Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients

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>i</i> recurrent hits in <b>n</b> patients would decrease exponentially with <i>i</i>; hence, any mutation with <i>i</i> ≥ 3 hits in The Cancer Genome Atlas (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 (more than fivefold) fall on noncanonical 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<sup>5</sup>, most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes.

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Journal
eLife
Published
2024-09-05
DOI
https://doi.org/10.7554/elife.99341
Citations
2
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.57

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Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients

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Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients

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article en
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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>i</i> recurrent hits in <b>n</b> patients would decrease exponentially with <i>i</i>; hence, any mutation with <i>i</i> ≥ 3 hits in The Cancer Genome Atlas (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 (more than fivefold) fall on noncanonical 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<sup>5</sup>, most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes.

eLifeVol. 13
Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), University of Chicago (US), Shenzhen Institutes of Advanced Technology (CN), Biocontrol (Brazil) (BR), Southern Medical University (CN), Guangzhou Medical University (CN)
American Association for Cancer Research, National Natural Science Foundation of China, Sun Yat-sen University, Jinan University, Chinese Academy of Medical Sciences, Guangdong Provincial People's Hospital, Kunming Institute of Zoology, Chinese Academy of Sciences, Special Project for Research and Development in Key areas of Guangdong Province, Basic and Applied Basic Research Foundation of Guangdong Province
Good health and well-being
Openalex Percentile: Top 32%
Cancer Genomics and Diagnostics
0.57
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