A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer
Abstract Circulating tumor DNA (ctDNA) variants hold significant promise as cancer biomarkers in liquid biopsies, owing to their minimally invasive testing approach and capacity to capture the comprehensive tumor landscape. However, a comprehensive resource for studying ctDNA variants is still lacki...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05550-3 |
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| author | Yuncong Wang Jing Gan Haoyu Hu Manyi Xu Yongle Xu Yusen Zhao Wenbo Dong Xinrong Li Hongbo Zhu Shuangshuang Wang Jiaheng He Shangwei Ning Peng Wang Hui Zhi |
| author_facet | Yuncong Wang Jing Gan Haoyu Hu Manyi Xu Yongle Xu Yusen Zhao Wenbo Dong Xinrong Li Hongbo Zhu Shuangshuang Wang Jiaheng He Shangwei Ning Peng Wang Hui Zhi |
| author_sort | Yuncong Wang |
| collection | DOAJ |
| description | Abstract Circulating tumor DNA (ctDNA) variants hold significant promise as cancer biomarkers in liquid biopsies, owing to their minimally invasive testing approach and capacity to capture the comprehensive tumor landscape. However, a comprehensive resource for studying ctDNA variants is still lacking. Here, we developed CTDdgv to systematically identify ctDNA variants and interpret their clinical relevance. We manually curated 1674 experimentally validated clinical interpretations for ctDNA variants, concerning prognosis, drug resistance, tumor characteristics, metastasis monitoring, therapy, prospect for detection, and others. Furthermore, we developed and integrated a pipeline that identifies tumor driver genes (TDGs) and variants (TDVs) and evaluates the prognostic significance of potential TDGs. Using publicly available ctDNA mutation spectra, we identified potential TDGs and TDVs from 38 datasets across 17 cancer types. Based on these datasets, we provide a multi-dimensional analysis of TDG gene sets in specific cancer types, providing insights into their driving effects. Collectively, CTDdgv has significant potential to serve as a valuable resource for molecular diagnostics and therapeutic decision-making in cancer via liquid biopsy. |
| format | Article |
| id | doaj-art-d76b0a48ac054e789d889ed1bc868135 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-d76b0a48ac054e789d889ed1bc8681352025-08-20T03:45:44ZengNature PortfolioScientific Data2052-44632025-07-0112111010.1038/s41597-025-05550-3A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancerYuncong Wang0Jing Gan1Haoyu Hu2Manyi Xu3Yongle Xu4Yusen Zhao5Wenbo Dong6Xinrong Li7Hongbo Zhu8Shuangshuang Wang9Jiaheng He10Shangwei Ning11Peng Wang12Hui Zhi13College of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityAbstract Circulating tumor DNA (ctDNA) variants hold significant promise as cancer biomarkers in liquid biopsies, owing to their minimally invasive testing approach and capacity to capture the comprehensive tumor landscape. However, a comprehensive resource for studying ctDNA variants is still lacking. Here, we developed CTDdgv to systematically identify ctDNA variants and interpret their clinical relevance. We manually curated 1674 experimentally validated clinical interpretations for ctDNA variants, concerning prognosis, drug resistance, tumor characteristics, metastasis monitoring, therapy, prospect for detection, and others. Furthermore, we developed and integrated a pipeline that identifies tumor driver genes (TDGs) and variants (TDVs) and evaluates the prognostic significance of potential TDGs. Using publicly available ctDNA mutation spectra, we identified potential TDGs and TDVs from 38 datasets across 17 cancer types. Based on these datasets, we provide a multi-dimensional analysis of TDG gene sets in specific cancer types, providing insights into their driving effects. Collectively, CTDdgv has significant potential to serve as a valuable resource for molecular diagnostics and therapeutic decision-making in cancer via liquid biopsy.https://doi.org/10.1038/s41597-025-05550-3 |
| spellingShingle | Yuncong Wang Jing Gan Haoyu Hu Manyi Xu Yongle Xu Yusen Zhao Wenbo Dong Xinrong Li Hongbo Zhu Shuangshuang Wang Jiaheng He Shangwei Ning Peng Wang Hui Zhi A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer Scientific Data |
| title | A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer |
| title_full | A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer |
| title_fullStr | A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer |
| title_full_unstemmed | A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer |
| title_short | A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer |
| title_sort | comprehensive database for identifying and interpreting ctdna driver genes and variants in cancer |
| url | https://doi.org/10.1038/s41597-025-05550-3 |
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