G protein-coupled receptors (GPCRs) form the most frequently exploited drug target family, moreover they are often found mutated in cancer. Here we used an aggregated dataset of mutations found in cancer patient samples derived from the Genomic Data Commons and compared it to the natural human variance as exemplified by data from the 1000 Genomes project. While the location of these mutations across the protein domains did not differ significantly in the two datasets, a mutation enrichment was observed in cancer patients among conserved residues in GPCRs such as the 'DRY' motif. We subsequently created a ranking of high scoring GPCRs, using a multi-objective approach (Pareto Front Ranking). The validity of our approach was confirmed by re-discovery of established cancer targets such as the LPA and mGlu receptor families, and we identified novel GPCRs that had not been directly linked to cancer before such as the P2Y Receptor 10 (P2RY10). As a proof of concept, we projected the structurally investigated mutations in the crystal structure of the C-C Chemokine (CCR) 5 receptor, one of the high-ranking GPCRs previously linked to cancer. Several positions were pinpointed that relate to either structural integrity or endogenous and synthetic ligand binding, providing a rationale to their mechanism of influence in cancer. In conclusion, this study identifies a list of GPCRs that are prioritized for experimental follow up characterization to elucidate their role in cancer. The computational approach here described can be adapted to investigate the roles in cancer of any protein family.
G Protein-coupled receptors (GPCRs) are the most frequently exploited drug target family, moreover they are often found mutated in cancer. Here we used a dataset of mutations found in patient samples derived from the Genomic Data Commons and compared it to the natural human variance as exemplified by data from the 1000 genomes project. We explored cancer-related mutation patterns in all GPCR classes combined and individually. While the location of the mutations across the protein domains did not differ significantly in the two datasets, a mutation enrichment in cancer patients was observed among class-specific conserved motifs in GPCRs such as the Class A “DRY” motif. A Two-Entropy Analysis confirmed the correlation between residue conservation and cancer-related mutation frequency. We subsequently created a ranking of high scoring GPCRs, using a multi-objective approach (Pareto Front Ranking). Our approach was confirmed by re-discovery of established cancer targets such as the LPA and mGlu receptor families, but also discovered novel GPCRs which had not been linked to cancer before such as the P2Y Receptor 10 (P2RY10). Overall, this study presents a list of GPCRs that are amenable to experimental follow up to elucidate their role in cancer.
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