A Novel Autophagy-Related Long Non-Coding RNA Signature to Predict Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34815705", "kind": "science-record", "revision": 4, "content_hash": "sha256:f82495c553581a84660dd53284308e34d8fdb4c626f245561f1c3f081ab44d16", "created_at": "2026-11-01T17:36:31Z", "updated_at": "2026-11-01T22:05:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Autophagy-Related Long Non-Coding RNA Signature to Predict Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma.", "doi": "10.2147/IJGM.S333697", "pmid": "34815705", "authors": ["Xiaobo Shi", "Xiaoxiao Liu", "Shupei Pan", "Yue Ke", "Yuxing Li", "Wei Guo", "Yuchen Wang", "Qinli Ruan", "Xiaozhi Zhang", "Hongbing Ma"], "journal": "International journal of general medicine", "year": 2021, "abstract": "BACKGROUND: Considering the significance of autophagy and long non-coding RNAs (lncRNAs) in the biology of esophageal squamous cell carcinoma (ESCC), the present study aimed to identify a new autophagy-related lncRNA signature to forecast the clinical outcomes of ESCC patients and to guide individualized treatment.\nMETHODS: The expression profiles were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. We extracted autophagy-related genes from the Human Autophagy Database and identified autophagy-related lncRNAs through Spearman correlation analysis. Univariate, least absolute shrinkage and selection operator and multivariate Cox regression analyses were performed on GSE53625 to construct an autophagy-related lncRNAs prognostic signature. The model was subjected to bootstrap internal validation, and the expression levels of lncRNAs were verified by TCGA database. The potential molecular mechanism of the model was explored by gene set enrichment analysis (GSEA). Spearman correlation coefficient examined the correlation between risk score and ferroptosis-associated genes as well as the response to immunotherapy and chemotherapy.\nRESULTS: We identified and validated an autophagy-related lncRNAs prognostic signature in 179 patients with ESCC. The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001). The reliability of the model was verified by Brier score and ROC. GSEA results showed significant enrichment of cancer- and autophagy-related signaling pathways in the high-risk group and metabolism-related pathways in the low-risk group. Correlation analysis indicated that the model can effectively forecast the effect of immunotherapy and chemotherapy. About 35.41% (74/209) ferroptosis-related genes were significantly correlated with risk scores.\nCONCLUSION: In brief, we constructed a novel autophagy-related lncRNAs signature (LINC02024, LINC01711, LINC01419, LCAL1, FENDRR, ADAMTS9-AS1, AC025244.1, AC015908.6 and AC011997.1), which could improve the prediction of clinical outcomes and guide individualized treatment of ESCC patients.", "claims": [{"id": "claim-method", "statement": "We extracted autophagy-related genes from the Human Autophagy Database and identified autophagy-related lncRNAs through Spearman correlation analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34815705", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We extracted autophagy-related genes from the Human Autophagy Database and identified autophagy-related lncRNAs through Spearman correlation analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The results presented here are based upon data generated by the TCGA and GEO. TCGA-ESCC (https://www.cancer.gov/tcga) and the data sets of GSE53625 from GEO (https://www.ncbi.nlm.nih.gov/geo/) are publicly open and available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34815705", "locator": "sections[25] \"Data Sharing Statement\" paragraph 2", "quote": "The results presented here are based upon data generated by the TCGA and GEO. TCGA-ESCC (https://www.cancer.gov/tcga) and the data sets of GSE53625 from GEO (https://www.ncbi.nlm.nih.gov/geo/) are publicly open and available."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001).", "kind": "quantitative", "target": {"value": 0.001, "unit": "p-value", "tolerance": null, "source": "The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001)."}, "evidence": [{"asset": "source:pmid:34815705", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001).", "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:34815705"], "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:GSE53625"], "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:GSE53625"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34815705", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/IJGM.S333697", "sha256": "sha256:6cfcfec9cb9c21043112da74609223326805091a2b7bf9935a18af1200eee99c", "bytes": 28406, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/IJGM.S333697", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8605829", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE53625", "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=GSE53625", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE53625", "version": null, "note": "The results presented here are based upon data generated by the TCGA and GEO. 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