Deep sequencing and pathway-focused analysis revealed multigene oncodriver signatures predicting survival outcomes in advanced colorectal cancer

Oncogenesis
Francesca De NicolaMarcello Maugeri-Saccà

Abstract

Genomic technologies are reshaping the molecular landscape of colorectal cancer (CRC), revealing that oncogenic driver mutations (APC and TP53) coexist with still underappreciated genetic events. We hypothesized that mutational analysis of CRC-linked genes may provide novel information on the connection between genetically-deregulated pathways and clinical outcomes. We performed next-generation sequencing (NGS) analysis of 16 recurrently mutated genes in CRC exploiting tissue specimens from 98 advanced CRC patients. Multiple correspondence analysis (MCA) was used to identify gene sets characterizing negative and positive outliers (patients in the lowest and highest quartile of progression-free survival, PFS). Variables potentially affecting PFS and overall survival (OS) were tested in univariate and multivariate Cox proportional hazard models. Sensitivity analyses and resampling were used to assess the robustness of genomic predictors. MCA revealed that APC and TP53 mutations were close to the negative outlier group, whereas mutations in other WNT pathway genes were in proximity of the positive outliers. Reasoning that genetic alterations interact epistatically, producing greater or weaker consequences in combination than when ...Continue Reading

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Citations

Dec 31, 2020·Clinical and Translational Medicine·Frauke GoemanMarcello Maugeri-Saccà

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Software Mentioned

MCA
DesignStudio
SPSS
OncoDriver
Illumina BaseSpace Cloud environment
Truseq Amplicon analysis
OncoKB
Mutation Assessor
Illumina Variant Studio

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