Evidence map›Paper›PMID 42694682›Full record

ReviewFrontiers in immunology2026

Lipid metabolism and the immune microenvironment in gastric cancer.

Zhuoyang Wang, Yichen Du, Qinglin Gu, Xinjie Liu, Ming Lu

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 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

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.

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

5 authors.

Zhuoyang Wang *First Clinical Medical College, Anhui Medical University, Hefei, Anhui, China.
Yichen Du *First Clinical Medical College, Anhui Medical University, Hefei, Anhui, China.
Qinglin GuSecond Clinical Medical College, Anhui Medical University, Hefei, Anhui, China.
Xinjie LiuFirst Clinical Medical College, Anhui Medical University, Hefei, Anhui, China.
Ming LuDepartment of Immunology, School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The treatment of gastric cancer (GC) has entered an era of precision medicine combining molecular subtyping, immune checkpoint inhibitors (ICIs), anti-human epidermal growth factor receptor 2 (HER2), anti-claudin 18.2 (CLDN18.2), anti-angiogenic therapy, and chemotherapy. However, efficacy remains limited by tumor microenvironment (TME) heterogeneity, immune exclusion, myeloid suppression, nutrient competition, and metabolic adaptation. Lipid metabolic reprogramming represents a class of mechanisms with high translational value among metabolic immune checkpoints in GC: it supports tumor-cell membrane synthesis, redox homeostasis, peritoneal/omental metastasis, and adaptation to therapeutic stress, while also affecting regulatory T cells (Tregs), tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), dendritic cells, and CD8+ T cells. This review focuses on cluster of differentiation 36 (CD36)-mediated fatty acid uptake; carnitine palmitoyltransferase 1A (CPT1A)-dependent fatty acid oxidation (FAO); fatty acid synthase (FASN), acetyl-CoA carboxylase (ACC), sterol regulatory element-binding protein 1 (SREBP-1), and stearoyl-CoA desaturase 1 (SCD1)-mediated

Indexed as

Lipid MetabolismStomach NeoplasmsTumor MicroenvironmentAnimalsHumansMetabolic ReprogrammingCD36fatty acid oxidationfatty acid synthasegastric cancerimmunotherapy resistancelipid metabolismsaturated and unsaturated fatty acidssterol regulatory element-binding protein 1

Identifiers

PMID42694682
PMCPMC13539484

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.