On the discovered Cancer Driving Nucleotides (CDNs) –Distributions across genes, cancer types and patients

Author:

Zhang Lingjie1ORCID,Deng Tong1,Liufu Zhongqi12,Chen Xiangnyu1,Wu Shijie1,Liu Xueyu1,Shi Changhao1,Chen Bingjie13,Hu Zheng4ORCID,Cai Qichun5,Lu Xuemei2,Liu Chenli4,Li Mengfeng6,Wen Haijun1,Wu Chung-I17ORCID

Affiliation:

1. State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University

2. Center for Excellence in Animal Evolution and Genetics, The Chinese Academy of Sciences

3. GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University

4. CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

5. Cancer Center, Clifford Hospital, Jinan University

6. Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University

7. Department of Ecology and Evolution, University of Chicago

Abstract

A central goal of cancer genomics is to identify, in each patient, all the cancer driving mutations. Among them, point mutations are referred to as Cancer Driving Nucleotides (CDNs), which recur in cancers. The companion study shows that the probability of i recurrent hits in n patients would decrease exponentially with i ; hence, any mutation with i ≥ 3 hits in the TCGA database is a high-probability CDN. This study characterizes the 50∼150 CDNs identifiable for each cancer type of TCGA (while anticipating 10 times more undiscovered ones) as follows: i) CDNs tend to code for amino acids of divergent chemical properties. ii) At the genic level, far more CDNs (>5-fold) fall on non-canonical than canonical cancer driving genes (CDGs). Most undiscovered CDNs are expected to be on unknown CDGs. iii) CDNs tend to be more widely shared among cancer types than canonical CDGs, mainly because of the higher resolution at the nucleotide than the whole-gene level. iv) Most important, among the 50∼100 coding region mutations carried by a cancer patient, 5∼8 CDNs are expected but only 0∼2 CDNs have been identified at present. This low level of identification has hampered functional test and gene targeted therapy. We show that, by expanding the sample size to 10 5 , most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes.

Publisher

eLife Sciences Publications, Ltd

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