WO2014173986A2

WO2014173986A2 - Methods for diagnosing and monitoring the response to treatment of hepatocellular carcinoma

Info

Publication number: WO2014173986A2
Application number: PCT/EP2014/058293
Authority: WO
Inventors: Bruno Clement; Cédric COULOUARN; Mehmet ÖZTÜRK
Original assignee: INSERM (Institut National de la Santé et de la Recherche Médicale); Universite Grenoble I Joseph Fourier; Universite De Rennes 1
Priority date: 2013-04-25
Filing date: 2014-04-24
Publication date: 2014-10-30
Also published as: WO2014173986A3

Abstract

The present invention relates to a method for evaluating the vital prognosis of a subject suffering or suspected to suffer from hepatocellular carcinoma.

Description

Methods for diagnosing and monitoring the response to treatment of hepatocellular carcinoma

FIELD OF THE INVENTION

BACKGROUND OF THE INVENTION

Hepatocellular carcinoma (HCC) is a deadly cancer worldwide, mainly due to tumour heterogeneity which represents a genuine challenge for tailored treatments. HCC is the fifth most common cancer worldwide, causing more than 500 000 deaths annually. HCC occurs mostly in sub-Saharan Africa and in Eastern Asia, due to the endemic hepatitis B virus infection. Moreover, its incidence is increasing in other parts of the world, being related to greater prevalence of hepatitis C virus infection, alcohol consumption and metabolic diseases. High mortality rate is related to late diagnosis, underlying liver disease, heterogeneity of tumours and paucity of medical options.

The therapeutic care of the patients having cancer is primarily based on surgery, radiotherapy and chemotherapy and the practitioner has to choose the most adapted therapeutic strategy for the patient. Therefore, in the majority of the cases, the choice of the therapeutic protocol is based on clinical examination, biological analyses, imaging and histological features of liver biopsies.

However, the predictive accuracy of those HCC diagnosis/staging strategies remains limited, as they may not reflect the complexity of molecular events driving HCC onset and progression.

Gene expression profiling has been used to elucidate the pathways involved in liver carcinogenesis and to identify HCC subtypes. However, use of molecular signatures to predict patient outcome has not entered clinical practice yet. Unsupervised selection of differentially expressed genes may lack of specificity considering the complexity of tumorigenic pathways. Therefore, the methods to determine hepatocellular carcinoma prognosis and select patients for appropriate therapy are still mainly established based upon parameters such as tumor size, tumor grade, the age of the patient, and lymph node metastasis.

Accurate prognosis of survival of hepatocellular carcinoma patients would permit selective administration of appropriate therapy, with patient having poorer prognosis being given the most aggressive treatment. Thus, there is still an unfulfilled need for the identification of prognostic markers that can accurately distinguish tumors associated with good prognosis including low probability of metastasis, late disease progression, decreased disease recurrence or increased patient survival, from the others. Using such markers, the practitioner would be able to accurately predict the patient's prognosis and would be able to effectively target the individuals who would most likely benefit from therapy or who need a more intensive monitoring.

SUMMARY OF THE INVENTION

The inventors have established that measuring the level of expression of 23 very specific genes gives accurate prediction of HCC prognosis and patient survival. Those 23 genes, sorted out from an initial quantity of 643 genes, constitute a 23-gene senescence signature that is highly promising for perfecting the strategies of treatment of HCC. Due to its small size, this signature is easy to implement in clinical setting. Said signature can be readily adapted for HCC management as well as patient allocation in clinical trials with new drugs.

DETAILED DESCRIPTION OF THE INVENTION

The inventors observed that cellular senescence leads to stable cell-cycle arrest and limits cell proliferation. This phenomenon is thus an important barrier against tumour development. Usually, senescence program occurs as a response to oxidative stress, oncogenic activation and DNA damage, including telomere dysfunction. Alternatively, cancer cells may adapt to high levels of oncogenic signals by disabling senescence program.

In the liver, hepatocyte telomeres undergo shortening during chronic injuries leading to cirrhosis and senescent hepatocytes can be detected in HCC, as a response to TGFp. Importantly, impairing CD4⁺ T-cell-mediated immune surveillance of pre-malignant senescent hepatocytes results in the development of HCC.

Therefore, the inventors hypothesized that a gene signature reflecting the capacity of tumor to escape senescence would be relevant to the HCC prognosis. To test this hypothesis, they used a model of replicative senescence induction in Huh7 HCC cells.

From this specific cell line, the inventors generated clones reprogrammed for replicative senescence and immortal clones. The method used is disclosed in Ozturk N, et al., Pore. Natls. Acad. Sci. USA 103, 2178-2183 (2006).

Reprogrammed and immortal clones displayed similar proliferation profiles at early passages. However, reprogrammed clones entered a state of senescence arrest characterized by flat morphology, shortened telomeres, senescence-associated β-galactosidase activity, and permanent arrest of DNA synthesis at about 90 population doublings.

In contrast, immortal cells maintained stable telomere lengths and proliferative capacity for at least 150 population doublings.

These two types of clones were profiled to identify genes associated with hepatocellular senescence and immortality.

By applying stringent selection criteria, the inventors found out that 1498 probes are differentially expressed. Accordingly, the inventors putted in light the fact that the expression of the corresponding 1017 non-redundant genes clearly discriminated immortal from senescent cells by hierarchical clustering.

Senescent-associated genes were involved in telomere maintenance and p53 signalling whereas immortal- associated genes were enriched in E2F1 targets and INK4A locus inhibitors. As example, senescence-associated genes included master effectors of apoptosis (e.g. BIK, PERP) and cyclin-dependent kinase inhibitors (e.g. CDKNlA/p21) and immortal- associated genes included plethora of cell cycling and DNA repair genes (e.g. BRCA1, EXOl, TOP3A) consistent with a sustained proliferation.

Next, the inventors surprisingly found out that senescent-associated genes were relevant to discriminate HCC subtypes.

Indeed, for this purpose, the inventors applied an integrative genomics approach using HCC datasets for which gene expression profiles and clinical data were available.

To further increase the specificity of the analysis, the inventors selected from the senescence- associated genes (n=1017), those which were detected in more than 50% HCCs.

Based on the expression of the resulting 643 genes, hierarchical clustering of the integrated dataset identified two clusters, both in the testing and the validating datasets.

Remarkably, senescence-associated gene profiles non-randomly segregated HCC into distinct clusters, allowing them to classify as:

immortal-type, and

senescent- type HCCs.

Immortal-type HCC included tumours from previously defined patients exhibiting an unfavourable prognosis, while senescent-type HCC recapitulated tumours from previously defined patients with a better prognosis.

Furthermore, immortal-type HCC coincided with tumours from patients with the worse prognosis that were identified previously using a hepatoblast (HB) gene expression signature representing hepatic progenitors. Then, the inventors selected genes whose expression in HCC was significantly associated with patient survival (P<0.05, log-rank test). In order to optimize the accuracy of the gene selection, the inventors retained from the survival-associated genes only those whose expression patterns correlated with immortality/bad prognosis and senescence/good prognosis model.

This strategy resulted in the selection of five immortality-associated genes over-expressed in HCC from patients with a bad prognosis, and 18 senescence-associated genes over-expressed in HCC from patients with a good prognosis.

This minimal 23-gene signature was used to perform integrative genomics using HCC gene profiles from the testing and validating sets. Hierarchical clustering of the integrated datasets based solely on the expression of the 23 genes recapitulated the findings of the inventors obtained with the initial 643-gene signature. More importantly, Kaplan-Meier plots and log- rank statistics demonstrated a significant difference (P<0.001) in the 5-year overall survival between the two groups of patients defined by the 23-gene signature. As expected, immortal- type and senescence-type HCCs were associated with bad and good patient survivals, respectively. Finally, the inventors showed that senescence-based classification of HCC was independent of patient gender, etiology, serum alpha-fetoprotein levels, underlying liver disease and tumour size.

Thus, accordingly, in a first aspect, the invention relates to a method for evaluating the vital prognosis of a subject suffering or suspected to suffer from hepatocellular carcinoma, said method comprising the step a) of:

- measuring the level of expression of the genes SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT in a biological sample of said subject; or

measuring the level of expression of at least one gene selected from the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB 3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT in a biological sample of said subject,

wherein

an overexpression of at least one gene selected in the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, and BUB3 is associated with a negative vital prognosis; and an overexpression of at least one gene selected in the group consisting of TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT is associated with a positive vital prognosis.

The method of the invention is thus a method which predicts clinical outcome of a patient suffering from hepatocellular carcinoma. Indeed, the 23-gene senescence signature discovered by the inventors efficiently predicts HCC prognosis and patient survival.

Due to its small size, this signature is easy to implement in clinical setting. It can be readily adapted for HCC management as well as patient allocation in clinical trials with new drugs. The prediction of clinical outcome is a crucial information for the practitioner in order for him to determine the appropriate therapeutic strategy to deploy and/or decide whether the patient should be treated by adjuvant therapy, i.e. additional therapy.

In a preferred embodiment, the method of the invention further comprises a step of providing a sample of hepatocellular carcinoma from said subject.

The term "SEMA6B" refers to the gene of sema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6B. Said gene encodes a member of the semaphorin family, a group of proteins characterized by the presence of a conserved semaphorin (sema) domain. Whereas some semaphorins are transmembrane proteins, others are secreted. Semaphorins play a major role in axon guidance. The protein encoded by this gene may be involved in both peripheral and central nervous system development. The sequence of said gene can be found under the Ensembl accession number Ensembl: ENSG00000167680.

The term "EXOSC9" refers to the gene of "Exosome component 9". Said genes encodes a component of the human exosome, a exoribonuclease complex which processes and degrades RNA in the nucleus and cytoplasm. This component may play a role in mRNA degradation and the polymyositis/scleroderma autoantigen complex. The sequence of said gene can be found under the Ensembl accession number: ENSG00000123737.

The term "MLF1IP" refers to the gene of "MLF1 interacting protein". This gene encodes a factor required for centromere assembly. The sequence of said gene can be found under the Ensembl accession number: ENSG00000151725.

The term "DSN1" refers to the gene of DSN1, MIND kmetochore complex component, homolog (S. cerevisiae). This gene encodes a kinetochore protein that functions as part of the minichromosome instability- 12 centromere complex. The encoded protein is required for proper kinetochore assembly and progression through the cell cycle. The sequence of said gene can be found under the Ensembl accession number: ENSG00000149636. The term "BUB3" refers to the gene of BUB3 mitotic checkpoint protein. This gene encodes a protein involved in spindle checkpoint function. The encoded protein contains four WD repeat domains and has sequence similarity with the yeast BUB3 protein. The sequence of said gene can be found under the Ensembl accession number: ENSG00000154473.

The term "TMCC1" refers to the gene of transmembrane and coiled-coil domain family 1. The sequence of said gene can be found under the Ensembl accession number: ENSG00000172765.

The term "PINK1" refers to the gene of PTEN induced putative kinase 1. This gene encodes a serine/threonine protein kinase that localizes to mitochondria. It is thought to protect cells from stress-induced mitochondrial dysfunction. Mutations in this gene cause one form of autosomal recessive early-onset Parkinson disease. The sequence of said gene can be found under the Ensembl accession number: ENSG00000158828.

The term "RAB43" refers to the gene of RAB43, member RAS oncogene family. The sequence of said gene can be found under the Ensembl accession number: ENSG00000172780.

The term "TPPl" refers to the gene of tripeptidyl peptidase I. This gene encodes a member of the sedolisin family of serine proteases. The protease functions in the lysosome to cleave N- terminal tnpeptides from substrates, and has weaker endopeptidase activity. It is synthesized as a catalytically-inactive enzyme which is activated and auto-proteolyzed upon acidification. Mutations in this gene result in late-infantile neuronal ceroid lipofuscinosis, which is associated with the failure to degrade specific neuropeptides and a subunit of ATP synthase in the lysosome. The sequence of said gene can be found under the Ensembl accession number: ENSG00000166340.

The term "ATP6V1A" refers to the gene of ATPase, H+ transporting, lysosomal 70kDa, VI subunit A. This gene encodes a component of vacuolar ATPase (V- ATPase), a multisubunit enzyme that mediates acidification of eukaryotic intracellular organelles. V- ATPase dependent organelle acidification is necessary for such intracellular processes as protein sorting, zymogen activation, receptor-mediated endocytosis, and synaptic vesicle proton gradient generation. V- ATPase is composed of a cytosolic VI domain and a transmembrane V0 domain. The VI domain consists of three A and three B subunits, two G subunits plus the C, D, E, F, and H subunits. The VI domain contains the ATP catalytic site. The V0 domain consists of five different subunits: a, c, c', c", and d. Additional isoforms of many of the VI and V0 subunit proteins are encoded by multiple genes or alternatively spliced transcript variants. This encoded protein is one of two VI domain A subunit isoforms and is found in all tissues. The sequence of said gene can be found under the Ensembl accession number: ENSG0000011457.

The term "STARDIO" refers to the gene of StAR-related lipid transfer (START) domain containing 10. The sequence of said gene can be found under the Ensembl accession number: ENSG00000214530.

The term "C4BPB" refers to the gene of complement component 4 binding protein, beta. This gene encodes a member of a superfamily of proteins composed predominantly of tandemly arrayed short consensus repeats of approximately 60 amino acids. A single, unique beta-chain encoded by this gene assembles with seven identical alpha-chains into the predominant isoform of C4b-binding protein, a multimeric protein that controls activation of the complement cascade through the classical pathway. C4b-binding protein has a regulatory role in the coagulation system also, mediated through the beta-chain binding of protein S, a vitamin K-dependent protein that serves as a cofactor of activated protein C. The genes encoding both alpha and beta chains are located adjacent to each other on human chromosome 1 in the regulator of complement activation gene cluster. The sequence of said gene can be found under the Ensembl accession number: ENSG00000123843.

The term "AMDHD1" refers to the gene of amidohydrolase domain containing 1. The sequence of said gene can be found under the Ensembl accession number: ENSG00000139344.

The term "DPP4" refers to the gene of dipeptidyl-peptidase 4. The protein encoded by this gene is identical to adenosine deaminase complexing protein-2, and to the T-cell activation antigen CD26. It is an intrinsic membrane glycoprotein and a serine exopeptidase that cleaves X-proline dipeptides from the N-terminus of polypeptides. The sequence of said gene can be found under the Ensembl accession number: Ensembl: ENSG00000197635.

The term "SMPD1" refers to the gene of sphingomyelinphosphodiesterase 1, acid lysosomal. The protein encoded by this gene is a lysosomal acid sphingomyelinase that converts sphingomyelin to ceramide. The encoded protein also has phospholipase C activity. Defects in this gene are a cause of Niemann-Pick disease type A (NPA) and Niemann-Pick disease type B (NPB). The sequence of said gene can be found under the Ensembl accession number: Ensembl: ENSG00000166311.

The term "IL6R" refers to the gene of interleukin 6 receptor, his gene encodes a subunit of the interleukin 6 (IL6) receptor complex. Interleukin 6 is a potent pleiotropic cytokine that regulates cell growth and differentiation and plays an important role in the immune response. The IL6 receptor is a protein complex consisting of this protein and interleukin 6 signal transducer (IL6ST/GP130/IL6-beta), a receptor subunit also shared by many other cytokines. Dysregulated production of IL6 and this receptor are implicated in the pathogenesis of many diseases, such as multiple myeloma, autoimmune diseases and prostate cancer. The sequence of said gene can be found under the Ensembl accession number: Ensembl: ENSG00000160712.

The term "PCSK6" refers to proprotein convertase subtilisin/kexin type 6. The protein encoded by this gene belongs to the subtilisin-like proprotein convertase family. The members of this family are proprotein convertases that process latent precursor proteins into their biologically active products. This encoded protein is a calcium-dependent serine endoprotease that can cleave precursor protein at their paired basic amino acid processing sites. Some of its substrates are - transforming growth factor beta related proteins, proalbumin, and von Willebrand factor. This gene is thought to play a role in tumor progression. The sequence of said gene can be found under the Ensembl accession number: Ensembl: ENSG00000140479.

The term "EPHX1" refers to the gene of epoxide hydrolase 1, microsomal (xenobiotic). Epoxide hydrolase is a critical biotransformation enzyme that converts epoxides from the degradation of aromatic compounds to trans-dihydrodiols which can be conjugated and excreted from the body. Epoxide hydrolase functions in both the activation and detoxification of epoxides. Mutations in this gene cause preeclampsia, epoxide hydrolase deficiency or increased epoxide hydrolase activity. The sequence of said gene can be found under the Ensembl accession number: Ensembl: ENSG00000143819.

The term "TMEM140" refers to the gene of transmembrane protein 140. The sequence of said gene can be found under the Ensembl accession number: ENSG00000146859.

The term "CAND2" refers to the gene of cullin-associated and neddylation-dissociated 2 (putative). The sequence of said gene can be found under the Ensembl accession number: ENSG00000144712.

The term "UGT2B4" refers to UDP glucuronosyltransferase 2 family, polypeptide B4. The sequence of said gene can be found under the Ensembl accession number: ENSG00000156096.

The term "AKR1C1" refers to the gene of aldo-keto reductase family 1, member CI. This gene encodes a member of the aldo/keto reductase superfamily, which consists of more than 40 known enzymes and proteins. These enzymes catalyze the conversion of aldehydes and ketones to their corresponding alcohols by utilizing NADH and/or NADPH as cofactors. The enzymes display overlapping but distinct substrate specificity. This enzyme catalyzes the reaction of progesterone to the inactive form 20-alpha-hydroxy-progesterone. The sequence of said gene can be found under the Ensembl accession number: ENSG00000187134.

The term "BAAT" refers to the gene of bile acid CoA: amino acid N-acyltransferase (glycine N-choloyltransferase). The protein encoded by this gene is a liver enzyme that catalyzes the transfer of C24 bile acids from the acyl-CoA thioester to either glycine or taurine, the second step in the formation of bile acid- amino acid conjugates. The bile acid conjugates then act as a detergent in the gastrointestinal tract, which enhances lipid and fat-soluble vitamin absorption. Defects in this gene are a cause of familial hypercholanemia (FHCA).The sequence of said gene can be found under the Ensembl accession number: Ensembl: ENSG00000136881.

As used herein, the term "subject" refers to an individual with symptoms of and/or suspected of having hepatocellular carcinoma.

The term "cancer" or "tumor", as used herein, refers to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Preferably the cancer is a liver cancer, more preferably a hepatocellular carcinoma. More preferably, said cancer is a hepatocellular carcinoma in an early stage without local or systemic invasion, still more preferably a small-size hepatocellular carcinoma.

As used herein, the term "positive vital prognosis" refers to an increased patient survival and/or a late disease progression and/or a decreased disease recurrence and/or a decreased metastasis formation. A patient having a positive vital prognosis according to the invention therefore constitutes a good candidate for further therapeutic strategies, such as adjuvant therapy.

The term "negative vital prognosis" indicates a decreased patient survival and/or an early disease progression and/or an increase disease recurrence and/or an increase metastasis formation. A patient having a negative vital prognosis according to the invention is a patient having a high risk of passing away because of the hepatocellular cancer. Therefore, such patient may not be regarded as a good candidate for further therapeutic strategies, such as adjuvant therapy.

The term "adjuvant therapy", as used herein, refers to any type of treatment of cancer given as additional treatment, usually after surgical resection of the primary tumor, in a patient affected with a cancer that is at risk of metastasizing and/or likely to recur. The aim of such an adjuvant treatment is to improve the prognosis. Adjuvant therapies comprise radiotherapy and therapy, preferably systemic therapy, such as hormone therapy, chemotherapy, immunotherapy and monoclonal antibody therapy.

As used herein, the term "gene" refers to a nucleic acid fragment that expresses a specific protein, including regulatory sequences preceding (5' non-coding sequences) and following (3' non-coding sequences) the coding sequence.

As used herein, the expression "gene of interest according to the invention" or "gene of interest" refers to one of the followings genes: SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT.

As used herein, the term "gene expression level" or "the expression level of a gene" refers to an amount or a concentration of a transcription product, for instance mRNA, or of a translation product, for instance a protein or polypeptide. Typically, a level of mRNA expression can be expressed in units such as transcripts per cell or nanograms per microgram of tissue. A level of a polypeptide can be expressed as nanograms per microgram of tissue or nanograms per milliliter of a culture medium, for example. Alternatively, relative units can be employed to describe an expression level.

As used herein, the expression "mRNA transcript" refers to the product resulting from RNA polymerase-catalyzed transcription of a DNA sequence without introns and that can be translated into polypeptides by the cell.

As used herein, the term "biological sample" as used herein refers to any biological sample obtained for the purpose of evaluation in vitro. Typically, said biological sample can be obtained from solid tissues and tumor tissues. Examples of additional test samples include blood, serum, plasma, nipple aspirate fluid, urine, saliva, synovial fluid and cephalorachidian liquid (CRL). Preferably, said biological sample is liver tissue, more preferably hepatocellular carcinoma tissue. Hepatocellular carcinoma tissue can be obtained by biopsy. Alternatively, said biological sample is blood, which may comprise tumor derived material such as tumor cells or tumor relapsed proteins and/or nucleic acids.

As used herein, the expression of "measuring the expression level of a gene" encompasses the step of measuring the quantity of a transcription product, preferably mRNA obtained through transcription of said gene, and/or the step of measuring the quantity of translation product, preferably the protein obtained through translation of said gene. Preferably, the step of measuring the expression of a gene refers to the step of measuring the quantity of mRNA obtained through transcription of said gene. Typically, the step a) of measuring the level of gene expression of said gene(s) may be performed according to the routine techniques, well known of the person skilled in the art.

In one embodiment, step a) of measuring the level of expression of said gene(s) is a step of measuring the expression level of translation products of said gene(s), preferably proteins. Methods for measuring the quantity of protein in a biological sample may be measured by using standard immunodiagnostic techniques, including immunoassays such as competition, direct reaction, or sandwich type assays. In such embodiments, cancer cells are purified from the isolated biological sample. Such assays include, but are not limited to, agglutination tests; enzyme-labelled and mediated immunoassays, such as ELISAs; biotin/avidin type assays; radioimmunoassays; immunoelectrophoresis; immunoprecipitation.

The reactions generally include revealing labels such as fluorescent, chemiluminescent, radioactive, enzymatic labels or dye molecules, or other methods for detecting the formation of a complex between the antigen and the antibody or antibodies reacted therewith.

More particularly, an ELISA method can be used, wherein the wells of a microtiter plate are coated with a set of antibodies against the target protein of the invention. The cancer cells of the biological sample that are suspected of containing a target protein of the invention, are then added to the coated wells. After a period of incubation sufficient to allow the formation of antibody-antigen complexes, the plate(s) can be washed to remove unbound moieties and a detectably labelled secondary binding molecule added. The secondary binding molecule is allowed to react with any captured sample marker protein, the plate washed and the presence of the secondary binding molecule detected using methods well known in the art.

In a particular embodiment, the methods of the invention comprise contacting the cancer cells of the biological sample with a binding partner capable of selectively interacting with at least one of the target proteins of the invention (i.e a protein coded by one of the genes of interest of the invention) present in the biological sample. The binding partner may be an antibody that may be polyclonal or monoclonal, preferably monoclonal. In another embodiment, the binding partner may be an aptamer.

Polyclonal antibodies of the invention or a fragment thereof can be raised according to known methods by administering the appropriate antigen or epitope to a host animal selected, e.g., from pigs, cows, horses, rabbits, goats, sheep, and mice, among others. Various adjuvants known in the art can be used to enhance antibody production. Although antibodies useful in practicing the invention can be polyclonal, monoclonal antibodies are preferred.

Monoclonal antibodies of the invention or a fragment thereof can be prepared and isolated using any technique that provides for the production of antibody molecules by continuous cell lines in culture. Techniques for production and isolation include but are not limited to the hybridoma technique originally described by Kohler and Milstein (1975); the human B-cell hybridoma technique (Cote et al., 1983); and the EBV-hybridoma technique (Cole et al. 1985).

Alternatively, techniques described for the production of single chain antibodies (see e.g. U.S. Pat. No. 4,946,778) can be adapted to produce single chain antibodies specific to a target protein of the invention. Antibodies useful in practicing the present invention also include fragments including but not limited to F(ab')2 fragments, which can be generated by pepsin digestion of an intact antibody molecule, and Fab fragments, which can be generated by reducing the disulfide bridges of the F(ab')2 fragments. Alternatively, Fab and/or scFv expression libraries can be constructed to allow rapid identification of fragments having the desired specificity to the target protein of the invention. For example, phage display of antibodies may be used. In such a method, single-chain Fv (scFv) or Fab fragments are expressed on the surface of a suitable bacteriophage, e. g., M13. Briefly, spleen cells of a suitable host, e. g., mouse, that has been immunized with a protein are removed. The coding regions of the VL and VH chains are obtained from those cells that are producing the desired antibody against the protein. These coding regions are then fused to a terminus of a phage sequence. Once the phage is inserted into a suitable carrier, e. g., bacteria, the phage displays the antibody fragment. Phage display of antibodies may also be provided by combinatorial methods known to those skilled in the art. Antibody fragments displayed by a phage may then be used as part of an immunoassay.

In another embodiment, the binding partner may be an aptamer. Aptamers are a class of molecule that represents an alternative to antibodies in term of molecular recognition. Aptamers are oligonucleotide or oligopeptide sequences with the capacity to recognize virtually any class of target molecules with high affinity and specificity. Such ligands may be isolated through Systematic Evolution of Ligands by Exponential enrichment (SELEX) of a random sequence library, as described in Tuerk C. 1997. The random sequence library is obtainable by combinatorial chemical synthesis of DNA. In this library, each member is a linear oligomer, eventually chemically modified, of a unique sequence. Possible modifications, uses and advantages of this class of molecules have been reviewed in Jayasena S.D., 1999. Peptide aptamers consist of conformationally constrained antibody variable regions displayed by a platform protein, such as E. coli Thioredoxin A, that are selected from combinatorial libraries by two hybrid methods (Colas et al., 1996). The binding partners of the invention, such as antibodies or aptamers, may be labelled with a detectable molecule or substance, such as a fluorescent molecule, a radioactive molecule or any others labels known in the art. Labels are known in the art that generally provide (either directly or indirectly) a signal.

As used herein, the term "labelled", with regard to the antibody, is intended to encompass direct labelling of the antibody or aptamer by coupling (i.e., physically linking) a detectable substance, such as a radioactive agent or a fluorophore (e.g. fluorescein isothiocyanate (FITC) or phycoerythrin (PE) or Indocyanine (Cy5)) to the antibody or aptamer, as well as indirect labelling of the probe or antibody by reactivity with a detectable substance. An antibody or aptamer of the invention may be labelled with a radioactive molecule by any method known in the art. For example radioactive molecules include but are not limited radioactive atom for scintigraphic studies such as 1123, 1124, In 111 , Rel86, Rel88.

The aforementioned assays generally involve the binding of the binding partner (ie. antibody or aptamer) to a solid support. Solid supports which can be used in the practice of the invention include substrates such as nitrocellulose (e. g., in membrane or microtiter well form); polyvinylchloride (e. g., sheets or microtiter wells); polystyrene latex (e.g., beads or microtiter plates); polyvinylidine fluoride; diazotized paper; nylon membranes; activated beads, magnetically responsive beads, and the like.

In another embodiment, said step a) of measuring the level of expression of said gene(s) is a step of measuring the expression level of transcription products of said gene(s), preferably mRNA. Methods for measuring the quantity of mRNA are well known in the art. Typically, the nucleic acid contained in the biological sample may be extracted according to standard methods, for example using lytic enzymes or chemical solutions or extracted by nucleic-acid- binding resins following the manufacturer's instructions. The extracted mRNA may be then detected by hybridization (e. g., Northern blot analysis). Alternatively, the extracted mRNA may be subjected to coupled reverse transcription and amplification, such as reverse transcription and amplification by polymerase chain reaction (RT-PCR), using specific oligonucleotide primers that enable amplification of a region in said genes. Preferably, quantitative or semi-quantitative RT-PCR is used. Extracted mRNA may be reverse- transcribed and amplified, after which amplified sequences may be detected by hybridization with a suitable probe or by direct sequencing, or any other appropriate method known in the art. Other methods of amplification include ligase chain reaction (LCR), transcription- mediated amplification (TMA), strand displacement amplification (SDA) and nucleic acid sequence based amplification (NASBA). Nucleic acids having at least 10 nucleotides and exhibiting sequence complementarity or homology to the mRNA of interest herein find utility as hybridization probes or amplification primers. It is understood that such nucleic acids need not be identical, but are typically at least about 80% identical to the homologous region of comparable size, more preferably 85% identical and even more preferably 90-95% identical. In certain embodiments, it will be advantageous to use nucleic acids in combination with appropriate means, such as a detectable label, for detecting hybridization. A wide variety of appropriate indicators are known in the art including, fluorescent, radioactive, enzymatic or other ligands (e. g. avidin/biotin).

Probes typically comprise single- stranded nucleic acids of between 10 to 1000 nucleotides in length, for instance of between 10 and 800, more preferably of between 15 and 700, typically of between 20 and 500.

Primers typically are shorter single- stranded nucleic acids, of between 10 to 25 nucleotides in length, designed to perfectly or almost perfectly match a nucleic acid of interest, to be amplified. The probes and primers are "specific" to the nucleic acids they hybridize to, i.e. they preferably hybridize under high stringency hybridization conditions (corresponding to the highest melting temperature Tm, e.g., 50 % formamide, 5x or 6x SCC. SCC is a 0.15 M NaCl, 0.015 M Na-citrate).

The nucleic acid primers or probes used in the above amplification and detection method may be assembled as a kit. Such a kit includes consensus primers and molecular probes. A preferred kit also includes the components necessary to determine if amplification has occurred. The kit may also include, for example, PCR buffers and enzymes; positive control sequences, reaction control primers; and instructions for amplifying and detecting the specific sequences.

Examples of specific primers of the genes of the invention are summarised in the table 1 :

Table 1: List of suitable primers

SEMA6B Left primer SEQ ID N° 1 CTCTTTGTGTGCGGTTCCAA

Right primer SEQ ID N°2 GAGCATCCCGTCAGAGAAGA

EXOSC9 Left primer SEQ ID N°3 ACGTAATTTTCCTGCGCCTC

Right primer SEQ ID N°4 TCCAAGTTCCACAATGCAGC

MLF1IP Left primer SEQ ID N°5 TG CC ATTATCCC AG AC AG CA

Right primer SEQ ID N°6 TTCCCACGGTGAGATATCGG

DSN1 Left primer SEQ ID N°7 ATTCACC AG GG C ATC AC AG A

Right primer SEQ ID N°8 ACTG AAG CCCTTAGTGTCCC

BUB3 Left primer SEQ ID N°9 TTCTG AG G G AAG C A AG G AG G Right primer SEQ ID N°10 AGGAGGAGACAAGCAGGAAC

TMCC1 Left primer SEQ ID N°11 AGAGAGGGACAAGCTTGCAT

Right primer SEQ ID N°12 AG CTG GTAG GTG C ATC AGTT

PINK1 Left primer SEQ ID N°13 GGGCTTGGCAAATGGAAGAA

Right primer SEQ ID N°14 TCCCACTCCCGTAACTGAAC

RAB43 Left primer SEQ ID N°15 GCTAATCCTTCAGTGCCAGC

Right primer SEQ ID N°16 TGAGGCAGTTAAGGGTCCAG

TPP1 Left primer SEQ ID N°17 TTGTAAGGTCCCCACATCCC

Right primer SEQ ID N°18 TTGTAAGGTCCCCACATCCC

ATP6V1A Left primer SEQ ID N°19 GTGCAAGTATGGCCTGTACG

Right primer SEQ ID N°20 GGCTCCAGGGATAGCAGTAG

STARD10 Left primer SEQ ID N°21 GCCCGATGACCAAGACTTTC

Right primer SEQ ID N°22 CCATCCGGCACTTGATCTTG

C4BPB Left primer SEQ ID N°23 AACCAGAGTGTGAGAAGGCA

Right primer SEQ ID N°24 TCCTCCATTGTCATGCCACT

AMDHD1 Left primer SEQ ID N°25 CTGGAGACCGAGCTCAAGAT

Right primer SEQ ID N°26 TGTCCACGTGTATTTCCCCA

DPP4 Left primer SEQ ID N°27 AGTTGTGAGCTGAATCCGGA

Right primer SEQ ID N°28 TTGGAGGGCATCTGGACATT

SMPD1 Left primer SEQ ID N°29 CTCTTCCTCACTGACCTGC

Right primer SEQ ID N°30 CACCATATCAAAAGGGCCGG

IL6R Left primer SEQ ID N°31 CTGAGGGTGAGTGGGTGAAT

Right primer SEQ ID N°32 TCTCCTCTCCTTCCTCTGCT

PCSK6 Left primer SEQ ID N°33 CGAAGGGTGAAGAGACAGGT

Right primer SEQ ID N°34 GGACATTCATTTCCGACCGG

EPHX1 Left primer SEQ ID N°35 TCCTGACTGACCCCAAGAAC

Right primer SEQ ID N°36 CCAGTCCCCTCCTTGAATGT

TMEM140 Left primer SEQ ID N°37 GACAGGACACATGGGGTACA

Right primer SEQ ID N°38 TCACAGCGAGGATTTGGAGT

CAND2 Left primer SEQ ID N°39 GGAATGGGTTGGGTAGGGAA

Right primer SEQ ID N°40 TGGAAGATGCCCATTGTTGC

UGT2B4 Left primer SEQ ID N°41 CAAACCTGCCAAACCCCTAC

Right primer SEQ ID N°42 GTTACTGACCATCGACCCCA

AKR1C1 Left primer SEQ ID N°43 TCCTCTCACATGCCATTGGT

Right primer SEQ ID N°44 AATCCCAGGACAGGCATGAA

BAAT Left primer SEQ ID N°45 AAGAATCATCCCAGGTGCCA

Right primer SEQ ID N°46 TGAAAGGGAATCAGGCCTGT Most preferably, said step a) of measuring the level of expression of said gene(s) are performed by DNA microarray.

As used herein, the expression "microarray" or "DNA microarray" refers to a set of oligonucleotide probes arranged on a solid matrix, such as a microscope slide or silicon wafer. The term "microarray" is thus meant to indicate analysis of many small spots to facilitate large scale nucleic acid analysis enabling the simultaneous analysis of thousands of DNA sequences. This technique is seen as an improvement on existing methods, which are largely based on gel electrophoresis. For a review, see Nature Gen. (1999) 21 Suppl. 1. Line blot assay and microarray methods both use circumscribed areas containing specific DNA fragments. The utility of DNA arrays for genetic analysis has been demonstrated in numerous applications including mutation detection, genotyping, physical mapping and gene-expression monitoring. The basic mechanism is hybridization between arrays of nucleotides and target nucleic acid.

In the context of this invention, the person skilled in the art may use the following probes for carrying out the invention and determining the expression level of the genes of interest according to the invention.

Said suitable probes for assessing the level of the genes of interest are depicted in the table 2:

Table 2: List of suitable probes

Gene of SEQ Sequence

interest ID

SEMA6B 47 CGCCAACTACAGCATAGACACCCTGCAGCCCGTCGGAGACAACATCAGCGGTA

TGGCCCG

EXOSC9 48 CCACTCTCAAACTGCGAACGCCGCTTCCTACTCCGTGCCATCGAAGAGAAGAA

GCGGCTG

MLF1IP 49 TGGGTTTCATTGCTCCTAGTTTCATCTGCTTCATCTGTTGTAAACTCTTCTTCCTT

TATT

DSN1 50 CAGCCGGTCTATCAGTGTCGATTTAGCAGAAAGCAAACGGCTTGGCTGTCTCCT

GCTTTC

BUB3 51 GGACCAATCGGCCCCCTAGACTGAGACGTTGGCGTTTGAAATCAGCCAATGGC

AGGTCTA

TMCC1 52 AAATCAACAGGAAGTCTGGTCAGGAGATGACAGCTGTTATGCAGTCAGGCCGA

CCCAGGT

PINK1 53 AGTGAATGGCCAAGCTGGTCTAGTAGATGAGGCTGGACTGAGGAGGGGTAGG

CCTGCATC

RAB43 54 AGGTCCAAGTAGAAGCTTGCATCCTTGAGGCTCAGGGATGAGAGGGCACCGCA AGGCACC

TPP1 55 AACCCCCTCTGTGATCCGTAAGCGATACAACTTGACCTCACAAGACGTGGGCT

CTGGCAC

ATP6V1A 56 CATCCTCTGTTGACTGGCCAGAGAGTCCTTGATGCCCTTTTTCCGTGTGTCCAG

GGAGGA

STARD10 57 CCTATAGCAGGGCTGGGGTGTCTGTCTGGGTGCAGGCTGTGGAGATGGATCGG

ACGCTGC

C4BPB 58 AGAAGGCACTTCTTGCCTTTCAGGAGAGTAAGAACCTCTGCGAAGCCATGGAG

AACTTTA

AMDHD1 59 GGCTACCTACTGCGGGGCTCATTCAGTGCCTAAAGGAAAAACTGCTACTGAAG

CTGCTGA

DPP4 60 GGTCCTGGTCTGCCCCTCTATACTCTACACAGCAGCGTGAATGATAAAGGGCT

GAGAGTC

SMPD1 61 CGGACCCTGACTGTGCAGACCCACTGTGCTGCCGCCGGGGTTCTGGCCTGCCG

CCCGCAT

IL6R 62 GTATCTCAGGGCCTGGTCGTTTTCAACAGAATTATAATTAGTTCCTCATTAGCA

TTTTGC

PCSK6 63 AGGCCCTTTACTTCAACGACCCCATTTGGTCCAACATGTGGTACCTGCATTGTG

GCGACA

EPHX1 64 TTTGAAGTCATCTGCCCTTCCATCCCTGGCTATGGCTTCTCAGAGGCATCCTCC

AAGAAG

TMEM140 65 CAAAGCTTCCCTGGACCTGAAGCCAGACAGGGCAGAGGCGTCCGCTGACAAAT

CACTCCC

CA D2 66 AATTTCAAAATACTTATTAGCAAATTGGGCAACAATGGGCATCTTCCATGCCAC

CACCCA

UGT2B4 67 CCAAACCCCTACCGAAGGAAATGGAAGAGTTTGTCCAGAGCTCTGGAGAAAAT

GGTGTTG

AKR1C1 68 ATTGCTCTTATAGCCTGTGAGGGAGGAAGAAAGAAACATTTGCCAGCCAGGCT

AGTGACA

BAAT 69 GACAGCTACCCCTGTGAGTGCACTTGTTGATGAGCCAGTGCATATCCGAGCTA

CAGGCCT

As used herein, the term "probe" refers to a nucleic acid sequence designed to hybridize specifically to a target sequence of interest. In the context of the present invention, oligonucleotide probes comprise about 50 nucleotides. These probes are thus used to detect the presence of complementary target sequences by hybridization with the target sequences. Preferably, the method of the invention may comprise a step b), further to step a) of determining the expression profile of said gene(s). Indeed, once expression levels are determined, an expression profile can be created. Typically, expression profile is obtained with the expression level(s) of one or several gene(s), preferably several genes. The expression profiles are highly convenient for simultaneously comparing the expression level of several genes.

As used herein, the term "expression profile" refers to quantitative and qualitative expression of one or more genes in a sample. The expression profile of a single gene corresponds to the expression level of said gene.

The expression profile is a repository of the expression level data that can be used to compare the expression levels of different genes, in whatever units are chosen. The term "profile" is also intended to encompass manipulations of the expression level data derived from a cell, tissue or individual. For example, once relative expression levels are determined for a given set of genes, the relative expression levels for that cell, tissue or individual can be compared to a standard to determine if expression levels are higher or lower relative to the same genes in a standard. Standards can include any data deemed by one of skilled in the art to be relevant for comparison, for example determined threshold value or expression profile of a positive and/or negative control.

In a preferred embodiment, the method of the invention further comprises a step c), further to step b) of comparing the expression profile obtained in step b) with threshold value(s).

Alternatively, the method of the invention further comprises a step c'), further to step b) of comparing the expression profile obtained in step b) with the expression profile of said gene(s) of interest obtained for at least one control selected from the group consisting of a positive control and a negative control.

This step of comparing the expression profile obtained in step b) to a threshold value or to the expression profiles of a control is useful to identify subjects presenting HCC.

As used herein, the expression "comparing the expression profile" in all its grammatical forms, refers to the evaluation of the quantitative and/or qualitative difference in expression of a gene. Typically, the person skilled in the art may compare the level of expression of a gene to a control value or threshold value.

Typically, a "control value" or "threshold value" or "cut-off value" can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and/or clinical conditions, as would be recognized by person skilled in the art. Preferably, the person skilled in the art may compare the expression profile of the gene(s) of interest according to the invention with threshold value(s) for said gene(s). For each gene to be compared to a threshold value, the skilled person in the art will compare the level of expression of said gene to a threshold value.

The inventors have shown that expressions of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3 are increased in patients having a negative vital prognosis. They also have shown that expression of TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, BAAT are increased in patients having a positive vital prognosis.

In another embodiment, the step c') is a step of comparing the expression profile obtained in step b) with the expression profile of at least one control chosen in the group consisting of a positive control and a negative control.

In this particular embodiment, said positive control is the expression profile of a subject suffering from hepatocellular carcinoma or a subject who died from hepatocellular carcinoma. Preferably, said negative control is the expression profile of a healthy subject or a subject who overcame hepatocellular carcinoma.

The expression profile of the gene(s) of interest of the present invention is set for said positive and negative controls. The person skilled in the art is thus able to compare the expression profile of the gene(s) of interest in the biological sample of said subject to the expression profile of a positive and/or a negative control. Such comparison will then lead the person skilled in the art to determine the vital prognosis of a subject suffering from hepatocellular carcinoma.

In a further aspect, the invention concerns a method for:

selecting a subject affected with a hepatocellular carcinoma for a therapy, preferably an adjuvant therapy, or

determining whether a subject affected with a hepatocellular carcinoma is susceptible to benefit from a therapy, preferably an adjuvant therapy,

wherein said method comprises measuring the level of expression of the genes SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT in a biological sample of said subject.

All the technical features disclosed above are applicable.

Therapeutic method according to the invention

The invention relates to a method of treatment of a patient suffering from hepatocellular carcinoma comprising the step of: 1) predicting the vital prognosis of said subject by measuring the level of expression of at least one gene selected in the group consisting of TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARDIO, C4BPB, AMDHDl, DPP4, SMPDl, IL6R, PCSK6, EPHXl, TMEM140, CAND2, UGT2B4, AKR1C1, BAAT,

2) if said step 1) shows an overexpression of at least one of said genes, providing the appropriate therapy to said patient.

All the technical features disclosed above are applicable.

As used herein, the term "patient" denotes a mammal, such as a rodent, a feline, a canine, and a primate. Preferably, a patient according to the invention is a human.

In the context of the invention, the term "treating" or "treatment", as used herein, means reversing, alleviating, inhibiting the progress of, or preventing the disorder or condition to which such term applies, or reversing, alleviating, inhibiting the progress of, or preventing one or more symptoms of the disorder or condition to which such term applies.

Kits according to the invention

The invention also relates to a kit :

(a) for predicting clinical outcome of a subject suffering from hepatocellular carcinoma and/or

(b) for selecting a subject affected with a hepatocellular carcinoma for a therapy or determining whether a subject affected with a hepatocellular carcinoma is susceptible to benefit from a therapy; wherein the kit comprises:

(i) at least one antibody specific to a protein encoded by a gene selected from the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARDIO, C4BPB, AMDHDl, DPP4, SMPDl, IL6R, PCSK6, EPHXl, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT; and/or

(ii) at least one probe specific to the mRNA, cDNA or genomic DNA of a gene selected from the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB 3,

TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARDIO, C4BPB, AMDHDl, DPP4, SMPDl, IL6R, PCSK6, EPHXl, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT; and/or

(iii) at least one nucleic acid primer pair specific to said genomic DNA, mRNA or cDNA; and optionally, a leaflet providing guidelines to use such a kit.

All the technical features disclosed above are applicable.

Preferably, said kit comprises the probes as defined in sequences SEQ ID N°47 to 69. Method for monitoring the response to treatment

The inventors surprisingly discovered a 23 gene senescence associated signature that is a robust predictor of the clinical outcome of patient suffering from HCC.

More precisely, they showed that high levels of expression of very specific genes in the cells of a patient are indicative of a positive vital prognosis, whereas as the overexpression of other genes indicates a negative vital prognosis.

The invention thus provides a method for monitoring the response to a treatment of a patient suffering from a hepatocellular cancer comprising:

a. treating said patient with an anti-cancer agent, for example by surgery; then b. measuring the level of expression of at least one gene selected from the group consisting of at least one gene selected from the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCS 6, EPHX1, TMEM140, CAND2, UGT2B4, AKRICI, and BAAT in a biological sample of said subject.

All the technical features disclosed above are applicable.

Typically, in a patient suffering from hepatocellular carcinoma, high levels of expression of SEMA6B, EXOSC9, MLF1IP, DSN1, and/or BUB3 are associated with a negative vital prognosis and said patient can therefore be construed as a bad candidate for further treatment. Typically, a patient having a negative vital prognosis would have high risk of treatment failure to drug therapies, a cancer recurrence after surgery, and/or metastases.

On the contrary, in a patient suffering from hepatocellular carcinoma, high levels of expression of at least one gene selected in the group consisting of TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKRICI, and/or BAAT are associated with a positive vital prognosis. Such patient is thus a good candidate for further therapeutic strategies, including partial or total hepatectomy and drug therapies.

In one embodiment of the invention, step b. of measuring the gene expression level is performed by the following method:

i) obtaining a biological sample comprising cancer cells, preferably hepatocellular carcinoma, from said patient, and

ii) measuring the level of expression of said gene(s) in said cancer cells in said biological sample. According to the invention, in case of monitoring the response to a treatment of a patient suffering from HCC, a biological sample may be a sample of the HCC tissue or HCC cells obtained from the patient according to methods known in the art. Said biological sample is for example a biopsy.

Typically, step b. of measuring the gene expression level may be performed according to the routine techniques, well known of the person skilled in the art.

More preferably, the measurement comprises contacting the cancer cells of the biological sample with selective reagents such as probes, primers, ligands or antibodies, and thereby detecting the presence of nucleic acids or proteins of interest originally in the sample.

FIGURE LEGEND Figure 1

Identification of a minimal subset of 23 senescence-associated genes predictive of patient survival in human HCC.

(a) Volcano plot visualization of 1,498 Affymetrix probes differentially expressed between immortal (I) and senescent (S) Huh7 cells. Probes selection (blue dots) was based on the significance of the differential expression (above horizontal red line; <0.001 using a random-variance f-test) and the fold change (left and right sides of vertical red lines; fold- change >2).

(b) Hierarchical cluster analysis of the corresponding 1,017 non-redundant genes. Columns represent individual samples (immortal (I) and senescent (S) HuH7 cells) and rows in the heat- map represent each genes.

(c) Hierarchical cluster analysis of the integrated gene expression data from immortal (I) and senescent (S) Huh7 cells, and from human HCC. Clustering was based on the expression of

643 senescence-associated genes (from (b)) which expression was detected in at least 50% of human HCC for each of the testing (62 HCC) and validating (80 HCC) datasets (upper and lower part, respectively). Two major clusters (1 and 2) of HCC were identified based on the co-clustering with immortal (I) and senescent (S) Huh7 cells. The distribution of human HCC samples according to previously described subgroups with respect to survival (A: bad prognosis; B: good prognosis) and cell origin (HB: hepatoblast)², is indicated at the end of each row.

(d) Venn diagram of survival-associated genes in human HCC and senescence-associated genes in Huh7 cells. Intersection of the two gene sets identified 23 genes. Genes coloured in red and blue were induced in immortal and senescent cells, respectively, and simultaneously induced in HCC from patient with bad and good survival, respectively.

(e) Hierarchical cluster analysis of integrated gene expression data from immortal (I) and senescent (S) Huh7 cells, and from human HCC based on the expression of 23 senescence- and survival-associated genes. As in (c), integrative analysis was performed using a testing set of HCC (upper part) and a validating set (lower part).

(f) Kaplan-Meier plots analysis of 5-years survival from individuals assigned to the senescent (S) and immortal (I) clusters by the integrative clustering analysis performed in (e) using the 23 senescent-associated genes from the testing set (upper part) and the validating set (lower part). P<0.0001, log-rank test.

EXAMPLE

Material and methods

Gene expression profiling of senescent and immortal Huh7 clones

The establishment and culture conditions of senescence-programmed C3 and G12, and immortal CI and Gi l clones, and genome-wide gene expression profiling with microarray technology have been described previously¹⁰. Briefly, senescence-arrested C3 and G12 clones and immortal CI and Gi l clones (PD 150) were plated in triplicate onto 15-cm diameter petri dishes, left in culture for three days and collected for RNA extraction. Total RNA was extracted using total RNA isolation kit (Promega, Madison, USA). DNase digestion was performed following kit instructions. RNA samples were analysed using Agilent Bioanalyzer. All samples passed the quality control tests. Affymetrix platform with GeneChip Human Genome U133 Plus 2.0 arrays were used for microarray analysis. GeneChip Operating Software (Affymetrix) was used to collect and store microarray data. CEL files were uploaded to RMAExpress software to assess the quality of the arrays at the image level (http://rmaexpress.bmbolstad.com). Quality assessment of the Affymetrix datasets was performed using affyPLM (http://www.bioconductor.org). NUSE and RLE plots were drawn and outliers with high deviation from the average probe intensity value were excluded from further analyses. All samples passed microarray quality control tests. The microarray data reported in this paper have been deposited in the Gene Expression Omnibus (GEO) database under accession numbers.

Statistical analysis of microarray data

Raw data from Affymetrix microarray CEL files were first processed by using the MAS5.0 algorithm from Bioconductor R library. Normalization of microarray data was based on the quantile algorithm. Before statistical analysis, probe set intensity was threshold at a value of 10 and probe sets with missing values (Affymetrix 'detection call absent') in >50% samples were filtered out. Accordingly, the processed dataset used for statistical analysis consisted in 24,247 probes corresponding to 11,612 unique annotated genes. Analyses were performed using the stable v4.2.1 release of BRB-ArrayTools developed by Dr. Richard Simon and BRB-ArrayTools Development Team from the Biometric Research Branch of NCI. Briefly, differentially expressed genes were identified by a univariate two-sample /-test with a random variance model as in Coulouarn et al.⁴. Individual genes were selected on the basis of both statistical significance ( <0.001, two-sample f-test) and fold change difference between the compared groups (2-fold change). A stringent significance threshold was used to limit the number of false positive genes. A global test was also performed and permutation P-values for significant genes were computed based on 10,000 random permutations. For the class comparison analysis between immortal and senescent cells, permutation P-values were below 0.01 and the false discovery rate was below 1%.

Integrative genomics

Integration of genomic data from Huh7 cell lines and human primary HCC was performed following standardization as previously described^2"4. Meta-analysis used publicly available gene expression datasets downloaded from the gene expression omnibus (GEO) database (www.ncbi.nlm.nih.gov/geo/). Briefly, two series of human HCC profiles (GSE1898 and GSE4024, from GEO) were used to generate a testing HCC dataset and a validating HCC dataset. To test whether our findings were relevant regardless of HCC etiology, the testing (62 HCC) and validating (80 HCC) sets included tumours from patients of two ethnic groups (Asian and Caucasian, respectively) as described previously². Gene expression profiling experiments using these samples were approved from the respective Institutional Review Board, as described previously². Following standardization, clustering analysis of the integrated datasets was performed by using the Cluster 3.0 software with uncentered correlation and average linkage options. Data were further visualized with Tree View 1.6. Results

The hypothesis was that a gene signature reflecting the capacity of tumour cells to escape senescence would be relevant for HCC prognosis.

To test this hypothesis, a unique model of replicative senescence induction in Huh7 HCC cells was used. From this cell line, clones reprogrammed for replicative senescence were generated and immortal clones¹⁰ were used. Reprogrammed and immortal clones displayed similar proliferation profiles at early passages. However, reprogrammed clones entered a state of senescence arrest characterized by flat morphology, shortened telomeres, senescence- associated β-galactosidase activity, and permanent arrest of DNA synthesis at about 90 population doublings. In contrast, immortal cells maintained stable telomere lengths and proliferative capacity for at least 150 population doublings¹⁰. These two types of clones were profiled to identify genes associated with hepatocellular senescence and immortality. By applying stringent selection criteria (P<0.001 and 2-fold change), 1,498 probes were found to be differentially expressed (Fig. la). Accordingly, the expression of the corresponding 1,017 non-redundant genes clearly discriminated immortal from senescent cells by hierarchical clustering (Fig.lb). Senescent-associated genes were involved in telomere maintenance and p53 signalling whereas immortal-associated genes were enriched in E2F1 targets and INK4A locus inhibitors. As example, senescence-associated genes included master effectors of apoptosis (e.g. BIK, PERP) and cyclin-dependent kinase inhibitors (e.g. CDKNlA/p21) and immortal-associated genes included plethora of cell cycling and DNA repair genes (e.g. BRCAl, EXOl, TOP3A) consistent with a sustained proliferation. Next, the inventors tested whether senescent-associated genes were relevant to discriminate HCC subtypes. For this purpose, they applied an integrative genomics approach using HCC datasets for which gene expression profiles and clinical data were available^2"5'¹¹. To improve data accuracy and to determine whether our findings were relevant regardless of patient ethnicity, HCC were divided into testing (n=62) and validating sets (n=80), which included tumours from Chinese and American/European patients, respectively². To further increase the specificity of the analysis, the inventors selected from the senescence-associated genes (n=l,017) that were detected in more than 50% HCCs. Based on the expression of the resulting 643 genes, hierarchical clustering of the integrated dataset identified two clusters, both in the testing and the validating datasets (Fig. lc). Remarkably, senescence-associated gene profiles non- randomly segregated HCC into distinct clusters, allowing them to classify as immortal-type and senescent-type HCCs. Immortal-type HCC included tumours from previously defined A- type patients exhibiting an unfavourable prognosis, while senescent-type HCC recapitulated tumours from previously defined B-group patients with a better prognosis¹¹ (Fig. lc). Furthermore, immortal-type HCC coincided with tumours from patients with the worse prognosis that were identified previously using a hepatoblast (HB) gene expression signature representing hepatic progenitors¹¹ (Fig. lc). Then, the inventors selected genes whose expression in HCC was significantly associated with patient survival (P<0.05, log-rank test). In order to optimize the accuracy of the gene selection, they retained from the survival- associated genes only those whose expression patterns correlated with immortality/bad prognosis and senescence/good prognosis model. This strategy resulted in the selection of five immortality- associated genes over-expressed in HCC from patients with a bad prognosis, and 18 senescence-associated genes over-expressed in HCC from patients with a good prognosis (Fig. Id;). Those gene are listed in table 1 :

Table 1: List of 23 senescence-and immortality-associated survival genes in hepatocellular carcinoma

Immortal vs. senescent cells Hepatocellular carcinoma survival analysis

Gene description Exp. Ratio* P FDR Hazard Ratio log-rank P P FDR

Genes over-expressed in immortal cellsand bad prognosis tumors

10 SEMA6B 3.36 0.0001 0.0015 3.8150.0040 0.0005 0.0109

EXOSC9 2.40 <0.0001 0.0009 3.591<0.0001 0.0003 0.0073

MLF1IP 2.37 0.0002 0.0024 2.118 0.0130 0.0001 0.0042

DSN1 2.25 <0.0001 0.0007 13.727 <0.0001 <0.0001 0.0010

BUB3 2.05 0.0004 0.0036 2.407 0.0120 0.0009 0.0146

1 J

Genes over-expressed in senescent cells and good prognosis tumors

TMCC1 -2.00 <0.0001 0.0001 0.233 <0.0001 0.0002 0.0061

PINK1 -2.04 0.0010 0.0070 0.414 <0.0001 0.0001 0.0036

20 RAB43 -2.08 0.0001 0.0016 0.333 <0.0001 0.0004 0.0098

TPP1 -2.13 0.0003 0.0033 0.419 0.0020 0.0006 0.0113

ATP6V1A -2.13 <0.0001 0.0001 0.159 0.0320 <0.0001 0.0025

STARD10 -2.17 0.0003 0.0033 0.611 <0.0001 <0.0001 0.0025

C4BPB -2.22 0.0003 0.0032 0.722 0.0010 0.0002 0.0061

25 AMDHD1 -2.22 0.0005 0.0047 0.686 0.0410 0.0009 0.0144

DPP4 -2.27 0.0001 0.0013 0.642 0.0240 0.0009 0.0144

SMPD1 -2.38 0.0002 0.0023 0.400 0.0310 0.0001 0.0042

IL6R -2.50 <0.0001 0.0004 0.541 0.0300 <0.0001 0.0025

PCSK6 -2.50 0.0002 0.0024 0.577 <0.0001 <0.0001 0.0029

30 EPHX1 -2.56 0.0007 0.0057 0.726 0.0040 <0.0001 0.0025

TMEM140 -3.33 <0.0001 0.0008 0.366 <0.0001 0.0001 0.0049

CAND2 -5.26 <0.0001 0.0002 0.412 0.0070 0.0002 0.0057

UGT2B4 -9.09 <0.0001 0.0007 0.724 <0.0001 <0.0001 0.0024

AKR1C1 -12.50 <0.0001 0.0001 0.739 0.0080 0.0002 0.0057

35 BAAT -20.00 <0.0001 <0.0001 0.727 0.0010 0.0002 0.0059

*Exp. ratio: Immortal/senescent phenotype expression ratio; FDR: False-discovery rate

This minimal 23-gene signature was used to perform integrative genomics using HCC gene profiles from the testing and validating sets (Fig. le). Hierarchical clustering of the integrated datasets based solely on the expression of the 23 genes (Fig. le) recapitulated our findings obtained with the initial 643-gene signature (Fig. lc). More importantly, Kaplan-Meier plots and log-rank statistics demonstrated a significant difference (P<0.001) in the 5-year overall survival between the two groups of patients defined by the 23-gene signature. As expected, immortal-type and senescence-type HCCs were associated with bad and good patient survivals, respectively (Fig. If). Senescence-based classification of HCC was independent of patient gender, etiology, serum alpha-fetoprotein levels, underlying liver disease and tumour size. The results as summarised in table 2.

Table 2: Clinical and biological features of Immortal- and Senescent-type HCC

In conclusion, the inventors established a 23-gene senescence signature that efficiently predicts HCC prognosis and patient survival. Due to its small size, this signature is easy to implement in clinical setting. It can be readily adapted for HCC management as well as patient allocation in clinical trials with new drugs.

REFERENCES

Throughout this application, various references describe the state of the art to which the invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

1. El-Serag, H.B. & Rudolph, K.L. Gastroenterology 132, 2557-2576 (2007).

2. Lee, J.S. et al. Nat. Med. 12, 410-416 (2006).

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4. Coulouarn, C, Factor, V.M. & Thorgeirsson, S.S. Hepatology 47, 2059-67 (2008).

5. Coulouarn, C. et al. Cancer Res. 72, 2533-2542 (2012).

6. Collado, M. & Serrano, M. Nat. Rev. Cancer 10, 51-57 (2010).

7. Mooi, W.J. & Peeper, D.S. N. Engl. J. Med. 355, 1037-1046 (2006).

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11. Lee, J.S. et al. Hepatology 40, 667-676 (2004).

Claims

1. Method for evaluating the vital prognosis of a subject suffering or suspected to suffer from hepatocellular carcinoma, said method comprising the step a) of:

wherein

an overexpression of at least one gene selected in the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, and BUB3 is associated with a negative vital prognosis; an overexpression of at least one gene selected in the group consisting of TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT is associated with a positive vital prognosis.

2. The method according to claim 1, wherein said biological sample is liver tissue, more preferably hepatocellular carcinoma tissue.

3. The method according to claim 1 or 2, wherein step a) of measuring the level of expression of said gene(s) is a step of measuring the expression level of translation products of said gene(s), preferably proteins.

4. The method according to of claim 1 or 2, wherein said step a) of measuring the level of expression of said gene(s) is a step of measuring the expression level of transcription product of said gene(s), preferably mRNA.

5. The method according to claim 4, wherein the step a) of measuring the level of expression is a step of DNA microarray.

6. The method according to any one of claims 1 to 5, wherein said method further comprises a step b) of determining the expression profile(s) of said gene(s).

7. The method according to claim 6, wherein said method further comprises a step c) of comparing the expression profile(s) obtained in step b) to a threshold value.

8. The method according to claim 6, wherein said method further comprises a step c') of comparing the expression profile(s) obtained in step b) with the expression profile(s) of at least one control chosen in the group consisting of a positive control and a negative control.

9. The method according to claim 8, wherein said positive control is the expression profile of a subject suffering from hepatocellular carcinoma or a subject who died from hepatocellular carcinoma.

10. The method according to claim 8, wherein said negative control is the expression profile of a healthy subject or a subject who overcame hepatocellular carcinoma.

11. A method for:

wherein said method comprises measuring the level of expression of the genes SEMA6B, EXOSC9, MLF1IP, DSN1, BUB 3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARD10, C4BPB, AMDHD1, DPP4, SMPD1, IL6R, PCSK6, EPHX1, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT in a biological sample of said subject.

12. A kit:

(a) for predicting clinical outcome of a subject suffering from hepatocellular carcinoma, and/or (b) for selecting a subject affected with a hepatocellular carcinoma for a therapy or determining whether a subject affected with a hepatocellular carcinoma is susceptible to benefit from a therapy; wherein the kit comprises: (i) at least one antibody specific to a protein encoded by a gene selected from the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARDIO, C4BPB, AMDHDl, DPP4, SMPDl, IL6R, PCSK6, EPHXl, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT ; and/or

(ii) at least one probe specific to the mRNA, cDNA or genomic DNA of a gene selected from the group consisting of SEMA6B, EXOSC9, MLF1IP, DSN1, BUB3, TMCC1, PINK1, RAB43, TPP1, ATP6V1A, STARDIO, C4BPB, AMDHDl, DPP4, SMPDl, IL6R, PCSK6, EPHXl, TMEM140, CAND2, UGT2B4, AKR1C1, and BAAT; and/or

(iii) at least one nucleic acid primer pair specific to said genomic DNA, mRNA or cDNA; and

(iv) optionally, a leaflet providing guidelines to use such a kit.