Multi-omic analysis suggests tumor suppressor genes evolved specific promoter features to optimize cancer resistance

Author:

Huang Dan1,Wang Xiansong1,Liu Yingzhi1,Huang Ziheng1,Hu Xiaoxu1,Hu Wei2,Li Qing2,Chan Hung2,Zou Yidan2,Ho Idy H T2,Wang Yan2,Cheng Alfred S L2,Kang Wei2,To Ka F2,Wang Maggie H T1,Wong Sunny H2,Yu Jun2,Gin Tony2,Zhang Qingpeng3,Li Zheng4,Shen Jianxiong4ORCID,Zhang Lin2,Chan Matthew T V2,Liu Xiaodong2,Wu William K K5ORCID

Affiliation:

1. Chinese University of Hong Kong and the CUHK-Shenzhen Research Institute, China

2. Chinese University of Hong Kong, China

3. City University of Hong Kong, China

4. Peking Union Medical College Hospital, China

5. Chinese University of Hong Kong and a researcher at the CUHK-Shenzhen Research Institute, China

Abstract

Abstract Tumor suppressor genes (TSGs) exhibit distinct evolutionary features. We speculated that TSG promoters could have evolved specific features that facilitate their tumor-suppressing functions. We found that the promoter CpG dinucleotide frequencies of TSGs are significantly higher than that of non-cancer genes across vertebrate genomes, and positively correlated with gene expression across tissue types. The promoter CpG dinucleotide frequencies of all genes gradually increase with gene age, for which young TSGs have been subject to a stronger evolutionary pressure. Transcription-related features, namely chromatin accessibility, methylation and ZNF263-, SP1-, E2F4- and SP2-binding elements, are associated with gene expression. Moreover, higher promoter CpG dinucleotide frequencies and chromatin accessibility are positively associated with the ability of TSGs to resist downregulation during tumorigenesis. These results were successfully validated with independent datasets. In conclusion, TSGs evolved specific promoter features that optimized cancer resistance through achieving high expression in normal tissues and resistance to downregulation during tumorigenesis.

Funder

Shenzhen Science and Technology Programme

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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