Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:23028479", "kind": "science-record", "revision": 6, "content_hash": "sha256:9c0ae4b407b7f28bd6effb8ce52627e6451d9cbec70dccd80d66678f9f711e18", "created_at": "2026-11-01T15:40:02Z", "updated_at": "2026-11-01T21:19:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma.", "doi": "10.1371/journal.pone.0043923", "pmid": "23028479", "authors": ["Mai Yamauchi", "Rui Yamaguchi", "Asuka Nakata", "Takashi Kohno", "Masao Nagasaki", "Teppei Shimamura", "Seiya Imoto", "Ayumu Saito", "Kazuko Ueno", "Yousuke Hatanaka", "Ryo Yoshida", "Tomoyuki Higuchi", "Masaharu Nomura", "David G Beer", "Jun Yokota", "Satoru Miyano", "Noriko Gotoh"], "journal": "PloS one", "year": 2012, "abstract": "PURPOSE: To identify stage I lung adenocarcinoma patients with a poor prognosis who will benefit from adjuvant therapy.\nPATIENTS AND METHODS: Whole gene expression profiles were obtained at 19 time points over a 48-hour time course from human primary lung epithelial cells that were stimulated with epidermal growth factor (EGF) in the presence or absence of a clinically used EGF receptor tyrosine kinase (RTK)-specific inhibitor, gefitinib. The data were subjected to a mathematical simulation using the State Space Model (SSM). \"Gefitinib-sensitive\" genes, the expressional dynamics of which were altered by addition of gefitinib, were identified. A risk scoring model was constructed to classify high- or low-risk patients based on expression signatures of 139 gefitinib-sensitive genes in lung cancer using a training data set of 253 lung adenocarcinomas of North American cohort. The predictive ability of the risk scoring model was examined in independent cohorts of surgical specimens of lung cancer.\nRESULTS: The risk scoring model enabled the identification of high-risk stage IA and IB cases in another North American cohort for overall survival (OS) with a hazard ratio (HR) of 7.16 (P = 0.029) and 3.26 (P = 0.0072), respectively. It also enabled the identification of high-risk stage I cases without bronchioalveolar carcinoma (BAC) histology in a Japanese cohort for OS and recurrence-free survival (RFS) with HRs of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively.\nCONCLUSION: The set of 139 gefitinib-sensitive genes includes many genes known to be involved in biological aspects of cancer phenotypes, but not known to be involved in EGF signaling. The present result strongly re-emphasizes that EGF signaling status in cancer cells underlies an aggressive phenotype of cancer cells, which is useful for the selection of early-stage lung adenocarcinoma patients with a poor prognosis.\nTRIAL REGISTRATION: The Gene Expression Omnibus (GEO) GSE31210.", "claims": [{"id": "claim-method", "statement": "A partial Cox regression method was used to decrease the complexity of the model by a partial least squares regression to avoid overfitting when more genes than the number of samples [19] are used, as previously reported [18].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:23028479", "locator": "sections[6] \"Construction of the risk scoring model based on gene signature and validation of the risk scoring model\" paragraph 2", "quote": "A partial Cox regression method was used to decrease the complexity of the model by a partial least squares regression to avoid overfitting when more genes than the number of samples [19] are used, as previously reported [18]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The Gene Expression Omnibus (GEO) GSE31210", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:23028479", "locator": "sections[0] \"Abstract\" paragraph 5", "quote": "The Gene Expression Omnibus (GEO) GSE31210"}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study used State Space Model (SSM) analysis to identify gefitinib-sensitive genes and developed a 139-gene risk-scoring model whose source data are available through GEO accession GSE31210; the model identified high-risk stage I cases without BAC histology in a Japanese cohort, with OS and RFS hazard ratios of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:23028479", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The data were subjected to a mathematical simulation using the State Space Model (SSM)."}, {"asset": "source:pmid:23028479", "locator": "sections[0] \"Abstract\" paragraph 5", "quote": "The Gene Expression Omnibus (GEO) GSE31210"}, {"asset": "source:pmid:23028479", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "A risk scoring model was constructed to classify high- or low-risk patients based on expression signatures of 139 gefitinib-sensitive genes in lung cancer using a training data set of 253 lung adenocarcinomas of North American cohort."}, {"asset": "source:pmid:23028479", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "It also enabled the identification of high-risk stage I cases without bronchioalveolar carcinoma (BAC) histology in a Japanese cohort for OS and recurrence-free survival (RFS) with HRs of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study used State Space Model (SSM) analysis to identify gefitinib-sensitive genes and developed a 139-gene risk-scoring model whose source data are available through GEO accession GSE31210; the model identified high-risk stage I cases without BAC histology in a Japanese cohort, with OS and RFS hazard ratios of 8.79 (P = 0.001) and 3.72 (P = 0.0049), 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:23028479"], "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. 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