The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs)

Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size <b>n</b>=300-1000), point mutations may recur in <i>i</i> out of <b>n</b> patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (<i>i<sup>*</sup></i>) driven solely by neutral evolution. Since no neutral mutation can reach <i>i<sup>*</sup></i>=3, all mutations recurring at <i>i</i>≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if <b>n</b> increases to 100,000 for each cancer type. At present, only <10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.

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Publication Details

Journal
eLife
Published
2024-09-03
DOI
https://doi.org/10.7554/elife.99340
Citations
6
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
1.71

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article

The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs)

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6 citations
eLife
Cancer Genomics and Diagnostics
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article

The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs)

Xueyu Liu, Zhongqi Liufu, Lingjie Zhang, Chung‐I Wu, Miles E Tracy, Chenli Liu, Zheng Hu, Xuemei Lu, Tong Deng, Haijun Wen, Bingjie Chen
article en
6 citations

Abstract

Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size <b>n</b>=300-1000), point mutations may recur in <i>i</i> out of <b>n</b> patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (<i>i<sup>*</sup></i>) driven solely by neutral evolution. Since no neutral mutation can reach <i>i<sup>*</sup></i>=3, all mutations recurring at <i>i</i>≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if <b>n</b> increases to 100,000 for each cancer type. At present, only <10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.

eLifeVol. 13
Sun Yat-sen University (CN), Kunming Institute of Zoology (CN), Chinese Academy of Sciences (CN), University of Chicago (US), Biocontrol (Brazil) (BR), 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 15%
Cancer Genomics and Diagnostics
1.71
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