Institut National De La Sante Et De La Recherche Medicale

Centre National De La Recherche Scientifique

Institut Pasteur

Assistance Publique-hopitaux De Paris

Sorbonne Université

Universite De Tours

Centre Hospitalier Régional Universitaire De Tours

Ctre Recherche Pathologies Prostatiques

Ligue Nationale Contre Le Cancer

Aurélien De Reynies

Olivier Cussenot

David S Rickman

Marie-Annick Buendia

Carolina Armengol Niell

Stefano Cairo

Jessica Zucman-Rossi

Sandrine Boyault

Aurélie Kamoun

Géraldine Cancel-tassin

Gaëlle Fromont-hankard

David Rickman

A method for predicting the risk of prostate cancer recurrence in a subject affected with prostate cancer, including: (a) providing a sample from the subject, (b) determining the TMPRSS/ERG fusion status of the sample, (c) if the sample is positive for TMPRSS/ERG fusion (Fus), determining a molecular signature of the sample by measuring the expression level of at least 6 prostate cancer markers selected from the ANPEP, AZGP1, CHRNA2, COMP, KHDRBS3 and SFRP4, (d) comparing the molecular signature to a reference signature, and (e) assigning the subject to a risk group based on the correlation of the molecular signature with the reference signature, thereby predicting the risk of cancer recurrence in the subject.

Molecular signature and use thereof for the identification of indolent prostate cancer

The present invention concerns a method to determine the gene expression profile on a sample previously obtained from a patient diagnosed for a liver tumor, comprising assaying the expression of a set of genes in this sample and determining the gene expression profile (signature). In a particular embodiment, said method enables to determine the grade of the liver tumor, such as hepatoblastoma (HB) or a hepatocellular carcinoma (HCC). The invention is also directed to kits comprising a plurality of pairs of primers or a plurality of probes specific for a set of genes, as well as to solid support or composition comprising a set of probes specific for a set of genes. These methods are useful to determine the grade of a liver tumor in a sample obtained from a patient, to determine the risk of developing metastasis and/or to define the therapeutic regimen to apply to a patient.

Molecular signature of liver tumor grade and use to evaluate prognosis and therapeutic regimen

Methodology for the in vitro classification and/or prognosis of hepatocellular carcinoma (HCC) from a HCC sample is based on the determination of the expression profile of particular gene combinations. For example, in one embodiment, a method comprises measuring the expression level in an HCC sample of at least 8 genes selected from the group consisting of: RAB1A, REG3A, NRAS, RAMP3, MERTK, PIR, EPHA1, LAMA3, G0S2, HN1, PAK2, AFP, CYP2C9, CDH2, HAMP, SAE1, ADH6, DCN, FLJ10159, ALDH1L1, IGF1, LECT2, SLC38A1, SPARCL1, CTNNA2, GLUL, LEF1, MATN2, MME, PFN2, SPINT2, TBX3, and FGFR2; b) calculating 6 subgroup distances from the expression profile; and c) classifying the HCC tumor in the subgroup for which the subgroup distance is the lowest, wherein the 6 subgroups G1, G2, G3, G4, G5, and G6 are defined by the presence (+) or absence (&#x2212;) of their clinical and genetic features.

Method of hepatocellular carcinoma classification and prognosis

Growing community of inventors

Paris, France

Aurélien De Reynies