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 recurrent hits in n patients would decrea...
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eLife Sciences Publications Ltd
2024-12-01
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| Online Access: | https://elifesciences.org/articles/99341 |
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| author | Lingjie Zhang Tong Deng Zhongqi Liufu Xiangnyu Chen Shijie Wu Xueyu Liu Changhao Shi Bingjie Chen Zheng Hu Qichun Cai Chenli Liu Mengfeng Li Miles E Tracy Xuemei Lu Chung-I Wu Hai-Jun Wen |
| author_facet | Lingjie Zhang Tong Deng Zhongqi Liufu Xiangnyu Chen Shijie Wu Xueyu Liu Changhao Shi Bingjie Chen Zheng Hu Qichun Cai Chenli Liu Mengfeng Li Miles E Tracy Xuemei Lu Chung-I Wu Hai-Jun Wen |
| author_sort | Lingjie Zhang |
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| description | 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 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 105, most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes. |
| format | Article |
| id | doaj-art-d277e2022dba457ba1aa1ec3bbb6ae22 |
| institution | Kabale University |
| issn | 2050-084X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj-art-d277e2022dba457ba1aa1ec3bbb6ae222024-12-17T17:37:10ZengeLife Sciences Publications LtdeLife2050-084X2024-12-011310.7554/eLife.99341Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patientsLingjie Zhang0https://orcid.org/0000-0002-6506-4457Tong Deng1Zhongqi Liufu2Xiangnyu Chen3https://orcid.org/0000-0001-5078-8906Shijie Wu4Xueyu Liu5Changhao Shi6Bingjie Chen7Zheng Hu8https://orcid.org/0000-0003-1552-0060Qichun Cai9Chenli Liu10Mengfeng Li11Miles E Tracy12Xuemei Lu13https://orcid.org/0000-0001-6044-6002Chung-I Wu14https://orcid.org/0000-0001-7263-4238Hai-Jun Wen15https://orcid.org/0000-0001-8676-1254State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China; Center for Excellence in Animal Evolution and Genetics, The Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China; GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, ChinaCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaCancer Center, Clifford Hospital, Jinan University, Guangzhou, ChinaCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaCancer Research Institute, School of Basic Medical Sciences, Southern Medical University, Guangzhou, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaCenter for Excellence in Animal Evolution and Genetics, The Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China; Department of Ecology and Evolution, University of Chicago, Chicago, United StatesState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, ChinaA 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 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 105, most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes.https://elifesciences.org/articles/99341cancer evolutioncancer driverstargeted therapy |
| spellingShingle | Lingjie Zhang Tong Deng Zhongqi Liufu Xiangnyu Chen Shijie Wu Xueyu Liu Changhao Shi Bingjie Chen Zheng Hu Qichun Cai Chenli Liu Mengfeng Li Miles E Tracy Xuemei Lu Chung-I Wu Hai-Jun Wen Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients eLife cancer evolution cancer drivers targeted therapy |
| title | Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients |
| title_full | Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients |
| title_fullStr | Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients |
| title_full_unstemmed | Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients |
| title_short | Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients |
| title_sort | characterization of cancer driving nucleotides cdns across genes cancer types and patients |
| topic | cancer evolution cancer drivers targeted therapy |
| url | https://elifesciences.org/articles/99341 |
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