A Prognostic Risk Signature of Two Autophagy-Related Genes for Predicting Triple-Negative Breast Cancer Outcomes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39246674", "kind": "science-record", "revision": 3, "content_hash": "sha256:387c6ff760f141d0f120d2a0d0415e15e84d17ad660c595dbb899093e9915433", "created_at": "2026-11-01T20:29:22Z", "updated_at": "2026-11-01T22:12:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Prognostic Risk Signature of Two Autophagy-Related Genes for Predicting Triple-Negative Breast Cancer Outcomes.", "doi": "10.2147/BCTT.S475007", "pmid": "39246674", "authors": ["Bing Yu", "Zhimei Xing", "Xiaoxuan Tian", "Rui Feng"], "journal": "Breast cancer (Dove Medical Press)", "year": 2024, "abstract": "Background: Triple-negative breast cancer (TNBC) is recognized as the most aggressive molecular subtype of breast cancer. Recent studies have highlighted the complex role of autophagy in the pathogenesis of TNBC.\nMethods: In this study, we evaluated 18,330 genes, including 1111 autophagy-related genes, (ARGs), across 579 TNBC samples from online databases. Differentially expressed ARGs in TNBC were identified using high-throughput RNA-seq data from the Cancer Genome Atlas (TCGA). Prognostic factors were examined through Cox regression and multivariate Cox analyses, with predictive efficacy assessed using receiver operating characteristic (ROC) curves. A nomogram integrating the risk signature with clinicopathological factors, such as TNM stage, was developed. Immunohistochemical analysis of clinical samples was also conducted.\nResults: EIF4EBP1 and NPAS3 were significantly correlated with prognostic outcomes in patients with TNBC. Multivariate Cox regression analysis demonstrated that the expression levels of these two genes were accurate predictors of disease progression in TNBC samples from TCGA and the GSE31519 dataset. The efficacy of this predictive model was validated using ROC curve analysis and calibration plots, confirming its ability to accurately estimate the 1-, 2-, and 3-year survival rates for individuals with TNBC. Additionally, EIF4EBP1 and NPAS3 expression influenced drug sensitivity in TNBC cell lines, with notably lower NPAS3 expression in TNBC tissues, particularly in Stage III cases. This study is the first to report NPAS3 expression in patients with TNBC.\nConclusion: The autophagy-related genes EIF4EBP1 and NPAS3 may serve as independent prognostic factors for individuals with TNBC.", "claims": [{"id": "claim-method", "statement": "To assess which differentially expressed ARGs could function as prognostic indicators for patients with TNBC, a univariate Cox regression model was used to identify significant predictors, with a significance threshold of P-values < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39246674", "locator": "sections[5] \"Construction of an ARG-Related Prognostic Model\" paragraph 2", "quote": "To assess which differentially expressed ARGs could function as prognostic indicators for patients with TNBC, a univariate Cox regression model was used to identify significant predictors, with a significance threshold of P-values < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original data used to support the findings of this study was obtained from public databases. Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39246674", "locator": "sections[25] \"Data Sharing Statement\" paragraph 2", "quote": "The original data used to support the findings of this study was obtained from public databases. Further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The EIF4EBP1- and NPAS3-based prognostic R score predicted 1-, 2-, 3-, and 5-year survival with AUCs of 0.75, 0.789, 0.76, and 0.572, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39246674", "locator": "sections[15] \"Development of the Prognostic R Score Model Based on EIF4EBP1 and NPAS3 Genes\" paragraph 4", "quote": "The AUC for 1-, 2-, 3-, and 5-years of survival were calculated as 0.75, 0.789, 0.76, and 0.572, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The EIF4EBP1- and NPAS3-based prognostic R score predicted 1-, 2-, 3-, and 5-year survival with AUCs of 0.75, 0.789, 0.76, and 0.572, 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:39246674"], "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:GSE31519"], "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:GSE31519"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39246674", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/BCTT.S475007", "sha256": "sha256:2bb95904b2045ad2ff3f0715c363bbc3f87bdd2f87f9f725be2ee6dfd296df8a", "bytes": 43177, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/BCTT.S475007", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11379032", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE31519", "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=GSE31519", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE31519", "version": null, "note": "The original data used to support the findings of this study was obtained from public databases. Further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original data used to support the findings of this study was obtained from public databases. Further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM782523", "GSM782524", "GSM782525", "GSM782526", "GSM782527", "GSM782528", "GSM782529", "GSM782530", "GSM782531", "GSM782532", "GSM782533", "GSM782534", "GSM782535", "GSM782536", "GSM782537", "GSM782538", "GSM782539", "GSM782540", "GSM782541", "GSM782542", "GSM782543", "GSM782544", "GSM782545", "GSM782546", "GSM782547", "GSM782548", "GSM782549", "GSM782550", "GSM782551", "GSM782552", "GSM782553", "GSM782554", "GSM782555", "GSM782556", "GSM782557", "GSM782558", "GSM782559", "GSM782560", "GSM782561", "GSM782562", "GSM782563", "GSM782564", "GSM782565", "GSM782566", "GSM782567", "GSM782568", "GSM782569", "GSM782570", "GSM782571", "GSM782572", "GSM782573", "GSM782574", "GSM782575", "GSM782576", "GSM782577", "GSM782578", "GSM782579", "GSM782580", "GSM782581", "GSM782582", "GSM782583", "GSM782584", "GSM782585", "GSM782586", "GSM782587", "GSM782588", "GSM782589"], "sample_count": 67, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "A Clinically Relevant Gene Signature in Triple-Negative and Basal-Like Breast 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:GSE31519 not downloaded", "asset:data:geo:GSE31519 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "To assess which differentially expressed ARGs could function as prognostic indicators for patients with TNBC, a univariate Cox regression model was used to identify significant predictors, with a significance threshold of P-values < 0.05."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.8, "band": "high", "quote": "LIMMA"}}, {"id": "method-4", "family": "correlation_analysis", "specific": "spearman", "label": "Correlation analysis", "dsl_operations": ["spearman_rho"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Spearman correlation"}}, {"id": "method-5", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC curve"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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Pr", "Expressed Autophagy-Related Genes (DE-ATGs) RNA-Seq data sourced from TCGA were normalized, and"], "order_basis": "paper_text_order:504", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["l factors, such as TNM stage, was developed. Immunohistochemical analysis of clinical samples was also conduc", "s was examined using TIMER2 and GEPIA2021.16 Immunohistochemistry Staining of Human TNBC Tissue Samples To det", "key ARGs, tissue microarrays designated for immunohistochemical (IHC) staining were analyzed. These arrays i", "ue sections were selected for degreasing and immunohistochemistry staining. 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