ArticleCommunications biology2023
Pan-cancer landscape of epigenetic factor expression predicts tumor outcome.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Progress in epigenetic research of breast cancer: a bibliometric analysis since the 2000s.Frontiers in oncology · 2025Pooled it
- Identification of Epigenetic Regulator-Associated Genes in Keloid Disease Through Integrated Bulk and Single-Cell Transcriptomics With RT-qPCR Validation.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Epigenetic Factor Dysregulation and Distinct Expression Signatures in Retinoblastoma: A Transcriptomic Analysis.Investigative ophthalmology & visual science · 2026Article
- Clinical utility of sarcoma methylation classifiers in soft tissue sarcoma diagnosis.Journal of cancer research and clinical oncology · 2026Article
- UTY (KDM6C) in Cancer: Epigenetic Regulation, Tumour Suppressor Functions, and Clinical Implications.Epigenomes · 2026Review
- Integrative Transcriptomics and Machine Learning Reveal the Association of CBX4 with Inflammation in Ulcerative Colitis as a Potential Epigenetic Regulator.Biomedicines · 2026Article
- Article
- The impact of epigenetics on tumor metabolism: Friend or foe in drug response?Frontiers in epigenetics and epigenomics · 2026Review
- The dysregulation score method identifies epigenetic regulator genes that predict cancer prognosis and efficiency of cancer immunotherapy.Molecular therapy. Nucleic acids · 2025Article
- ggalign: Bridging the Grammar of Graphics and Biological Multilayered Complexity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Epigene functional diversity: isoform usage, disordered domain content, and variable binding partners.Epigenetics & chromatin · 2025Article
- Convergence of evolving artificial intelligence and machine learning techniques in precision oncology.NPJ digital medicine · 2025Article
- The DNA methylation landscape of musculoskeletal sarcomas.Exploration of targeted anti-tumor therapy · 2025Review
- Exploring the role of epigenetic regulation in cancer prognosis with epigenetic score.Frontiers in pharmacology · 2025Article
- Introducing artificial intelligence and sperm epigenetics in the fertility clinic: a novel foundation for diagnostics and prediction modelling.Frontiers in reproductive health · 2025Article
- Research on biliary atresia and epigenetic factors from the perspective of transcriptomics: identification of key genes and experimental validation.Frontiers in pediatrics · 2025Article
- ASXL1 truncating variants in BOS and myeloid leukemia drive shared disruption of Wnt-signaling pathways but have differential isoform usage of RUNX3.BMC medical genomics · 2024Article
- Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction.Scientific reports · 2024Article
- Recent Advancements in Research on DNA Methylation and Testicular Germ Cell Tumors: Unveiling the Intricate Relationship.Biomedicines · 2024Review
- Mechanisms and technologies in cancer epigenetics.Frontiers in oncology · 2024Review
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.