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Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer

Authors :
Francesca Belardinilli
Carlo Capalbo
Umberto Malapelle
Pasquale Pisapia
Domenico Raimondo
Edoardo Milanetti
Mahdavian Yasaman
Carlotta Liccardi
Paola Paci
Pasquale Sibilio
Francesco Pepe
Caterina Bonfiglio
Silvia Mezi
Valentina Magri
Anna Coppa
Arianna Nicolussi
Angela Gradilone
Marialaura Petroni
Stefano Di Giulio
Francesca Fabretti
Paola Infante
Sonia Coni
Gianluca Canettieri
Giancarlo Troncone
Giuseppe Giannini
Source :
Frontiers in Oncology, Vol 10 (2020)
Publication Year :
2020
Publisher :
Frontiers Media S.A., 2020.

Abstract

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.

Details

Language :
English
ISSN :
2234943X
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.0b3984ae08894e55827693487456c527
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2020.00560