N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers
Abstract Background Accurately identifying effective biomarkers and translating them into clinical practice have significant implications for improving clinical outcomes in hepatocellular carcinoma (HCC). In this study, our objective is to explore appropriate methods to improve the accuracy of bioma...
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BMC
2024-11-01
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| Series: | Biology Direct |
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| Online Access: | https://doi.org/10.1186/s13062-024-00554-2 |
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| author | Xiaokai Yan Yao Qi Xinyue Yao Lulu Yin Hao Wang Ji Fu Guo Wan Yanqun Gao Nanjing Zhou Xinxin Ye Xiao Liu Xing Chen |
| author_facet | Xiaokai Yan Yao Qi Xinyue Yao Lulu Yin Hao Wang Ji Fu Guo Wan Yanqun Gao Nanjing Zhou Xinxin Ye Xiao Liu Xing Chen |
| author_sort | Xiaokai Yan |
| collection | DOAJ |
| description | Abstract Background Accurately identifying effective biomarkers and translating them into clinical practice have significant implications for improving clinical outcomes in hepatocellular carcinoma (HCC). In this study, our objective is to explore appropriate methods to improve the accuracy of biomarker identification and investigate their clinical value. Methods Concentrating on the N6-methyladenosine (m6A) modification regulators, we utilized dozens of multi-omics HCC datasets to analyze the expression patterns and genetic features of m6A regulators. Through the integration of big data analysis with function experiments, we have redefined the biological roles of m6A regulators in HCC. Based on the key regulators, we constructed m6A risk models and explored their clinical value in estimating prognosis and guiding personalized therapy for HCC. Results Most m6A regulators exhibit abnormal expression in HCC, and their expression is influenced by copy number variations (CNV) and DNA methylation. Large-scale data analysis has revealed the biological roles of many key m6A regulators, and these findings are well consistent with experimental results. The m6A risk models offer significant prognostic value. Moreover, they assist in reassessing the therapeutic potential of drugs such as sorafenib, gemcitabine, CTLA4 and PD1 blockers in HCC. Conclusions Our findings suggest that the mutual validation of big data analysis and functional experiments may facilitate the precise identification and definition of biomarkers, and our m6A risk models may have the potential to guide personalized chemotherapy, targeted treatment, and immunotherapy decisions in HCC. |
| format | Article |
| id | doaj-art-7a4412f01cbd4f63ad65fc124dd4b681 |
| institution | OA Journals |
| issn | 1745-6150 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Biology Direct |
| spelling | doaj-art-7a4412f01cbd4f63ad65fc124dd4b6812025-08-20T02:13:35ZengBMCBiology Direct1745-61502024-11-0119111810.1186/s13062-024-00554-2N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkersXiaokai Yan0Yao Qi1Xinyue Yao2Lulu Yin3Hao Wang4Ji Fu5Guo Wan6Yanqun Gao7Nanjing Zhou8Xinxin Ye9Xiao Liu10Xing Chen11Department of Oncology, The Second Affiliated Hospital of Zunyi Medical UniversityShanghai Molecular Medicine Engineering Technology Research CenterDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical UniversityDepartment of Nursing, The People’s Hospital of SuiyangDepartment of Surgery, The People’s Hospital of SuiyangDepartment of Surgery, Suiyang County Traditional Chinese Medicine HospitalDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical UniversityDepartment of Internal Medicine, The Second Affiliated Hospital of Zunyi Medical UniversityDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical UniversityDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical UniversityDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical UniversityDepartment of Hepatopancreatobiliary Surgery, Hangzhou Institute of Medicine (HIM), Zhejiang Cancer Hospital, Chinese Academy of SciencesAbstract Background Accurately identifying effective biomarkers and translating them into clinical practice have significant implications for improving clinical outcomes in hepatocellular carcinoma (HCC). In this study, our objective is to explore appropriate methods to improve the accuracy of biomarker identification and investigate their clinical value. Methods Concentrating on the N6-methyladenosine (m6A) modification regulators, we utilized dozens of multi-omics HCC datasets to analyze the expression patterns and genetic features of m6A regulators. Through the integration of big data analysis with function experiments, we have redefined the biological roles of m6A regulators in HCC. Based on the key regulators, we constructed m6A risk models and explored their clinical value in estimating prognosis and guiding personalized therapy for HCC. Results Most m6A regulators exhibit abnormal expression in HCC, and their expression is influenced by copy number variations (CNV) and DNA methylation. Large-scale data analysis has revealed the biological roles of many key m6A regulators, and these findings are well consistent with experimental results. The m6A risk models offer significant prognostic value. Moreover, they assist in reassessing the therapeutic potential of drugs such as sorafenib, gemcitabine, CTLA4 and PD1 blockers in HCC. Conclusions Our findings suggest that the mutual validation of big data analysis and functional experiments may facilitate the precise identification and definition of biomarkers, and our m6A risk models may have the potential to guide personalized chemotherapy, targeted treatment, and immunotherapy decisions in HCC.https://doi.org/10.1186/s13062-024-00554-2Hepatocellular carcinomam6A regulatorsLarge-scale data analysisPrecise definition of biomarkersRisk modelsClinical applications |
| spellingShingle | Xiaokai Yan Yao Qi Xinyue Yao Lulu Yin Hao Wang Ji Fu Guo Wan Yanqun Gao Nanjing Zhou Xinxin Ye Xiao Liu Xing Chen N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers Biology Direct Hepatocellular carcinoma m6A regulators Large-scale data analysis Precise definition of biomarkers Risk models Clinical applications |
| title | N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers |
| title_full | N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers |
| title_fullStr | N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers |
| title_full_unstemmed | N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers |
| title_short | N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers |
| title_sort | n6 methyladenosine regulators in hepatocellular carcinoma investigating the precise definition and clinical applications of biomarkers |
| topic | Hepatocellular carcinoma m6A regulators Large-scale data analysis Precise definition of biomarkers Risk models Clinical applications |
| url | https://doi.org/10.1186/s13062-024-00554-2 |
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