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pmid:34771544

The Epithelial and Stromal Immune Microenvironment in Gastric Cancer: A Comprehensive Analysis Reveals Prognostic Factors with Digital Cytometry.

Wenjun Shen · Guoyun Wang · Georgia R Cooper · Yuming Jiang · Xin Zhou

Cancers · 2021 doi:10.3390/cancers13215382

Paper

complete

Experiment

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Data

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Analysis

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title
The Epithelial and Stromal Immune Microenvironment in Gastric Cancer: A Comprehensive Analysis Reveals Prognostic Factors with Digital Cytometry.
doi
10.3390/cancers13215382
pmid
34771544
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Wenjun Shen
[1]
Guoyun Wang
[2]
Georgia R Cooper
[3]
Yuming Jiang
[4]
Xin Zhou
journal
Cancers
year
2021
abstract
Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Tumor heterogeneity continues to confound researchers' understanding of tumor growth and the development of an effective therapy. Digital cytometry allows interpretation of heterogeneous bulk tissue transcriptomes at the cellular level. We built a novel signature matrix to dissect epithelium and stroma signals using a scRNA-seq data set (GSE134520) for GC and then applied cell mixture deconvolution to estimate diverse epithelial, stromal, and immune cell proportions from bulk transcriptome data in four independent GC cohorts (GSE62254, GSE15459, GSE84437, and TCGA-STAD) from the GEO and TCGA databases. Robust computational methods were applied to identify strong prognostic factors for GC. We identified an EMEC population whose proportions were significantly higher in patients with stage I cancer than other stages, and it was predominantly present in tumor samples but not typically found in normal samples. We found that the ratio of EMECs to stromal cells and the ratio of adaptive T cells to monocytes were the most significant prognostic factors within the non-immune and immune factors, respectively. The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89-0.94, p=2.05×10-9). The entire GC cohort was stratified into three risk groups (high-, moderate-, and low-risk), which yielded incremental survival times (p<0.0001). For stage III disease, patients in the moderate- and low-risk groups experienced better survival benefits from radiation therapy ((HR = 0.16, 95% CI = 0.06-0.4, p<0.0001), whereas those in the high-risk group did not (HR = 0.49, 95% CI = 0.14-1.72, p=0.25). We concluded that the STEM score is a promising prognostic factor for gastric cancer.
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We performed multivariate Cox regression analysis of the STEM score correcting for clinicopathological variables, including age, sex, stage, Lauren histology, and adjuvant chemotherapy treatment.
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We performed multivariate Cox regression analysis of the STEM score correcting for clinicopathological variables, including age, sex, stage, Lauren histology, and adjuvant chemotherapy treatment.
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The data analyzed in this study are available from the Gene Expression Omnibus (accession numbers: GSE62254; GSE15459; GSE84437; GSE134520), The Cancer Genome Atlas Project, or from the authors upon reasonable request.
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The data analyzed in this study are available from the Gene Expression Omnibus (accession numbers: GSE62254; GSE15459; GSE84437; GSE134520), The Cancer Genome Atlas Project, or from the authors upon reasonable request.
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The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89–0.94, p=2.05×10−9).
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The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89–0.94, p=2.05×10−9).
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The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89–0.94, p=2.05×10−9).
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The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89–0.94, p=2.05×10−9).
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sample_count
300
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
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]
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE84437
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84437
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE84437
version
null
note
The data analyzed in this study are available from the Gene Expression Omnibus (accession numbers: GSE62254; GSE15459; GSE84437; GSE134520), The Cancer Genome Atlas Project, or from the authors upon reasonable request.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The data analyzed in this study are available from the Gene Expression Omnibus (accession numbers: GSE62254; GSE15459; GSE84437; GSE134520), The Cancer Genome Atlas Project, or from the authors upon reasonable request.
access_statement_kind
data_availability_statement
sample_accessions array · 483 items
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[286]
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[370]
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[384]
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[385]
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[390]
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[391]
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[393]
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[394]
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[395]
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[396]
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[397]
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[398]
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[399]
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[400]
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[415]
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[481]
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[482]
GSM4419533
sample_count
483
group_sizes
null
group_sizes_basis
null
platform
6947
taxon
Homo sapiens
title
Molecular subtypes in gastric cancer.
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE134520 not downloaded
[1]
asset:data:geo:GSE134520 licence not read
[2]
asset:data:geo:GSE15459 not downloaded
[3]
asset:data:geo:GSE15459 licence not read
[4]
asset:data:geo:GSE62254 not downloaded
[5]
asset:data:geo:GSE62254 licence not read
[6]
asset:data:geo:GSE84437 not downloaded
[7]
asset:data:geo:GSE84437 licence not read
analysis object · 4 fields
state
complete
methods array · 2 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
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interpretation of heterogeneous bulk tissue transcriptomes at the cellular level. We built a novel sign
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Digital cytometry allows interpretation of heterogeneous bulk tissue transcriptomes at the cellular level. We built a novel signature matrix to dissect epithelium and stroma signals using a scRNA-seq data set (GSE134520) for GC and then applied cell mixture deconvolution to estimate diverse epithelial, stromal, and immune cell proportions from bulk transcriptome data in four independent GC cohorts (GSE62254, GSE15459, GSE84437, and TCGA-STAD) from the GEO and TCGA databases. Robust computational methods were applied to identify strong prognostic factors for GC. We identified an EMEC population whose proportions were significantly higher in patients with stage I cancer than other stages, and it was predominantly present in tumor samples but not typically found in normal samples. We found that the ratio of EMECs to stromal cells and the ratio of adaptive T cells to monocytes were the most significant prognostic factors within the non-immune and immune factors, respectively. The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89-0.94, p=2.05×10-9). The entire GC cohort was stratified into three risk groups (high-, moderate-, and low-risk), which yielded incremental survival times (p<0.0001). For stage III disease, patients in the moderate- and low-risk groups experienced better survival benefits from radiation therapy ((HR = 0.16, 95% CI = 0.06-0.4, p<0.0001), whereas those in the high-risk group did not (HR = 0.49, 95% CI = 0.14-1.72, p=0.25). 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No tolerance is published because the paper states none."}, {"id": "target-published-estimate-hazard-ratio", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 0.92, "unit": "hazard ratio", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}, {"id": "target-published-estimate-p-value", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 2.05, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. 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