突变
癌变
生物
遗传学
癌症
表型
突变
选择(遗传算法)
计算生物学
分子进化
体细胞
癌症的体细胞进化
进化生物学
基因
基因组
计算机科学
人工智能
作者
Vincent L. Cannataro,Kira A. Glasmacher,C. Hampson
标识
DOI:10.1016/j.bbadis.2024.167268
摘要
Cancers are the product of evolutionary events, where molecular variation occurs and accumulates in tissues and tumors. Sequencing of this molecular variation informs not only which variants are driving tumorigenesis, but also the mechanisms behind what is fueling mutagenesis. Both of these details are crucial for preventing premature deaths due to cancer, whether it is by targeting the variants driving the cancer phenotype or by measures to prevent exogenous mutations from contributing to somatic evolution. Here, we review tools to determine both molecular signatures and cancer drivers, and avenues by which these metrics may be linked.
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