Genome-scale and systematic variant profiling delineates the radiogenomic landscape of cancer
Genome-scale and systematic variant profiling delineates the radiogenomic landscape of cancer \r
BACKGROUND: The impact of the preponderance of common or rare cancer genetic alterations on the sensitivity of cells to ionizing radiation remain unknown. We conducted a systematic, large-scale profiling effort to identify genetic variants that alter cellular sensitivity to radiation. METHODS: Candidate variants were prioritized on the basis of their location within conserved protein domains (UniProt), predicted functional impact (MutationAssessor), and genotype-phenotype associations from large-scale cancer cell line irradiation efforts. We used site-directed mutagenesis to generate mutant clones and transferred the ORFs into lentiviral vectors for stable expression under a PGK and/or EF-1a promoter in SV40 or hTERT immortalized cells, or the NCI-H1299 cancer cell line. For variants predicted to confer loss of gene function, the endogenous loci were deleted using a novel intro-exon junctional CRISPR method (J-CRISPR). The effect of individual variants on radiation responses were benchmarked using the cyto- and radio-protective NFE2L2 E79K gain-of-function mutation (resistance) or the deletion of the DNA repair gene TP53BP1 (sensitivity). Candidate variants that effected sensitivity or resistance were selected using a Gaussian mixture model and were validated by colony formation assays. RESULTS: Over 1600 replicates were tested, comprising 91 genes and 560 variants. Variants that were nominated by our in silico enrichment methods, are evolutionary conserved, or those under somatic oncogenic selection were significantly more likely to result in a variant that conferred changes in the vulnerability of cells to radiation. The vast majority of common cancer variants did not alter the radio-phenotype; several rare cancer variants did. We annotated known and new radioresistant and radiosensitive variants involved in several cellular functional categories including cellular signaling, cytoskeleton, cell cycle, apoptosis, DNA methylation, and DNA repair. Phenotypic impact profiling reveals distinct metabolic and gene expression pathways that, upon modulation, alter the sensitivity of cells to irradiation CONCLUSION: Determining the impact of cancer genetic alterations on the clinical responses to irradiation remains a major obstacle in the implementation of personalized radiotherapy. Here, we report on a large-scale profiling effort to identify and classify mutant alleles that govern radiation survival. Our results reveal new insights into the mechanisms of cellular survival to radiation and genome maintenance during therapeutic stress.