, which is dependent on the normalized level of expression of the gene, defined by: INDEX.sub.gene=+1*? coefficient of the gene, if ?Ct.sub.gene>reference threshold of the gene, and INDEX.sub.gene=?1*? coefficient of the gene, if ?Ct.sub.gene<reference threshold of the gene, and in which the ? coefficient and the reference threshold (S.sub.ref) of a given gene are as defined below TABLE-US-00016 Gene S.sub.ref ? coefficient NME4 3.1864 ?1.3207 ITPR3 6.4014 1.0850 SESN3 3.6262 1.0301 ARL4C 2.6286 1.3577 RPLP1 6.3748 1.0101 ii) a value INDEX.sub.paient equal to the sum of the INDEX.sub.gene of the genes of the combination is determined for a given patient, and iii) INDEX.sub.patient is compared against a final reference threshold previously determined for the combination of genes.
12. Method according to claim 11, in which the level of expression of the 5 marker genes is measured, the final reference threshold being 1.102, an INDEX.sub.patient less than 1.102 indicating a prognosis of long-term survival.
13. Method for monitoring the efficacy of a treatment for pancreatic cancer, advantageously treatment with gemcitabine, by implementing the method described in any one of claims 2 to 12, advantageously at treatment time intervals.
14. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival, determined by the method according to any one of claims 1 to 12.
15. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 14, in which, in step a), the level of expression of at least two genes is measured, advantageously of 3, more advantageously of 4, and preferably of 5 genes.
16. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 14 or 15, in which the blood sample is a sample of peripheral whole blood.
17. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to any one of claims 14 to 16, in which the level of expression of the gene or genes is measured by measuring the quantity of the protein or proteins encoded by said gene that is/are present in the blood sample.
18. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to any one of claims 14 to 17, in which the level of expression of the gene or genes is measured from the transcription level of the RNA or cDNA of said gene.
19. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 18, in which, in step a), besides the level of expression of a marker gene (Ct.sub.gene) or of each gene of a combination of at least 2 marker genes, the level of expression of at least one ubiquitous gene is measured, said levels of expression being measured as number of cycle(s) (Ct, cycle threshold) by real-time quantitative PCR (qPCR), then the level of expression of the marker gene(s) is normalized with respect to the level of expression of the at least one ubiquitous gene according to
?Ct.sub.gene=Ct.sub.gene?[(mean value of the)Ct(ubiquitous gene(s))] to obtain a normalized level of expression ?Ct.sub.gene for each marker gene the level of expression of which has been measured.
20. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 18, in which the normalized level of expression ?Ct of a marker gene or of each gene of a combination of at least two marker genes is normalized with respect to two ubiquitous B2M and GAPDH genes.
21. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 20, in which, in step a), the level of expression of a single marker gene is measured and, in steps b) and c), the reference thresholds (S.sub.ref) of a given gene are: TABLE-US-00017 Gene S.sub.ref NME4 3.1864 ITPR3 6.4014 SESN3 3.6262 ARL4C 2.6286 RPLP1 6.3748 normalized level of expression ?Ct of NME4 greater than 3.1864 and/or a normalized level of expression ?Ct of ITPR3, SESN3, ARL4C and/or RPLP1 less than 6.4015, 3.6262, 2.6286 and 6.3748 respectively indicating a prognosis of long-term survival.
22. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 20, in which, in step a), the level of expression of a combination of at least two marker genes is measured and, in steps b), for each gene the expression of which has been measured i) a value INDEX.sub.gene is determined, which is dependent on the normalized level of expression of the gene, defined by: INDEX.sub.gene=+1*? coefficient of the gene, if ?Ct.sub.gene>reference threshold of the gene, and INDEX.sub.gene=?1*? coefficient of the gene, if ?Ct.sub.gene<reference threshold of the gene, and in which the ? coefficient and the reference threshold (S.sub.ref) of a given gene are as defined below TABLE-US-00018 Gene S.sub.ref ? coefficient NME4 3.1864 ?1.3207 ITPR3 6.4014 1.0850 SESN3 3.6262 1.0301 ARL4C 2.6286 1.3577 RPLP1 6.3748 1.0101 ii) a value INDEX.sub.patient, equal to the sum of the INDEX.sub.gene of the genes of the combination, is determined for a given patient, and iii) INDEX.sub.patient is compared against a final reference threshold previously determined for the combination of genes.
23. Gemcitabine for use for treating pancreatic cancer in a patient who has a prognosis of long-term survival according to claim 22, in which the level of expression of the 5 marker genes is measured, the final reference threshold being 1.102, an INDEX.sub.patient less than 1.102 indicating a prognosis of long-term survival.
24. Gemcitabine for use for treating pancreatic cancer in a patient who has an INDEX.sub.patient less than 1.102, INDEX.sub.patient being determined by the method according to claim 12.
25. Gemcitabine for use for treating pancreatic cancer in a patient who has an INDEX.sub.patient less than 1.102, INDEX.sub.patient being determined by an in-vitro method comprising the following steps: a) measuring the level of expression of a combination of the five marker genes NME4, ITPR3, SESN3, ARL4C and RPLP1 and of two ubiquitous B2M and GADPH genes in a blood sample taken previously from said patient, the level of expression of the genes corresponding to the transcription level of the RNA or cDNA of said genes, measured as number of cycle(s) (Ct, cycle threshold) by real-time quantitative PCR (qPCR), the level of expression of the five marker genes then being normalized with respect to the level of expression of the ubiquitous genes according to
?Ct.sub.gene=Ct.sub.gene?[mean value of the Ct.sub.ubiquitous genes] to obtain a normalized level of expression ?Ct.sub.gene for each of the five marker genes, b) comparing the level of expression measured for the marker genes selected in step a) in said patient and for each gene the expression of which has been measured: i) a value INDEX.sub.gene is determined, which is dependent on the normalized level of expression of the gene, defined by: INDEX.sub.gene=+1*? coefficient of the gene, if ?Ct.sub.gene>reference threshold of the gene, and INDEX.sub.gene=?1*? coefficient of the gene, if ?Ct.sub.gene<reference threshold of the gene, and in which the ? coefficient and the reference threshold (S.sub.ref) of a given gene are as defined below TABLE-US-00019 Gene S.sub.ref ? coefficient NME4 3.1864 ?1.3207 ITPR3 6.4014 1.0850 SESN3 3.6262 1.0301 ARL4C 2.6286 1.3577 RPLP1 6.3748 1.0101 ii) a value INDEX.sub.patient, equal to the sum of the INDEX.sub.gene of the genes of the combination, is determined for a given patient, and iii) INDEX.sub.patient is compared against the final reference threshold of 1.102; c) evaluating the survival time for said patient, an INDEX.sub.patient less than 1.102 indicating a prognosis of long-term survival.
26. Kit for determining the prognosis of pancreatic cancer in a patient, comprising means for detecting the level of expression of at least two genes selected from the group constituted by NME4, ITPR3, SESN3, ARL4C and RPLP1, advantageously for detecting the level of expression of all 5 genes NME4, ITPR3, SESN3, ARL4C and RPLP1.
27. Use of at least one gene selected from the group constituted by the NME4, ITPR3, SESN3, ARL4C and RPLP1 genes or homologous genes, or of the combination of the 5 genes or homologous genes, for prognosis of pancreatic cancer, in a patient.
28. Use of at least one gene selected from the group constituted by the NME4, ITPR3, SESN3, ARL4C and RPLP1 genes or homologous genes, or of the combination of the 5 genes or homologous genes, for monitoring the efficacy of a treatment for pancreatic cancer, advantageously treatment with gemcitabine in a patient.
Description
[0135] The present invention will be better understood and other advantages and features will become apparent on reading the following examples and the appended drawings in which:
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EXAMPLE 1: IDENTIFICATION OF A SET OF GENES FOR THE PROGNOSIS OF PANCREATIC CANCER
[0154] 1.1 Preparation of the RNA
[0155] Samples of whole blood from 61 patients, taken before treatment, packaged in PAXgene tubes in dry ice (supplier: LabConnect, United States) were received and stored at ?80? C. They were designated week 0.
[0156] The total RNA was extracted from the 61 samples of whole blood and designated week 0. Analysis of the transcriptome (search for biomarkers) was only carried out on these week 0 samples.
[0157] The 61 samples of RNA were analysed in order to determine their quality. The integrity of the RNA was checked with the Bioanalyzer 2100 (Agilent Technologies, Palo Alto, United States) using the Eukaryotic total RNA 6000 Nano Chip from Agilent Technologies). The quantity of RNA was checked using a NanoDrop ND-1000 spectrophotometer (THERMO Scientific). The purified RNAs were stored at ?80? C.
[0158] One sample was eliminated from the study on account of the poor quality of the RNA (RNA Integrity Number <8).
[0159] 60 samples of whole blood RNA, which correspond to reference blood samples, were extracted from the blood previously collected (blood sampling tubes PAXgene, BD) using PAXgene Blood RNA Kit V.2 (PreAnalitix) according to the manufacturer's recommendations.
[0160] Digital gene expression (DGE) experiments were carried out for selecting a set of putative biomarkers.
[0161] The biomarkers were validated using a COBAS platform (LC480, Roche Diagnostics) and the appropriate biostatistical approaches were used for filtering the best biomarkers.
TABLE-US-00010 Subject No. Treatment Deaths Survival (days) Survival (months) 110 Gemcitabine YES 183 6.0 111 Gemcitabine NO 744 24.4 112 Gemcitabine YES 112 3.7 113 Gemcitabine NO 589 19.4 207 Gemcitabine YES 98 3.2 208 Gemcitabine YES 87 2.9 211 Gemcitabine YES 160 5.3 508 Gemcitabine YES 253 8.3 805 Gemcitabine YES 654 21.5 1104 Gemcitabine YES 402 13.2 1203 Gemcitabine YES 252 8.3 1612 Gemcitabine YES 47 1.5 1613 Gemcitabine YES 73 2.4 2009 Gemcitabine YES 113 3.7 2403 Gemcitabine YES 222 7.3 2703 Gemcitabine YES 61 2.0 2704 Gemcitabine YES 134 4.4 3110 Gemcitabine YES 260 8.5 3111 Gemcitabine YES 144 4.7 3308 Gemcitabine YES 217 7.1 3309 Gemcitabine YES 112 3.7 3407 Gemcitabine YES 171 5.6 3408 Gemcitabine YES 350 11.5 3706 Gemcitabine NO 774 25.4 4407 Gemcitabine YES 135 4.4 4409 Gemcitabine YES 515 16.9 4410 Gemcitabine NO 708 23.3 4411 Gemcitabine YES 105 3.4 4414 Gemcitabine YES 437 14.4 4415 Gemcitabine YES 17 0.6 4503 Gemcitabine NO 700 23.0 4702 Gemcitabine YES 31 1.0 4902 Gemcitabine YES 161 5.3 4903 Gemcitabine NO 602 19.8 5008 Gemcitabine YES 588 19.3 5201 Gemcitabine YES 584 19.2 5202 Gemcitabine YES 43 1.4 5331 Gemcitabine YES 699 23.0 5336 Gemcitabine YES 486 16.0 5339 Gemcitabine YES 65 2.1 5340 Gemcitabine YES 356 11.7 5341 Gemcitabine YES 120 3.9 5342 Gemcitabine YES 393 12.9 5344 Gemcitabine YES 667 21.9 5345 Gemcitabine YES 251 8.2 5346 Gemcitabine YES 163 5.4 5703 Gemcitabine YES 261 8.6 5901 Gemcitabine YES 555 18.2 6201 Gemcitabine YES 52 1.7 6303 Gemcitabine YES 269 8.8 8001 Gemcitabine YES 458 15.0 8003 Gemcitabine YES 335 11.0 8106 Gemcitabine YES 461 15.1 8901 Gemcitabine YES 460 15.1 9312 Gemcitabine YES 141 4.6 9508 Gemcitabine YES 169 5.6 9509 Gemcitabine YES 318 10.4 9901 Gemcitabine YES 153 5.0 10303 Gemcitabine YES 131 4.3 10304 Gemcitabine YES 234 7.7 11207 Gemcitabine YES 231 7.6
[0162] 1.2. Construction of the DGE Library and Beacon-Gene Mapping
[0163] The RNA samples were divided into 2 groups: [0164] M4: corresponding to the patients who received gemcitabine after collection of the reference blood samples, and who died before month 4; [0165] M15: corresponding to the patients who received gemcitabine after collection of the reference blood samples, and were alive after month 15.
[0166] For each group, equimolar quantities of each sample of total RNA from the patients were mixed in order to constitute a pool of total RNA.
[0167] 6 libraries of the DGE type (technique repeated three times for each group) were constructed from said pools.
[0168] The libraries were constructed with the kit provided for this purpose by the company Illumina (DGE Tag profiling kit) according to the manufacturers protocol (version 2.1B), using 2 ?g of total RNA.
[0169] The sequencing and the subsequent analyses were carried out using the Pipeline device from Illumina.
[0170] The MGX platform (Montpellier, France) was used.
[0171] The data of each DGE library were analysed with the BIOTAG software (Acobiom, Montpellier, France) for detecting and counting beacons, and assessment of the quality of the DGE libraries (Piquemal et al., 2002).
[0172] 1.3. Labelling and Selection of Beacons
[0173] A database compiling sequences of Homo sapiens and related data was generated starting from sequences obtained from the UniGene database (Built#232, March 2012, NCBI).
[0174] For each sequence in the database, the expected DGE beacon (canonical beacon) situated upstream of the Nlalll restriction site (CATG) nearest the 3 end of the sequence (R1), as well as the putative beacons situated at internal positions (labelled R2, R3 and R4 starting from the 3 end of the transcript), were extracted (Piquemal et al., 2002).
[0175] Experimental beacons obtained from the DGE libraries were paired and labelled (exact correspondences for the 17 bp) using this collection of virtual beacons. A correspondence for each experimental beacon with the virtual canonical beacons (R1) was sought first. Then, the experimental beacons not paired with the beacons R2, then with R3 and R4 were labelled.
[0176] The DGE experiments were analysed using the edgeR method (version 2.6.9, Bioconductor). The genes analysed were selected as a function of (1) mathematical filters having the largest factor of differential variation (differential Fold Change, >1.5),
[0177] The rate of false positives (FDR) is an adjusted p-value (here FDR<10% is assumed), which is calculated according to the type 1 error (?=5%) reported in the general considerations. (J.R. Statist. Soc. B, 2010, Discovering the false discovery rate, Y Benjamini)
[0178] (2) Biological Filters with the Application of Targeted Genes in Specific Processes and Known Metabolic Pathways.
[0179] 1.4. Synthesis of cDNA for qPCR
[0180] Reverse transcription was carried out for each of the 60 samples of RNAs in 20 ?l of final reaction volume with 300 ng of total RNA using 200 units of the enzyme SuperScript II (M-MLV type TA, Invitrogen) and 250 ng of random primers according to the manufacturer's instructions (25? C., 10 min, 42? C., 50 min, 70? C. 15 min), on the same day with the same pipette and the same manipulator.
[0181] 1.5. qPCR
[0182] The targeted genes were validated by qPCR on a platform from Roche Diagnostics.
[0183] The qPCR experiments were carried out using a LightCycler? 480 DNA SYBR Green Master mix (Roche Diagnostics) on a Roche Diagnostics LightCycler480? instrument according to the manufacturer's instructions.
[0184] For the assays with SYBR Green, the reaction mixture was prepared as follows in a final volume of 10 ?l: 5 ?l of LightCycler 480 DNA SYBR Green Master 2? (Roche), 4 ?l of primer pairs at 50 ?M (Eurogentec), 1 ?l of cDNA matrix (1/15 final dilution).
[0185] The PCR programme consists of a first step of preincubation at 95? C. for 10 min followed by 45 cycles of PCR (95C for 10 s, 63? C. for 15 s and 72? C. for 15 s).
[0186] In order to distinguish the specific products from the non-specific products and the primer dimers, melting was obtained by gradually increasing the temperature from 65 to 97? C.
TABLE-US-00011 TABLE4 primerscorrespondingtothe5biomarkersused forqPCRaswellasthe2referencegenes (*ubiquitousgenes). Bio- marker Senseprimer Antisenseprimer NME4 CATGATTGGACACACCGACTC GACGCTGAAGTCACCCCTT (SEQIDNO.1) AT(SEQIDNO.2) ITPR3 TCCTGGGGAAGAGTTGTACG AGGAGAAAAACAAGCGGTC (SEQIDNO.3) A(SEQIDNO.4) SESN3 TTGCCTTTGTAGTCCTGTGC CATTAGTCCAGTCACGTGC (SEQIDNO.5) TTC (SEQIDNO.6) ARL4C AAAGCCCTGTGGTGTATCAA GCTTCCTCTGTTGGGTCAG (SEQIDNO.7) A(SEQIDNO.8) RPLP-1 TGGGCTTTGGTCTTTTTGAC CAGACCATTTTTGCAGAGC (SEQIDNO.9) A(SEQIDNO.10) B2M* GCTCAGTAAAGACACAACCA CATCTGTGGATTCAGCAAA TCC CC(SEQIDNO.12) (SEQIDNO.11) GAPDH* ATGGGGAAGGTGAAGGTCG GGGGTCATTGATGGCAACA (SEQIDNO.13) ATA (SEQIDNO.14)
[0187] The data from qPCR were analysed using the Delta.Ct (?Ct) method (Livak and Schmittgen, 2001). For all the target genes, the ?Ct values were determined by application of the formula
?Ct=Ct(gene)?[Ct(B2M)+Ct(GAPDH)]/2
The two ubiquitous genes are: [0188] B2M (NM_009735, beta-2 microglobulin from Mus musculus, mRNA) and [0189] GAPDH (NM_002046, glyceraldehyde-3-phosphate dehydrogenase, transcription variant 1, mRNA+NM_001256799 glyceraldehyde-3-phosphate dehydrogenase from Homo sapiens, transcription variant 2, mRNA).
1.6. Results
Identification of the Genetic Fingerprint
[0190] Using the DGE method, the transcriptome profiles of patients' whole blood were obtained and 169 genes were selected with the edgeR method as described in section 1.3.
In a qPCR assay, a positive reaction is detected by an accumulation of a fluorescent signal.
[0191] With Ct defined as the number of PCR cycles necessary for the fluorescent signal to exceed the background noise, the Ct value is inversely proportional to the quantity of target nucleic acid in the sample. Thus, the lower the Ct value, the greater the quantity of target nucleic acid in the sample.
[0192] An additional pharmacogenomic study was also carried out. Samples of the RNA from blood from 61 patients were taken before any treatment, and they were analysed by RT-PCR.
[0193] A genetic pro-metastatic fingerprint present in 65% of the patients, highly predictive of the overall survival, and, moreover, interacting with the type of treatment, was demonstrated. The patients treated with gemcitabine who have the genetic pro-metastatic fingerprint have a low overall survival rate (OS) (5.0 months).
[0194] The NME4, ITPR3, SESN3, ARL4C and RPLP1 genes were selected by the inventors from the 169 genes, in agreement with the multifactorial nature of this indication.
TABLE-US-00012 GenBank identifier Name Description Ensembl identifier (example of mRNA) NME4 Homo sapiens ENSG00000103202 ENSDG00000103202 NME/NM23 nucleoside (SEQ ID NO. 15) diphosphate kinase 4 NM_001286433.1 (SEQ ID NO. 16) NM_001286439.1 (SEQ ID NO. 17) NM_001286440.1 (SEQ ID NO. 18) NM_001286438.1 (SEQ ID NO. 19) NM_001286436.1 (SEQ ID NO. 20) NM_005009.2 (SEQ ID NO. 21) NM_001286435.1 (SEQ ID NO. 22) ITPR3 inositol 1,4,5-triphosphate ENSG00000096433 ENSG00000096433 receptor, type 3 (SEQ ID NO. 23) NM_002224.3 (SEQ ID NO. 24) XM_011514576.1 (SEQ ID NO. 25) XM_011514577.1 (SEQ ID NO. 26) SESN3 sestrin 3 ENSG00000149212 ENSG00000149212 (SEQ ID NO. 27) NM_001271594.1 (SEQ ID NO. 28) NM_144665.3 (SEQ ID NO. 29) ARL4C ADP-ribosylation factor ENSG00000188042 NM_005737 like 4C (SEQ ID NO. 30) AJ579850* (SEQ ID NO. 31) AJ57985* (SEQ ID NO. 32) NM_001282431.1 (SEQ ID NO. 33) NM_005737.3 (SEQ ID NO. 34) RPLP1 Large ribosomal protein ENSG00000137818 NM_001003 P1 (SEQ ID NO. 35) NM_213725 (SEQ ID NO. 36) NM_001003.2 (SEQ ID NO. 37) NM_213725.1 (SEQ ID NO. 38) GAPDH glyceraldehyde-3- ENSG00000111640 NM_002046 phosphate (SEQ ID NO. 39) dehydrogenase NM_001256799 (SEQ ID NO. 40) B2M beta-2 microglobulin ENSG00000166710 NM_009735 (SEQ ID NO. 41) *Splice variants of the transcript of the ARL7 gene (Homo sapiens mRNA for ADP ribosylation factor-like protein 7 (ARL7 gene), splice variant 1 (ENSG00000188042), known to be homonyms of ARL4C.
[0195] The identification of the genetic fingerprint described here opens up a new route to personalized therapy in this indication.
[0196] The genetic pro-metastatic fingerprint, based on a specific value of Delta.Ct (?Ct), can usually be determined by RT-PCT starting from RNA of blood samples. The ?Ct value illustrating the level of expression of a given gene in a given patient is obtained by RT-PCR amplification of the given gene and after normalizing with respect to the reference genes (B2M, GAPDH). The lower the ?Ct value, the greater the level of expression of the gene.
[0197] The patients who have a high survival prognosis and/or are eligible for treatment with gemcitabine have a specific INDEX value.
[0198] Determination of the INDEX Values
[0199] More precisely, each gene identified (NME4, ITPR3, SESN3, ARL4C and RPLP1) was evaluated for its prognostic value for overall survival on a standard population of patients with pancreatic cancer (reference population), before said patients received treatment (see point 1.1).
[0200] A threshold value of ?CT was defined by qPCR for said reference population and for the 5 genes identified (NME4, ITPR3, SESN3, ARL4C and RPLP1).
[0201] Then, for the 5 genes identified (NME4, ITPR3, SESN3, ARL4C and RPLP1), a Mantel-Cox model (or Log-Rank test, logarithmic test by rank) tested the difference in survival between long-term survival and short-term survival, and established a reference threshold (S.sub.ref) and a beta coefficient for each gene identified. This Log-rank test makes it possible to compare two groups the survival curves of which have been calculated by the Kaplan Meier method. It tests the null hypothesis H0 of equality of the survival functions in the two groups considered. Under H0, as the risk of death is the same at a given time Ti between the two groups, an identical proportion of deaths in the latter is expected (Bland & Altman, 2004).
[0202] Table 2 below shows the values of the reference threshold (S.sub.ref) and of the beta coefficient obtained for the 5 genes NME4, ITPR3, SESN3, ARL4C and RPLP1, on the reference population.
TABLE-US-00013 TABLE 2 threshold and beta coefficient (? coefficient) for the 5 genes identified Name S.sub.ref ? coefficient NME4 3.1864 ?1.3207 ITPR3 6.4014 1.0850 SESN3 3.6262 1.0301 ARL4C 2.6286 1.3577 RPLP1 6.3748 1.0101
[0203] A normalized expression level ?Ct of NME4 greater than 3.1864, and/or [0204] normalized expression level ?Ct of ITPR3, SESN3, ARM4C and/or RPLP1 less than 6.4015, 3.6262, 2.6286 and 6.3748 respectively, indicates a prognosis of long-term survival, whereas [0205] a normalized expression level ?Ct of NME4 less than 3.1864, and/or [0206] a normalized expression level ?Ct of ITPR3, SESN3, ARM4C and/or RPLP1 greater than 6.4015, 3.6262, 2.6286 and 6.3748 respectively, indicates a short-term survival prognosis.
[0207] The prognosis may be refined by taking a combination of the 5 genes in Table 2.
[0208] The ?CT value obtained is then corrected as a variable that may take two values: [0209] +1 if the ?CT value of the samples is strictly greater than the value of S.sub.ref defined for the gene considered; [0210] ?1 if the ?CT value of the samples is strictly less than the value of S.sub.ref defined for the gene considered.
[0211] This then makes it possible to define, for each gene considered, an INDEX value that is calculated according to: INDEX=(+1 or ?1)?(? coefficient).
[0212] Thus, for the genes considered, the INDEX calculated on the reference population of patients suffering from pancreatic cancer may take the values given in Table 3 below:
TABLE-US-00014 TABLE 3 INDEX NME4 = (+1 or ?1) ? (?1.3207) = ?1.3207 INDEX ITPR3 = (+1 or ?1) ? (+1.0850) = ?1.0850 INDEX SESN3 = (+1 or ?1) ? (+1.0301) = ?1.0301 INDEX ARL4C = (+1 or ?1) ? (+1.3577) = ?1.3577 INDEX RPLP1 = (+1 or ?1) ? (+1.0101) = ?1.0101
[0213] It is the INDEX of the combination of genes retained for assessing the survival prognosis for the patient that will then allow the prognosis to be established.
[0214] The Mantel-Cox model (or Log-Rank test), taking into account the calculated INDEX values, made it possible to determine a final reference threshold for each of the combinations, which will allow the survival prognosis for the patient tested to be established.
[0215] The value of the final reference threshold for the combination of all 5 genes considered is equal to 1.102.
[0216] On the basis of the final reference threshold value defined for each gene or for each combination, it is possible to establish the survival prognosis for the patient tested: [0217] if INDEX.sub.patient calculated for the patient tested is less than the value of the final reference threshold, the prognosis is long-term survival and [0218] if INDEX.sub.patient calculated for the patient tested is greater than the value of the final reference threshold, the prognosis is short-term survival.