ArticleBMC cancer2021
Construction of the optimization prognostic model based on differentially expressed immune genes of lung adenocarcinoma.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 17 citations in OpenAlex.
- A lactylation-driven prognostic model for lung adenocarcinoma: cellular lactylation heterogeneity and immune insights.Translational lung cancer research · 2025Article
- Investigation of biomarkers and associated molecular mechanism shared between colorectal cancer and lung adenocarcinoma.Discover oncology · 2025Article
- FKBP10 expression and TP53 mutation predict prognosis and chemotherapy response in triple-negative breast cancer.Discover oncology · 2025Article
- Novel prognostic signature for lung adenocarcinoma based on immune-related mRNA pairs.Heliyon · 2024Article
- FKBP3 aggravates the malignant phenotype of diffuse large B-cell lymphoma by PARK7-mediated activation of Wnt/β-catenin signalling.Journal of cellular and molecular medicine · 2024Article
- MESIA: multi-epigenome sample integration approach for precise peak calling.Scientific reports · 2023Article
- Construction of the metabolism-related models for predicting prognosis and infiltrating immune phenotype in lung squamous cell carcinoma.Journal of Cancer · 2023Article
- Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma.Journal of personalized medicine · 2022Article
- Construction of mRNA prognosis signature associated with differentially expressed genes in early stage of stomach adenocarcinomas based on TCGA and GEO datasets.European journal of medical research · 2022Article
- Proteomic alterations associated with residual disease in neoadjuvant chemotherapy treated ovarian cancer tissues.Clinical proteomics · 2022Article
- Identification of a 6-RBP gene signature for a comprehensive analysis of glioma and ischemic stroke: Cognitive impairment and aging-related hypoxic stress.Frontiers in aging neuroscience · 2022Article
- Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis.Frontiers in cell and developmental biology · 2021Article
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9 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundLung adenocarcinoma (LUAD) is the most common pathology subtype of lung cancer. In recent years, immunotherapy, targeted therapy and chemotherapeutics conferred a certain curative effects. However, the effect and prognosis of LUAD patients are different, and the efficacy of existing LUAD risk prediction models is unsatisfactory.
methodsThe Cancer Genome Atlas (TCGA) LUAD dataset was downloaded. The differentially expressed immune genes (DEIGs) were analyzed with edgeR and DESeq2. The prognostic DEIGs were identified by COX regression. Protein-protein interaction (PPI) network was inferred by STRING using prognostic DEIGs with p value< 0.05. The prognostic model based on DEIGs was established using Lasso regression. Immunohistochemistry was used to assess the expression of FERMT2, FKBP3, SMAD9, GATA2, and ITIH4 in 30 cases of LUAD tissues.
resultsIn total,1654 DEIGs were identified, of which 436 genes were prognostic. Gene functional enrichment analysis indicated that the DEIGs were involved in inflammatory pathways. We constructed 4 models using DEIGs. Finally, model 4, which was constructed using the 436 DEIGs performed the best in prognostic predictions, the receiver operating characteristic curve (ROC) was 0.824 for 3 years, 0.838 for 5 years, 0.834 for 10 years. High levels of FERMT2, FKBP3 and low levels of SMAD9, GATA2, ITIH4 expression are related to the poor overall survival in LUAD (p < 0.05). The prognostic model based on DEIGs reflected infiltration by immune cells.
conclusionsIn our study, we built an optimal prognostic signature for LUAD using DEIGs and verified the expression of selected genes in LUAD. Our result suggests immune signature can be harnessed to obtain prognostic insights.
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