ArticleWorld journal of surgical oncology2022
Identification of a TGF-β signaling-related gene signature for prediction of immunotherapy and targeted therapy for lung adenocarcinoma.
Article in World journal of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 12 citations in OpenAlex.
- Shared Genomic Features Between Lung Adenocarcinoma and Type 2 Diabetes: A Bioinformatics Study.Biology · 2025Article
- TGFβ in Pancreas and Colorectal Cancer: Opportunities to Overcome Therapeutic Resistance.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Review
- Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response.Journal of bone oncology · 2023Article
- Development of a TGF-β signaling-related genes signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma.Frontiers in oncology · 2023Article
- TGF-β based risk model to predict the prognosis and immune features in glioblastoma.Frontiers in neurology · 2023Article
- Progress and perspectives of perioperative immunotherapy in non-small cell lung cancer.Frontiers in oncology · 2023Review
- Cuproptosis-related gene index: A predictor for pancreatic cancer prognosis, immunotherapy efficacy, and chemosensitivity.Frontiers in immunology · 2022Article
- Identification of TGF-β signaling-related molecular patterns, construction of a prognostic model, and prediction of immunotherapy response in gastric cancer.Frontiers in pharmacology · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTransforming growth factor (TGF)-β signaling functions importantly in regulating tumor microenvironment (TME). This study developed a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical outcome of patients with lung adenocarcinoma (LUAD).
methodsTGF-β signaling-related genes came from The Molecular Signature Database (MSigDB). LUAD prognosis-related genes were screened from all the genes involved in TGF-β signaling using least absolute shrinkage and selection operator (LASSO) Cox regression analysis and then used to establish a risk score model for LUAD. ESTIMATE and CIBERSORT analyzed infiltration of immune cells in TME. Immunotherapy response was analyzed by the TIDE algorithm.
resultsA LUAD prognostic 5-gene signature was developed based on 54 TGF-β signaling-related genes. Prognosis of high-risk patients was significantly worse than low-risk patients. Both internal validation and external dataset validation confirmed a high precision of the risk model in predicting the clinical outcomes of LUAD patients. Multivariate Cox analysis demonstrated the model independence in OS prediction of LUAD. The risk model was significantly related to the infiltration of 9 kinds of immune cells, matrix, and immune components in TME. Low-risk patients tended to respond more actively to anti-PD-1 treatment, while high-risk patients were more sensitive to chemotherapy and targeted therapy.
conclusionsThe 5-gene signature based on TGF-β signaling-related genes showed potential for LUAD management.
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