Identification of a Novel Epithelial-to-mesenchymal-related Gene Signature in Predicting Survival of Patients with Hepatocellular Carcinoma
| Autor: | Hui Rao, Junjie Hu, Guohua Zheng, Lei Sheng, Simeng Xiao, Na Hu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Oncology
Multivariate statistics medicine.medical_specialty Carcinoma Hepatocellular Microarray Kaplan-Meier Estimate 03 medical and health sciences 0302 clinical medicine Internal medicine Drug Discovery Gene expression medicine Biomarkers Tumor Humans 030304 developmental biology 0303 health sciences Framingham Risk Score business.industry Proportional hazards model Organic Chemistry Liver Neoplasms Univariate General Medicine Gene signature medicine.disease Computer Science Applications Gene Expression Regulation Neoplastic 030220 oncology & carcinogenesis Hepatocellular carcinoma business |
| Zdroj: | Combinatorial chemistryhigh throughput screening. 25(8) |
| ISSN: | 1875-5402 |
| Popis: | Background: Epithelial-mesenchymal transformation (EMT) promotes cancer metastasis, including hepatocellular carcinoma. Therefore, EMT-related gene signature was explored. Objective: The present study was designed to develop an EMT-related gene signature for predicting the prognosis of patients with hepatocellular carcinoma. Methods: An integrated gene expression analysis based on tumor data of the patients with hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), HCCDB18, and GSE14520 dataset was conducted. An EMT-related gene signature was constructed by the least absolute shrinkage and selection operator (LASSO) and COX regression analysis of univariate and multivariate survival. Results: A 3-EMT gene signature was developed and validated based on gene expression profiles of hepatocellular carcinoma from three microarray platforms. Patients with a high-risk score had significantly worse overall survival (OS) than those with low-risk scores. The EMT-related gene signature showed a high performance in accurately predicting prognosis and examining the clinical characteristics and immune score analysis. Univariate and multivariate Cox regression analyses confirmed that the EMT-related gene signature was an independent prognostic factor for predicting survival in hepatocellular carcinoma patients. Compared with the existing models, our EMTrelated gene signature reached a higher area under the curve (AUC). Conclusion: Our findings provide novel insight into understanding EMT and help identify hepatocellular carcinoma patients with poor prognosis. |
| Databáze: | OpenAIRE |
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