Integration of genomic data analysis for demonstrating potential targets in the subgroup populations of squamous cell lung cancer patients

Abstract

Squamous cell carcinoma (SCC) is the second most frequent histologic subtype of non-small cell lung cancer (NSCLC), causing approximately 400, 000 deaths per year worldwide. Although targeted therapies have improved outcomes in patients with adenocarcinoma, the most common subtype of NSCLC, the genomic alterations in SCC have not been comprehensively characterized and no therapeutic agents have been approved specifically for the patients with SCC. Therefore, development of novel therapeutic approaches is urgently needed. Here, we developed an integrative approach, called DLSA, to integrate genomic, epigenomic and transcriptomic data. DLSA stratified SCC patients into distinct survival subgroups and identified the potential molecular drivers in individual survival subtypes. Three subgroups of SCC patients with diverse molecular and clinical characteristics were unveiled through DLSA. Combined analysis of clinical and molecular data on those subgroups suggested that the molecular features in the stratified subgroups are not only consistent with the previous findings, but also provide a guide to targeted agents that worth to be evaluated in clinical trials for SCC patients with poor survival. In conclusion, DLSA offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.