Pan-cancer landscape of epigenetic factor expression predicts tumor outcome
Abstract Oncogenic pathways that drive cancer progression reflect both genetic changes and epigenetic regulation. Here we stratified primary tumors from each of 24 TCGA adult cancer types based on the gene expression patterns of epigenetic factors (epifactors). The tumors for five cancer types (ACC,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-11-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-023-05459-w |
| _version_ | 1797557191873396736 |
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| author | Michael W. Cheng Mithun Mitra Hilary A. Coller |
| author_facet | Michael W. Cheng Mithun Mitra Hilary A. Coller |
| author_sort | Michael W. Cheng |
| collection | DOAJ |
| description | Abstract Oncogenic pathways that drive cancer progression reflect both genetic changes and epigenetic regulation. Here we stratified primary tumors from each of 24 TCGA adult cancer types based on the gene expression patterns of epigenetic factors (epifactors). The tumors for five cancer types (ACC, KIRC, LGG, LIHC, and LUAD) separated into two robust clusters that were better than grade or epithelial-to-mesenchymal transition in predicting clinical outcomes. The majority of epifactors that drove the clustering were also individually prognostic. A pan-cancer machine learning model deploying epifactor expression data for these five cancer types successfully separated the patients into poor and better outcome groups. Single-cell analysis of adult and pediatric tumors revealed that expression patterns associated with poor or worse outcomes were present in individual cells within tumors. Our study provides an epigenetic map of cancer types and lays a foundation for discovering pan-cancer targetable epifactors. |
| first_indexed | 2024-03-10T17:13:52Z |
| format | Article |
| id | doaj.art-2330722c33ff4532b3a3d5d46b6ba01a |
| institution | Directory Open Access Journal |
| issn | 2399-3642 |
| language | English |
| last_indexed | 2024-03-10T17:13:52Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj.art-2330722c33ff4532b3a3d5d46b6ba01a2023-11-20T10:33:36ZengNature PortfolioCommunications Biology2399-36422023-11-016111810.1038/s42003-023-05459-wPan-cancer landscape of epigenetic factor expression predicts tumor outcomeMichael W. Cheng0Mithun Mitra1Hilary A. Coller2Bioinformatics Interdepartmental Program, University of CaliforniaDepartment of Molecular, Cell and Developmental Biology, University of CaliforniaBioinformatics Interdepartmental Program, University of CaliforniaAbstract Oncogenic pathways that drive cancer progression reflect both genetic changes and epigenetic regulation. Here we stratified primary tumors from each of 24 TCGA adult cancer types based on the gene expression patterns of epigenetic factors (epifactors). The tumors for five cancer types (ACC, KIRC, LGG, LIHC, and LUAD) separated into two robust clusters that were better than grade or epithelial-to-mesenchymal transition in predicting clinical outcomes. The majority of epifactors that drove the clustering were also individually prognostic. A pan-cancer machine learning model deploying epifactor expression data for these five cancer types successfully separated the patients into poor and better outcome groups. Single-cell analysis of adult and pediatric tumors revealed that expression patterns associated with poor or worse outcomes were present in individual cells within tumors. Our study provides an epigenetic map of cancer types and lays a foundation for discovering pan-cancer targetable epifactors.https://doi.org/10.1038/s42003-023-05459-w |
| spellingShingle | Michael W. Cheng Mithun Mitra Hilary A. Coller Pan-cancer landscape of epigenetic factor expression predicts tumor outcome Communications Biology |
| title | Pan-cancer landscape of epigenetic factor expression predicts tumor outcome |
| title_full | Pan-cancer landscape of epigenetic factor expression predicts tumor outcome |
| title_fullStr | Pan-cancer landscape of epigenetic factor expression predicts tumor outcome |
| title_full_unstemmed | Pan-cancer landscape of epigenetic factor expression predicts tumor outcome |
| title_short | Pan-cancer landscape of epigenetic factor expression predicts tumor outcome |
| title_sort | pan cancer landscape of epigenetic factor expression predicts tumor outcome |
| url | https://doi.org/10.1038/s42003-023-05459-w |
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