Genome-wide modeling of mutation spectra of human cancer-risk agents using experimental systems

Abstract : Cancer genomes harbour a mosaic of mutation patterns from which thirty mutational signatures have been identified, each attributable to a particular known or yet undetermined causal process. Deciphering the origins of these global mutational signatures in full could help identify the causes of human cancer, especially for about 40% of those signatures identified thus far that remain without a known etiological factor. Thus, well-controlled experimental exposure models can be used to assign particular mutational signatures to various mutagenic factors.During the time frame of my PhD work, I characterized and employed innovative in vitro and in vivo models of carcinogen exposure, namely, primary Hupki MEF cells, HepaRG and lymphoblastoid cell lines as well as rodent tumors. The cytotoxic and genotoxic conditions for each tested exposure compound were established and DNA adduct formation was assessed in select cases. Following a pre-screen by TP53 gene sequencing, genome-wide sequencing of immortalized Hupki MEF clones derived from exposure to acrylamide, glycidamide and ochratoxin A was performed, alongside whole genome sequencing of ochratoxin A induced rat renal tumors. The results reveal a novel mutational signature of acrylamide mediated by its active metabolite, glycidamide, a pattern that can be explained by the parallel analysis of individual glycidamide-DNA adducts. In addition, an integrative mutation analysis using in vitro and in vivo models suggests a lack of direct mutagenicity for OTA and possible indirect effects due to the ROS-mediated mode-of-action in MEF cells. The presented robust experimental strategy can facilitate the interpretation of mutation fingerprints identified in human tumors, thereby elucidating cancer etiology, elucidating the relationship between mutagenesis and carcinogenesis and ultimately providing mechanistic evidence for IARC’s carcinogen classification
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Maria Zhivagui. Genome-wide modeling of mutation spectra of human cancer-risk agents using experimental systems. Cancer. Université de Lyon, 2017. English. ⟨NNT : 2017LYSE1278⟩. ⟨tel-02145207⟩

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