Potential Genes Associated with the Survival of Lung Adenocarcinoma Were Identified by Methylation

Autor: Chenlu He, Shuiping Huang, Haimiao Chen, Lishun Xiao, Yingliang Jin, Ziyuan Shen
Rok vydání: 2020
Předmět:
Male
Lung Neoplasms
Nedd4 Ubiquitin Protein Ligases
Suppressor of Cytokine Signaling Proteins
Kaplan-Meier Estimate
0302 clinical medicine
Databases
Genetic
Gene expression
Protein Interaction Maps
Likelihood Functions
0303 health sciences
Applied Mathematics
General Medicine
Methylation
Prognosis
Ankyrin Repeat
Gene Expression Regulation
Neoplastic
medicine.anatomical_structure
030220 oncology & carcinogenesis
Modeling and Simulation
Adenocarcinoma
Female
Algorithms
Research Article
Article Subject
Computer applications to medicine. Medical informatics
R858-859.7
Adenocarcinoma of Lung
Computational biology
Biology
Polymorphism
Single Nucleotide
General Biochemistry
Genetics and Molecular Biology
03 medical and health sciences
Text mining
Biomarkers
Tumor
medicine
Humans
Lung cancer
Gene
Aged
Proportional Hazards Models
030304 developmental biology
Lung
General Immunology and Microbiology
Proportional hazards model
business.industry
Computational Biology
DNA Methylation
medicine.disease
business
Genome-Wide Association Study
Zdroj: Computational and Mathematical Methods in Medicine, Vol 2020 (2020)
Computational and Mathematical Methods in Medicine
ISSN: 1748-6718
1748-670X
DOI: 10.1155/2020/7103412
Popis: Background. Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. The purpose of this study is to search for genes related to the prognosis of LUAD through methylation based on a linear mixed model (LMM). Methods. Gene expression, methylation, and survival data of LUAD patients were downloaded from the TCGA database. Based on the LMM model, the GEMMA algorithm was used to screen the predictive genes related to LUAD survival. The Cox model was used to further screen the predicted genes, and then, protein-protein interaction (PPI) network was constructed. Through the software plugin Cytoscape MCODE 3.8.0, the most closely related genes in the PPI network module were selected for in-depth biological function analysis to further explore the interaction and correlation between genes. Results. We screened out 97 predictive genes from 18,834 genes and eliminated one gene associated with lung squamous cell carcinoma from previous studies, leaving 96 genes. The MCODE and the Kaplan-Meier curve analysis were used to finally identify two genes ASB16 and NEDD4 that are related to the prognosis of LUAD. Conclusions. The newly identified two genes associated with the prognosis of LUAD may provide a basis for the treatment of patients.
Databáze: OpenAIRE
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