Literature DB >> 32928078

13-lncRNAs Signature to Improve Diagnostic and Prognostic Prediction of Hepatocellular Carcinoma.

Xinxin Zhang1, Jia Yu1, Juan Hu1, Fang Tan1, Juan Zhou1, Xiaoyan Yang1, Zhizhong Xie1, Huifang Tang2, Sen Dong1, Xiaoyong Lei1.   

Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) is a common type of cancer with a high mortality rate and is usually detected at the middle or late stage, missing the optimal treatment period. The current study aims to identify potential long non-coding RNA (lncRNAs) biomarkers that contribute to the diagnosis and prognosis of HCC.
METHODS: The differentially expressed lncRNAs (DElncRNAs) in HCC patients were detected from the Cancer Genome Atlas (TCGA) dataset. LncRNAs signature was screened by LASSO regression, univariate, and multivariate Cox regression. The models for predicting diagnosis and prognosis were established, respectively. The prognostic model was evaluated by Kaplan-Meier survival curve receiver operating characteristic (ROC) curve and stratified analysis. The diagnostic model was validated by ROC. The lncRNAs signature was further demonstrated by functional enrichment analysis.
RESULTS: We found the 13-lncRNAs signature that had a good performance in predicting prognosis and could help to improve the value of diagnosis. In the training set, testing set, and entire cohort, the low-risk group had longer survival than the high-risk group (median OS: 3124 vs. 649 days, 2456 vs. 770 days and 3124 vs. 755 days). It performed well in 1-, 3-, and 5-year survival prediction. 13-lncRNAs-based risk score, age, and race were good predictors of prognosis. The AUC of diagnosis was 0.9487, 0.9265, and 0.9376, respectively. Meanwhile, the 13-lncRNAs were involved in important pathways, including the cell cycle and multiple metabolic pathways.
CONCLUSION: In our study, the 13-lncRNAs signature may be a potential marker for the prognosis of HCC and improve the diagnosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  HCC; TCGA; bioinformatics analysis; diagnosis; lncRNAs; prognosis

Year:  2021        PMID: 32928078     DOI: 10.2174/1386207323666200914095616

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  1 in total

1.  A Ferroptosis-Related lncRNA Model to Enhance the Predicted Value of Cervical Cancer.

Authors:  Zhaojing Jiang; Jingyu Li; Wenqing Feng; Yujie Sun; Junguo Bu
Journal:  J Oncol       Date:  2022-02-08       Impact factor: 4.375

  1 in total

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