Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity
Abstract Background Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. However, the lack of a quick and convenient approach to determine the intratumoral epigenetic heterogeneity (...
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BMC
2025-01-01
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| Series: | Cell & Bioscience |
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| Online Access: | https://doi.org/10.1186/s13578-024-01337-y |
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| author | Binbin Liu Yumo Xie Yu Zhang Guannan Tang Jinxin Lin Ze Yuan Xiaoxia Liu Xiaolin Wang Meijin Huang Yanxin Luo Huichuan Yu |
| author_facet | Binbin Liu Yumo Xie Yu Zhang Guannan Tang Jinxin Lin Ze Yuan Xiaoxia Liu Xiaolin Wang Meijin Huang Yanxin Luo Huichuan Yu |
| author_sort | Binbin Liu |
| collection | DOAJ |
| description | Abstract Background Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. However, the lack of a quick and convenient approach to determine the intratumoral epigenetic heterogeneity (eITH) limit the application of eITH in clinical settings. Here, we aimed to develop a tool that can evaluate the eITH using the DNA methylation profiles from bulk tumors. Methods Genomic DNA of three laser micro-dissected tumor regions, including digestive tract surface, central bulk, and invasive front, was extracted from formalin-fixed paraffin-embedded sections of colorectal cancer patients. The genome-wide methylation profiles were generated with methylation array. The most variable methylated probes were selected to construct a DNA methylation-based heterogeneity (MeHEG) estimation tool that can deconvolve the proportion of each reference tumor region with the support vector machine model-based method. A PCR-based assay for quantitative analysis of DNA methylation (QASM) was developed to specifically determine the methylation status of each CpG in MeHEG assay at single-base resolution to realize fast evaluation of epigenetic heterogeneity. Results In the discovery set with 79 patients, the differentially methylated CpGs among the three tumor regions were found. The 7 most representative CpGs were identified and subsequently selected to develop the MeHEG algorithm. We validated its performance of deconvolution of tumor regions in an independent cohort. In addition, we showed the significant association of MeHEG-based epigenetic heterogeneity with the genomic heterogeneity in mutation and copy number variation in our in-house and TCGA cohorts. Besides, we found that the patients with higher MeHEG score had worse disease-free and overall survival outcomes. Finally, we found dynamic change of epigenetic heterogeneity based on MeHEG score in cancer cells under the treatment of therapeutic drugs. Conclusion By developing a 7-loci panel using a machine learning approach combined with the QASM assay for PCR-based application, we present a valuable method for evaluating intratumoral heterogeneity. The MeHEG algorithm offers novel insights into tumor heterogeneity from an epigenetic perspective, potentially enriching current knowledge of tumor complexity and providing a new tool for clinical and research applications in cancer biology. |
| format | Article |
| id | doaj-art-758f3523dda645f2bd2161882863187d |
| institution | Kabale University |
| issn | 2045-3701 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Cell & Bioscience |
| spelling | doaj-art-758f3523dda645f2bd2161882863187d2025-01-26T12:54:19ZengBMCCell & Bioscience2045-37012025-01-0115111610.1186/s13578-024-01337-ySpatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneityBinbin Liu0Yumo Xie1Yu Zhang2Guannan Tang3Jinxin Lin4Ze Yuan5Xiaoxia Liu6Xiaolin Wang7Meijin Huang8Yanxin Luo9Huichuan Yu10Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen UniversityDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen UniversityDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen UniversityDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen UniversityDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen UniversityAbstract Background Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. However, the lack of a quick and convenient approach to determine the intratumoral epigenetic heterogeneity (eITH) limit the application of eITH in clinical settings. Here, we aimed to develop a tool that can evaluate the eITH using the DNA methylation profiles from bulk tumors. Methods Genomic DNA of three laser micro-dissected tumor regions, including digestive tract surface, central bulk, and invasive front, was extracted from formalin-fixed paraffin-embedded sections of colorectal cancer patients. The genome-wide methylation profiles were generated with methylation array. The most variable methylated probes were selected to construct a DNA methylation-based heterogeneity (MeHEG) estimation tool that can deconvolve the proportion of each reference tumor region with the support vector machine model-based method. A PCR-based assay for quantitative analysis of DNA methylation (QASM) was developed to specifically determine the methylation status of each CpG in MeHEG assay at single-base resolution to realize fast evaluation of epigenetic heterogeneity. Results In the discovery set with 79 patients, the differentially methylated CpGs among the three tumor regions were found. The 7 most representative CpGs were identified and subsequently selected to develop the MeHEG algorithm. We validated its performance of deconvolution of tumor regions in an independent cohort. In addition, we showed the significant association of MeHEG-based epigenetic heterogeneity with the genomic heterogeneity in mutation and copy number variation in our in-house and TCGA cohorts. Besides, we found that the patients with higher MeHEG score had worse disease-free and overall survival outcomes. Finally, we found dynamic change of epigenetic heterogeneity based on MeHEG score in cancer cells under the treatment of therapeutic drugs. Conclusion By developing a 7-loci panel using a machine learning approach combined with the QASM assay for PCR-based application, we present a valuable method for evaluating intratumoral heterogeneity. The MeHEG algorithm offers novel insights into tumor heterogeneity from an epigenetic perspective, potentially enriching current knowledge of tumor complexity and providing a new tool for clinical and research applications in cancer biology.https://doi.org/10.1186/s13578-024-01337-yDNA methylationIntratumor heterogeneityEpigeneticColorectal cancer |
| spellingShingle | Binbin Liu Yumo Xie Yu Zhang Guannan Tang Jinxin Lin Ze Yuan Xiaoxia Liu Xiaolin Wang Meijin Huang Yanxin Luo Huichuan Yu Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity Cell & Bioscience DNA methylation Intratumor heterogeneity Epigenetic Colorectal cancer |
| title | Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity |
| title_full | Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity |
| title_fullStr | Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity |
| title_full_unstemmed | Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity |
| title_short | Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity |
| title_sort | spatial deconvolution from bulk dna methylation profiles determines intratumoral epigenetic heterogeneity |
| topic | DNA methylation Intratumor heterogeneity Epigenetic Colorectal cancer |
| url | https://doi.org/10.1186/s13578-024-01337-y |
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