A Novel Lysosome-Related Gene Signature Predicts Lung Cancer Prognosis: A Bioinformatics-Driven Study.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39633837", "kind": "science-record", "revision": 3, "content_hash": "sha256:5ec486b15ffb5046873741b340a7ee55576fac8f6f21bf0e6ec63551d82928b2", "created_at": "2026-11-01T20:29:54Z", "updated_at": "2026-11-01T22:13:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Lysosome-Related Gene Signature Predicts Lung Cancer Prognosis: A Bioinformatics-Driven Study.", "doi": "10.1002/hsr2.70236", "pmid": "39633837", "authors": ["Wei Ye", "Lin Sun", "Cong Fu", "Huajie Dong", "Tong Zhou"], "journal": "Health science reports", "year": 2024, "abstract": "Background and Aims: The biological function of lysosomes has been increasingly appreciated in cancer. However, the relationship between lysosome and lung adenocarcinoma (LUAD) was not well understood. In this study, a lysosome-related signature was developed for LUAD risk stratification and prognosis prediction.\nMethods: Download RNA-seq data of LUAD and clinical information of corresponding samples from the UCSC-Xena platform. GSE31210 databases is used as a validation cohort. The lysosome-related genes was obtained from molecular signature database. The differentially expressed genes (DEGs) as well as lysosome-associated prognosis signatures were identified by using univariate, multivariate cox, and Lasso regression. A nomogram was constructed and evaluated using ROC and DCA.\nResults: A total of 109 lysosome-related DEGs were identified and 30 prognostic related DEGs were subsequently screened. Cluster analysis further divides the TCGA cohort into clusters 1 and 2. Patients in cluster 2 had a worse prognosis (p = 0.016), lower LYSOSOME score. Enrichment analysis showed that 21 significantly enriched gene sets in the cluster 2 were activated. And 10 pathways, such as E2F_TARGETS, G2M_CHECKPOINT were upregulated. Multivariate Cox regression analysis identified 17 best prognostic genes as risk signature. An independent prognostic factor, the risk signature, was identified. A prognostic nomogram including risk signature, age, TNM stage, and gender was constructed, and ROC and DCA curves proved its excellent performance. We examined CTSZ and AP3S2 protein expression in 48 stage 3-4 NSCLC samples. Low AP3S2 expression was associated with better prognosis (median overall survival: 37.87 vs. 8.53 months, p = 0.0211). Increased CTSZ expression also indicated better prognosis (median overall survival: 6.77 vs. 30.50 months, p = 0.0306).\nConclusion: We identified molecular subtypes and lysosomal-based prognostic signatures for LUAD patients, as well as 17 genes that serve as a biomarker for evaluating the prognosis of LUAD patients.", "claims": [{"id": "claim-method", "statement": "Based on the prognostic lysosome‐related genes mentioned above, LASSO Cox analysis was performed using glmnet package to screen characteristic genes for the construction of lysosome‐related prognostic signature. The TCGA‐LUAD and GSE31210 datasets were analyses using both univariate and multivariate Cox regression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39633837", "locator": "sections[7] \"Building and Validating the Prognostic Signature\" paragraph 2", "quote": "Based on the prognostic lysosome‐related genes mentioned above, LASSO Cox analysis was performed using glmnet package to screen characteristic genes for the construction of lysosome‐related prognostic signature."}, {"asset": "source:pmid:39633837", "locator": "sections[7] \"Building and Validating the Prognostic Signature\" paragraph 5", "quote": "The TCGA‐LUAD and GSE31210 datasets were analyses using both univariate and multivariate Cox regression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used in this study are available in the manuscript and Supplementary File. For additional inquiries, please contact the corresponding author directly via email.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39633837", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "The data used in this study are available in the manuscript and Supplementary File. For additional inquiries, please contact the corresponding author directly via email."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified molecular subtypes and lysosomal‐based prognostic signatures for LUAD patients, as well as 17 genes that serve as a biomarker for evaluating the prognosis of LUAD patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39633837", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "We identified molecular subtypes and lysosomal‐based prognostic signatures for LUAD patients, as well as 17 genes that serve as a biomarker for evaluating the prognosis of LUAD patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified molecular subtypes and lysosomal‐based prognostic signatures for LUAD patients, as well as 17 genes that serve as a biomarker for evaluating the prognosis of LUAD patients.", "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:39633837"], "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:GSE31210"], "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:GSE31210"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39633837", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/hsr2.70236", "sha256": "sha256:d5acd38bec7ea9683e566fbca1d4b7e99a1ed4d67e2a554eee146b81aa45583a", "bytes": 30360, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1002/hsr2.70236", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11615650", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE31210", "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=GSE31210", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE31210", "version": null, "note": "The data used in this study are available in the manuscript and Supplementary File. For additional inquiries, please contact the corresponding author directly via email.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data used in this study are available in the manuscript and Supplementary File. 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