Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36543847", "kind": "science-record", "revision": 3, "content_hash": "sha256:1a6912a2d79e4c022cc671f1e929a0fca49b2509a760a32a60722e924be69fc4", "created_at": "2026-11-01T19:01:04Z", "updated_at": "2026-11-01T22:08:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinoma.", "doi": "10.1038/s41598-022-26427-0", "pmid": "36543847", "authors": ["Peng Zhang", "Wenmiao Wang", "Lei Liu", "HouQiang Li", "XinYu Sha", "Silin Wang", "Zhanghao Huang", "Youlang Zhou", "Jiahai Shi"], "journal": "Scientific reports", "year": 2022, "abstract": "Lung cancer is one of the most common malignant tumors, and ranks high in the list of mortality due to cancers. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite progress in the diagnosis and treatment of lung cancer, the prognosis of these patients remains dismal. Therefore, it is crucial to identify the predictors and treatment targets of lung cancer to provide appropriate treatments and improve patient prognosis. In this study, the gene modules related to immunotherapy were screened by weighted gene co-expression network analysis (WGCNA). Using unsupervised clustering, patients in The Cancer Genome Atlas (TCGA) were divided into three clusters based on the gene expression. Next, gene clustering was performed on the prognosis-related differential genes, and a six-gene prognosis model (comprising PLK1, HMMR, ANLN, SLC2A1, SFTPB, and CYP4B1) was constructed using least absolute shrinkage and selection operator (LASSO) analysis. Patients with LUAD were divided into two groups: high-risk and low-risk. Significant differences were found in the survival, immune cell infiltration, Tumor mutational burden (TMB), immune checkpoints, and immune microenvironment between the high- and low-risk groups. Finally, the accuracy of the prognostic model was verified in the Gene Expression Omnibus (GEO) dataset in patients with LUAD (GSE30219, GSE31210, GSE50081, GSE72094).", "claims": [{"id": "claim-method", "statement": "Lasso Cox regression analysis was performed on 78 differential genes related to prognosis, and Lasso coefficient spectra of 6 potential prognostic genes related to immunity were established (Fig. 5a).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36543847", "locator": "sections[16] \"Construction of prognosis model\" paragraph 2", "quote": "Lasso Cox regression analysis was performed on 78 differential genes related to prognosis, and Lasso coefficient spectra of 6 potential prognostic genes related to immunity were established (Fig. 5a)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data were publicly available from TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) datasets. These data are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36543847", "locator": "sections[32] \"notes\" paragraph 1", "quote": "All data were publicly available from TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) datasets. These data are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Survival analysis showed that there were significant differences between the high-risk group and low-risk group, and the survival of the high-risk group was worse (P < 0.001, Fig. 5g).", "kind": "quantitative", "target": {"value": 0.001, "unit": "p-value", "tolerance": null, "source": "Survival analysis showed that there were significant differences between the high-risk group and low-risk group, and the survival of the high-risk group was worse (P < 0.001, Fig. 5g)."}, "evidence": [{"asset": "source:pmid:36543847", "locator": "sections[16] \"Construction of prognosis model\" paragraph 2", "quote": "Survival analysis showed that there were significant differences between the high-risk group and low-risk group, and the survival of the high-risk group was worse (P < 0.001, Fig. 5g)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Survival analysis showed that there were significant differences between the high-risk group and low-risk group, and the survival of the high-risk group was worse (P < 0.001, Fig. 5g).", "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:36543847"], "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:GSE30219"], "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:GSE30219"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36543847", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-022-26427-0", "sha256": "sha256:d31a576283203b316681fe1c7f8e0c9e4e3f4c71c9d5b0e7ad717c0cddf4d6f7", "bytes": 46128, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-022-26427-0", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9772350", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE30219", "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=GSE30219", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE30219", "version": null, "note": "All data were publicly available from TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) datasets. 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