A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer

Abstract

Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified.Methods: We obtained 371 tumor specimens and 50 normal tissues from the TCGA database. These samples were randomly divided into the training queue and verification queue. The exosome-related lncRNA risk model was verified by correlation analysis, Lasso regression analysis, and Cox regression analysis. The differences in the immune microenvironment in the two risk groups were obtained by analyzing the infiltration of different immune cells.Results: Five exosome-related lncRNAs associated (MKLN1-AS, TMCC1-AS1, AL031985.3, LINC01138, AC099850.3) with a poor prognosis were identified and used to construct the signature. Receiver operating curve (ROC) and survival curves were used to confirm the predictive ability of this signature. Based on multivariate regression analysis in the training cohort (HR: 3.033, 95% CI: 1.762–5.220) and validation cohort (HR: 1.998, 95% CI: 1.065–3.751), the risk score was found to be an independent risk factor for patient prognosis. Subsequently, a nomogram was constructed to predict the 1-, 3-, 5-years survival rates of liver cancer patients. Moreover, this signature was also related to overexpressed immune checkpoints (PD-1, B7-H3, VSIR, PD-L1, LAG3, TIGIT and CTLA4).Conclusion: Our study showed that exosome-related lncRNAs and the corresponding nomogram could be used as a better index to predict the outcome and immune regulation of liver cancer patients. This signature might provide a new idea for the immunotherapy of liver cancer in the future.

Risk factors of primary liver cancer initiation associated with tumour initiating cell emergence: novel targets for promising preventive therapies

“…63 In a TCGA analysis from 371 HCC samples, 5 exosome-related lncRNA were associated with poor outcome and also related to overexpressed immune checkpoints. 64 This lncRNA-exosomal signature may help to propose an adapted and personalised immunotherapy for each HCC patient. Interestingly, one of these lncRNA, muskelin 1 antisense RNA (MKLN1-AS), was shown to promote tumour growth 65 or drive EMT of liver cancer cells.…”

Extracellular Vesicle-Related Non-Coding RNAs in Hepatocellular Carcinoma: An Overview

“…From the in silico analysis of human liver cancer tissue datasets, Su et al identified a predictive signature based on five upregulated exosome-related lncRNAs (AC099850.3, LINC01138, MKLN1-AS, AL031985.3, and TMCC1-AS1) which have been associated with poor prognosis in liver cancer patients [111]. In the risk model created by the authors, the signature is correlated with the elevated expression of some crucial regulatory mechanisms of the immune system, and is related to the tumor immune microenvironment [111].…”

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

“…However, previous studies only evaluated the prognosis of OC based on exosome-related genes prediction models (32) and did not integrate the necessary information about exosome lncRNA. Previous studies have demonstrated the effectiveness of exosome-related lncRNA prognostic models in breast cancer (33), esophageal squamous cell carcinoma (34), and hepatocellular carcinoma (35,36). However, their applicability in OC remains uncertain.…”