A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer
Abstract Increasing evidence underscores the driving role of coding and non-coding variants in cancer development. Analyzing gene sets in biological processes offers deeper insights into the molecular mechanisms of carcinogenesis. Here, we developed geMER to identify candidate driver genes genome-wi...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-08-01
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| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-025-01060-y |
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| author | Jing Gan Yuncong Wang Zhuoran Shi Haoyu Hu Manyi Xu Xinrong Li Wenbo Dong Jiaheng He Yusen Zhao Yakun Zhang Yue Sun Caiyu Zhang Qianyi Lu Shangwei Ning Yan Jin Hui Zhi |
| author_facet | Jing Gan Yuncong Wang Zhuoran Shi Haoyu Hu Manyi Xu Xinrong Li Wenbo Dong Jiaheng He Yusen Zhao Yakun Zhang Yue Sun Caiyu Zhang Qianyi Lu Shangwei Ning Yan Jin Hui Zhi |
| author_sort | Jing Gan |
| collection | DOAJ |
| description | Abstract Increasing evidence underscores the driving role of coding and non-coding variants in cancer development. Analyzing gene sets in biological processes offers deeper insights into the molecular mechanisms of carcinogenesis. Here, we developed geMER to identify candidate driver genes genome-wide by detecting mutation enrichment regions within coding and non-coding elements. We subsequently designed a pipeline to identify a core driver gene set (CDGS) that broadly promotes carcinogenesis across multiple cancers. CDGS comprising 25 genes for 25 cancers displayed instability in DNA aberrations. Variants within the TTN enrichment region may influence the folding of the I-set domain by altering local polarity or side-chain chemistry properties of amino acids, potentially disrupting its antigen-binding capacity in LUAD. Multi-omics analysis revealed that APOB emerged as a candidate oncogene in LIHC, whose genetic alterations within the enrichment region may activate key TFs, upregulate DNA methylation levels, modulate critical histone modifications, and enhance transcriptional activity in the HepG2 and A549 cell lines compared to Panc1. Additionally, CDGS mutation status was an independent prognostic factor for the pan-cancer cohort. High-risk patients tended to develop an immunosuppressive microenvironment and demonstrated a higher likelihood of responding to ICI therapy. Finally, we provided a user-friendly web interface to explore candidate driver genes using geMER ( http://bio-bigdata.hrbmu.edu.cn/geMER/ ). |
| format | Article |
| id | doaj-art-ef2bb2b297594e9e8fb49896684b37b5 |
| institution | Kabale University |
| issn | 2397-768X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Precision Oncology |
| spelling | doaj-art-ef2bb2b297594e9e8fb49896684b37b52025-08-20T03:45:44ZengNature Portfolionpj Precision Oncology2397-768X2025-08-019111910.1038/s41698-025-01060-yA core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancerJing Gan0Yuncong Wang1Zhuoran Shi2Haoyu Hu3Manyi Xu4Xinrong Li5Wenbo Dong6Jiaheng He7Yusen Zhao8Yakun Zhang9Yue Sun10Caiyu Zhang11Qianyi Lu12Shangwei Ning13Yan Jin14Hui Zhi15College of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityThe Second Affiliated Hospital of 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 Increasing evidence underscores the driving role of coding and non-coding variants in cancer development. Analyzing gene sets in biological processes offers deeper insights into the molecular mechanisms of carcinogenesis. Here, we developed geMER to identify candidate driver genes genome-wide by detecting mutation enrichment regions within coding and non-coding elements. We subsequently designed a pipeline to identify a core driver gene set (CDGS) that broadly promotes carcinogenesis across multiple cancers. CDGS comprising 25 genes for 25 cancers displayed instability in DNA aberrations. Variants within the TTN enrichment region may influence the folding of the I-set domain by altering local polarity or side-chain chemistry properties of amino acids, potentially disrupting its antigen-binding capacity in LUAD. Multi-omics analysis revealed that APOB emerged as a candidate oncogene in LIHC, whose genetic alterations within the enrichment region may activate key TFs, upregulate DNA methylation levels, modulate critical histone modifications, and enhance transcriptional activity in the HepG2 and A549 cell lines compared to Panc1. Additionally, CDGS mutation status was an independent prognostic factor for the pan-cancer cohort. High-risk patients tended to develop an immunosuppressive microenvironment and demonstrated a higher likelihood of responding to ICI therapy. Finally, we provided a user-friendly web interface to explore candidate driver genes using geMER ( http://bio-bigdata.hrbmu.edu.cn/geMER/ ).https://doi.org/10.1038/s41698-025-01060-y |
| spellingShingle | Jing Gan Yuncong Wang Zhuoran Shi Haoyu Hu Manyi Xu Xinrong Li Wenbo Dong Jiaheng He Yusen Zhao Yakun Zhang Yue Sun Caiyu Zhang Qianyi Lu Shangwei Ning Yan Jin Hui Zhi A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer npj Precision Oncology |
| title | A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer |
| title_full | A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer |
| title_fullStr | A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer |
| title_full_unstemmed | A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer |
| title_short | A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer |
| title_sort | core driver gene set identified based on gemer reveals its potential driver mechanism in pan cancer |
| url | https://doi.org/10.1038/s41698-025-01060-y |
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