WO2018095933A1 - Method of prognosticating, or for determining the efficiency of a compound for treating cancer - Google Patents

Abstract

An in vitro or ex vivo method for determining the efficiency of a compound modulating the c-Myc oncogene activity for treating cancer, preferentially pancreatic adenocarcinoma, of a human in need thereof, or for prognosticating said cancer, comprising the step of measuring, in a biological sample from said human, the expression level of at least one specific marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1, CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

Description

METHOD OF PROGNOSTICATING, OR FOR DETERMINING THE EFFICIENCY OF A COMPOUND FOR TREATING CANCER

TECHNICAL FIELD OF THE INVENTION

The invention relates to an in vitro or ex vivo method for determining the efficiency of a compound modulating the c-Myc oncogene activity for treating cancer, preferentially pancreatic adenocarcinoma of a human in need thereof, and to an in vitro or ex vivo method for prognosticating such a cancer. It also relates to compositions, kits and solid supports, that are suitable for use in said methods.

BACKGROUND OF THE INVENTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, and a major public issue since there are approximately 230,000 new PDAC cases per year worldwide with approximately the same number of death. Like others malignant diseases, PDAC results from a complex combination of genetic, epigenetic and environmental factors which gives rise to a particularly heterogeneous disease, with patients having different set of symptoms, predisposition to early metastasis, and therapeutic responses. Current treatments for patients with a PDAC are not highly effective primarily due to the recently discovered fact that these tumors are both molecularly and clinically heterogeneous. For example, the response of these tumors to gemcitabine and Folfirinox, the two gold standard therapies against PDAC, is of only 10 (Burris et al, 1997) and 31% (Conroy et al, 2011) respectively. The variability in this response seems to be due, on one hand, to the difficulty for drugs to reach the transformed cells because of the compact PDAC stroma (resulting in hypovascularization) and, on the other hand, to the marked differences in cellular susceptibility to drugs into the tumors. Therefore, it has become important to develop methods to stratify patients in a manner that allows to predicting their susceptibility to the treatments so as to increase their therapeutic responses which will results in increased survival expectancies. The patent document WO2016/091888 is an example of such strategy.

A frequently deregulated, although insufficiently therapeutically exploited pathway in PDAC involves the c- Myc oncogene. This transcription factor influences the expression of a significant number of genes involved in cell growth, proliferation and apoptosis. In fact, this oncogene has been implicated in the pathogenesis of one- third of all human malignancies. As it relates to pancreatic cancer, c-Myc is found to be amplified in more than 30% as well as overexpressed in more than 40% of tumors, with additional cases displaying rearrangement or changes in methylation of this locus. Early studies confirmed the oncogenic role of c-Myc in PDAC using genetically engineered mouse models, which upon overexpression of this gene display increased pancreatic tumorigenesis . In addition, using a variety of experimental models, it has been later shown that the MYC pathway activation induces tumor growth, DNA replication, protein synthesis and increases tumor cell metabolism, angiogenesis and suppression of the host immune response. Moreover, MYC activates sternness, blocks cellular senescence, and its overexpression is frequently associated with poor clinical outcome and aggressiveness. This indicates that c-MYC behaves as a cancer driver gene for PDAC.

Consequently, many efforts have been dedicated to identify potent MYC inhibitors as new therapeutic options. Key to these efforts, the discovery that the Bromodomain and extra-terminal family of proteins (BET) , which are efficiently inhibited by a compound known as JQ1, are necessary for MYC activity. Notably, JQ1 suppresses PDAC development in mice by inhibiting both the MYC activity and inflammatory signals. Conversely, inhibition of MYC activity is thought to be also an essential mechanism by which BET inhibitors suppress tumor progression in hematological malignancies. Thus, identifying a subgroup of pancreatic patients based on their MYC-high status and testing their response to JQ1 is timely and of paramount medical importance.

Based on this observation, there remains a need for discovering potential markers for patients stratification and, more precisely, potential markers involved by the c- Myc oncogene pathway. In other words, there remains a need for identifying pathways that are deregulated in tumors. The blockage of these pathways with specific inhibitors should lead to cell growth arrest, death and tumor regression. Finally, there remains a need for selecting, by means of a few markers, a particular subgroup of patients in order to attain more specific and efficient cancer treatments and, in particular, PDAC treatments . SUMMARY OF THE INVENTION

In accordance with a first aspect, the invention relates to an in vitro or ex vivo method for determining the efficiency of a compound modulating the c-Myc oncogene activity for treating cancer, preferentially pancreatic adenocarcinoma, of a human in need thereof, comprising the steps of:

a) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; and

b) determining the efficiency of said compound on the c- Myc oncogene activity from the measurement obtained in step a) .

According to a second aspect, the invention relates to an in vitro or ex vivo method for prognosticating a cancer, preferentially pancreatic adenocarcinoma, of a human, comprising the steps of:

al) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; and

a2) determining, from said measurement, if the MYC pathway is activated or not in said cancer; and

b) prognosticating said cancer from the determination and measurement obtained in steps al) and a2) .

According to a third aspect, the invention relates to a composition comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, preferentially pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

According to a fourth aspect, the invention relates to a kit comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, preferentially pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

According to a fifth aspect, the present invention relates to a solid support comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, preferentially pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

Then, according to a sixth aspect, the invention relates to a method for selecting cancer markers, according to which :

transcriptomes of tumor cells are provided for a plurality of patients;

a specific expression pathway of one or a plurality of specific genes that are involved in said cancer are identified; an expression profile of said specific genes is established for said specific expression pathway;

the transcriptomes are analyzed for the plurality of patients;

some reference genes are selected for the considered specific pathway, for said cancer ; and

a signature characterizing said pathway for said cancer is defined. Advantageously, the in vitro or ex vivo method for determining the efficiency of a compound modulating the c-Myc oncogene expression for treating cancer, preferentially pancreatic adenocarcinoma, of human in need thereof, is characterized in that: - in step a) it is measured the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD; - in step a) it is measured the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; - in step a) it is measured the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD, and the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; - in step a) it is measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD; - in step a) it is measured the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; - it is determined the efficiency of a compound for treating cancer of human in need thereof in which a Myc-high pathway is involved; - it is determined the efficiency of a compound for treating cancer of human in need thereof in which a Myc- low pathway is involved; - the compound is a BET proteins inhibitor; - the compound is selected from a group consisting of ( S) - tert-butyl 2- ( 4- ( 4-chlorophenyl ) -2 , 3 , 9- trimethyl-6fi-thieno [3, 2-f] [ 1 , 2 , 4 ] triazolo [ 4 , 3- a] [1, 4] diazepin-6-yl) acetate, OTX015/MK-8628 (Merck™), TEN-010 (Tensha Therapeutics™), ZEN-3365 (Zenith Epigenetics™) , ABBV-075 (AbbVie™) , INCB-54329 (Incyte™), GS-5829 (Gilead Sciences™); - the biological sample is selected from the group consisting of a tumor sample, a xenograft, a primary culture and an organoid derived from biopsy .

BRIEF DESCRIPTION OF THE FIGURES

Other features and aspects of the present invention will be apparent from the following description and the accompanying drawings, in which: Fig. 1A illustrates the hierarchical clustering and expression heatmap for the top significantly high- expressed genes in MYC-high patients, and includes a dendrogram illustrating the genetic distance between patients of two major subgroups, which are defined as the MYC-high and MYC-low subgroups;

Fig. IB provides the enrichment scores obtained for the MYC-high vs. MYC-low subgroups, for various biological processes including the cell cycle process, the digestion, the DNA replication and the glycoprotein metabolism, and using Gene Set Enrichment Analysis (GSEA) ; Fig. 1C illustrates (i) a semi-quantitative Ki67 scoring, and (ii) a differentiation scoring between the MYC-high and MYC-low subgroups, wherein corresponds to p

<0.01 and corresponds to p < 0.001;

Fig. ID illustrates the relapse free and the overall survival of the MYC-high and the MYC-low subgroups along time ; Fig. 2A represents the hierarchical clustering and expression heatmap for the top significantly low- expressed genes in MYC-high patients;

Fig. 2B provides the transcripts of the 6 top-score upregulated marker genes in the MYC-low subgroup;

Fig. 2C provides the transcripts of the 10 top-score upregulated marker genes in the MYC-high subgroup; Fig. 2D shows the box plots representing the normalized expression ratios for the sixteen selected transcripts in the MYC-associated signature, wherein expression ratios > 1 correspond to the MYC-high profile, expression ratios < 1 correspond to the MYC-low profile, and the § symbol points out 4 false positives that were detected in the signature ;

Fig. 3A are box plots representing normalized expression ratios from the transcriptomic data (Affimetrix™) as in Fig. 2D for 4 Patient Derived Xenografts (PDX) of each MYC-high and MYC-low subgroup; Fig. 3B are box plots representing normalized expression ratios by RT-qPCR for the same 4 PDX as in Fig. 3A;

Fig. 3C are box plots representing normalized expression ratios by RT-qPCR for the same eight PDX (as in Fig. 3A) derived primary cultures, wherein corresponds to p

< 0.001;

Fig. 4A are chemograms obtained for the 8 PDX derived cell lines showing the viability of cells treated by JQ1 (i) for four patients presenting the upregulated marker genes in MYC-high, and (ii) for four patients presenting the upregulated marker genes in MYC-low; Fig. 4B provides box plots representing the JQ1 sensitivity for the 6 highest concentrations used in chemograms ;

Fig. 4C are histograms representing the IC50 for JQ1 for 4 MYC-high and 4 MYC-low cell lines;

Fig. 4D are histograms representing spheroids volumes from 3 derived cell lines in each group treated with JQ1 at 2 μΜ during 72h or with DMSO (0.05%), wherein corresponds to p < 0.001;

Fig. 4E illustrates the effect of the JQ1 treatment on MYC-high primary cell CRCM16 ; Fig. 5A provides box plots representing the normalized expression ratios for the MYC signature in 16 new PDX, used as validation or test cohort, by RT-qPCR. Fig. 5B provides chemograms for 8 PDX derived cells lines: the viability of cells which is treated by JQ1 (i) for 4 patients presenting the upregulated marker genes in MYC-high pathway, and (ii) for 4 patients presenting the upregulated marker genes in MYC-low pathway;

Fig. 5C shows a graph representing JQ1 sensitivity for the 6 highest concentrations used in chemograms, and wherein "*" corresponds to p < 0.05 and corresponds to p < 0.01;

Fig. 5D contains histograms that are representing the ICso for JQ1 for the 3 MYC-high and the 3 MYC-low cell lines taken from the validation cohort, and wherein "*" corresponds to p<0.05; and

Figs. 6A and 6B are images illustrating the Ki67 and differentiation scores. Fig. 7 shows representative microphotographies (on top) and Hematoxylin & Eosin staining (on bottom) of different organoid cultures established from EUS-FNA biopsies. White scale bars (on top) represent lOOOpm and black scale bars (on bottom) represent 200pm.

DETAILLED DESCRIPTION OF THE INVENTION

Current treatments for patients with a cancer and, in particular, PDAC, are not always effective primarily due to the recently discovered fact that their tumors can be both molecularly and clinically heterogeneous. The variability in the treatment responses appears to be due, on one hand, to the difficulty for drugs to reach the transformed cells, which is the case for PDAC because of the compact PDAC stroma, resulting in hypo- vascularization, and, on the other hand, to the marked differences in cellular susceptibility to drugs into the tumors due to their molecular heterogeneity.

Therefore, it is important to develop methods to stratify patients in a manner that allows to predict their susceptibility to the treatments so as to increase their therapeutic responses which will results in increased survival expectancies.

The invention focuses on a subgroup of cancers which are characterized by a deregulation of the c-MYC pathway. A specific molecular signature is established, allowing to identify tumors and, in particular, PDAC, wherein it is possible to specifically inhibit the expression of BET- proteins . As used herein: the terms "c-MYC pathway", "c-MYC" and grammatical variations thereof, refer to a pathway wherein the c-Myc oncogene is involved; the terms "MYC-high", "MYC-high subtype", "MYC-high subgroup" and grammatical variations thereof, refer to a pathway wherein the c-Myc oncogene is involved, and notably by overexpressed or upregulated specific marker genes involved in the particular MYC-high pathway; the terms "MYC-low", "MYC-low subtype", "MYC-low subgroup" and a grammatical variations thereof, refer to a pathway wherein the c-MYC oncogene is involved, and notably by overexpressed or upregulated specific marker genes involved in the particular MYC-low pathway; the acronym "BET" means "bromodomain and extra- terminal". It can be used in the below description the terms "BET" or "BET-proteins" which mean "bromodomain and extra-terminal proteins". The terms "BET-inhibitors" may also been used, which mean "bromodomain and extra- terminal proteins inhibitors"; the acronym "JQ1" mean " ( S) - tert-butyl 2- (4- (4- chlorophenyl ) -2, 3, 9-trimethyl-6H-thieno [3, 2- f] [ 1 , 2 , 4 ] triazolo [ 4 , 3-a] [ 1 , 4 ] diazepin-6-yl ) acetate" . For "JQ1", it can also be used in the below description the term "thienotriazolodiazepine" . c-Myc controls more than 15% of genes responsible for proliferation, differentiation, and cellular metabolism in pancreatic adenocarcinoma as well as other cancers making this transcription factor a prime target for treating patients.

Consistent with these observations it is defined a MYC transcriptional program as a restricted signature that allowed the selection of distinct subtype of cancer, notably PDAC tumors. This MYC-associated signature is established by using selected MYC target genes available from the molecular signature database and which are reported to be directly regulated by this transcription factor. From the 239 putative MYC-dependent genes (see the following table 1), 16 targets were selected according to the fold change between c-MYC-high and c- MYC-low PDAC (see the following table 2) .

PRDX4 17102111 4, 97 0.001996 0.004458 1,31

MRT04 16660199 4, 93 0.001996 0.004458 1, 36

PRPS2 17101517 4, 92 0.001996 0.004458 1,36

NDUFAB1 16825097 4, 92 0.001996 0.004458 1, 32

TBRG4 17057433 4,83 0.001996 0.004458 1,21

PRPF31 16865193 4, 77 0.001996 0.004458 1,28

RRM1 16721126 4,74 0.001996 0.004458 1,47

EIF2S2 16918485 4, 69 0.001996 0.004458 1,29

MCM6 16903090 4, 68 0.001996 0.004458 -3- ¾ 5

PCNA 16916958 4, 61 0.001996 0.004458 1, 44

SSB 16887334 4, 58 0.001996 0.004458 1,25

SRM 16681611 4, 54 0.001996 0.004458 1,7

PRDX3 16718922 4, 54 0.001996 0.004458 1,42

LAS1L 17111688 4,5 0.001996 0.004458 1, 33

HNRNPR 16683271 4, 44 0.001996 0.004458 1,25

EIF1AX 17109706 4, 36 0.001996 0.004458 1, 37

GSPT1 16824004 4, 35 0.001996 0.004458 1, 34

KPNB1 16835272 4,28 0.001996 0.004458 1,23

PPM1G 16895848 4,27 0.001996 0,004458 1, 29

EIF3M 16723294 4,24 0.001996 0.004458 1,29

CANX 16993397 4,23 0.003992 0.007633 1,15

PSMA1 16736049 4,21 0.001996 0.004458 1, 25

RNPS1 16823097 4, 14 0.001996 0.004458 1, 25

PTGES3 16766283 4, 14 0.001996 0.004458 1,21

RPL6 16770445 4,12 0.001996 0.004458 1,33

H2AFZ 16978334 4, 06 0.001996 0.004458 1,29

OTP20 16755750 4, 05 0.001996 0.004458 1,71

TRA2B 16962359 4, 05 0.007984 0.01344 1, 18

RANBPl 16927198 4,02 0.003992 0.007633 1,24

TYMS 16850477 4, 01 0.001996 0.004458 1,7

NH 2 17003479 4,01 0.001996 0.004458 1, 4

ETF1 17000465 4 0.001996 0.004458 1, 31

USPl 16665447 3 9 0.001996 0.004458 1, 39

CNBP 16958953 3, 93 0.001996 0.004458 1, 18

199 EIF3J 16800431 1, 38 0.4092 0.4445 1, 12

200 TARDBP 16658926 1, 33 0.00998 0.01656 1, 31

201 RPS6 17092737 1,28 0.1717 0.1992 1,17

202 MYC 17072669 1,24 0.1138 0.138 1,4

203 EIF4G2 16735801 1,24 0.3852 0.4204 1,01

204 HK2 16881838 1, 22 0.4331 0.4642 1, 04

205 HNRNPD 16977340 1,18 0.6108 0.6402 1,02

206 MPHOSPHIO 16881274 1,17 0.08782 0.1122 1, 15

207 HPRT1 17107045 1, 16 0.3214 0.3572 1,16

208 NCBP2 16963402 1, 15 0.1277 0.1534 1, 15

209 U2AF1 16926148 1, 15 0.3713 0.4089 1,09

210 DEK 17015987 1,14 0.2236 0.2569 1, 13

211 EPRS 16699392 1, 13 0.3832 0.4202 1,05

212 TFB2M 16701407 1,11 0.2635 0.2984 1, 05

213 PES1 16933931 1, 07 0.1756 0.2028 1, 19

214 GNL3 16941661 1, 04 0.5349 0.5657 1,11

215 PSMDi 16892039 1, 03 0.6906 0.7145 1, 04

216 HNRNPA2B1 17056031 0.9459 0.1437 0.17 1, 06

217 SNRPD3 16928282 0.8702 0.3074 0.3433 1,05

218 SMARCCl 16953199 0.8071 0.2275 0.2602 1, 01

219 MRPL23 16720820 0.8037 0.3453 0.3821 1,06

220 HDGF 16694742 0.7125 0.4132 0.4448 1, 02

221 SERBP1 16688308 0.5663 0.6467 0.6749 1, 06

222 ΜΆΡ3Κ6 16683960 0.558 0.2834 0.318 1, 03

223 LSM7 16866940 0.5212 0.6647 0.6907 1, 05

224 SLC29A2 16740778 0.4233 0.5349 0.5657 1, 01

225 OBE2L3 16927615 0.3884 0.7505 0.7731 1,03

226 RPS19BP1 16935264 0.3745 0.9321 0.9321 1, 02

227 TMEM97 16832429 0.3107 0.8723 0.8833 1, 04

228 RPL34 16969624 0.3099 0.9142 0.918 1, 02

229 NCBP1 17087343 0.2708 0.7745 0.791 1,08

230 HNRNPA3 16888031 -0.2364 0.8244 0.8384 -1,08

231 MRPS18A 17019516 -0.2544 0.8902 0.8977 -1,01

232 RPRML 16846035 -0.4361 0.5788 0.6094 -1,04 233 PABPCl 17079672 -0.4857 0.7605 0.7801 1, 12

234 SLC19A1 16926595 -0.5267 0.525 0.5601 -1,02

235 HNRNPC 16790233 -1,3 0.1357 0.1614 -1,1

236 PPA2 16978661 -1, 32 0.4132 0.4448 -1,03

237 DUSP2 16900441 -1,83 0 · 2335 0.2658 -1,07

238 SORD 16800506 -1, 94 0.09182 0.1161 -1,2

239 FAM120A 17086921 -2, 12 0.05788 0.07997 -1,11

Table 1 : Rank-listed transcripts

Gene Affimetri Ref Seq mRNA Symbol x ID assignment

CDC20 16663514 NM 001255 Homo sapiens cell division cycle 20

KPNA2 16837270 NM 002266 Homo sapiens karyopherin alpha 2

PLK1 16817017 ENST0000030009 Homo sapiens

3 polo-like

kinase 1

Up-

SRM 16681611 NM 003132 Homo sapiens regulated

spermidine trancript

synthase s in Myc-

RFC4 16962493 NM 002916 Homo sapiens high

replication cohort

factor C (activator 1) 4

MCM2 16945101 ENST0000026505 Homo sapiens

6 mini chromosom e maintenance complex component 2

RUVBL2 16863946 NM 006666 Homo sapiens RuvB-like 2

(E. coli)

MAD2L1 16979389 ENST0000029650 Homo sapiens

9 MAD2 mitotic arrest deficient^¬ like 1

CCT4 16898175 NM 006430 Homo sapiens chaperonin containing TCP1, subunit 4 (delta)

CAD 16878137 NM 004341 Homo sapiens carbamoyl- phosphate synthetase 2

VSIG2 16745683 NM 014312 Homo sapiens

V-set and immunoglohuli n domain containing 2

BCL2L1 16691121 NM 001010922 Homo sapiens

5 BCL2-like 15

Up- (BCL2L15) regulated

RAB25 16671901 NM 020387 Homo sapiens trancript

RAB25, member s in Myc- RAS oncogene low

family

cohort

TX IP 16669796 NM 006472 Homo sapiens thioredoxin interacting protein

CTSE 16676547 NM 001910 Homo sapiens cathepsin E, transcript variant 1

ERN2 16825120 M 033266 Homo sapiens endoplasmic reticulum to nucleus signaling 2

Table 2: List of biomarkers used in the transcriptomic signature in PDAC Those targets usefully identify highly proliferative PDAC with low degree of differentiation and patient with poor clinical outcome as shown in Figure 1C and ID. An efficient signature, like the one reported here, which is easily applicable and of low cost, for detecting patients having a MYC-high PDAC for example is of clear clinical interest, particularly in non-operable patients which represents about 85% of PDAC.

The present invention relates to an in vitro or ex vivo method for determining the efficiency of a compound modulating the c-Myc oncogene activity for treating cancer, preferentially pancreatic adenocarcinoma, of human in need thereof, comprising the steps of: a) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; and, b) determining the efficiency of said compound on the c-Myc oncogene activity from the measurement obtained in step a) . According to the invention, "measuring the expression of at least one gene" encompasses measuring the expression of at least one nucleic acid encoded by said at least one gene, which includes RNA molecules encoded by said at least one gene. In a non-limitative manner, the product of one gene may comprise RNA molecules including mRNA, tRNA, rRNA, small-interfering RNAs (siRNA) , non-coding RNAs and microRNAs, which can be modified or not. The expression of at least one gene may also encompass, in a more indirect manner, measuring the expression of at least one protein encoded by said at least one gene.

Methods for measuring the expression of at least one gene in a biological sample are known from the art. In a non- limitative manner, the expression of a protein may be achieved using Western blot, Slot blot, Dot blot, ELISA (Enzyme Linked Immuno-Sorbent Assay) , immunofluorescence, electronic or confocal microscopy FRET (fluorescence resonance energy transfer) , TR-FRET (time resolved FRET/FRET) , FLIM (fluorescence lifetime imaging microscopy) , FSPIM (fluorescence spectral imaging microscopy) , FRAP (fluorescence recovery after photobleaching, flux cytometry, enzymatic tests.

Preferably, measuring the expression of at least one gene includes measuring the expression of at least one nucleic acid encoded by said at least one gene. In a non-limitative manner, the expression of a nucleic acid may be achieved using polymerase-chain reaction (PCR) , reverse transcriptase polymerase-chain reaction (RT-PCR) , Northern Blot, Ribonuclease protection assays, microarrays, in situ hybridization.

In particular, the expression of a nucleic acid may be advantageously achieved by using the nCounter® DX Analysis System with Flare configuration commercialized by NanoString Technologies® company. The nCounter® Gene Expression Assay is designed to provide a sensitive, reproducible and highly multiplexed method for detecting nucleic acid such as mRNA with molecular barcodes called nCounter Reporter probes without the use of reverse transcription or amplification. The probe pair consists of the Reporter Probe, which carries the signal on its 5' end, and the Capture Probe which carries a biotin on the 3' end. The color codes carry six positions and each position can be one of four colors, thus allowing for a large diversity of tags that can be mixed together in a single well for direct hybridization to targets and yet still be individually resolved and identified during data collection. Unlike microarrays or PCR-based gene expression analysis technologies, such system does not rely on synthesis of a cDNA strand or PCR amplification. No enzymes are used in this procedure. Instead, the barcode-labeled probes anneal directly to mRNAs in solution, and the hybrid molecule is then immobilized, detected, and counted.

The method according to the present invention is advantageously characterized in that, in step a) it is measured the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD. In a preferred embodiment, in step a) it is measured the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, in step a) it is measured the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2, PLK1, SRM, RFC4 , MCM2, RUVBL2 , MAD2L1 , CCT4 and CAD, and the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, in step a) it is measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD. Advantageously, in step a) it is measured the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, in step a) it is measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

According to the invention, the efficiency of a compound for treating cancer and, in particular, pancreatic adenocarcinoma, of human in need thereof, and in which a Myc-high pathway and/or a Myc-low pathway is involved, is determined .

Treatments of cancer patients are preceded by the molecular characterization of their tumor. This specific characterization is allowing to select the most appropriate treatments towards an individualized medicine approach . The compounds that are tested are notably BET proteins inhibitors. The BET family of proteins includes BRD2, BRD3, BRD4 and BRDT (Asangani IA, Dommeti VL, Wang X, Malik R, Cieslik M, Yang R, Escara-Wilke J, Wilder-Romans K, Dhanireddy S, Engelke C et al (2014) Therapeutic targeting of BET bromodomain proteins in castration- resistant prostate cancer. Nature 510: 278-282). According to the invention, the word "compound" is to be understood as any compound which may have a potential therapeutic effect for treating cancer and, in particular, PDAC, or alternatively for improving or maintaining the prognosis of a human. A "derivative" of said compound may comprise any active metabolite that is susceptible to be obtained in vivo from said compound after its administration, and which thus includes any active metabolite of said compound, and/or salt thereof. It is noted that the compounds and derivatives thereof may be considered either alone or in combination, without departing from the scope of the invention. In particular, any pharmaceutical composition comprising said compounds, either alone or in combination is to be considered within the scope of the invention. When the aforementioned compounds are considered in combination, they may be administered either individually or sequentially.

The compounds are more particularly selected from a group consisting of ( S) -tert-butyl 2- ( 4- ( 4-chlorophenyl ) -2 , 3 , 9- trimethyl-6fi-thieno [3, 2-f^"] [ 1 , 2 , 4 ] triazolo [ 4 , 3- a] [1, 4] diazepin-6-yl) acetate, OTX015/MK-8628 (Merck™), TEN-010 (Tensha Therapeutics™), ZEN-3365 (Zenith Epigenetics™) , ABBV-075 (AbbVie™) , INCB-54329 (Incyte™), GS-5829 (Gilead Sciences™) .

Mechanistically, ( S) -tert-butyl 2- ( 4- ( 4-chlorophenyl ) -

2,3, 9-trimethyl-6H-thieno [3, 2-f] [l,2,4]triazolo[4,3- a] [ 1 , 4 ] diazepin-6-yl ) acetate competitively inhibits the BET proteins from binding to acetylated lysines residues of histones. This process prevents the association of transcriptional complexes with chromatin and thus decreases expression of RNA species that are dependent of this mechanism of transcription. Many studies suggest that the main mechanism by which BET inhibitors affect tumoral growth is by their effects on c-MYC expression and activity. The efficiency of the compound as determined in step b) is considered to be good if the condition of the patient is expected to improve after administration of said compound or, alternatively, if the life expectancy of said patient is expected to improve after administration of the compound. In other words, according to the invention, "determining the efficiency of a compound for treating cancer in said human" encompasses determining if the compound is suitable for killing cells, in particular primary cells or xenografts, that derive from said cancer.

The method according to the present invention is advantageously characterized in that it is applied for treating pancreatic adenocarcinoma of human in need thereof.

According to the present invention, the biological samples are tumor samples derived from cancer, notably tumor samples derived from pancreatic adenocarcinoma, and more preferably tumor samples derived from the head or the tail of the pancreas. The words "tumor sample" and "tumor tissue sample" encompass (i) a global primary tumor (as a whole) , (ii) a tissue sample from the center of the tumor, (iii) a tissue sample from the tissue directly surrounding the tumor which tissue may be more specifically named the "invasive margin" of the tumor, (iv) lymphoid islets in close proximity with the tumor, (v) the lymph nodes located at the closest proximity of the tumor, (vi) a tumor tissue sample collected prior surgery (for follow- up of patients after treatment for example) , (vii) a tumor tissue sample collected after surgery, (viii) a tumor tissue sample derived from the head of the pancreas, (viii) a tumor tissue sample derived from the tail of the pancreas, and (ix) a distant metastasis.

A tumor tissue sample, irrespective of whether it is derived from the tail or the head of the pancreas, the center of the tumor, from the invasive margin of the tumor, or from the closest lymph nodes, encompasses pieces or slices of tissue, or even cell samples, that have been removed from the tumor, including following a surgical tumor resection or following the collection of a tissue sample for biopsy, for further quantification of one or several biological markers, notably through histology or immunohistochemistry methods, through flow cytometry methods and through methods of gene or protein expression analysis, including genomic and proteomic analysis. The tumor sample derived from PDAC can be a sample collected by endoscopic aspiration, including Endoscopic Ultrasound-Guided Fine-Needle Aspiration, or by surgery. It is worth noting that only 15 to 20% of patients are operated whereas virtually all the patients with a PDAC are submitted to a biopsy under Endoscopic UltraSound-guided Fine-Needle Aspiration (EUS-FNA) . These biopsies can become an inestimable source of living material from each PDAC. However, said biopsies, when obtained, are strongly contaminated by blood and stromal components, which impedes their direct utilization for the macromolecules extractions. To bypass this major inconvenient the inventors set up the production of organoids directly from PDAC biopsies and after a few days of growth the material become almost without contamination.

These organoids are a well-cleaned source of materials for extracting, in small quantities but pure, RNA, DNA, proteins etc. by using standards approaches developed for small amounts of material (such as the nCounter® Dx Analysis Sytem with Flex configuration) .

Moreover, organoid cultures enable various molecular studies due to the high purity to epithelial tumor compartment. Indeed, RNA-, DNA- and protein-based assays are readily and quickly accomplishable with organoid. Unlike the PDX procedure, which take at least two months to grow, organoids allow to obtain biological exploitable material in a window of time in which an optimized therapeutic strategy may be efficiently applied to the patients. Moreover, organoids conserves the degree of intratumoral characteristics of the primary tumor and is able to be amplifiable conserving these characteristics for at least several passages.

Thus, in another preferred embodiment, the biological sample is an organoid derived from a tumor tissue sample obtained from patient undergoing surgery or, preferably, from biopsy.

Organoids are preferably derived from pancreatic tumor sample such as tumor tissue sample from patients undergoing surgery or from pancreatic biopsies of patients suffering from Pancreatic Ductal Adenocarinoma (PDAC) . More preferably organoid are derived from pancreatic biopsy of patients suffering from PDAC.

The words "organoid" refers to miniaturized and simplified version of an organ produced in vitro in three dimensions that shows realistic micro-anatomy. It is derived from one or a few cells from a tumor tissue sample, preferably from a biopsy from patients with tumor .

In another embodiment, the biological sample is selected from the group consisting of a xenograft and a primary culture, notably a primary culture of epithelial cells. The present invention also relates to an in vitro or ex vivo method for prognosticating cancer of a human, comprising the steps of: al) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; a2) determining, from said measurement, if the MYC pathway is activated or not in said cancer; and b) prognosticating said cancer from the measurement and determination obtained in steps al) and a2) . More precisely, the in vitro or ex vivo method of present invention is advantageously for prognosticating pancreatic adenocarcinoma. Nevertheless, all cancers wherein the MYC pathway is activated are generally known to have poor clinical outcome, and aggressiveness. Thus, the measure of the expression levels of the above markers genes, and the determination of the activation or of the non-activation of the MYC pathway, would permit to determine if a cancer is MYC-high or MYC-low, and thus to prognosticate such cancer. As used herein, the expression "prognosticating", "prognosis" and "prognosis of progression of cancer" encompasses the prognosis, in a patient wherein the occurrence of cancer has already been diagnosed, of various events, including: (i) the chances of occurrence of metastasis; (ii) the chances of occurrence of loco- regional recurrence of cancer, including PDAC; and (iii) the chances of occurrence of "short-term" or "long-term" survival following testing with the in vitro or ex vivo prognosis method according to the invention.

According to the invention, "short-term" and "long-term" survival relate to the life expectancy of one given human having cancer, notably PDAC. In particular, a "short-term survival" may refer to a life expectancy of one given human having cancer, notably PDAC, which does not exceed 8 months. A "long-term survival" may refer to a life expectancy of one given human having cancer, notably PDAC, which exceeds 8 months. In even more preferred embodiment, the in vitro or ex vivo method for prognosticating a cancer, notably pancreatic adenocarcinoma, of a human in which the c-MYC oncogene is involved, comprising the steps of a) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; and b) prognosticating said cancer from the measurement obtained in step a) .

This method is advantageously characterized in that, in step a) , it is measured the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD. In a preferred embodiment, in step a), it is measured the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. In the method for prognosticating according to the invention, and in particular in step a) it is measured the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD, and the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, in step a) it is measured the expression level of CDC20, KPNA2 , PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD. Advantageously, in step a) it is measured the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, in step a) it is measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

The invention also relates to a composition comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, notably pancreatic adenocarcinoma marker gene, involved by the c- Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

This composition is advantageously characterized in that, at least one probe measures the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD. In another embodiment, the probe measures the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Preferentially, a probe measures the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD, and a probe measures the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, the at least one probe measure the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD. at least one probe measures the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, at least one probe measured the expression level of CDC20, KPNA2 , PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. The present invention also concerns a kit comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, notably pancreatic adenocarcinoma marker gene, involved by the c- Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4 , MCM2 , RUVBL2 , MAD2L1 , CCT4 , CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. The kit is advantageously characterized in that, at least one probe measured the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD. In a preferred embodiment, at least one probe measured the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. In the kit according to the invention, at least one probe measured the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2 , PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD, and at least one probe measured the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, at least one probe measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD. Advantageously, at least one probe measured the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, at least one probe measured the expression level of CDC20, KPNA2 , PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

Another aspect of the present invention relates to a solid support comprising a probe for quantitative measuring the expression level of at least one cancer marker gene, notably pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2 , PLK1, SRM, RFC4 , MCM2 , RUVBL2, MAD2L1 , CCT4 , CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Again, the solid support is advantageously characterized in that, at least one probe measured the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD. In a preferred embodiment, at least one probe measured the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. In the solid support according to the invention, at least one probe measured the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD, and at least one probe measured the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, at least one probe measured the expression level of CDC20, KPNA2 , PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4 and CAD. Advantageously, at least one probe measured the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2. Advantageously, at least one probe measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

This work was focused on c-MYC but a similar approach can be applied to other pathways for other cancer types.

EXAMPLE 1 Methods

The following methods were used for the implementation of the invention, and in the examples:

PDAC samples and cell culture

Two types of samples were obtained from patient having PDAC: endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) biopsies from patients with unresectable tumors and tumor tissue samples from patients undergoing surgery. All the samples were anonymized, and postsurgical anatomopathology reports were provided. Histopathologic evaluation was performed on 5 pm hematoxylin and eosin stained sections of patient tumors and xenografts, which were examined under a light microscope. These sections were compared with the original human tumor when available. Samples from EUS-FNA were mixed with 100 μΐ of Matrigel™ (BD Biosciences™, Franklin Lakes, NJ) and injected in the upper right flank of a nude mouse (Swiss Nude Mouse Crl : NU (lco) -Foxnlnu; Charles River Laboratories, Wilmington, MA) . Samples from surgery were fragmented, mixed with 100 μΐ of Matrigel™, and implanted with a trocar (10 gauge; Innovative Research of America, Sarasota, FL) in the subcutaneous right upper flank of an anesthetized and disinfected mouse. When the tumors reached 1 cm3, the mice were sacrificed, and the tumors were removed. Xenografts that failed to develop within 6 months were discontinued. Primary cell cultures were obtained from xenografts. Tissues were splited into several small pieces and processed in a biosafety chamber. After a fine mincing, they were treated with collagenase type V (ref C9263; Sigma™) and trypsin/EDTA (ref 25200-056; Gibco, Life Technologies™) and suspended in DMEM supplemented with 1% w/w Penicillin/Streptomycin (Gibco, Life

Technologies™) and 10% Fetal Bovine Serum (Lonza) . After centrifugation, cells were re-suspended in Serum Free Ductal Media (SFDM) adapted from the method of Schreiber et al . (Schreiber FS, Deramaudt TB, Brunner TB, Boretti MI, Gooch KJ, Stoffers DA, Bernhard EJ, Rustgi AK (2004) Successful growth and characterization of mouse pancreatic ductal cells: functional properties of the Ki- RAS (G12V) oncogene. Gastroenterology 127: 250-260) without antibiotic and incubated at 37°C in a 5% C02 incubator . Gene Expression Microarrays

Total RNA was purified from xenograft using TRIzol® Reagent (Gibco, Life Technologies™) . 50 to 100 mg of fresh frozen tissue per ml of TRIzol® was disrupted using a homogenizer followed by a single step of phenol/chloroform purification. Total RNA was quantified using the Nanodrop spectrophotometer (NanoDrop Technologies™, Inc) and RNA Integrity Number (RIN) was calculated using the Agilent 2100 Bioanalyzer (Agilent Technologies™, Santa Clara, CA) . RNA samples that reached a RIN between 8 and 10 were used for microarray hybridization (GeneChip; Affymetrix™ Inc., Santa Clara, CA) . The Genechip Human Gene 2.0 ST Arrays were washed and stained using the Affymetrix GeneChip fluidic station 450 (protocol EukGE-WS2v5_450 ) and were scanned using a GeneChip scanner 3000 G7 (Affymetrix™ Inc., Santa Clara, CA) . GeneChip operating software version 1.4 (Affymetrix™ Inc., Santa Clara, CA) was used to obtain chip images and for quality control. Background subtraction and normalization of probe set intensities were performed using the method of Robust Multi-array Analysis (RMA) (Irizarry RA, Hobbs B, Collin F, Beazer- Barclay YD, Antonellis KJ, Scherf U, Speed TP (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4: 249-264) . Microarray analysis was performed by the CHU de Quebec Research Center Gene Expression Platform (Quebec City, Quebec, Canada) . 17 samples of the cohort were previously published (Duconseil P, Gilabert M, Gayet 0, Loncle C, Moutardier V, Turrini 0, Calvo E, Ewald J, Giovannini M, Gasmi M et al (2015) Transcriptomic analysis predicts survival and sensitivity to anticancer drugs of patients with a pancreatic adenocarcinoma) .

Bioinformatics analysis

RMA normalized data from microarrays were imported into GENE-E (version 3.0.204; Broad Institute, Cambridge, MA, USA) to generate heatmaps . The color intensity on the heatmap reflects global expression within a minimum (25%) in blue and a maximum (75%) in red. Cluster analysis, using Euclidian distance correlation of samples only, and distance for the clustering were calculated using a complete linkage algorithm. Differentially expressed genes were identified using t-test ratio and false discovery rate were estimated using Benjamini & Hochberg method (Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I (2001) Controlling the false discovery rate in behavior genetics research. Behavioural brain research 125: 279- 284) . Gene set enrichment analysis (GSEA) was performed using the Broad Institute platform and statistical significance (false discovery rate) was seated at 0.05. GSEA Analysis

Two categories of pre-defined gene sets in the Molecular Signatures Database (MSigDB, Broad Institute, Cambridge, MA, USA) were selected for analysis named the Hallmarks set, and the C5 set, a Gene Ontology (GO) molecular function gene set derived from the Molecular Function Ontology database (Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles, Proc Natl Acad Sci U S A 102: 15545-15550) . The gene sets included in the analysis were limited to those that contained between 15 and 500 genes. Permutation was conducted 1,000 times according to default-weighted enrichment statistics and by using a t- test ratio metric to rank genes according to their differential expression levels across the MYC-high and MYC-low subgroups. Significant gene sets were defined as those with a nominal p-value <0.05. Calculation of the false discovery rate (FDR) was used to correct for multiple comparisons and gene set sizes (Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I (2001) Controlling the false discovery rate in behavior genetics research, Behavioural brain research 125: 279-284).

Chemograms

Cells were screened for their chemosensitivity to JQ1 compound ( Sigma-Aldrich™, St Louis, MO, USA) . Five thousand cells per well were plated in 96-wells plates in SFDM medium. Twenty four hours later the media was supplemented with increasing concentrations of JQ1 and incubated for an additional 72 h period. Each experiment was done in triplicate and repeated at least three times. 10 increasing concentrations of JQ1 were used ranging from 0 to 30 μΜ.

Spheroids outgrowth assay

Fifteen thousand cells per well were seeded in 96-well round bottom plates with medium containing 20% methylcellulose ( Sigma-Aldrich™, St Louis, MO, USA) . After 48 h incubation, cells with spheroids of uniform size and shape were incubated with 2 μΜ JQ1 during 72h. Images were captured every day with an Evos microscope, equipped with a 4X/N.A. (0.13) objective lens (Thermo Fisher Scientifics™, Waltham, MA, USA) . Spheroids volumes were determined by the following equation: Vspheroids = 4/3 n*r³. Results were expressed as a percentage of spheroid growth compared with no treatment condition (DMSO 0.05%).

Viability assays

Cell viability was estimated after addition of PrestoBlue™ reagent (Life Technologies™, Carlsbad, CA, USA) for 3h, following the supplier protocol.

Proteins extraction and western-blotting

Cells were washed with ice-cold PBS and lysed in Laemmli sodium dodecyl sulfate-sample buffer (90 mM Tris-HCl [pH 6.8], 2.5% sodium dodecyl sulfate, 15% glycerol). Samples were then boiled, sonicated, and protein concentrations were determined using the bicinchoninic acid (BCA) assay (Biorad™, Hercules, CA, USA) with bovine serum albumin as standard. B-mercaptoethanol and bromophenol blue were then added to a final concentration of 1% and 0.005%, respectively. Proteins (20 pg) were separated by SDS-PAGE in 10% or 12.5% gels and were detected immunologically following electro-transfer onto equilibrated PVDF (Imobilon-P membranes, Millipore™, Billerica, MA, USA). PVDF membranes were stained with Ponceau Red to assure a correct transfer of proteins and molecular weight markers. Membranes were blocked in PBS containing 5% powdered milk and 0.05% Tween® 20 for lh at 25°C. Membranes were then incubated overnight at 4°C with primary antibodies in blocking solution and thereafter with horseradish peroxidase-conjugated IgG for lh. Blots were visualized using the Amersham ECL system. The MYC antibody was purified from hybridomas clone 9E10 and used at 1/500 (ATCC® CRL-1729, ATCC France) . The p27kipl antibody (C19) was purchased from Santa Cruz™ and used at 1/1000. The cleaved caspase 3 (Aspl75) antibodies was purchased from Cell Signaling™ (#9661) and used at 1/500. The β-actin antibody (AC-74) was purchased from Sigma-Aldrich™ and used at 1/10000.

Real Time quantitative PCR

Total RNA (1 pg) was used as a template for cDNA synthesis, using the GoScript™ reverse transcription kit (Promega™, Madison, WI, USA) . The GoTaq® qPCR 2X Master Mix (Promega™, Madison, WI, USA) that include all components for quantitative PCR, except sample DNA, primers and water, was used to quantified the sixteen MYC-high signature markers. Primers list for each transcript is available in the following Table 3.

F R

primer primer

Transcrip Forward primer Reverse primer

s s ts sequence (5 ' -3 ' ) sequence (5 ' -3 ' )

positi positi on on

Table 3: Primers list for each transcript

Reaction conditions were denaturation at 95°C for 2 min; 40 cycles of 15s at 95°C, 45s at 60°C. Reactions were carried out using the AryaMx real-time PCR system and analyzed using the AriaMx software vl .1 (Agilent Technologies™, Santa Clara, CA, USA) .

Ki67 staining and quantification

Full-thickness, 5-μιη sections were cut from formalin- fixed, paraffin-embedded blocks from all 55 PDX. The samples were then stained with the Ki67 antibody (MIB-1 clone, 1:160; Dako™, France) using tonsillar tissue as a positive control. Negative controls were run simultaneously with the primary antibody replaced with a buffer. Antigen retrieval was conducted in citrate buffer at pH 6.0 under pressure for 3 min. Envision Dual Link Kit (Dako™) was used for detection, with diaminobenzidine (DAB) as the chromogen and hematoxylin as the counterstain . Staining was considered positive when brown nuclear labeling was observed in epithelial compartment. A standard Olympus BX41 microscope was used to identify tumor hot spots in each case. The percentage of tumor cell staining was independently counted by three reviewers (BB, MB, and ND) and with « eyeballing » methodology .

Differentiation scoring

Formalin-fixed tumors were submitted to an hospital histology core facility, and paraffin-embedded sections were cut for hematoxylin and eosin (H&E) staining. For histopathological scoring, H&E-stained slides were scored for the penetrance of each histological hallmark on a scale of 0 to 2. The predominant tumor phenotype gave the pathological score for the whole tumor (0 = poorly differentiated, 1 = moderately differentiated, 2 = well differentiated) .

Method for normalizing expression ratios

Considering the expression of upregulated gene i in patient a as uia and the expression of downregulated gene j in patient a as dja, the sum of expression of each marker in all patients was calculated:

Ui =∑_a wia , 1 < i < 10 and Dj =∑_a dja , 1 < i < 6

The mean centered normalized expression was then calculated for the two set of markers:

Uia.(100) Dja.(100)

Uia and Dja

Ui Dj

The normalized ratio between upregulated gene Ui and downregulated gene Dj is: , 1 < i < 10 and 1 < / < 6

The median of the 60 normalized ratios is then calculated: mcc = medianififa , V 1 < i < 10 and 1 < j < 6 ) mcc > 1 show a MYC-high profile and mcc < 1 show a MYC-low profile .

Statistical analysis Overall survival and relapse free survival were analyzed using the Kaplan-Meier log-rank test to assess differences in survival. Box-and-whiskers plots show the medians, quartiles and range of continuous data to demonstrate the variability of data and the degree of normality. For continuous variables, non-parametric unpaired two-tailed t-test were perform under the assumption of equal variance.

Results

Selection of PDAC patients with MYC-high or MYC-low activity by using a gene expression profile signature. In order to stratify a cohort of 55 PDAC patients, 30 primary tumors obtained from surgery and 25 biopsy samples taken by EUS-FNA were implanted subcutaneously into mice and preserved as PDX. The histopathologic and clinical characteristics of the patients from the learning cohort are displayed in the following Table 4.

Patients Distribution (learning cohort)

All Resectable Unresectable n 55 30 25

Male 34 (62%) 18 16

Sex

Female 21 (38%) 12 9

Mean 64 66 61

Age

(Min-Max) (41-86) (45-86) (41-83)

Other No 44 (80%) 20 24

Cancers Yes 11 (20%) 10 1

Tumor Head 32 (58%) 19 13

Location Undefined 6 (11%) 0 6 Body 3 (5.5%) 2 1

14

Tail 9 5

(25.5%)

Primary tumor 46 (84%) 30 16

Specimen Hepatic

5 (9%) 0 5

Type Metastasis

Carcinomatosis 4 (7%) 0 4

Localized 29 (53%) 28 1

Tumor

Locally Advanced 8 (14,5%) 2 6

Status

13

at Metastastic 0 13

(23.5%)

Diagnosis

Carcinomatosis 5 (9%) 0 5

Clinicopathological parameters from the learning cohort of patients The main anatomopathological characteristics of the patients primary tumors were preserved in xenografts after successive passages. Growth rates to reach a tumor volume of 1 cm³ ranged from 2 to 6 months in most of the PDX. Total RNA was obtained from the 55 PDX, and the gene expression profiling was performed using an Affymetrix™ platform. Subsequently, a selection was achieve of a panel of 239 RNAs regulated by MYC in accordance to the MYC targets vl and v2 list from Molecular Signatures Database (MSigDB) (see the rank-listed transcripts available in Table 1) . Figure 1A represent the hierarchical clustering and expression heatmap for the top significantly high-expressed genes in MYC-high patients. The dendrogram showing the genetic distance between patients indicates the presence of two major subgroups defined as MYC-high and MYC-low. Interestingly, it is observed that 17/55 (30.9%) patients are characterized by an increase in the expression of 134/239 MYC targets RNAs (p-values <0.03 and q-values (FDR) <0.05) . In order to gain insight into the potential biological processes enriched in MYC-high versus MYC-low subgroups it a Gene Set Enrichment Analysis (GSEA) was performed. As shown in Figure IB, the MYC-high subgroup is characterized by a low differentiated phenotype and their two more significant associated biological processes are cell cycle process (Normalized Enrichment Score = 3.60 and FDR <0.25) and DNA replication and genome maintenance (Normalized Enrichment Score = 3.24 and FDR <0.25) . In contrast, the MYC-low subgroup is characterized by biological processes that reflect a more differentiated state of pancreatic tumors such as digestion (Normalized Enrichment Score = -2.23 and FDR <0.25) and glycoproteins metabolism (Normalized Enrichment Score = -1.76 and FDR <0.25) . To confirm that MYC-high patients give rise to PDX with high proliferative index, it is performed an IHC-based Ki67 staining scoring on the epithelial compartment of the 55 PDXs . As shown in Figure 1C (left part) , this semi-quantitative scoring reveals that MYC- high patient-derived PDXs proliferate more than MYC-low subgroup (Ki67 mean score 2.88 ± 0.25 N=17 vs. 2.06 ± 0.12 N=38, p=0.0018) . In addition, it is determined the degree of differentiation for both subgroups on H&E staining on paraffin embedded tissues sections. As shown in Figure 1C (right part) , MYC-high subgroup shows lower differentiation state than MYC-low subgroup

(differentiation mean score 0.77 ± 0.2 N=17 vs. 1.82 ± 0.08 N=38, p<0.0001). The Ki67 and differentiation scores are shown in Figures 6A and 6B. Moreover, we analyzed the clinical outcome of both MYC-high and MYC-low patients using a Kaplan-Meier analysis and considering both the overall and the relapsing free survival time for the 55 patient cohort. As shown in Figure ID, the overall survival median is 9.2 months for the MYC-high vs. 18.8 months for the MYC-low subgroup (HR=2.43 [1.1 to 5.1]). The relapse free survival median is 5.6 months and 11.5 months for MYC-high and MYC-low subgroup respectively (HR=2.7 [1.3 to 5.8]). Altogether, these observations indicate that it can be identified patients with MYC-high and MYC-low activity. Moreover, PDAC with MYC-high activity are characterized by increased proliferation, lower differentiation status and they have poor survival expectancy. Combined, these observations constitute a solid characterization of the molecular, biological, and medical features of the c-Myc status in patient derived xenograft, which is necessary to build the trajectory toward the testing of novel therapies aimed at treating this distinct subgroup of tumors.

MYC-dependent RNAs signatures can be used for classifying distinct PDAC subtypes

To define a specific MYC signature, that can be used to classify tumor subtypes, it is selected a total of 16 genes. The first 10 (Figure 2C) were identified from the gene set corresponding to the upregulated in the MYC-high group of patients. To obtain the genes upregulated in the MYC-low subgroup it is identified the 6 top-score upregulated genes in the MYC-low patients by a t-test analysis from the whole gene expression profiles (Figure 2A and Figure 2B) . The list of these 16 biomarkers used in the transcriptomic signature is shown in the above Table 2.

For each patient, 60 ratios were computed after mean centered normalization of the 16 markers revealing the MYC-high or MYC-low profiles. As shown in Figure 2D, it is possible to detect the 17 MYC-high patients with medians of expression ratios up to 1 with an excellent specificity and accuracy. Affymetrix™ data was then confirmed by RT-qPCR on 4 putative MYC-high and 4 MYC-low patients. Each transcript was normalized with the 28S ribosomal RNA, the relative quantity was calculated by the AACt method and the ratios were calculated after normalization. The signature was able to definitively detect all MYC-high and MYC-low profiles by RT-qPCR as shown in Figures 3A and 3B. It is then assessed the MYC signature on primary cultures derived from the same 8 xenografts (Figure 3C) and found that the corresponding MYC-high or MYC-low profiles were correctly detected. Therefore, it is concluded that the signature based on these transcripts is a reliable for identifying tumor subtypes based on their c-MYC status.

MYC-high PDX are sensitive to growth inhibition by the BET inhibitor JQ1

It was hypothesized that the subgroup of PDX belonging to the MYC-high phenotype should be more sensitives to pharmacological inhibition of MYC activity, which currently cannot be targeted directly but instead through the inactivation of BET proteins. To test this hypothesis, a panel of pancreatic PDX-derived primary cultures was treated with the well-characterized BET inhibitor JQ1. According to their MYC signature, it was selected 4 MYC-high PDX (CRCM16 , CRCM17 CRCMO 4 , and CRCM08) and 4 MYC-low patients (CRCMO 5, CRCM11, CRCM10, and CRCM109) (Figure 2D) . It was then assessed the viability of cells with increasing dose of drug (chemograms) for 72h. As shown in Figures 4A and 4B, MYC- high cells exhibit higher sensitivity to JQ1 treatment compared to the MYC-low ones. The mean of IC50 for the MYC-high cells is 2.3 μΜ±0.8 whereas the one corresponding to MYC-low primary cells was of 39.22 μΜ±16 (Figure 4C) . It was also evaluated the effect of JQ1 in patient derived cells grown in 3D culture conditions. As shown in Figure 4D, MYC-high spheroids were more sensitive to the JQ1 treatment for 72h (50% reduction in volume) than their MYC-low counterpart (25% reduction in volume) . As a positive control, the effect of JQ1 treatment on the MYC-high primary cell CRCM16 was analyzed and a significant decrease of MYC protein level was determined (Figure 4E) . Importantly, MYC depletion is accompanied with an increase of ρ27^κ1ρ! level and an increase in the cleavage of caspase 3 which may explain the antitumor effect of the compound. Thus, these experimental therapeutic experiments suggest that inhibition of BET proteins by small drugs like JQ1 will be beneficial to antagonize the growth of pancreatic cells which carry the c-MYC-high status.

MYC-dependent RNA signature identify MYC-high patients on an independent validation cohort

Sixteen new PDAC patients were included in the study as an independent validation cohort. The histopathologic and clinical characteristics of patients from the test cohort are displayed in Table 5.

Table 5: Clinicopathological parameters from the

validation cohort of patients.

16 PDX were obtained and, from them, 6 PDX-derived cells, The expression of 16 MYC-associated marker genes by RT- qPCR was measured and it was determined that 8 patients present a MYC-high profile (CRCM43, CRCM26, CRCM50, CRCM19 , CRCM30, CRCM114, CRCM116 and CRCM34) and 8 shows a MYC-low profile (CRCM23, CRCM21, CRCM108, CRCM25, CRCM28, CRCM112 , CRCM29, CRCM42) as described in Figure 5A. Of the 6 primary cultures available, 3 presented a MYC-high (CRCM116, CRCM114 and CRCM34) and 3 a MYC-low profile (CRCM112 , CRCM21 and CRCM28) . To test their sensitivity to BET inhibitors, cells were treated with increasing concentrations of JQ1 and as expected the 3 MYC-high cells showed to be more sensitive than the MYC- low cells as shown in Figure 5C. The mean of IC50 for the MYC-high cells is 5.65 μΜ±2.4 whereas it is of 223.71 μΜ±191.5 for the MYC-low primary cultures (Figure 5D) which are close to the study cohort presented in Figure 5C. These results confirm that cells from PDAC presenting a MYC-high profile are more sensitive to JQ1 treatment compared to the cell presenting a MYC-low profile.

EXAMPLE 2 : Use of organoid as biological sample

Contrary to example 1 wherein Patient Derived Xenografts (PDX) is used in order to obtain a quantity of nucleic acid sufficient to perform molecular analyses (see chapter "PDAC samples and cell culture" above) , the inventor have also demonstrated that organoids can be used alternatively. Unlike the PDX procedure, which take at least two months to grow, organoids allow to obtain biological exploitable material in a window of time in which an optimized therapeutic strategy may be efficiently applied to the patients.

Then, after RNA extraction, the inventors proceeded to Signature validation with nCounter® Dx Analysis System with FLEX configuration from NanoString® Technologies Companies .

Methods :

Obtaining EUS-FNA biopsy

The samples were obtained by Endoscopic UltraSound-guided Fine-Needle Aspiration (EUS-FNA) biopsies from patients with unresectable tumors who represent up to 85% of all PDAC patients as part of the standard care of patients having a PDAC.

Methodology to obtain an maintain Biopsy Derived Pancreatic Organoids (BDPO)

BDPO are generated from EUS-FNA biopsies that were rapidly digested using Tumor dissociation kit, human (Miltenyi Biotec) . After centrifugation, samples were re- suspended in Red Blood Cell (RBC) lysis buffer (eBioscience) . Mixtures were filtered on cell EASY strainer ΙΟΟμηι (Greiner Bio One) and re-suspended into Pancreatic Organoids Feeding Medium (POFM) [DMEM: F12 supplemented with HEPES (lx Invitrogen) + Glutamax (lx, Invitrogen), penicillin/streptomycin (lx, Invitrogen) + EGF (0.05 g/ml) + A83-01 (0.5 μΜ) + FGF (0.1 g/ml) + Gastrin (InM) + mNoggin (O.^g/ml) + N-Acetylcystein 1.25 mM + Nicotinamide (lOmM) + human R-spondin (^g/ml) + Wnt3a (0.1 μg/ml) + Growth Factor Reduced (GFR) MatriGel® (5%) ] .

BDPO suspensions were then placed into 12-well plate coated with 150μ1 GFR MatriGel® (Corning) . Media were replaced every 2-3 days. For the BDPO passaging, media were harvested and keep on ice during the digestion step. For the digestion: 0.5ml/well Digestion Media [DMEM supplemented with 1% collagenase/dispase (lOOmg/ml, Sigma)] were add to the well and incubate at 37°C for 1 to 1.5 hours. The incubation was then stopped with Resuspension Media [DMEM supplemented with 1% BSA and 1% penicillin/streptomycin]. Digested pulps were gently spin and supernatants were discard and replaced with 2ml of StemPro Accutase (Life Technology) cell dissociation reagent for an additional 30 min period at 37°C. BDPO can be re-seeding at a density of 150.000 to 200.000 cells per well in a 12-well plate or used for direct macromolecules extraction. Figure 7 shows the result of different organoids cultures established from EUS-FNA biopsies.

RNA extraction from BDPO

For RNA isolation, organoids were harvested by dissolving Matrigel including organoids with ice-cold PBS. Following centrifugation at 700 rpm for 5min at 4 °C, supernatant was removed and pelleted organoids were carefully resuspended and homogenized in 350 μΐ of RLT buffer (Qiagen) . Total RNA was isolated using the RNeasy Mini Kit (Qiagen) according to the manufacturer' s instructions. RNA concentration and purity (A260/A280 ratio) was determined by spectrophotometric analysis (Epoch Microplate Spectrophotometer, Bioteck

Instruments) . RNA Integrity Number (RIN) was calculated using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) . RNA samples that reached a RIN between 8 and 10 were used for Nanostring hybridization. Signature validation with nCounter Dx analysis system with FLEX configuration from Nanostring technology

Briefly, for each BDPO sample, 100 nanograms of total RNA was hybridized to a custom probeset relative to specific molecular signatures and according to the manufacturer' s instructions. Raw count data were normalized by: (1) Background correction (2) positive control correction and (3) housekeeping gene correction.

The codeset is composed by sequences of a reporter probe and a capture probe that hybridize 10 c-Myc targets (CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD), 6 PDAC expressed genes down-regulated in PDAC with high c-Myc activity (VSIG2, BCL2L15, RAB25, TXNIP, CTSE, ERN2) and 6 housekeeping genes (RBM47, AP1G2, GRIPAP1, HNRNPA3, NDUFS1, CDV3) used for normalization procedure. This signature is able to detect poor outcome patients with an aggressive PDAC sensitive to BET inhibitors.

Each Capture Probe and Reporter probe are designed in order to hybridize a target sequence for each gene of interest. The target sequences are the following:

BCL2L15 :

TATTTTAAGAGACTCTATCTTAGGAGAGCTTAAGTGATTGGGCTGCAGGAAGAAGAC ATTGTAACCCAGGAATTAAAAATGGATTCAGATTGCCTGATTT

CAD :

TTCCTCGATGGGACCTTAGCAAGTTCCTGCGAGTCAGCACAAAGATTGGGAGCTGCA TGAAGAGCGTTGGTGAAGTCATGGGCATTGGGCGTTCATTTGA CCT4 : GCGTTCGTGCTTTTGCAGATGCTATGGAGGTCATTCCATCTACACTAGCTGA AAATGCCGGCCTGAATCCCATTTCTACAGTAACAGAACTAAGAAACCG

CDC20 :

GGAACATCAGAAAGCCTGGGCTTTGAACCTGAACGGTTTTGATGTAGAGGAAGCCAA GATCCTTCGGCTCAGTGGAAAACCACAAAATGCGCCAGAGGGT

CTSE :

TTTGTGGCAAAAATACTTCCTAGGTGGTGCTGGGTACTTCTTGTTGCATCCTGTCAG GAGGCAGATAATGCTGGTGCCTCTCTATTGGTAATGTTAAGAC

ERN2 :

ATCGAAGGACCAATGTACGTCACAGAAATGGCCTTTCTCTCTGACCCAGCAGATGGC AGCCTGTACATCTTGGGGACCCAAAAACAACAGGGATTAATGA

KPNA2 M:

TGATGATCCAGAAGTATTAGCAGATACCTGCTGGGCTATTTCCTACCTTACTGATGG TCCAAATGAACGAATTGGCATGGTGGTGAAAACAGGAGTTGTG AD2L1

TGGCCGAGTTCTTCTCATTCGGCATCAACAGCATTTTATATCAGCGTGGCATATATC CATCTGAAACCTTTACTCGAGTGCAGAAATACGGACTCACCTT

MCM2 :

CCATTCTCCTCGCAGATCTGGTGGACAGCTGCAAGCCAGGAGACGAGATAGAGCTGA

CTGGCATCTATCACAACAACTATGATGGCTCCCTCAACACTGC

PLK1 :

GCTTGGCTGCCAGTACCTGCACCGAAACCGAGTTATTCATCGAGACCTCAAGCTGGG CAACCTTTTCCTGAATGAAGATCTGGAGGTGAAAATAGGGGAT

RAB25 : GGCCCGAATGTTCGCTGAAAACAATGGACTGCTCTTCCTGGAGACCTCAGCCCTGGA CTCTACCAATGTTGAGCTAGCCTTTGAGACTGTCCTGAAAGAA

RFC4 :

ACAGGTGGAAAGGAGATCACAGAGAAAGTGATTACAGACATTGCCGGGGTAATACCA GCTGAGAAAATTGATGGAGTATTTGCTGCCTGTCAGAGTGGCT

RUVBL2 :

GACGCAGGCCTTCCGGCGGTCCATCGGCGTTCGCATCAAGGAGGAGACGGAGATCAT CGAAGGGGAGGTGGTGGAGATCCAGATTGATCGACCAGCAACA

SRM:

GCAGTAAGACCTATGGCAACGTGCTGGTGTTGGACGGTGTCATCCAGTGCACGGAGA GAGACGAGTTCTCCTACCAGGAGATGATCGCCAACCTGCCTCT

TXNIPNM:

CCCCTTCCTGCCCTGTGTTAGGAGATAGGGATATTGGCCCCTCACTGCAGCTGCCAG CACTTGGTCAGTCACTCTCAGCCATAGCACTTTGTTCACTGTC VSIG2

GAGTGGCCGGAGCTCTGATTGGGGTGCTCCTGGGCGTGCTGTTGCTGTCAGTTGCTG CGTTCTGCCTGGTCAGGTTCCAGAAAGAGAGGGGGAAGAAGCC

Claims

1. An in vitro or ex vivo method for determining the efficiency of a compound modulating the c-Myc oncogene expression for treating cancer, preferentially pancreatic adenocarcinoma, of a human in need thereof, comprising the steps of:

a) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ; and

b) determining the efficiency of said compound on the c- Myc oncogene expression from the measurement obtained in step a) .

2. The method according to claim 1, wherein in step a) it is measured the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD.

3. The method according to anyone of preceding claims, wherein in step a) it is measured the expression level of at least one marker gene selected from a group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

4. The method according to anyone of the preceding claims, wherein in step a) it is measured the expression level of at least one marker gene selected from a first group consisting of CDC20, KPNA2 , PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4 and CAD, and the expression level of at least one marker gene selected from a second group consisting of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

5. The method according to anyone of the preceding claims, wherein in step a) it is measured the expression level of CDC20, KPNA2, PLK1, SRM, RFC4 , MCM2 , RUVBL2 , AD2L1, CCT4 and CAD.

6. The method according to anyone of the preceding claims, wherein in step a) it is measured the expression level of VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

7. The method according to anyone of the preceding claims, wherein it is determined the efficiency of a compound for treating cancer of human in need thereof in which a Myc-high pathway is involved.

8. The method according to anyone of the preceding claims, wherein it is determined the efficiency of a compound for treating cancer of human in need thereof in which a Myc-low pathway is involved.

9. The method according to anyone of preceding claims, wherein the compound is a BET proteins inhibitor.

10. The method according to anyone of the preceding claims, wherein the compound is selected from a group consisting of (S) -tert-butyl 2- ( 4- ( 4-chlorophenyl ) -2 , 3 , 9- trimethyl-6fi-thieno [ 3 , 2-f] [l,2,4]triazolo[4,3-a] [l,4]diazepin- 6-yl) acetate, OTX015 /MK-8628 , TEN-010, ZEN-3365, ABBV-075, INCB-54329, GS-5829.

11. The method according to anyone of the preceding claims, wherein the biological sample is selected from the goup consisting of a tumor sample, a xenograft, a primary culture and an organoid.

12. An in vitro or ex vivo method for prognosticating a cancer, preferentially pancreatic adenocarcinoma, of a human, comprising the steps of:

al) measuring, in a biological sample from said human, the expression level of at least one marker gene selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2 ;

a2) determining, from said measurement, if the MYC pathway is activated or not in said cancer; and

b) prognosticating said cancer from the measurement and determination obtained in steps al) and a2) .

13. A composition comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, preferentially pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

14. A kit comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, preferentially pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2, RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.

15. A solid support comprising at least one probe for quantitative measuring the expression level of at least one cancer marker gene, preferentially pancreatic adenocarcinoma marker gene, involved by the c-Myc oncogene and selected from a group consisting of CDC20, KPNA2, PLK1, SRM, RFC4, MCM2 , RUVBL2, MAD2L1 , CCT4, CAD, VSIG2, BCL2L15, RAB25, TXNIP, CTSE and ERN2.