Establishment and validation of a prognostic model for idiopathic pulmonary fibrosis based on mitochondrial-related genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39678889", "kind": "science-record", "revision": 3, "content_hash": "sha256:3f7daec6e53829b9f83d6ba612d2b0d088144b981667752c08e32f82fdefbcdb", "created_at": "2026-11-01T20:29:58Z", "updated_at": "2026-11-01T22:13:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Establishment and validation of a prognostic model for idiopathic pulmonary fibrosis based on mitochondrial-related genes.", "doi": "10.21037/jtd-24-760", "pmid": "39678889", "authors": ["Xuewen Wang", "Luqin Yang", "Yuxuan Wang", "Xinran Dou", "Yonghao Li", "Ke Wang", "Huilan Zhang"], "journal": "Journal of thoracic disease", "year": 2024, "abstract": "Background: The prognosis for patients diagnosed with idiopathic pulmonary fibrosis (IPF) is exceedingly grim, and there are currently no pharmacological interventions available that effectively reduce mortality rates. Emerging evidence underscores the intimate connection between mitochondrial dysfunction and the onset and advancement of IPF. However, there remains a scarcity of prognostic models for assessing the risk associated with mitochondrial-related genes in IPF. This study aims to develop a comprehensive prognostic model for IPF that incorporates mitochondrial-related genes to enhance risk assessment and guide clinical decision-making.\nMethods: Two IPF-related microarray expression profiling datasets (GSE28042 and GSE70866) accompanied with survival data were acquired from the Gene Expression Omnibus (GEO) database. The \"limma\" R package was used to identify differentially expressed mitochondrial-related genes between normal samples and IPF samples. The prognostic model was constructed using univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and multivariate Cox regression analysis. Multivariate independent prognostic analysis was conducted to ascertain whether the risk score could serve as an independent prognostic factor for predicting clinicopathological outcomes. A nomogram was employed to forecast the survival probability of IPF patients, providing valuable support for clinical decision-making processes. The CIBERSORT algorithm was utilized to examine discrepancies in immune cell infiltration within the model. The expression of genes screened from the prognostic model was validated in external data sets and western blot assays.\nResults: We developed a prognostic model for mitochondrial-related risks, incorporating ARMCX2 and ACOT11, and subsequently validated its predictive efficacy in the validation set. The IPF samples were stratified into high-risk and low-risk groups based on the median of the risk score. According to Kaplan-Meier curve analysis, the high-risk group exhibited inferior outcomes compared to the low-risk group. The time-dependent receiver operating characteristic (ROC) analysis demonstrated the accurate prognostic capability of the risk model for IPF. A nomogram, accompanied by calibration curves, was presented to predict 1-, 2-, and 3-year survival in IPF patients. The risk model we employed not only unveiled significant disparities in functional enrichment between the high-risk and low-risk groups, but also demonstrated a robust correlation with the infiltration of specific immune cells.\nConclusions: In this study, the mitochondrial-related prognostic model incorporating ARMCX2 and ACOT11 demonstrates potential clinical utility for informing decision-making in IPF patients and offers valuable insights for future therapeutic interventions.", "claims": [{"id": "claim-method", "statement": "The prognostic model was constructed using univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and multivariate Cox regression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39678889", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The prognostic model was constructed using univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and multivariate Cox regression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "IPF-related microarray expression profiling datasets (GSE28042, GSE70866 and GSE38958) were acquired from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), among which the GSE28042 dataset was used as the training set, the GSE70866 dataset was used as the validation set and the GSE38958 data set was used to validate the expression of genes screened from the prognostic model. Harvested from the GPL5175 platform, the GSE28042 dataset encapsulates gene expression profiles for 75 patients with IPF, accompanied with survival data.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39678889", "locator": "sections[4] \"Data collection\" paragraph 3", "quote": "IPF-related microarray expression profiling datasets (GSE28042, GSE70866 and GSE38958) were acquired from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), among which the GSE28042 dataset was used as the training set, the GSE70866 dataset was used as the validation set and the GSE38958 data set was used to validate the expression of genes screened from the prognostic model. Harvested from the GPL5175 platform, the GSE28042 dataset encapsulates gene expression profiles for 75 patients with IPF, accompanied with survival data."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The mitochondrial-related prognostic risk model achieved training-cohort AUC values of 0.76, 0.87, and 0.88 for predicting 1-, 3-, and 5-year overall survival, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39678889", "locator": "sections[15] \"Construction of a mitochondrial-related prognostic model in the train set\" paragraph 6", "quote": "To assess the accuracy of prognostic risk models in predicting 1-, 3-, and 5-year OS, ROC curves were plotted with AUC values of 0.76, 0.87, and 0.88, respectively (Figure 4B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The mitochondrial-related prognostic risk model achieved training-cohort AUC values of 0.76, 0.87, and 0.88 for predicting 1-, 3-, and 5-year overall survival, respectively.", "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:39678889"], "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:GSE135893"], "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:GSE135893"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39678889", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/jtd-24-760", "sha256": "sha256:ea307407cab5d840a2d60bb33827fc6d0b987270146afe18afbf4c7b4f803136", "bytes": 43641, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/jtd-24-760", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11635208", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE135893", "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=GSE135893", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE135893", "version": null, "note": "IPF-related microarray expression profiling datasets (GSE28042, GSE70866 and GSE38958) were acquired from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), among which the GSE28042 dataset was used as the training set, the GSE70866 dataset was used as the validation set and the GSE38958 data set was used to validate the expression of genes screened from the prognostic model. 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Methods: Two IPF-related microarray expression profiling datasets (GSE28042 and"], "order_basis": "paper_text_order:755", "id": "assay:1"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["odel was validated in external data sets and western blot assays. Results: We developed a prognostic m", "quently, these proteins underwent meticulous Western blotting analysis, utilizing well-established protoco", "is. Statistical analysis All analyses except western blotting were performed with R version 4.3.2 and the", "y significant. The results obtained from the western blotting experiments were rigorously analyzed and sub"], "order_basis": "paper_text_order:1787", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The prognostic model was constructed using univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and multivariate Cox regression analysis."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}