Evidence map›Paper›PMID 42639287›Full record

ArticleNAR genomics and bioinformatics2026

Expression quantitative trait methylation across multiple cancer types with functional and therapeutic characterization using Onco-eQTM.

Bhanu Teja Korra, Mayilaadumveettil Nishana, Rahul Kumar

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Bhanu Teja KorraDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502284, India.ORCID https://orcid.org/0009-0005-3088-2854
Mayilaadumveettil NishanaSchool of Biology, Indian Institute of Science Education and Research, Thiruvananthapuram, Maruthamala P.O., Vithura, Kerala 695551, India.
Rahul KumarDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502284, India.ORCID https://orcid.org/0000-0002-6927-5390

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation plays a crucial role in gene expression and tumorigenesis. Most pan-cancer resources primarily focus on genetic variants and their association with gene expression without clearly demonstrating how methylation itself regulates gene activity and clinical features. To address this gap, we developed Onco-eQTM, a web-based database that links DNA methylation at CpG sites to gene regulation and multiple functional and clinical layers across 27 cancer types. These layers include miRNA regulation and biological pathways, as well as immune cell infiltration and predicted drug response, enabling both functional and therapeutic interpretation. We analyzed 6880 TCGA samples and identified 5.25 million CpG-gene associations. Beyond gene expression, Onco-eQTM links CpG methylation to 4.52 million miRNA-related associations, 14.45 million drug-response associations, 13.6 million pathway activity associations from PARADIGM, and 3.55 million immune-infiltration associations covering 68 immune cell types. The database enables users to visualize how methylation impacts these biological and clinical factors. Onco-eQTM enables researchers to gain a deeper understanding of cancer-related methylation changes and identify potential therapeutic targets. The database is freely available at https://project.iith.ac.in/cgntlab/OncoeQTM/.

Indexed as

Databases, GeneticDNA MethylationGene Expression Regulation, NeoplasticNeoplasmsQuantitative Trait LociCpG IslandsHumansMicroRNAsMicroRNAs

Identifiers

PMID42639287
PMCPMC13501137

What OpenQuestion holds

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Registered trials

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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.