ArticleBMC cancer2024
RACGAP1 promotes the progression and poor prognosis of lung adenocarcinoma through its effects on the cell cycle and tumor stemness.
Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Development of a risk model for outcome prediction and treatment guidance in lung adenocarcinoma based on hypoxia, glycolysis, and lymph node metastasis-related genes.Discover oncology · 2026Article
- RACGAP1 defines a malignant proliferative niche and represents a therapeutic vulnerability in lung adenocarcinoma.Translational lung cancer research · 2026Article
- Transient Receptor Potential Melastatin 4 (TRPM4) is associated with an immuno-stimulatory TME and better prognosis in BLCA.Discover oncology · 2025Article
- Comprehensive analysis of a machine learning prognostic model for the interaction between mitochondrial function and lactylation in lung adenocarcinoma.Discover oncology · 2025Article
- Diethyldithiocarbamate-CuNanomedicine (London, England) · 2025Article
- RacGAP1 Plays an Oncogenic Role in Lung Adenocarcinoma by Regulating the Wnt/β-Catenin Pathway.Cells · 2025Article
- Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.Scientific reports · 2025Article
- The Expression Regulation and Cancer-Promoting Roles of RACGAP1.Biomolecules · 2024Review
- Elevated RACGAP1 Expression Enhances Malignant Potential in Lung Adenocarcinoma and Serves as a Prognostic Factor.Journal of Cancer · 2024Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
objectionInvestigating the key genes and mechanisms that influence stemness in lung adenocarcinoma.
methodsFirst, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes. Then, machine learning methods were employed to screen and identify the key genes within these modules. Lastly, functional analysis of the key genes was conducted through cell scratch assays, colony formation assays, transwell migration assays, flow cytometry cell cycle analysis, and xenograft tumor models.
resultsFirst, two groups of patients with different stemness scores were obtained, where the high stemness score group exhibited poor prognosis and immunotherapy efficacy. Next, LASSO regression analysis and random forest regression were employed to identify genes (PBK, RACGAP1) associated with high stemness scores. RACGAP1 was significantly upregulated in the high stemness score group of lung adenocarcinoma and closely correlated with clinical pathological features, poor overall survival (OS), recurrence-free survival (RFS), and unfavorable prognosis in lung adenocarcinoma patients. Knockdown of RACGAP1 suppressed the migration, proliferation, and tumor growth of cancer cells.
conclusionRACGAP1 not only indicates poor prognosis and limited immunotherapy benefits but also serves as a potential targeted biomarker influencing tumor stemness.
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