COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

Colonomics is a multi-omics dataset that includes 250 samples: 50 samples from healthy colon mucosa donors and 100 paired samples from colon cancer patients (tumor/adjacent). From these samples, Colonomics project includes data from genotyping, DNA methylation, gene expression, whole exome sequencing and micro-RNAs (miRNAs) expression. It also includes data from copy number variation (CNV) from tumoral samples. In addition, clinical data from all these samples is available. The aims of the project were to explore and integrate these datasets to describe colon cancer at molecular level and to compare normal and tumoral tissues. Also, to improve screening by finding biomarkers for the diagnosis and prognosis of colon cancer. This project has its own website including four browsers allowing users to explore Colonomics datasets. Since generated data could be reuse for the scientific community for exploratory or validation purposes, here we describe omics datasets included in the Colonomics project as well as results from multi-omics layers integration

ICO amplicon NGS data analysis: a web tool for variant detection in common high-risk hereditary cancer genes analyzed by amplicon GS junior next-Generation Sequencing

Next-generation sequencing (NGS) has revolutionized genomic research and is set to have a major impact on genetic diagnostics thanks to the advent of benchtop sequencers and flexible kits for targeted libraries. Among the main hurdles in NGS are the difficulty of performing bioinformatic analysis of the huge volume of data generated and the high number of false positive calls that could be obtained, depending on the NGS technology and the analysis pipeline. Here, we present the development of a free and user-friendly Web data analysis tool that detects and filters sequence variants, provides coverage information, and allows the user to customize some basic parameters. The tool has been developed to provide accurate genetic analysis of targeted sequencing of common high-risk hereditary cancer genes using amplicon libraries run in a GS Junior System. The Web resource is linked to our own mutation database, to assist in the clinical classification of identified variants. We believe that this tool will greatly facilitate the use of the NGS approach in routine laboratories.Peer ReviewedPostprint (published version

ICO amplicon NGS data analysis: a web tool for variant detection in common high-risk hereditary cancer genes analyzed by amplicon GS junior next-Generation Sequencing

Next-generation sequencing (NGS) has revolutionized genomic research and is set to have a major impact on genetic diagnostics thanks to the advent of benchtop sequencers and flexible kits for targeted libraries. Among the main hurdles in NGS are the difficulty of performing bioinformatic analysis of the huge volume of data generated and the high number of false positive calls that could be obtained, depending on the NGS technology and the analysis pipeline. Here, we present the development of a free and user-friendly Web data analysis tool that detects and filters sequence variants, provides coverage information, and allows the user to customize some basic parameters. The tool has been developed to provide accurate genetic analysis of targeted sequencing of common high-risk hereditary cancer genes using amplicon libraries run in a GS Junior System. The Web resource is linked to our own mutation database, to assist in the clinical classification of identified variants. We believe that this tool will greatly facilitate the use of the NGS approach in routine laboratories.Peer Reviewe

Optimization of RAS/BRAF Mutational Analysis Confirms Improvement in Patient Selection for Clinical Benefit to Anti-EGFR Treatment in Metastatic Colorectal Cancer.

In metastatic colorectal cancer (mCRC), recent studies have shown the importance to accurately quantify low-abundance mutations of the RAS pathway because anti-EGFR therapy may depend on certain mutation thresholds. We aimed to evaluate the added predictive value of an extended RAS panel testing using two commercial assays and a highly sensitive and quantitative digital PCR (dPCR). Tumor samples from 583 mCRC patients treated with anti-EGFR- (n = 255) or bevacizumab- (n = 328) based therapies from several clinical trials and retrospective series from the TTD/RTICC Spanish network were analyzed by cobas, therascreen, and dPCR. We evaluated concordance between techniques using the Cohen kappa index. Response rate, progression-free survival (PFS), and overall survival (OS) were correlated to the mutational status and the mutant allele fraction (MAF). Concordance between techniques was high when analyzing RAS and BRAF (Cohen kappa index around 0.75). We observed an inverse correlation between MAF and response in the anti-EGFR cohort (