Evidence map›Paper›PMID 39397186›Full record

ArticleDiscover oncology2024

Immunotherapy and pan-apoptotic characterization of the tumor microenvironment in gastric cancer (STAD): a single-cell multidimensional analysis.

Sheng Zhang, Jianhong Wang, Huan Zhang, Benhua Li, Shun Gao

Abstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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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

2 citing papers in PubMed.

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4 · The record

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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.

Sheng ZhangDepartment of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, China.
Jianhong WangDepartment of Internal Medicine, Guang'an Vocational & Technical College, Guang'an, 638000, China.
Huan ZhangDepartment of Internal Medicine, Guang'an Vocational & Technical College, Guang'an, 638000, China.
Benhua LiDepartment of Clinical Laboratory, The Second People's Hospital of Liangshan yi Autonomous Prefecture, Xichang, 615000, China.
Shun GaoDepartment of Medical Affairs, Renshou County People's Hospital, Meishan, 620500, China. gscurryshun@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to elucidate the critical role of autophagy-related gene aggregation in gastric cancer tumor microenvironment cells and to investigate their major roles in cellular functions. In particular, the expression of these genes in tumor-associated fibroblast subtypes was scrutinized in an attempt to explain their cell-subpopulation-specific roles in cell-cell communication and regulation of cellular functions.

methodsIn this study, single-cell RNA sequencing data were first analyzed in multiple steps, including data preprocessing, cell clustering, and cell classification. Cell subpopulations and gene expression patterns were identified and analyzed using unsupervised non-negative matrix factorization (NMF) techniques. The dynamic expression of autophagy-related gene aggregates in various cell types was deciphered by pseudotime trajectory analysis (PTA). Intercellular communication analysis was performed using the CellChat R software package, revealing the intricate communication patterns and exchange of key signaling molecules between cell subpopulations, and SCENIC analysis was used to identify gene regulatory networks and reveal the mechanisms behind cellular heterogeneity.

resultCell subpopulations associated with pan-apoptosis were identified by NMF decomposition and SCENIC analysis. Cell-cell communication analysis revealed intricate communication patterns and exchange of key signaling molecules between cell subpopulations. Dynamic expression of autophagy-related genes aggregated in the pseudotemporal trajectory of STAD was observed by PTA. In the fibroblast subtype, different ligand-receptor interactions and their key roles in immunomodulation were observed.

conclusionBy deeply analyzing and comparing gene expression patterns within cellular subpopulations and intercellular communication, this study provides new insights into the role of pan-apoptosis-related genes in regulating immune responses and cellular functions in gastric cancer. These findings pave the way for further exploration of the role of these genes in tumorigenesis and immune regulation, as well as laying the foundation for potential therapeutic strategies.

Indexed as

ImmunotherapyMolecular markerNon-negative matrix factorizationPan-apoptosisSingle-cellStomach cancer

Identifiers

PMID39397186
PMCPMC11471748

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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.