Prognostic analysis of -related lncRNAs in liver hepatocellular carcinoma.

Ding Li, Xinxin Fan, Lihua Zuo, Xuan Wu, Yingxi Wu, Yuanyuan Zhang, Fanmei Zou, Zhi Sun, Wenzhou Zhang
Author Information
  1. Ding Li: Department of Pharmacy, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
  2. Xinxin Fan: Department of Hematology, Zhengzhou Third People's Hospital, Zhengzhou, China.
  3. Lihua Zuo: Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  4. Xuan Wu: Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
  5. Yingxi Wu: Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
  6. Yuanyuan Zhang: Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  7. Fanmei Zou: Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  8. Zhi Sun: Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  9. Wenzhou Zhang: Department of Pharmacy, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.

Abstract

Background: liver hepatocellular carcinoma (LIHC), whose incidence is increasing globally, is one of the most prevalent malignant cancers. -related pathways are involved in the cell proliferation, migration, apoptosis, and metabolism in LIHC. Long noncoding RNAs (lncRNAs) also play important roles in the progression and prognosis of LIHC. However, the clinical role, prognostic significance, and immune regulation of -related lncRNAs in LIHC remains unclear. Our study aims to construct and validate a -related lncRNA prognostic risk signature that can estimate the prognosis and response to immunotherapy in LIHC.
Methods: The clinical information and corresponding messenger RNA (mRNA)/lncRNA expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and 502 -related lncRNAs were identified by Pearson correlation analysis. A prognostic risk signature with 5 -related lncRNAs was then developed based on the Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm analyses. Subsequently, Kaplan-Meier survival curve, receiver operating characteristic (ROC) curve, and the nomogram were established to evaluate the predictive accuracy of the signature. In addition, the immune microenvironment, tumor mutation burden, and drug sensitivity associated with the signature were also analyzed in LIHC.
Results: Compared with the low-risk groups, the high-risk groups had an unfavorable outcome. Multivariate regression analysis revealed that the risk score signature was the independent prognostic factor superior to the other clinical variables. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses demonstrated that the risk score was highly associated with the nuclear division, DNA replication, and immune response. The group with high risk tended to hold a lower immune escape rate and better immunotherapy efficacy, while the group with low risk was more sensitive to some small molecular targeted drugs.
Conclusions: We developed a -related lncRNA risk signature that was highly associated with the prognosis and response to immunotherapy and targeted drugs and which provided novel mechanistic insights into the personalized treatment and potential drug selection for patients with LIHC.

Keywords

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Word Cloud

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