Dataset Information

A Four-Methylated lncRNAs-Based Prognostic Signature for Hepatocellular Carcinoma.

ABSTRACT: Currently, an increasing number of studies suggest that long non-coding RNAs (lncRNAs) and methylation-regulated lncRNAs play a critical role in the pathogenesis of various cancers including hepatocellular carcinoma (HCC). Therefore, methylated differentially expressed lncRNAs (MDELs) may be critical biomarkers of HCC. In this study, 63 MDELs were identified by screening The Cancer Genome Atlas (TCGA) HCC lncRNAs expression data set and lncRNAs methylation data set. Based on univariate and multivariate survival analysis, four MDELs (AC025016.1, LINC01164, LINC01183 and LINC01269) were selected to construct the survival prognosis prediction model. Through the PI formula, the study indicates that our new prediction model performed well and is superior to the traditional staging method. At the same time, compared with the previous prediction models reported in the literature, the results of time-dependent receiver operating characteristic (ROC) curve analysis show that our 4-MDELs model predicted overall survival (OS) stability and provided better prognosis. In addition, we also applied the prognostic model to Cancer Cell Line Encyclopedia (CCLE) cell lines and classified different hepatoma cell lines through the model to evaluate the sensitivity of different hepatoma cell lines to different drugs. In conclusion, we have established a new risk scoring system to predict the prognosis, which may have a very important guiding significance for the individualized treatment of HCC patients.

SUBMITTER: Liao LE

PROVIDER: S-EPMC7463540 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Four-Methylated lncRNAs-Based Prognostic Signature for Hepatocellular Carcinoma.

Liao Le-En LE Hu Dan-Dan DD Zheng Yun Y

Genes 20200808 8

Currently, an increasing number of studies suggest that long non-coding RNAs (lncRNAs) and methylation-regulated lncRNAs play a critical role in the pathogenesis of various cancers including hepatocellular carcinoma (HCC). Therefore, methylated differentially expressed lncRNAs (MDELs) may be critical biomarkers of HCC. In this study, 63 MDELs were identified by screening The Cancer Genome Atlas (TCGA) HCC lncRNAs expression data set and lncRNAs methylation data set. Based on univariate and multi ...[more]

PMID: 32784402

Similar Datasets

Project description:BackgroundMany studies have shown that long noncoding RNAs (lncRNA) are closely associated with the occurrence and development of various tumors and have the potential to be prognostic markers. Moreover, cirrhosis is an important prognostic risk factors in patients with liver cancer. Some studies have reported that lncRNA-related prognostic models have been used to predict overall survival (OS) and recurrence-free survival (RFS) in patients with hepatocellular carcinoma (HCC). However, no one has constructed a prognostic lncRNA model only in patients with cirrhotic HCC. Thus, it is necessary to screen novel potential lncRNA markers for improve the prognosis of cirrhotic HCC patients.MethodsThe probe expression profile dataset (GSE14520-GPL3921) from the Gene Expression Omnibus (GEO), which included 204 cirrhotic HCC samples, was reannotated and the lncRNA and mRNA expression dataset was obtained. The patients were randomly assigned to either the training set (n = 103) and testing set (n = 100). Univariate cox regression and the least absolute shrinkage and selection operator (LASSO) model were applied to screen lncRNAs linked to the OS of cirrhotic HCC in the training set. The lncRNAs having significant correlation with OS were then selected and the multivariate Cox regression model was implemented to construct the prognostic score model. Whether or not this model was related to RFS in the training set was simultaneously determined. The testing set was used to validate the lncRNA risk score model. A risk score based on the lncRNA signature was used for stratified analysis of different clinical features to test their prognostic performance. The prognostic lncRNA-related protein genes were identified by the co-expression matrix of lncRNA-mRNA, and the function of these lncRNAs was predicted through the enrichment of these co-expression genes.ResultsThe signature consisted of four lncRNAs:AC093797.1,POLR2J4,AL121748.1 and AL162231.4. The risk model was closely correlated with the OS of cirrhotic HCC in the training cohort, with a hazard ratio (HR) of 3.650 (95% CI [1.761-7.566]) and log-rank P value of 0.0002. Moreover, this model also showed favorable prognostic significance for RFS in the training set (HR: 2.392, 95% CI [1.374-4.164], log-rank P = 0.0015). The predictive performance of the four-lncRNA model for OS and RFS was verified in the testing set. Furthermore, the results of stratified analysis revealed that the four-lncRNA model was an independent factor in the prediction of OS and RFS of patients with clinical characteristics such as TNM (Tumor, Node, Metastasis system) stages I-II, Barcelona Clinic Liver Cancer (BCLC) stages 0-A, and solitary tumors in both the training set and testing set. The results of functional prediction showed that four lncRNAs may be potentially involve in multiple metabolic processes, such as amino acid, lipid, and glucose metabolism in cirrhotic HCC.

Dataset Information

A Four-Methylated lncRNAs-Based Prognostic Signature for Hepatocellular Carcinoma.

Publications

A Four-Methylated lncRNAs-Based Prognostic Signature for Hepatocellular Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets