ArticleCancer research2022
Tumor Expression Quantitative Trait Methylation Screening Reveals Distinct CpG Panels for Deconvolving Cancer Immune Signatures.
Article in Cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- CGPA: A Multicontext Cancer Gene Prognosis Atlas.Molecular cancer research : MCR · 2026Article
- A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer.NPJ precision oncology · 2025Article
- Cuproptosis-related DNA methylation signature predict prognosis and immune microenvironment in cutaneous melanoma.Discover oncology · 2024Article
- Torch-eCpG: a fast and scalable eQTM mapper for thousands of molecular phenotypes with graphical processing units.BMC bioinformatics · 2024Article
- Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis.Frontiers in genetics · 2024Article
- Epigenetic regulation and therapeutic targets in the tumor microenvironment.Molecular biomedicine · 2023Review
- Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction.Biomarker research · 2023Review
- Multi-omics Data Deconvolution and Integration: New Methods, Insights, and Translational Implications.Methods in molecular biology (Clifton, N.J.) · 2023Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
DNA methylation signatures in tumors could serve as reliable biomarkers that are accessible in archival tissues for tracking the epigenetic dynamics shaped by both cancer cells and the tumor microenvironment. However, given the ultrahigh dimensionality and noncollapsible nature of the data, it remains challenging to screen all CpG sites to identify the most promising marker panels. In this article, we introduce the concept of tumor-based expression quantitative trait methylation (eQTM) for the prioritization and systematic mining of predictive biomarkers. In melanoma as a disease model, eQTM CpGs and genes represent new and efficient candidate targets to be investigated for both prognostic and immune status monitoring purposes. Three cis-eQTM CpGs (cg07786657, cg12446199, and cg00027570) were strongly associated with and can serve as surrogate biomarkers for the tumor immune cytolytic activity score (CYT). In addition, multiple eQTM genes could be further exploited for predicting immunoregulatory phenotypes. A targeted gene panel analysis identified one eQTM in TCF7 (cg25947408) as a novel candidate biomarker for uncoupling overall T-cell differentiation and exhaustion status in a tumor. The prognostic significance of this eQTM as an independent signature to CYT was validated by both The Cancer Genome Atlas and Moffitt melanoma cohort data. Overall, eQTMs represent a mechanistically distinct class of potential biomarkers that can be used to predict patient prognosis and immune status. SIGNIFICANCE: This study provides a novel and promising approach to identify targeted epigenetic biomarkers in cancer and will spur further analysis in tumor immune phenotyping.
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