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.

Identification of a Five-Autophagy-Related-lncRNA Signature as a Novel Prognostic Biomarker for Hepatocellular Carcinoma

“…Three previously published HCC-related signatures derived from TCGA successfully and significantly predict the OS outcomes, including five-ARG signature (HDAC1, RHEB, ATIC, SPNS1, and SQSTM1) by Huo et al ( 2020 ) four-lncRNA signature (ENSG00000234608, ENSG00000242086, ENSG00000273032, ENSG00000228463) by Yang et al ( 2020 ) and four-lncRNA signature (RP11-322E11.5, RP11-150O12.3, AC093609.1, CTC-297N7.9) by Wang et al ( 2017 ). To compare the sensitivity and specificity of our five-AR-lncRNA signature for the prognosis prediction with these three existing signatures, we performed the time-dependent ROC analysis (Liao et al, 2020 ). The AUCs of 3-year OS for Hou's signature, Yang's signature, and Wang' signature was 0.655, 0.504, and 0.704, respectively, all of which were lower than that of our five-AR-lncRNA signature (AUC = 0.751) ( Figure 4C ).…”

The nomogram based on the 6-lncRNA model can promote the prognosis prediction of patients with breast invasive carcinoma

“…Among these dysregulated lncRNAs, some have the potential to be critical biomarkers for early detection and prognosis prediction 26 , 27 . To date, several lncRNA prognostic models have been proven to enhance the prognostic performance of different cancers 28 , 29 .…”

Development and Validation of a Mutational Burden-Associated LncRNA Signature for Improving the Clinical Outcome of Hepatocellular Carcinoma

“…One predictive model, published by Sui's study (Sui's model), consisted of four lncRNA-related signatures using the TCGA cohort (LINC00261, TRELM3P, GBP1P1, and CDKN2B-AS1) [19]. Another predictive model, derived from Liao's study (Liao's model), included four lncRNA-related signatures (AC025016.1, LINC01164, LINC01183 and LINC01269) using the TCGA cohort [20]. Our results showed that the AUC of one year of our predictive model is 0.739, which is superior to those of Sui's model (AUC: 0.600) and Liao's model (AUC: 0.635) (Figure 5A).…”