Identification of Key Genes Associated with Tumor Microenvironment Infiltration and Survival in Gastric Adenocarcinoma via Bioinformatics Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38610959", "kind": "science-record", "revision": 2, "content_hash": "sha256:87ee3629f2af5009a9de4011e5e9c93ba3cabb841fb9d34128d01016bcc9a5e4", "created_at": "2026-11-01T19:20:34Z", "updated_at": "2026-11-01T21:32:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Key Genes Associated with Tumor Microenvironment Infiltration and Survival in Gastric Adenocarcinoma via Bioinformatics Analysis.", "doi": "10.3390/cancers16071280", "pmid": "38610959", "authors": ["Georgios Konstantis", "Georgia Tsaousi", "Chryssa Pourzitaki", "Stefan Kasper-Virchow", "Gregor Zaun", "Elisavet Kitsikidou", "Moritz Passenberg", "Vasilis Spyridon Tseriotis", "Katharina Willuweit", "Hartmut H Schmidt", "Jassin Rashidi-Alavijeh"], "journal": "Cancers", "year": 2024, "abstract": "OBJECTIVE: Gastric carcinoma (GC) is the fifth most commonly diagnosed cancer and the third leading cause of cancer-related deaths globally. The tumor microenvironment plays a significant role in the pathogenesis, prognosis, and response to immunotherapy. However, the immune-related molecular mechanisms underlying GC remain elusive. Bioinformatics analysis of the gene expression of GC and paracancerous healthy tissues from the same patient was performed to identify the key genes and signaling pathways, as well as their correlation to the infiltration of the tumor microenvironment (TME) by various immune cells related to GC development.\nMETHODS: We employed GSE19826, a gene expression profile from the Gene Expression Omnibus (GEO), for our analysis. Functional enrichment analysis of Differentially Expressed Genes (DEGs) was conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes database.\nRESULTS: Cytoscape software facilitated the identification of nine hub DEGs, namely, FN1, COL1A1, COL1A2, THBS2, COL3A1, COL5A1, APOE, SPP1, and BGN. Various network analysis algorithms were applied to determine their high connectivity. Among these hub genes, FN1, COL1A2, THBS2, COL3A1, COL5A1, and BGN were found to be associated with a poor prognosis for GC patients. Subsequent analysis using the TIMER database revealed the infiltration status of the TME concerning the overexpression of these six genes. Specifically, the abovementioned genes demonstrated direct correlations with cancer-associated fibroblasts, M1 and M2 macrophages, myeloid-derived suppressor cells, and activated dendritic cells.\nCONCLUSION: Our findings suggest that the identified hub genes, particularly BGN, FN1, COL1A2, THBS2, COL3A1, and COL5A1, play crucial roles in GC prognosis and TME cell infiltration. This comprehensive analysis enhances our understanding of the molecular mechanisms underlying GC development and may contribute to the identification of potential therapeutic targets and prognostic markers for GC patients.", "claims": [{"id": "claim-method", "statement": "The GEO2R tool, available within the GEO series (https://www.ncbi.nlm.nih.gov/geo/geo2r/, accessed on 1 December 2023) [16], was employed to discern DEGs between non-cancerous tissue and GC tissue samples. Genes lacking corresponding gene symbols and those represented by multiple probes were excluded independently. A threshold of |Log2FC| > 1.5 and an adjusted p < 0.05 were applied as criteria for statistical significance.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38610959", "locator": "sections[4] \"2.2. Identification of DEGs between Normal and GC Tissue\" paragraph 2", "quote": "The GEO2R tool, available within the GEO series (https://www.ncbi.nlm.nih.gov/geo/geo2r/, accessed on 1 December 2023) [16], was employed to discern DEGs between non-cancerous tissue and GC tissue samples. Genes lacking corresponding gene symbols and those represented by multiple probes were excluded independently. A threshold of |Log2FC| > 1.5 and an adjusted p < 0.05 were applied as criteria for statistical significance."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used in this study are all available in online public databases.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38610959", "locator": "sections[24] \"Data Availability Statement\" paragraph 2", "quote": "The datasets used in this study are all available in online public databases."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 153 differentially expressed genes between gastric cancer and paired non-cancerous tissues.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38610959", "locator": "sections[11] \"3.1. Identification of DEGs between Normal and GC Tissue\" paragraph 2", "quote": "In GSE19826, a total of 153 DEGs were confirmed in the cancer tissue, including 91 down-regulated genes and 62 up-regulated genes (Figure 1)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 153 differentially expressed genes between gastric cancer and paired non-cancerous tissues.", "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:38610959"], "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:GSE19826"], "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:GSE19826"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38610959", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/cancers16071280", "sha256": "sha256:9692cd7885fc2daa48051a82c0a896a755b0dd205bd1a6797eef4e1989487828", "bytes": 53407, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3390/cancers16071280", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11010876", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE19826", "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=GSE19826", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19826", "version": null, "note": "The datasets used in this study are all available in online public databases.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets used in this study are all available in online public databases.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM495051", "GSM495052", "GSM495053", "GSM495054", "GSM495055", "GSM495056", "GSM495057", "GSM495058", "GSM495059", "GSM495060", "GSM495061", "GSM495062", "GSM495063", "GSM495064", "GSM495065", "GSM495066", "GSM495067", "GSM495068", "GSM495069", "GSM495070", "GSM495071", "GSM495072", "GSM495073", "GSM495074", "GSM495075", "GSM495076", "GSM495077"], "sample_count": 27, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data from gastric cancer", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE19826 not downloaded", "asset:data:geo:GSE19826 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-2", "family": null, "specific": null, "label": "GEO2R analysis with |Log2FC| > 1.5 and adjusted p < 0.05", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The GEO2R tool, available within the GEO series (https://www.ncbi.nlm.nih.gov/geo/geo2r/, accessed on 1 December 2023) [16], was employed to discern DEGs between non-cancerous tissue and GC tissue samples. 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