BACKGROUND: The diagnosis of colorectal cancer (CRC) is routinely accomplished through histopathologic examination. Prognostic information and treatment decisions are mainly determined by TNM classification, first defined in 1968. In the last decade, patient-specific CRC genomic landscapes were shown to provide important prognostic and predictive information. Therefore, there is a need for developing next generation sequencing (NGS) and bioinformatic workflows that can be routinely used for the assessment of prognostic and predictive biomarkers. MATERIALS AND METHODS: To foster the application of genomics in the clinical management of CRCs, the IDEA workflow has been built to easily adapt to the availability of patient specimens and the clinical question that is being asked. Initially, IDEA deploys ad-hoc NGS assays to interrogate predefined genomic target sequences (from 600 kb to 30 Mb) with optimal detection sensitivity. Next, sequencing data are processed through an integrated bioinformatic pipeline to assess single nucleotide variants, insertions and deletions, gene copy-number alterations, and chromosomal rearrangements. The overall results are gathered into a user-friendly report. RESULTS: We provide evidence that IDEA is capable of identifying clinically relevant molecular alterations. When optimized to analyze circulating tumor DNA, IDEA can be used to monitor response and relapse in the blood of patients with metastatic CRC receiving targeted agents. IDEA detected primary and secondary resistance mechanisms to ERBB2 blockade including sub-clonal RAS and BRAF mutations. CONCLUSIONS: The IDEA workflow provides a flexible platform to integrate NGS and bioinformatic tools for refined diagnosis and management of patients with advanced CRC.

A Genomic Analysis Workflow for Colorectal Cancer Precision Oncology / G. Corti, A. Bartolini, G. Crisafulli, L. Novara, G. Rospo, M. Montone, C. Negrino, B. Mussolin, M. Buscarino, C. Isella, L. Barault, G. Siravegna, S. Siena, S. Marsoni, F. Di Nicolantonio, E. Medico, A. Bardelli. - In: CLINICAL COLORECTAL CANCER. - ISSN 1533-0028. - (2019 Mar 07). [Epub ahead of print] [10.1016/j.clcc.2019.02.008]

A Genomic Analysis Workflow for Colorectal Cancer Precision Oncology

S. Siena;
2019

Abstract

BACKGROUND: The diagnosis of colorectal cancer (CRC) is routinely accomplished through histopathologic examination. Prognostic information and treatment decisions are mainly determined by TNM classification, first defined in 1968. In the last decade, patient-specific CRC genomic landscapes were shown to provide important prognostic and predictive information. Therefore, there is a need for developing next generation sequencing (NGS) and bioinformatic workflows that can be routinely used for the assessment of prognostic and predictive biomarkers. MATERIALS AND METHODS: To foster the application of genomics in the clinical management of CRCs, the IDEA workflow has been built to easily adapt to the availability of patient specimens and the clinical question that is being asked. Initially, IDEA deploys ad-hoc NGS assays to interrogate predefined genomic target sequences (from 600 kb to 30 Mb) with optimal detection sensitivity. Next, sequencing data are processed through an integrated bioinformatic pipeline to assess single nucleotide variants, insertions and deletions, gene copy-number alterations, and chromosomal rearrangements. The overall results are gathered into a user-friendly report. RESULTS: We provide evidence that IDEA is capable of identifying clinically relevant molecular alterations. When optimized to analyze circulating tumor DNA, IDEA can be used to monitor response and relapse in the blood of patients with metastatic CRC receiving targeted agents. IDEA detected primary and secondary resistance mechanisms to ERBB2 blockade including sub-clonal RAS and BRAF mutations. CONCLUSIONS: The IDEA workflow provides a flexible platform to integrate NGS and bioinformatic tools for refined diagnosis and management of patients with advanced CRC.
Bioinformatics; Colorectal cancer; Genetic alterations; IDEA; Next generation sequencing
Settore MED/06 - Oncologia Medica
7-mar-2019
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/638973
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