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pmid:35116249

A bioinformatics analysis to evaluate the prognostic value of stemness-related genes in gastric cancer.

Yu-Jie Lu · Lian Lian · Xiao-Ming Shen · Ying Li · Sheng-Jun Ji · Wen-Jie Wang · Yi Yang · Ying Wang · Wei-Ming Duan

Translational cancer research · 2021 doi:10.21037/tcr-20-2622

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

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pmid:35116249
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title
A bioinformatics analysis to evaluate the prognostic value of stemness-related genes in gastric cancer.
doi
10.21037/tcr-20-2622
pmid
35116249
authors array · 9 items
[0]
Yu-Jie Lu
[1]
Lian Lian
[2]
Xiao-Ming Shen
[3]
Ying Li
[4]
Sheng-Jun Ji
[5]
Wen-Jie Wang
[6]
Yi Yang
[7]
Ying Wang
[8]
Wei-Ming Duan
journal
Translational cancer research
year
2021
abstract
BACKGROUND: This study aimed to identify potential stemness-related targets in gastric cancer (GC) in order to support the development of new treatment strategies and improve patient survival. METHODS: Using the edgeR package, we identified stemness-related differentially expressed genes (DEGs) using GSE112631 and the stemness-related signaling pathways in the Gene Set Enrichment Analysis (GSEA) database. Lasso-penalized Cox regression analysis and multivariate Cox regression analysis tested by Akaike Information Criterion (AIC) were used to screen out survival genes in order to construct a prognostic model. We verified the accuracy of our prognostic model using a nomogram and receiver operating characteristic (ROC) curve analysis. Patients were divided into two groups based on the median risk score, and functional enrichment analysis was used to explore the differences between the two groups. RESULTS: Eight genes were selected to establish a prognostic model of The Cancer Genome Atlas (TCGA) and a validation model of the GSE84437 dataset from the Genome Expression Omnibus (GEO). In both models, we found that the low risk score group had better overall survival (OS) than the high-risk score group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between the two risk groups were totally different. CONCLUSIONS: We used eight stemness-related genes to build a prognostic model. The high-risk score group had a worse prognosis compared to the low-risk score group.
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A prognostic risk score was obtained for all patients by lasso-penalized Cox regression and multivariate Cox regression analysis.
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A prognostic risk score was obtained for all patients by lasso-penalized Cox regression and multivariate Cox regression analysis.
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All information from TCGA, GSEA and GEO is available and free for public, so the agreement of the medical ethics committee board was not necessary.
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The low-risk score group had a better overall survival (OS) than the high-risk score group (P<0.001; Figure 3A).
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sections[13] "Construction of the stemness-related gene prognostic model" paragraph 6
quote
The low-risk score group had a better overall survival (OS) than the high-risk score group (P<0.001; Figure 3A).
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sections[13] "Construction of the stemness-related gene prognostic model" paragraph 6
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In the validation model, the OS in the low-risk score group was longer than that in the high-risk score group (P=0.047; Figure 3B).
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The low-risk score group had a better overall survival (OS) than the high-risk score group (P<0.001; Figure 3A).
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[482]
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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
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licence_read
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[1]
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[2]
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[3]
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A prognostic risk score was obtained for all patients by lasso-penalized Cox regression and multivariate Cox regression analysis.
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Survival analysis
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specific
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candidate
Automated Assays Laravel application and simulated adapters
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blocked_on
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basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
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tier
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availability_state
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basis
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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statements array · 1 item
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basis
The paper names GSE84437, GSE112631 in Genome Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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review object · 5 fields
state
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kind
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provider
minimax
provider_family
minimax
read_at
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independence
single_reader
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method
verbatim
availability
verbatim
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extraction
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paper
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GEO GSE112631
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type
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PMID 35116249 full text
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GEO GSE112631
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A prognostic risk score was obtained for all patients by lasso-penalized Cox regression and multivariate Cox regression analysis.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35116249", "kind": "science-record", "revision": 6, "content_hash": "sha256:413974e8787fab3ad353ed114b4e8e310aaa322a39f11eb4257ff1cafadec309", "created_at": "2026-11-01T17:36:50Z", "updated_at": "2026-11-01T22:48:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A bioinformatics analysis to evaluate the prognostic value of stemness-related genes in gastric cancer.", "doi": "10.21037/tcr-20-2622", "pmid": "35116249", "authors": ["Yu-Jie Lu", "Lian Lian", "Xiao-Ming Shen", "Ying Li", "Sheng-Jun Ji", "Wen-Jie Wang", "Yi Yang", "Ying Wang", "Wei-Ming Duan"], "journal": "Translational cancer research", "year": 2021, "abstract": "BACKGROUND: This study aimed to identify potential stemness-related targets in gastric cancer (GC) in order to support the development of new treatment strategies and improve patient survival.\nMETHODS: Using the edgeR package, we identified stemness-related differentially expressed genes (DEGs) using GSE112631 and the stemness-related signaling pathways in the Gene Set Enrichment Analysis (GSEA) database. Lasso-penalized Cox regression analysis and multivariate Cox regression analysis tested by Akaike Information Criterion (AIC) were used to screen out survival genes in order to construct a prognostic model. We verified the accuracy of our prognostic model using a nomogram and receiver operating characteristic (ROC) curve analysis. Patients were divided into two groups based on the median risk score, and functional enrichment analysis was used to explore the differences between the two groups.\nRESULTS: Eight genes were selected to establish a prognostic model of The Cancer Genome Atlas (TCGA) and a validation model of the GSE84437 dataset from the Genome Expression Omnibus (GEO). In both models, we found that the low risk score group had better overall survival (OS) than the high-risk score group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between the two risk groups were totally different.\nCONCLUSIONS: We used eight stemness-related genes to build a prognostic model. The high-risk score group had a worse prognosis compared to the low-risk score group.", "claims": [{"id": "claim-method", "statement": "A prognostic risk score was obtained for all patients by lasso-penalized Cox regression and multivariate Cox regression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35116249", "locator": "sections[6] \"Establishment of a prognostic model and validation model\" paragraph 2", "quote": "A prognostic risk score was obtained for all patients by lasso-penalized Cox regression and multivariate Cox regression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All information from TCGA, GSEA and GEO is available and free for public, so the agreement of the medical ethics committee board was not necessary.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35116249", "locator": "sections[9] \"Statistical analysis\" paragraph 2", "quote": "All information from TCGA, GSEA and GEO is available and free for public, so the agreement of the medical ethics committee board was not necessary."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The low-risk score group had a better overall survival (OS) than the high-risk score group (P<0.001; Figure 3A).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35116249", "locator": "sections[13] \"Construction of the stemness-related gene prognostic model\" paragraph 6", "quote": "The low-risk score group had a better overall survival (OS) than the high-risk score group (P<0.001; Figure 3A)."}, {"asset": "source:pmid:35116249", "locator": "sections[13] \"Construction of the stemness-related gene prognostic model\" paragraph 6", "quote": "In the validation model, the OS in the low-risk score group was longer than that in the high-risk score group (P=0.047; Figure 3B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The low-risk score group had a better overall survival (OS) than the high-risk score group (P<0.001; Figure 3A).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35116249"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE112631"], "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:GSE112631"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35116249", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-20-2622", "sha256": 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necessary.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All information from TCGA, GSEA and GEO is available and free for public, so the agreement of the medical ethics committee board was not necessary.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3074620", "GSM3074621", "GSM3074622", "GSM3074623", "GSM3074624", "GSM3074625", "GSM3074626", "GSM3074627", "GSM3074628", "GSM3074629", "GSM3074630", "GSM3074631"], "sample_count": 12, "group_sizes": null, "group_sizes_basis": null, "platform": "10904", "taxon": "Homo sapiens", "title": "Expression of FACS-sorted CD133+ and CD133- cells of three gastric cell lines", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE84437", "role": "raw", "format": "geo-series", "media_type": 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