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Dettaglio pubblicazione

2020, FRONTIERS IN ONCOLOGY, Pages - (volume: 10)

Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer (01a Articolo in rivista)

Belardinilli Francesca, Capalbo Carlo, Malapelle Umberto, Pisapia Pasquale, Raimondo Domenico, Milanetti Edoardo, Mahdavian Yasaman, Liccardi Carlotta, Paci Paola, Sibilio Pasquale, Pepe Francesco, Bonfiglio Caterina, Mezi Silvia, Magri Valentina, Coppa Anna, Nicolussi Arianna, Gradilone Angela, Petroni Marialaura, Di Giulio Stefano, Fabretti Francesca, Infante Paola, Coni Sonia, Canettieri Gianluca, Troncone Giancarlo, Giannini Giuseppe

Extensive molecular characterization of human colorectal cancer (CRC) via Next Generation Sequencing (NGS) indicated that genetic or epigenetic dysregulation of a relevant, but limited, number of molecular pathways typically occurs in this tumor. The molecular picture of the disease is significantly complicated by the frequent occurrence of individually rare genetic aberrations, which expand tumor heterogeneity. Inter- and intratumor molecular heterogeneity is very likely responsible for the remarkable individual variability in the response to conventional and target-driven first-line therapies, in metastatic CRC (mCRC) patients, whose median overall survival remains unsatisfactory. Implementation of an extensive molecular characterization of mCRC in the clinical routine does not yet appear feasible on a large scale, while multigene panel sequencing of most commonly mutated oncogene/oncosuppressor hotspots is more easily achievable. Here, we report that clinical multigene panel sequencing performed for anti-EGFR therapy predictive purposes in 639 formalin-fixed paraffin-embedded (FFPE) mCRC specimens revealed previously unknown pairwise mutation associations and a high proportion of cases carrying actionable gene mutations. Most importantly, a simple principal component analysis directed the delineation of a new molecular stratification of mCRC patients in eight groups characterized by non-random, specific mutational association patterns (MAPs), aggregating samples with similar biology. These data were validated on a The Cancer Genome Atlas (TCGA) CRC dataset. The proposed stratification may provide great opportunities to direct more informed therapeutic decisions in the majority of mCRC cases.
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