Evidence map›Paper›PMID 41836024›Full record

SynthesisFrontiers in pharmacology2026

Novel roles of SETD2 in tumor metabolism and immunotherapy: a systematic review and meta-analysis.

Chunhui Liu, Lei Lin, Yonggang Fan

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in pharmacology, 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
–field-weighted citation impact
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.

Chunhui LiuThe First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology., Luoyang, China.
Lei LinLuoyang Central Hospital Affiliated to Zhengzhou University, Luoyang, China.
Yonggang FanThe First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology., Luoyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: SET domain-containing 2 (SETD2), the sole histone H3 lysine 36 trimethyltransferase, has emerged as a critical tumor suppressor across multiple cancer types. Recent evidence suggests SETD2 orchestrates complex interactions between metabolic reprogramming and immune evasion in the tumor microenvironment. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)2020 guidelines, we systematically searched PubMed, EMBASE, Web of Science, and Cochrane databases from inception through April 2024. We included studies investigating SETD2's role in tumor metabolism and immunotherapy response. Meta-analysis was performed using random-effects models to assess the association between SETD2 status and clinical outcomes. Protocol was developed Results: Of 2,847 initially identified records, 78 studies met inclusion criteria, encompassing approximately 12,400 patients across 12 cancer types. SETD2 loss was associated with metabolic reprogramming (pooled OR: 2.34, 95% confidence interval (CI): 1.89-2.89, p < 0.001) and decreased immunotherapy response (hazard ratio (HR): 1.56, 95% CI: 1.32-1.84, p < 0.001). Substantial heterogeneity was observed (I-squared heterogeneity statistic (I Conclusion: This meta-analysis identifies SETD2 as an epigenetic regulator linking tumor metabolic reprogramming to antitumor immunity. SETD2 loss was associated with altered metabolic states and reduced clinical benefit from immune checkpoint inhibitors, with the strongest translational relevance observed in ccRCC and substantial evidence in NSCLC and CRC. These findings support further prospective validation and standardized assessment of SETD2, as well as exploration of rational metabolic-immunotherapy combination strategies in SETD2-deficient tumors.

Indexed as

epigeneticsH3K36me3immunotherapySETD2systematic reviewtumor metabolism

Identifiers

PMID41836024
PMCPMC12983094

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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.