ArticleJournal of translational medicine2022
HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data.
Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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32 citing papers in PubMed.
- Decomposition-driven biomarker identification enhances non-invasive early cancer detection.iScience · 2026Article
- Metastasis-associated DNA methylation alterations persist after accounting for immune and stromal cell heterogeneity in primary colorectal tumors.Research square · 2026Article
- DNA methylation-based immune cell profiling in mouse blood using MouseRS-CMD.Genome biology · 2026Article
- Endothelial cell-specific DNA methylation alterations in breast cancer.Communications biology · 2026Article
- Retroelement Hypomethylation Links Hypoxia Signaling, Immune Phenotypes, and Survival in Clear Cell Renal Cell Carcinoma.bioRxiv : the preprint server for biology · 2026Article
- Tumor-intrinsic B4GALNT3 expression drives a protective immune microenvironment in endometriosis-associated ovarian cancer.Translational cancer research · 2026Article
- Guidelines on optimizing DNA methylation reference panels for cell-type deconvolution.Communications biology · 2026Article
- Preliminary insights into methylation patterns in Agent Orange exposed thyroid cancers: a pilot study.Environmental pollution (Barking, Essex : 1987) · 2026Article
- DNA methylation estimates of immune cell abundance have prognostic potential in triple negative breast cancer.Clinical epigenetics · 2026Article
- Article
- Which dominates recurrence: tumor or microenvironment?Journal of translational medicine · 2025Article
- Deciphering the Heterogeneity of Pancreatic Cancer: DNA Methylation-Based Cell Type Deconvolution Unveils Distinct Subgroups and Immune Landscapes.Epigenomes · 2025Article
- Retrotransposon methylation profiles and survival in Black women with high-grade serous ovarian carcinoma.Clinical epigenetics · 2025Article
- Deconer: An Evaluation Toolkit for Reference-based Deconvolution Methods Using Gene Expression Data.Genomics, proteomics & bioinformatics · 2025Article
- Quantitative proteomics analysis of triple-negative breast cancers.NPJ precision oncology · 2025Article
- Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations.STAR protocols · 2025Review
- MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model.Nature communications · 2025Article
- Advancing precision medicine: the transformative role of artificial intelligence in immunogenomics, radiomics, and pathomics for biomarker discovery and immunotherapy optimization.Cancer biology & medicine · 2025Review
- Normal gastric tissueEpigenetics reports · 2025Article
- Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data.Acta neuropathologica communications · 2024Article
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6 authors.
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Abstract
backgroundCellular compositions of solid tumor microenvironments are heterogeneous, varying across patients and tumor types. High-resolution profiling of the tumor microenvironment cell composition is crucial to understanding its biological and clinical implications. Previously, tumor microenvironment gene expression and DNA methylation-based deconvolution approaches have been shown to deconvolve major cell types. However, existing methods lack accuracy and specificity to tumor type and include limited identification of individual cell types.
resultsWe employed a novel tumor-type-specific hierarchical model using DNA methylation data to deconvolve the tumor microenvironment with high resolution, accuracy, and specificity. The deconvolution algorithm is named HiTIMED. Seventeen cell types from three major tumor microenvironment components can be profiled (tumor, immune, angiogenic) by HiTIMED, and it provides tumor-type-specific models for twenty carcinoma types. We demonstrate the prognostic significance of cell types that other tumor microenvironment deconvolution methods do not capture.
conclusionWe developed HiTIMED, a DNA methylation-based algorithm, to estimate cell proportions in the tumor microenvironment with high resolution and accuracy. HiTIMED deconvolution is amenable to archival biospecimens providing high-resolution profiles enabling to study of clinical and biological implications of variation and composition of the tumor microenvironment.
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