Mapping in silico genetic networks of tumour suppressor gene to uncover novel functional associations and cancer cell vulnerabilities

Cancers harbouring loss-of-function (LOF) alterations in tumour suppressor genes lack targeted therapies, thus alternative means to characterise gene function and identify vulnerabilities in these cancer cells are required. Here, we map the in silico genetic networks of KMT2D, a frequently mutated tumour suppressor gene, to demonstrate its utility in uncovering novel functional associations and vulnerabilities in cancer cells with tumour suppressor gene LOF alterations. In silico KMT2D networks revealed associated with histone modification, DNA replication, metabolism, and immune response. We identified synthetic lethal (SL) candidates encoding exising therapeutic targets. Analysing patient data from The Cancer Genome Atlas (TCGA) and the Personalized OncoGenomics Project (NCT021556210), we showed dysregulated pathways associated with SL candidates and elevated immune checkpoint response markers in KMT2DLOF cases, bringing forth evidence supporting KMT2D as a biomarker for immune checkpoint inhibitors. Our study presents a framework for identifying targetable vulnerabilities in cancers with tumour suppressor gene alterations.