Multi-Omic Analysis of CIC’s Functional Networks Reveals Novel Interaction Partners and a Potential Role in Mitotic Fidelity

Abstract

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CIC’s interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, as well as novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines, predominantly at 3′ and 5′ untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CIC’s functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CIC’s potential roles in cancer. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts.

Mappingin silicogenetic networks of theKMT2Dtumour suppressor gene to uncover novel functional associations and cancer cell vulnerabilities

“…For the pan-cancer dataset and each of the nine cancer type-specific datasets, we used GRETTA 6,15 to identify KMT2D LOF and KMT2D WT DepMap cancer cell lines (Supplemental Figure 1A; Supplementary Table S3A; Methods). Next, we compared the KMT2D mRNA and protein expression between the KMT2D WT and KMT2D LOF cell lines within each dataset.…”

“…The microsatellite status of DepMap cell lines was identified from supplementary files provided by Ghandi et al 43 . As performed previously 6,15 , we used GRETTA to query the genomic data (MAF and copy number data files) to identify KMT2D LOF and WRN LOF mutant cancer cell lines (homozygous, trans-heterozygous, and heterozygous LOF mutants) and KMT2D WT and WRN WT control cell lines. Only trans-heterozygous lines (lines with more than one LOF mutation or a combination of LOF mutation and copy number loss) and heterozygous lines were available for the KMT2D pan-cancer group.…”

“…As described previously 6,15 , we used GRETTA to perform pairwise Mann-Whitney U tests comparing lethality probabilities for all 18,333 genes targeted in DepMap’s CRISPR-Cas9 KO screen between LOF mutant lines and WT lines to obtain p-values. P-values were adjusted for multiple testing using a permutation approach by randomly resampling 10,000 of the lethality probability scores.…”

“…The functional inadequacy or complete lack of mutated tumour suppressor gene protein renders most inhibitory drugs illogical in contrast to therapies targeting oncogenic proteins 1 . Genetic networks, namely essentiality networks 2–6 and genetic interaction (GI) networks 7–9 , provide a powerful means to map and interrogate functional interaction landscapes and to identify vulnerabilities of cells harbouring LOF alterations in tumour suppressor genes. Briefly, essentiality networks include co-essential and anti-essential genes, where the perturbation of two genes has similar (synergistic) or opposing (antagonistic) effects on cell survival across various cell lines, respectively 2,4,5 .…”

“…GI networks include synthetic lethal (SL) and alleviating (AL) interactors, where the perturbation of two genes together in the same cell confers reduced or advantageous fitness effects, respectively, but the perturbation of either gene alone does not affect cell fitness 7 . Genetic network analyses have revealed novel functional relationships between genes, pathways, and cancer cell vulnerabilities 2–6,8,9 . Even so, mapping genetic networks at scale using in vitro screening techniques remains a challenge 10,11 .…”