Characterizing therapeutic signatures of transcription factors in cancer by incorporating profiles in compound treated cells.

Abstract

Cancers are promoted by abnormal alterations in biological processes, such as cell cycle and apoptosis. An immediate reason for those aberrant processes is the deregulation of their involved transcription factors (TFs). Thus, the deregulated TFs in cancer have been experimented as successful therapeutic targets, such as RARA and RUNX1. This therapeutic strategy can be accelerated by characterizing new potential TF targets. Two kinds of therapeutic signatures of TFs in A375 (skin) and HT29 (colon) cancer cells were characterized by analyzing TF activities under effective and ineffective compounds to cancer. First, the therapeutic TFs (TTs) were identified as the TFs that are significantly activated or repressed under effective compared to ineffective compounds. Second, the therapeutically correlated TF pairs (TCPs) were determined as the TF pairs whose activity correlations show substantial discrepancy between the effective and ineffective compounds. It was facilitated by incorporating (i)compound-induced gene expressions (LINCS), (ii) compound-induced cell viabilities (GDSC) and (iii) TF-target interactions (TRUST2). As a result, among 627 TFs, the 35 TTs (such as MYCN and TP53) and the 214 TCPs (such as FOXO3 and POU2F2 pair) were identified. The TTs and the proteins on the paths between TCPs were compared with the known therapeutic targets, tumor suppressors, oncogenes and CRISPR-Cas9 knockout screening, which yielded significant consequences. We expect that the results provide good candidates for therapeutic TF targets in cancer. The data and Python implementations are available at https://github.com/jmjung83/TT_and_TCP. Supplementary data are available at Bioinformatics online.