Screening and Identification of Key Biomarkers of Gastric Cancer: Three Genes Jointly Predict Gastric Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34485109", "kind": "science-record", "revision": 7, "content_hash": "sha256:cc456a6f11c4d9065f36b6a2e96755051dd9e3f31563bf7be2d0c4d4f42491dd", "created_at": "2026-11-01T15:41:50Z", "updated_at": "2026-11-01T22:04:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening and Identification of Key Biomarkers of Gastric Cancer: Three Genes Jointly Predict Gastric Cancer.", "doi": "10.3389/fonc.2021.591893", "pmid": "34485109", "authors": ["Meng-Jie Shan", "Ling-Bing Meng", "Peng Guo", "Yuan-Meng Zhang", "Dexian Kong", "Ya-Bin Liu"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "BACKGROUND: Gastric cancer (GC) is one of the most common cancers all over the world, causing high mortality. Gastric cancer screening is one of the effective strategies used to reduce mortality. We expect that good biomarkers can be discovered to diagnose and treat gastric cancer as early as possible.\nMETHODS: We download four gene expression profiling datasets of gastric cancer (GSE118916, GSE54129, GSE103236, GSE112369), which were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between gastric cancer and adjacent normal tissues were detected to explore biomarkers that may play an important role in gastric cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of overlap genes were conducted by the Metascape online database; the protein-protein interaction (PPI) network was constructed by the STRING online database, and we screened the hub genes of the PPI network using the Cytoscape software. The survival curve analysis was conducted by km-plotter and the stage plots of hub genes were created by the GEPIA online database. PCR, WB, and immunohistochemistry were used to verify the expression of hub genes. A neural network model was established to quantify the predictors of gastric cancer.\nRESULTS: The relative expression level of cadherin-3 (CDH3), lymphoid enhancer-binding factor 1 (LEF1), and matrix metallopeptidase 7 (MMP7) were significantly higher in gastric samples, compared with the normal groups (p<0.05). Receiver operator characteristic (ROC) curves were constructed to determine the effect of the three genes' expression on gastric cancer, and the AUC was used to determine the degree of confidence: CDH3 (AUC = 0.800, P<0.05, 95% CI =0.857-0.895), LEF1 (AUC=0.620, P<0.05, 95%CI=0.632-0.714), and MMP7 (AUC=0.914, P<0.05, 95%CI=0.714-0.947). The high-risk warning indicator of gastric cancer contained 8<CDH3<15 and 10<expression of LEF1<16.\nCONCLUSIONS: CDH3, LEF1, and MMP7 can be used as candidate biomarkers to construct a neural network model from hub genes, which may be helpful for the early diagnosis of gastric cancer.", "claims": [{"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34485109", "locator": "sections[29] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:34485109"], "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:GSE103236"], "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:GSE103236"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34485109", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2021.591893", "sha256": "sha256:fcf91aa10d8334475218266bd688b26043b046ed95d0625c5529fe2a58a0b0e4", "bytes": 39951, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2021.591893", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8416116", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE103236", "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=GSE103236", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE103236", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. 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"column_count": 2}, "table": {"label": "Table 1", "caption": "Primers and their sequences for PCR analysis.", "rows": [["Primer", "Sequence (5′–3′)"], ["Human", ""], ["GAPDH-F", "CGGAGTCAACGGATTTGGTCGTA"], ["GAPDH-R", "AGCCTTCTCCATGGTGGTGAAGAC"], ["CDH3-F", "ATCATCGTGACCGACCAGAAT"], ["CDH3-R", "GACTCCCTCTAAGACACTCCC"], ["MMP7-F", "ATGTGGAGTGCCAGATGTTGC"], ["MMP7-R", "AGCAGTTCCCCATACAACTTTC"], ["LEF1-F", "CCCGTGAAGAGCAGGCTAAA"], ["LEF1-R", "AGGCAGCTGTCATTCTTGGA"], ["Mouse", ""], ["CDH3-F", "AGTGTTCTGGAGGGAGTAATGC"], ["CDH3-R", "CCACCACCCCATTGTAAGTG"], ["MMP7-F", "CTTACCTCGGATCGTAGTGGA"], ["MMP7-R", "CCCCAACTAACCCTCTTGAAGT"], ["LEF1-F", "GCCACCGATGAGATGATCCC"], ["LEF1-R", "TTGATGTCGGCTAAGTCGCC"]], "row_count": 17, "column_count": 2, "numeric_cells": 1, "header_rows": 1, "locator": "section[8]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:34485109:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": 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