Rad18 confers hematopoietic progenitor cell DNA damage tolerance independently of the Fanconi Anemia pathway in vivo.

Abstract

In cultured cancer cells the E3 ubiquitin ligase Rad18 activates Trans-Lesion Synthesis (TLS) and the Fanconi Anemia (FA) pathway. However, physiological roles of Rad18 in DNA damage tolerance and carcinogenesis are unknown and were investigated here. Primary hematopoietic stem and progenitor cells (HSPC) co-expressed RAD18 and FANCD2 proteins, potentially consistent with a role for Rad18 in FA pathway function during hematopoiesis. However, hematopoietic defects typically associated with fanc-deficiency (decreased HSPC numbers, reduced engraftment potential of HSPC, and Mitomycin C (MMC) -sensitive hematopoiesis), were absent in Rad18(-/-) mice. Moreover, primary Rad18(-/-) mouse embryonic fibroblasts (MEF) retained robust Fancd2 mono-ubiquitination following MMC treatment. Therefore, Rad18 is dispensable for FA pathway activation in untransformed cells and the Rad18 and FA pathways are separable in hematopoietic cells. In contrast with responses to crosslinking agents, Rad18(-/-) HSPC were sensitive to in vivo treatment with the myelosuppressive agent 7,12 Dimethylbenz[a]anthracene (DMBA). Rad18-deficient fibroblasts aberrantly accumulated DNA damage markers after DMBA treatment. Moreover, in vivo DMBA treatment led to increased incidence of B cell malignancy in Rad18(-/-) mice. These results identify novel hematopoietic functions for Rad18 and provide the first demonstration that Rad18 confers DNA damage tolerance and tumor-suppression in a physiological setting.

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10.1093/nar/gkw072

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Yang, Yang, Jonathan C Poe, Lisong Yang, Andrew Fedoriw, Siddhi Desai, Terry Magnuson, Zhiguo Li, Yuri Fedoriw, et al. (2016). Rad18 confers hematopoietic progenitor cell DNA damage tolerance independently of the Fanconi Anemia pathway in vivo. Nucleic Acids Res, 44(9). pp. 4174–4188. 10.1093/nar/gkw072 Retrieved from https://hdl.handle.net/10161/12561.

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Zhiguo Li

Associate Professor of Biostatistics & Bioinformatics

survival analysis, dynamic treatment regimes, clinical trials


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