Somatic gene mutations involved in DNA damage response/Fanconi anemia signaling are tissue- and cell-type specific in human solid tumors - Rai, Sudhir Kumar; Du, Wei; Zhang, Jun; Yu, Herbert; Deng, Youping; Fei, Peiwen (Frontiers in Medicine, 2024)
With significant advancements in the study of DNA Damage Response (DDR) and Fanconi Anemia (FA) signaling, we previously introduced the term “FA signaling” to encompass “all signaling transductions involving one or more FA proteins.” This network has now evolved into the largest cellular defense network, integrating over 30 key players, including ATM, ATR, BLM, HRR6, RAD18, FANCA, FANCB, FANCC, BRCA2, FANCD2, FANCE, FANCF, FANCG, FANCI, BRIP1, FANCL, FANCM, PALB2, RAD51C, SLX4, ERCC4, RAD51, BRCA1, UBE2T, XRCC2, MAD2L2, RFWD3, FAAP20, FAAP24, FAAP100, and CENPX. This system responds to both endogenous and exogenous cellular insults. However, the mutational signatures associated with this defense mechanism in non-FA human cancers have not been extensively explored. In this study, we report that different types of human cancers are characterized by distinct somatically mutated genes related to DDR/FA signaling, each accompanied by a unique spectrum of potential driver mutations. For example, in pan-cancer samples, ATM emerges as the most frequently mutated gene (5%) among the 31 genes analyzed, with the highest number of potential driver mutations (1714), followed by BRCA2 (4% with 970 putative driver mutations). However, this pattern is not universal across specific cancer types. For example, FANCT is the most frequently mutated gene in breast (14%) and liver (4%) cancers. In addition, the alteration frequency of DDR/FA signaling due to these mutations exceeds 70% in a subtype of prostate cancer, with each subtype of brain, breast, lung, and prostate cancers displaying distinct patterns of gene alteration frequency. Furthermore, these gene alteration patterns significantly impact patient survival and disease-free periods. Collectively, our findings not only enhance our understanding of cancer development and progression but also have significant implications for cancer patient care and prognosis, particularly in the development of effective therapeutic strategies.