Development and validation of a survival model for esophageal adenocarcinoma based on autophagy-associated genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34252349", "kind": "science-record", "revision": 7, "content_hash": "sha256:1b4b7f44c695f7ea72c3e809853d8bcffce3da620c47e6c35d504cb1383ee0a7", "created_at": "2026-11-01T15:41:43Z", "updated_at": "2026-11-01T22:04:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and validation of a survival model for esophageal adenocarcinoma based on autophagy-associated genes.", "doi": "10.1080/21655979.2021.1946235", "pmid": "34252349", "authors": ["Lili Duan", "Lu Cao", "Rui Zhang", "Liaoran Niu", "Wanli Yang", "Weibo Feng", "Wei Zhou", "Junfeng Chen", "Xiaoqian Wang", "Yiding Li", "Yujie Zhang", "Jinqiang Liu", "Qingchuan Zhao", "Daiming Fan", "Liu Hong"], "journal": "Bioengineered", "year": 2021, "abstract": "Autophagy is a highly conserved catabolic process which has been implicated in esophageal adenocarcinoma (EAC). We sought to investigate the biological functions and prognostic value of autophagy-related genes (ARGs) in EAC. A total of 21 differentially expressed ARGs were identified between EAC and normal samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were then applied for the differentially expressed ARGs in EAC, and the protein-protein interaction (PPI) network was established. Cox survival analysis and Lasso regression analysis were performed to establish a prognostic prediction model based on nine overall survival (OS)-related ARGs (CAPN1, GOPC, TBK1, SIRT1, ARSA, BNIP1, ERBB2, NRG2, PINK1). The 9-gene prognostic signature significantly stratified patient outcomes in The Cancer Genome of Atlas (TCGA)-EAC cohort and was considered as an independently prognostic predictor for EAC patients. Moreover, Gene set enrichment analysis (GSEA) analyses revealed several important cellular processes and signaling pathways correlated with the high-risk group in EAC. This prognostic prediction model was confirmed in an independent validation cohort (GSE13898) from The Gene Expression Omnibus (GEO) database. We also developed a nomogram with a concordance index of 0.78 to predict the survival possibility of EAC patients by integrating the risk signature and clinicopathological features. The calibration curves substantiated favorable concordance between actual observation and nomogram prediction. Last but not least, Erb-B2 Receptor Tyrosine Kinase 2 (ERBB2), a member of the prognostic gene signature, was identified as a potential therapeutic target for EAC patients. To sum up, we established and verified a novel prognostic prediction model based on ARGs which could optimize the individualized survival prediction in EAC.", "claims": [{"id": "claim-method", "statement": "Then, the OS-related ARGs were subjected to LASSO COX regression analysis to establish the prognostic prediction model using the R package ‘glmnet’.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34252349", "locator": "sections[6] \"Identification and validation of the prognostic prediction model based on ARGs\" paragraph 2", "quote": "Then, the OS-related ARGs were subjected to LASSO COX regression analysis to establish the prognostic prediction model using the R package ‘glmnet’."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analyzed during this study are included in this article. The TCGA data portal (https://portal.gdc.cancer.gov/); the GSE13898 dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13898).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34252349", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "All data generated or analyzed during this study are included in this article. The TCGA data portal (https://portal.gdc.cancer.gov/); the GSE13898 dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13898)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:34252349"], "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:GSE13898"], "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:GSE13898"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34252349", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1080/21655979.2021.1946235", "sha256": "sha256:47678cbcbb91b6dadc147462c9a0dbbad9b6eaa7fac267957bb1fe27bec09e49", "bytes": 42540, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1080/21655979.2021.1946235", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8806464", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13898", "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=GSE13898", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13898", "version": null, "note": "All data generated or analyzed during this study are included in this article. 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coefficient"], ["1", "CAPN1", "Calpain 1", "Play a role in the initiation of autophagy", "−0.3070954"], ["2", "ARSA", "Arylsulfatase A", "Involved in regulation of autophagy", "−0.2100786"], ["3", "ERBB2", "Erb-B2 Receptor Tyrosine Kinase 2", "Regulate autophagy and apoptosis", "−0.1178015"], ["4", "NRG2", "Neuregulin 2", "Play a role in autophagy", "−0.1494456"], ["5", "PINK1", "PTEN Induced Kinase 1", "Involved in the clearance of damaged mitochondria via selective autophagy (mitophagy)", "−0.1800211"], ["6", "GOPC", "Golgi Associated PDZ And Coiled-Coil Motif Containing", "play a role in autophagy", "0.2283383"], ["7", "SIRT1", "Sirtuin 1", "Participate in the coordination of apoptosis and autophagy", "0.3195141"], ["8", "BNIP1", "BCL2 Interacting Protein 1", "Involved in mitochondrial autophagy and apoptosis", "0.1733898"], ["9", "TBK1", "TANK Binding Kinase 1", "Promoting autophagosome maturation", "0.3517779"]], "row_count": 10, "column_count": 5, "numeric_cells": 25, 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