COL5A2 is a prognostic-related biomarker and correlated with immune infiltrates in gastric cancer based on transcriptomics and single-cell RNA sequencing.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37723519", "kind": "science-record", "revision": 4, "content_hash": "sha256:4c1dd37e5484027899ca61b37681647b10f734abad9969539252fe5f1b0c315c", "created_at": "2026-11-01T19:02:33Z", "updated_at": "2026-11-01T22:10:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "COL5A2 is a prognostic-related biomarker and correlated with immune infiltrates in gastric cancer based on transcriptomics and single-cell RNA sequencing.", "doi": "10.1186/s12920-023-01659-9", "pmid": "37723519", "authors": ["Meiru Chen", "Xinying Zhu", "Lixian Zhang", "Dongqiang Zhao"], "journal": "BMC medical genomics", "year": 2023, "abstract": "BACKGROUND: There is still a therapeutic challenge in treating gastric cancer (GC) due to its high incidence and poor prognosis. Collagen type V alpha 2 (COL5A2) is increased in various cancers, yet it remains unclear how it contributes to the prognosis and immunity of GC.\nMETHODS: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to download transcriptome profiling (TCGA-STAD; GSE84437), single-cell RNA sequencing (scRNA-seq) data (GSE167297) and clinical information. COL5A2 expression and its relationship with clinicopathological factors were analyzed. We conducted survival analysis and Cox regression analysis to evaluate the prognosis and independent factors of GC. Co-expressed analysis was also performed. To identify the underlying mechanism, we conducted analyses of differentially expressed genes (DEGs) and functional enrichment. The correlations between COL5A2 expression and immune cell infiltration levels and immune infiltrate gene marker sets were further explored. Additionally, we analyzed the association of COL5A2 expression with immunological checkpoint molecules. Furthermore, the relationship between COL5A2 expression and immunotherapy sensitivity was also investigated.\nRESULTS: COL5A2 expression was elevated in GC. More than this, the scRNA-seq analysis revealed that COL5A2 expression had a spatial gradient. The upregulated COL5A2 was associated with worse overall survival. A significant correlation was found between COL5A2 overexpression and age, T classification and clinical stage in GC. COL5A2 was found to be an independent factor for the unfortunate outcome in Cox regression analysis. The co-expressed genes of COL5A2 were associated with tumor stage or poor survival. Enrichment analysis revealed that the DEGs were mainly associated with extracellular matrix (ECM)-related processes, PI3K-AKT signaling pathway, and focal adhesion. GSEA analyses revealed that COL5A2 was associated with tumor progression-related pathways. Meanwhile, COL5A2 expression was correlated with tumor-infiltrating immune cells. Moreover, immunophenoscore (IPS) analysis and PRJEB25780 cohorts showed that patients with low COL5A2 expression were highly sensitive to immunotherapy.\nCONCLUSIONS: COL5A2 might act as a prognostic biomarker of GC prognosis and immune infiltration and may provide a therapeutic intervention strategy.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37723519", "locator": "sections[7] \"Survival and significant prognostic marker analyses of COL5A2\" paragraph 2", "quote": "Univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). These data are free and publicly available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37723519", "locator": "sections[31] \"Availability of data and materials\" paragraph 2", "quote": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). These data are free and publicly available."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Survival rates were significantly lower in the group with high COL5A2 expression (p = 0.013, Fig. 4a).", "kind": "quantitative", "target": {"value": 0.013, "unit": "p-value", "tolerance": null, "source": "Notably, survival rates were significantly lower in the group with high COL5A2 expression (p = 0.013, Fig. 4a)."}, "evidence": [{"asset": "source:pmid:37723519", "locator": "sections[17] \"COL5A2 was an independent adverse prognostic factor in GC\" paragraph 2", "quote": "Notably, survival rates were significantly lower in the group with high COL5A2 expression (p = 0.013, Fig. 4a)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Survival rates were significantly lower in the group with high COL5A2 expression (p = 0.013, Fig. 4a).", "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:37723519"], "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:GSE167297"], "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:GSE167297"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37723519", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-023-01659-9", "sha256": "sha256:802bf6ce9415cea4653ae7a74d13f0f88f0080c6561c0f4f46022fece18e7625", "bytes": 62808, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-023-01659-9", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10506210", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE167297", "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=GSE167297", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE167297", "version": null, "note": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). These data are free and publicly available.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). These data are free and publicly available.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM5101013", "GSM5101014", "GSM5101015", "GSM5101016", "GSM5101017", "GSM5101018", "GSM5101019", "GSM5101020", "GSM5101021", "GSM5101022", "GSM5101023", "GSM5101024", "GSM5101025", "GSM5101026"], "sample_count": 14, "group_sizes": null, "group_sizes_basis": null, "platform": "20301", "taxon": "Homo sapiens", "title": "Spatially distinct reprogramming of the tumor microenvironment based on tumor invasion in diffuse-type gastric cancers", "resolution_checked_at": "2026-11-01T19:09:46Z", "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": "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 generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). These data are free and publicly available.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). 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"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}}, {"id": "data:geo:PRJEB25780", "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=PRJEB25780", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "PRJEB25780", "version": null, "note": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). These data are free and publicly available.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data generated and analyzed during this study are described in the following data record: 10.6084/m9.figshare.23647089 [72]. The datasets used and analyzed during the current study are available from the cancer genome database (TCGA-STAD) https://portal.gdc.cancer.gov and NCBI Gene Expression Omnibus (GEO: GSE84437) https://www.ncbi.nlm.nih.gov/geo/. Single-cell RNA sequencing (scRNA-seq) data GSE167297 was downloaded from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167297. RNA-Seq data PRJEB25780 were downloaded from ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB25780). 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