ArticleBMC medical genomics2022
Construction and experimental validation of an acetylation-related gene signature to evaluate the recurrence and immunotherapeutic response in early-stage lung adenocarcinoma.
Article in BMC medical genomics, 2022. 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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7 citing papers in PubMed, 11 citations in OpenAlex.
- Effectiveness of Artificial Intelligence Models in Predicting Lung Cancer Recurrence: A Gene Biomarker-Driven Review.Cancers · 2025Review
- Identification and validation a novel kinase-related gene signature for predicting prognosis and responsiveness to immunotherapy in hepatocellular carcinoma.Clinical and experimental medicine · 2025Article
- Identification of a chromatin regulator signature and potential candidate drugs for primary open-angle glaucoma.Epigenomics · 2025Article
- Epigenetic modifications in early stage lung cancer: pathogenesis, biomarkers, and early diagnosis.MedComm · 2025Review
- Interpreting the molecular mechanisms of RBBP4/7 and their roles in human diseases (Review).International journal of molecular medicine · 2024Review
- Development and experimental validation of an M2 macrophage and platelet-associated gene signature to predict prognosis and immunotherapy sensitivity in bladder cancer.Cancer science · 2024Article
- The artificial intelligence and machine learning in lung cancer immunotherapy.Journal of hematology & oncology · 2023Review
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3 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundAcetylation is a reversible epigenetic process, playing an important role in the initiation and progression of malignant tumors. However, the prognosis value of acetylation-related genes in the early-stage lung adenocarcinoma (LUAD) remains obscure. MATERIALS AND
methodsThe acetylation-related genes were collected and clustered based on transcriptome sequencing of the patients with early-stage LUAD from the Cancer Genome Atlas. The genomic divergence analysis, protein-protein interaction network construction, Lasso regression, and univariate Cox regression were used to identify the significant biomarkers for the recurrence of the early-stage LUAD. The multivariate Cox regression was used to establish the predictive model. Gene Expression Omnibus was systemically retrieved and four independent datasets were used for external validation. 23 early-stage LUAD samples were collected from the local hospital to detect the expression difference of the genes in the model. Transfection assays were performed to verify the regulatory ability of the screened gene to the proliferation of LUAD cell lines. The single-cell RNA sequencing of the early-stage LUAD patients and two lung cancer cohorts receiving immunotherapy were utilized to explore the predictive ability of the established model to immunotherapeutic sensitivity.
resultsThe clustering based on acetylation-related genes was significantly associated with the recurrence (P < 0.01) and immune infiltration statuses. Through a series of bioinformatical and machine learning methods, RBBP7 and YEATS2 were ultimately identified. Accordingly, a novel gene signature containing RBBP7 and YEATS2 was developed to evaluate the recurrence-free survival of early-stage LUAD, which was then validated in five independent cohorts (pooled hazard ratio = 1.88, 95% confidence interval = 1.49-2.37) and 23 local clinical samples (P < 0.01). The knock-down of YEATS2 obviously suppressed proliferation of H1975 and HCC-827 cells. Single-cell RNA sequencing analyses indicated that RBBP7 and YEATS2 were both associated with the tumor immune response, and the prognosis signature could predict the immunotherapeutic response in two cohorts receiving immunotherapy (P < 0.05; P < 0.01).
conclusionsTotally, an acetylation-related gene signature is constructed, helping to evaluate the recurrence and immunotherapeutic effectiveness of early-stage LUAD patients.
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