Functional variomics and network perturbation: connecting genotype to phenotype in cancer

Abstract

Proteins interact with other macromolecules in complex cellular networks for signal transduction and biological function. In cancer, genetic aberrations have been traditionally thought to disrupt the entire gene function. It has been increasingly appreciated that each mutation of a gene could have a subtle but unique effect on protein function or network rewiring, contributing to diverse phenotypic consequences across cancer patient populations. In this Review, we discuss the current understanding of cancer genetic variants including the broad spectrum of mutation classes and the wide range of mechanistic effects on gene function in the context of signaling networks. We highlight recent advances in computational and experimental strategies to study the diverse functional and phenotypic consequences of mutations at the base-pair resolution. Such information is critical for understanding the complex pleiotropic effect of cancer genes, and provides a possible link between genotype and phenotype in cancer.

MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology

“…In principle, somatic mutations may disrupt the overall structure of the corresponding protein, or alternatively exert specific effects on particular molecular interactions . To evaluate whether and how cancer mutations affect the binding of RBPs to their targets, we systematically explored the localization of somatic mutations on the three‐dimensional protein structures of RBPs.…”

“…Most previous studies modeled genotype–phenotype relationships based on the assumption that driver mutations lead to complete loss of protein function through radical changes, such as protein instability or misfolding. However, it has been increasingly appreciated that many driver mutations could act to perturb molecular interactions important for cellular functions . We previously reported that a considerable fraction of driver disease mutations caused protein–protein interaction‐specific or “edgetic” perturbations .…”

Mapping a diversity of genetic interactions in yeast

“…Analysis of the genetic determinants of cancer and other diseases, clearly shows that gene loss-of-function and gene amplification or gain-of-function are equally important determinants of disease progression [16–18]. Several different genome-wide reagent sets are available for the systematic analysis of genetic interactions involving overexpression alleles in yeast.…”

Regulome networks and mutational landscape in liver cancer: An informative path to precision medicine

“…However, few noncoding cancer‐associated mutations have been studied as of date. TFs often bind to noncoding regulatory DNAs to mediate transcription, therefore protein–DNA assays such as chromatin immunoprecipitation sequencing (ChIP‐seq), yeast one‐hybrid, and protein‐binding microarray can be used to assess the function of noncoding mutations . Moreover, in vivo assay of noncoding mutational effect is needed to gain better insight into carcinogenesis.…”

“…Moreover, in vivo assay of noncoding mutational effect is needed to gain better insight into carcinogenesis. Recent advances in the CRISPR technology enables genome‐wide screens to evaluate functional consequences of noncoding regions in vivo . Systematic experimental and analytical platforms will be insightful in identifying disease‐causing mutations and uncovering patient mutation‐specific disease mechanisms in liver cancer.…”