Evidence map›Paper›PMID 37781029›Full record

ArticleInternational journal of biological sciences2023

CD36-BATF2\MYB Axis Predicts Anti-PD-1 Immunotherapy Response in Gastric Cancer.

Qiuyu Jiang, Zhixue Chen, Fansheng Meng, Hao Zhang, He Chen, Jindan Xue, Xizhong Shen, Tianshu Liu, Ling Dong, Si Zhang and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
6.0field-weighted citation impact, top 3% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  3. Predictors of immunotherapy response in gastric cancer: the role of the tumor microenvironment and integrative predictive models.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  19. A CLRN3-Based CD8Biomolecules · 2024
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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

11 authors at 3 institutions in 1 country.

Qiuyu JiangDepartment of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Zhixue ChenDepartment of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Fansheng MengLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Hao ZhangDepartment of Oncology, Minhang Hospital, Fudan University, China.
He ChenDepartment of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Jindan XueSchool of Medicine, Anhui University of Science and Technology, Anhui, 232000, China.
Xizhong ShenDepartment of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Tianshu LiuDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Ling DongDepartment of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Si ZhangNHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Ruyi XueDepartment of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Fudan University · CNZhongshan Hospital · CNAnhui University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the utilization of anti-PD-1 therapy in gastric cancer (GC), the absence of a reliable predictive biomarker continues to pose a challenge. In this study, we utilized bioinformatic analysis and immunohistochemistry to develop a prediction model for activated CD4+ memory T cells, considering both mRNA and protein levels. An elevation of activated CD4+ memory T cells in GC was noted, which exhibited a strong association with the patients' overall survival. By utilizing WGCNA and DEG analysis, we discovered that BATF2, MYB, and CD36 are genes that exhibit differential expression and are linked to activated CD4+ memory T cells. Afterwards, a forecast model was built utilizing Stepwise regression and immunohistochemistry relying on the three genes. The model's high-risk score showed significant associations with a suppressive immune microenvironment. Moreover, our model exhibited encouraging prognostic value and superior performance in predicting response to immune checkpoint blockade therapy compared with the conventional CD8+PD-L1 model. In terms of mechanism, CD36 could function as a receptor upstream that identifies Helicobacter pylori and fatty acids. This recognition then results in the reduction of the BATF2-MYB protein complex and subsequent alterations in the transcription of genes associated with classical T cell activation. As a result, the activation state of CD4+ memory T cells is ultimately suppressed. The CD36-BATF2/MYB signature serves as a robust predictor of anti-PD-1 immunotherapy response in GC.

Indexed as

Stomach NeoplasmsB7-H1 AntigenBiomarkersCD4-Positive T-LymphocytesHumansImmunohistochemistryImmunotherapyTumor MicroenvironmentB7-H1 AntigenBiomarkersActivated CD4+ memory T cellsGastric cancerImmune cell related genesImmunotherapyPrognosisRisk signature

Identifiers

PMID37781029
PMCPMC10535701
OpenAlexW4386262779

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.