Tailoring treatment in lung cancer


Session type:

Jean-Charles Soria1
1Institut Gustave Roussy, Villejuif, France


The possibility to predict clinical efficacy of anti-cancer therapies according to the biological profile of each patient is a major challenge in modern medicine. Discovering new therapeutic targets or prognostic biomarkers associated to therapeutic response for lung cancer is drawing increasing attention and one of the major areas is molecular testing.

To date, the “quest” for the perfect predictive molecular marker has been mainly based on retrospective databases with 2 types of technology: (1) High throughput technology and (2) single biomarker approach. Large scale studies also reveal a substantial genomic heterogeneity across cancer genomes, implicating a few hundreds cancer genes, including many protein kinases, that undergo mutation and seem to be causally implicated in oncogenesis. Such lung cancer studies have identified frequent mutation mainly in TP53, RB1, CDKN2A, and STK11 tumour suppressor and in EGFR, KRAS and NRAS oncogenes. Many other molecular abnormalities have been reported at lower frequencies in genes such as PI3K, PTEN, AKT1, MDM2, APC, FGFR, HER2, KDR, MET, CTNNB1, ATM, BRAF, AKT1… However thecorrelation of presence of such abnormalities and clinical responses are still not firmly documented. Recently thepresence of a translocation of the EML4 and ALK genes, a kinase domain receptor, have been described in a small portion of patients corresponding to 5% of adenocarcinomas. This mutation is mutually exclusive with EGFR mutation and is associated to a high rate of response to ALK receptor kinase inhibitors in early phase of clinical development. Thus this somatic genetic change represents a new biomarker to select a subgroup of patients with lung cancer for a specific treatment. Most disappointing, there are no validated predictive markers in the ‘antiangiogenic setting’.