ArticleAging2023
A novel risk model of three gefitinib-related genes FBP1, SBK1 and AURKA is related to the immune microenvironment and is predicting prognosis of lung adenocarcinoma patients.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Metabolic Regulation of Immune Responses: Molecular Mechanisms, Diseases, and Therapeutic Targets.MedComm · 2026Review
- Elevated levels of SLC38A1 are correlated with an unfavorable prognosis, as well as accelerated cell proliferation and metastasis in lung adenocarcinoma.BMC cancer · 2026Article
- Decreased IL20RA expression serves as a predictor of unfavorable prognosis in endometrial cancer.Discover oncology · 2025Article
- The E2F1/SBK1 axis activates the Notch signaling pathway to accelerate the malignant progression of breast cancer.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Exploration and validation of the prognostic value of mitophagy and mitochondrial dynamics-related genes in cervical cancer.Scientific reports · 2025Article
- SBK3 suppresses angiotensin II-induced cardiac hypertrophy by regulating mitochondrial metabolism.Scientific reports · 2025Article
- The role of fructose-1,6-bisphosphatase 1 on regulating the cancer progression and drug resistance.Discover oncology · 2025Review
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Authors and funding
6 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeGefitinib, an anticancer drug, has been reported to potentially improve the prognosis of patients with lung adenocarcinoma (LUAD). This study aims to investigate the roles and mechanisms of Gefitinib.
methodsThe effects of Gefitinib on the growth and migration of LUAD cells were assessed using various methods, including CCK-8, flow cytometry, wound healing, and Transwell assays. To analyze the function and mechanisms of the differentially expressed Gefitinib target genes (GTGs), data from the TCGA database were utilized. Kaplan-Meier survival and ROC analysis identified prognostic-related GTGs and constructed a prognostic nomogram in LUAD. Consensus clustering, COX analysis and survival analysis evaluated the relationship between GTGs and the prognosis of LUAD patients. The mechanisms of the risk model involved LUAD progression, and the relationship between the risk model and immune microenvironment were investigated.
resultsGefitinib could inhibit proliferation, migration and invasion and promote cell apoptosis. 84 DEGTGs were involved in RAS, MAPK, ERBB pathways. The DEGTGs (FBP1, SBK1, and AURKA) were the independent risk factors for dismal prognosis of LUAD patients and were used to establish risk model and nomogram. Gefitinib could promote the expression of FBP1 and inhibit the expression of SBK1 and AURKA. High-risk LUAD patients had the dismal prognosis, and the high-risk score group was significantly associated with the immune microenvironment.
conclusionFBP1, SBK1, and AURKA are prognostic risk factors, and the risk model and nomogram of FBP1, SBK1 and AURKA are associated with dismal prognosis and immune cell infiltration, and have huge prospects for application in evaluating the prognosis in LUAD.
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