Identification of HMMR as a prognostic biomarker for patients with lung adenocarcinoma via integrated bioinformatics analysis

• Published in: PeerJ (San Francisco, CA) Vol. 9; p. e12624
• Main Authors: Li, Zhaodong, Fei, Hongtian, Lei, Siyu, Hao, Fengtong, Yang, Lijie, Li, Wanze, Zhang, Laney, Fei, Rui
• Format: Journal Article
• Language: English
• Published: United States PeerJ, Inc 22.12.2021; PeerJ Inc
• Subjects: Adenocarcinoma; Bioinformatics; Biomarkers; Cell Biology; Cell cycle; Connectivity; Correlation analysis; Datasets; Differentially expressed genes; Gene expression; Gene set enrichment analysis; Genomes; Genomics; HMMR; Identification; Kinases; Lung adenocarcinoma; Lung cancer; Lung carcinoma; Medical Genetics; Medical prognosis; Meta-analysis; Oncology; Patients; Prognosis; Protein interaction; Proteins; Respiratory Medicine; Signal transduction; Software; Statistical analysis; Survival analysis; Therapeutic targets; Tumors; Differentially expressed genes; Prognosis; HMMR; Lung adenocarcinoma; Bioinformatics

Lung adenocarcinoma (LUAD) is the most prevalent tumor in lung carcinoma cases and threatens human life seriously worldwide. Here we attempt to identify a prognostic biomarker and potential therapeutic target for LUAD patients. Differentially expressed genes (DEGs) shared by GSE18842, GSE75037, GSE1...