Exploration of the prognostic signature reflecting tumor microenvironment of lung adenocarcinoma based on immunologically relevant genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34612148", "kind": "science-record", "revision": 4, "content_hash": "sha256:98b94bfe7198bf52076dc56d833963bda49517826d4d6b7fc8c35bdeb76e4d50", "created_at": "2026-11-01T17:36:15Z", "updated_at": "2026-11-01T22:04:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of the prognostic signature reflecting tumor microenvironment of lung adenocarcinoma based on immunologically relevant genes.", "doi": "10.1080/21655979.2021.1974779", "pmid": "34612148", "authors": ["Wei Wu", "Liye Jia", "Yanan Zhang", "Juanjuan Zhao", "Yunyun Dong", "Yan Qiang"], "journal": "Bioengineered", "year": 2021, "abstract": "Lung adenocarcinoma (LUAD) represents the major histological type of lung cancer with high mortality globally. Due to the heterogeneous nature, the same treatment strategy to various patients may result in different therapeutic responses. Hence, we aimed to elaborate an effective signature for predicting patient survival outcomes. The TCGA-LUAD cohort from the TCGA portal was used as a training dataset. The GSE26939 and GSE68465 cohorts from the GEO database were taken as validation datasets. All immunologically relevant genes were extracted from the ImmPort. The ESTIMATE algorithm was employed to explore LUAD microenvironment in the training dataset. Further, the DEGs were picked out based on the immune-associated genes reflecting different statuses in the immune context of TME. Univariate/multivariate Cox regression was performed to determine six prognosis- specific genes (PIK3CG, BTK, VEGFD, INHA, INSL4, and PTPRC) and established a risk predictive signature. The time-dependent ROC indicated that AUC values were all greater than 0.70 at 1-, 3-, and 5- year intervals. Corresponding RiskScore of each LUAD patient was calculated from the signature, and they were stratified into the high- and low-risk groups by the median value of RiskScore. K-M curves and Log-rank test demonstrated significant survival differences between the two groups (P < 0.05). Similar results were exhibited in the validation datasets. The RiskScore was incredibly relevant to clinicopathological factors like gender, AJCC stage, and T stage. Also, it can mirror the distribution state of 15 kinds of TIICs and have some predictive value for the sensitivity of therapeutic drugs.", "claims": [{"id": "claim-method", "statement": "To determine the association between immune-TME-related DEGs and prognostic, the univariate Cox proportional hazards regression analysis was employed. And genes, which were found to be considered significant with a cutoff of P < 0.01, were suggested as candidates. Then, the weight of each gene was also generated via a stepwise multivariate Cox regression model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34612148", "locator": "sections[6] \"Identification of the risk prognostic signature\" paragraph 2", "quote": "To determine the association between immune-TME-related DEGs and prognostic, the univariate Cox proportional hazards regression analysis was employed. And genes, which were found to be considered significant with a cutoff of P < 0.01, were suggested as candidates. Then, the weight of each gene was also generated via a stepwise multivariate Cox regression model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Any datasets generated and/or analyzed contributing to the conclusions of this article were retrieved from TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34612148", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "Any datasets generated and/or analyzed contributing to the conclusions of this article were retrieved from TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A six-gene immune-TME-related risk prognostic signature was established using univariate/multivariate Cox regression; its 1-, 3-, and 5-year AUC values were 0.794, 0.727, and 0.760, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34612148", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Univariate/multivariate Cox regression was performed to determine six prognosis- specific genes (PIK3CG, BTK, VEGFD, INHA, INSL4, and PTPRC) and established a risk predictive signature."}, {"asset": "source:pmid:34612148", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The time-dependent ROC indicated that AUC values were all greater than 0.70 at 1-, 3-, and 5- year intervals."}, {"asset": "source:pmid:34612148", "locator": "sections[15] \"Analysis of the predictive efficacy of the prognostic signature\" paragraph 2", "quote": "The AUC values of 0.794, 0.727, and 0.760 were displayed at the 1-, 3-, and 5-year, respectively (Figure 4(c))."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A six-gene immune-TME-related risk prognostic signature was established using univariate/multivariate Cox regression; its 1-, 3-, and 5-year AUC values were 0.794, 0.727, and 0.760, 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:34612148"], "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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