Construction and validation of a novel Ferroptosis-related gene signature predictive model in rectal Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36414988", "kind": "science-record", "revision": 3, "content_hash": "sha256:55461cd19bb6ba6eef7d83f999f9b6dbf39c0fc824fe41464293cbbcb36b2e31", "created_at": "2026-11-01T19:00:52Z", "updated_at": "2026-11-01T22:08:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and validation of a novel Ferroptosis-related gene signature predictive model in rectal Cancer.", "doi": "10.1186/s12864-022-08996-6", "pmid": "36414988", "authors": ["Wei-Kun Shi", "Yu-Xin Liu", "Xiao-Yuan Qiu", "Jing-Ya Zhou", "Jiao-Lin Zhou", "Guo-Le Lin"], "journal": "BMC genomics", "year": 2022, "abstract": "BACKGROUND: Rectal cancer (RC) is one of the most common malignant tumors. Ferroptosis is an iron-dependent form of cell death, which plays an important role in various cancers. However, the correlation between ferroptosis-related genes (FRGs) and prognosis in RC remains unclear.\nMETHODS: Gene expression data from The Cancer Genome Atlas Rectum adenocarcinoma (TCGA-READ) and GSE87211 were downloaded. Clustering and functional enrichment were evaluated. A FRGs risk score was established based on the univariate Cox analysis and the Least absolute shrinkage and selection operator (LASSO) analysis. K-M analysis and ROC analysis were conducted to determine prognostic values. qRT-PCR was performed to validate levels of mRNA expression. Multivariate Cox analysis was used to build a prognostic prediction model based on the risk score.\nRESULTS: Based on FRGs, RC patients were grouped into two clusters. In the functional enrichment of differentially expressed genes between the two clusters, immune-related pathways dominated. A novel FRGs signature with 14 genes related to the overall survival (OS) of RC was established. qRT-PCR of the 14 genes identified TP63, ISCU, PLIN4, MAP3K5, OXSR, FANCD2 and ATM were overexpressed in RC tissue; HSPB1, MAPK1, ABCC1, PANX1, MAPK9 and ATG7 were underexpressed; TUBE1 had no difference. The high-risk group had a significantly lower OS than the low-risk group (P < 0.001), and ROC curve analysis confirmed the signature's predictive capacity. Multivariate analysis demonstrated that the risk score and age were independent prognostic factors.\nCONCLUSION: A novel FRGs model can be used to predict the prognosis in RC, as well as to guide individual treatment.", "claims": [{"id": "claim-method", "statement": "Multivariate Cox analysis was used to build a prognostic prediction model based on the risk score.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36414988", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Multivariate Cox analysis was used to build a prognostic prediction model based on the risk score."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and analysed during the current study are available in the TCGA repository, https://tcga-data.nci.nih.gov/tcga. The independent validation cohort data is available in the GEO repository, https://www.ncbi.nlm.nih.gov/geo (GSE87211).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36414988", "locator": "sections[29] \"notes\" paragraph 1", "quote": "The datasets generated and analysed during the current study are available in the TCGA repository, https://tcga-data.nci.nih.gov/tcga. The independent validation cohort data is available in the GEO repository, https://www.ncbi.nlm.nih.gov/geo (GSE87211)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The high-risk group had a significantly lower overall survival than the low-risk group, and the risk score and age were independent prognostic factors.", "kind": "quantitative", "target": {"value": 0.001, "unit": "p-value", "tolerance": null, "source": "The high-risk group had a significantly lower OS than the low-risk group (P < 0.001), and ROC curve analysis confirmed the signature’s predictive capacity."}, "evidence": [{"asset": "source:pmid:36414988", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The high-risk group had a significantly lower OS than the low-risk group (P < 0.001), and ROC curve analysis confirmed the signature’s predictive capacity."}, {"asset": "source:pmid:36414988", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Multivariate analysis demonstrated that the risk score and age were independent prognostic factors."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The high-risk group had a significantly lower overall survival than the low-risk group, and the risk score and age were independent prognostic factors.", "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:36414988"], "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:GSE87211"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {"p_value": "e Wilcoxon test and the p-value was corrected by Benjam"}, "inputs": ["data:geo:GSE87211"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36414988", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12864-022-08996-6", "sha256": "sha256:2e31db785461d42abb6404c41b05931d4e217b9db15dfa38f9c44be4e0a5e184", "bytes": 38068, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12864-022-08996-6", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9682793", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE87211", "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=GSE87211", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE87211", "version": null, "note": "The datasets generated and analysed during the current study are available in the TCGA repository, https://tcga-data.nci.nih.gov/tcga. 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