Evidence map›Paper›PMID 41177810›Full record

ArticleExperimental & molecular medicine2025

EHBMT, a method for visualizing tumor evolution, identifies a surge in gastric cancer with hybrid epithelial-mesenchymal phenotypes due to an inflammatory microenvironment.

Dandan Li, Zeng Zhou, Yuanjian Hui, Hedong Yu, Tao Ren, Lantian Zhai, Xinqi Li, Lin Yuan, Lingyun Xia, Weidong Leng and 1 more

Abstract read
In one paragraph

Article in Experimental & molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Dandan Li *Department of Stomatology, Taihe Hospital and Hubei Key Laboratory of Embryonic Stem Cell Research, School of Basic Medical Sciences, Hubei University of Medicine, Shiya, People's Republic of China.
Zeng Zhou *Laboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Yuanjian HuiLaboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Hedong YuLaboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Tao RenLaboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Lantian ZhaiLaboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Xinqi LiLaboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Lin YuanLaboratory of Tumor Biology, Academy of Bio-Medicine Research, Hubei University of Medicine, Shiyan, People's Republic of China.
Lingyun XiaDepartment of Stomatology, Taihe Hospital and Hubei Key Laboratory of Embryonic Stem Cell Research, School of Basic Medical Sciences, Hubei University of Medicine, Shiya, People's Republic of China.
Weidong LengDepartment of Stomatology, Taihe Hospital and Hubei Key Laboratory of Embryonic Stem Cell Research, School of Basic Medical Sciences, Hubei University of Medicine, Shiya, People's Republic of China. lwd35@163.com.
Shanshan QinDepartment of Stomatology, Taihe Hospital and Hubei Key Laboratory of Embryonic Stem Cell Research, School of Basic Medical Sciences, Hubei University of Medicine, Shiya, People's Republic of China. qinss77@163.com.ORCID http://orcid.org/0000-0002-8527-5278

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82203829National Natural Science Foundation of China (National Science Foundation of China) 82273451Natural Science Foundation of Hubei Province (Hubei Provincial Natural Science Foundation) 2023AFB842
6 · The paper itself

Abstract

A method for analyzing tumor evolution based on bulk RNA-sequencing data has not been reported yet. The epithelial-mesenchymal transition (EMT) is an evolutionarily conserved cellular program with high heterogeneity and plasticity. In this study, we proposed an EMT heterogeneity-based molecular typing (EHBMT) method to visualize cancer evolution and guide personalized medicine. Multiplex immunohistochemical assay and single-cell analysis were performed to confirm the feasibility of this method. EHBMT divided gastric (cancer) tissues into an epithelial phenotype cluster (EPC), hybrid epithelial-mesenchymal phenotype cluster (HPC) and mesenchymal phenotype cluster (MPC). Patients with gastric cancer with different EHBMT subtypes possessed distinct clinical features, molecular characteristics and prognostic outcomes. Furthermore, the proliferation ability of EPC, HPC and MPC subtypes decreases sequentially. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analysis showed that HPC subtypes are associated with inflammation and immune activation. More importantly, EHBMT discovered a sharp increase in the proportion of the HPC subtype during gastric cancer evolution. Traceability analysis indicated that the surge in HPC in gastric cancer was due to the transition from approximately 70-80% of normal EPC cases to cancerous HPC/MPC cases. In addition, the inflammatory factor IL-1β, highly expressed epithelial cells in the HPC subtype, should be a key driver for the decrease of epithelial cells by inducing EMT signaling. In conclusion, EHBMT is a novel method for visualizing cancer evolution using bulk transcriptomics. Gastric carcinogenesis is accompanied by a sharp increase in the proportion of HPC due to the abnormal EMT signaling pathway driven by an inflammatory microenvironment.

Indexed as

Epithelial-Mesenchymal TransitionInflammationStomach NeoplasmsTumor MicroenvironmentBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPhenotypePrognosisBiomarkers, Tumor

Identifiers

PMID41177810
PMCPMC12686072

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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.