Translating bioinformatics in oncology: Guilty by profiling meta-analysis and identification of KIF18B and CDCA3 as novel driver genes in liver carcinogenesis

Gene expression profiling studies in cancer research have traditionally investigated relevant transcriptomics changes from single patient cohorts. However, co-regulated genes are not identified in such analyses but may theoretically be closely functionally linked (guilt by association, guilt by profiling). Although bioinformatics procedures for guilt by profiling/association analyzes were previously reported, this comprehensive approach has not been applied to large scale cancer biology yet. Here, we analyzed the complete GSE2109 data repository of 2158 full cancer transcriptomes from 163 diverse cancer entities…