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pmid:33416081

Tumor microenvironment characterization in stage IV gastric cancer.

Xianxue Zhang · Feng Yang · Zhenbao Wang

Bioscience reports · 2021 doi:10.1042/BSR20201248

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Experiment

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Data

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Tumor microenvironment characterization in stage IV gastric cancer.
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10.1042/BSR20201248
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33416081
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Xianxue Zhang
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Feng Yang
[2]
Zhenbao Wang
journal
Bioscience reports
year
2021
abstract
Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment's clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. The identification of stage IV GC subtypes has potential clinical implications in stage IV GC treatment.
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The importance of survival time difference was calculated using the log-rank test and a threshold P-value <0.05.
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sections[19] "Data Availability" paragraph 2
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The datasets analyzed for the present study can be found in the GEO (http://www.ncbi.nlm.nih.gov/geo) and TCGA (https://www.cancer.gov).
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Molecular analysis of gastric cancer identifies discrete subtypes associated with distinct clinical characteristics and survival outcomes: the ACRG (Asian Cancer Research Group) study [gastric tumors]
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6947
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Homo sapiens
title
Molecular subtypes in gastric cancer.
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2026-11-01T15:39:55Z
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identifier_resolution_only_no_download_no_licence_read
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Summary of patient demographics and characteristics
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Stage IV GC sample datasets
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Table 1
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Summary of patient demographics and characteristics
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[3]
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36 (46.8%)
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197 (67.5%)
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21 (58.3%)
[3]
41 (53.2%)
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[2]
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[0]
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[1]
122 (41.8%)
[2]
14 (38.9%)
[3]
32 (41.6%)
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[0]
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170 (58.2%)
[2]
22 (62.1%)
[3]
45 (58.4%)
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IV
[1]
292 (100%)
[2]
36 (100%)
[3]
77 (100%)
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[2]
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130 (44.5%)
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11 (32.3%)
[3]
31 (40.3%)
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section[3]/table-wrap[1]#T1
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[0]
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[3]
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The importance of survival time difference was calculated using the log-rank test and a threshold P-value <0.05.
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
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[0]
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[0]
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[0]
The datasets analyzed for the present study can be found in the GEO (http://www.ncbi.nlm.nih.gov/geo) and TCGA (https://www.cancer.gov).
basis
The paper names GSE84437, GSE62254 in GEO (Gene Expression Omnibus) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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f2132e96ae6c7a4e
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The importance of survival time difference was calculated using the log-rank test and a threshold P-value <0.05.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33416081", "kind": "science-record", "revision": 6, "content_hash": "sha256:8e6176a55e43493d7f7170251c1e28d45df657004c57aaf7244afa5904174b0a", "created_at": "2026-11-01T15:41:22Z", "updated_at": "2026-11-01T21:24:28Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Tumor microenvironment characterization in stage IV gastric cancer.", "doi": "10.1042/BSR20201248", "pmid": "33416081", "authors": ["Xianxue Zhang", "Feng Yang", "Zhenbao Wang"], "journal": "Bioscience reports", "year": 2021, "abstract": "Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment's clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE62254"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE62254"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33416081", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1042/BSR20201248", "sha256": 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