A Coagulation-Related Gene-Based Prognostic Model for Invasive Ductal Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34621293", "kind": "science-record", "revision": 4, "content_hash": "sha256:e829b5bcdc1f50f3f98c1fb06998f87d2e932807043e175ee1e8a503d2af7bc8", "created_at": "2026-11-01T17:36:15Z", "updated_at": "2026-11-01T22:04:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Coagulation-Related Gene-Based Prognostic Model for Invasive Ductal Carcinoma.", "doi": "10.3389/fgene.2021.722992", "pmid": "34621293", "authors": ["Jing Li", "Jiajia Du", "Yanhong Wang", "Hongyan Jia"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "Background: Invasive ductal carcinoma (IDC) is the most common type of metastatic breast cancer. Due to the lack of valuable molecular biomarkers, the diagnosis and prognosis of IDC remain a challenge. A large number of studies have confirmed that coagulation is positively correlated with angiogenesis-related factors in metastatic breast cancer. Therefore, the purpose of this study was to construct a COAGULATION-related genes signature for IDC using the bioinformatics approaches. Methods: The 50 hallmark gene sets were obtained from the molecular signature database (MsigDB) to conduct Gene Set Variation Analysis (GSVA). Gene Set Enrichment Analysis (GSEA) was applied to analyze the enrichment of HALLMARK_COAGULATION. The COAGULATION-related genes were extracted from the gene set. Then, Limma Package was used to identify the differentially expressed COAGULATION-related genes (DECGs) between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) samples in GSE26340 data set. A total of 740 IDC samples from The Cancer Genome Atlas (TCGA) database were divided into a training set and a validation set (7:3). The univariate and multivariate Cox regression analyses were performed to construct a risk signature, which divided the IDC samples into the high- and low-risk groups. The overall survival (OS) curve and receiver operating characteristic (ROC) curve were drawn in both training set and validation set. Finally, a nomogram was constructed to predict the 1-, 2-, 3-, 4-, and 5-year survival rates of IDC patients. Quantitative real-time fluorescence PCR (qRT-PCR) was performed to verify the expression levels of the prognostic genes. Results: The \"HALLMARK_COAGULATION\" was significantly activated in IDC. There was a significant difference in the clinicopathological parameters between the DCIS and IDC patients. Twenty-four DECGs were identified, of which five genes (SERPINA1, CAPN2, HMGCS2, MMP7, and PLAT) were screened to construct the prognostic model. The high-risk group showed a significantly lower survival rate than the low-risk group both in the training set and validation set (p=3.5943e-06 and p=0.014243). The risk score was demonstrated to be an independent predictor of IDC prognosis. A nomogram including risk score, pathological_stage, and pathological_N provided a quantitative method to predict the survival probability of 1-, 2-, 3-, 4-, and 5-year in IDC patients. The results of decision curve analysis (DCA) further demonstrated that the nomogram had a high potential for clinical utility. Conclusion: This study established a COAGULATION-related gene signature and showed its prognostic value in IDC through a comprehensive bioinformatics analysis, which may provide a potential new prognostic mean for patients with IDC.", "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:34621293", "locator": "sections[26] \"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"}, {"id": "claim-target-result", "statement": "The study constructed a four-gene COAGULATION-related prognostic signature for IDC using SERPINA1, HMGCS2, MMP7, and PLAT.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34621293", "locator": "sections[17] \"Construction of the Prognostic Gene Signature in IDC\" paragraph 2", "quote": "Four genes (SERPINA1, HMGCS2, MMP7, and PLAT) were selected as prognostic gene signatures in IDC patients (Figure 3B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study constructed a four-gene COAGULATION-related prognostic signature for IDC using SERPINA1, HMGCS2, MMP7, and PLAT.", "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:34621293"], "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:GSE26340"], "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:GSE26340"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34621293", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2021.722992", "sha256": "sha256:eaec4ad084f953295b4a51e46a5c72690e80d61e93c130d1b88d14f615789bbd", "bytes": 37867, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2021.722992", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8490773", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE26340", "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=GSE26340", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE26340", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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