4.3 Article

Differentially expressed liver exosome-related genes as candidate prognostic biomarkers for hepatocellular carcinoma

期刊

ANNALS OF TRANSLATIONAL MEDICINE
卷 10, 期 15, 页码 -

出版社

AME PUBLISHING COMPANY
DOI: 10.21037/atm-21-4400

关键词

Exosome; hepatocellular carcinoma (HCC); immune microenvironment; immunotherapy; prognostic model

资金

  1. International Science and Technology Cooperation Projects [2016YFE0107100]
  2. CAMS Clinical and Translational Medicine Research Funds [2019XK320006]
  3. CAMS Innovation Fund for Medical Science [2017-I2M-4-003, 2018-I2M-3-001]
  4. Beijing Natural Science Foundation [L172055, 7192158]
  5. Fundamental Research Funds for the Central Universities [3332018032]
  6. CSCO-Hengrui Cancer Research Fund [Y-HR20190239]
  7. National Ten-Thousand Talent Program

向作者/读者索取更多资源

This study identified exosome-related genes in hepatocellular carcinoma (HCC) and established a prognostic model based on these genes. Exosome features were found to positively regulate immune response, indicating their potential role in precision treatment for HCC.
Background: Exosomes are involved in cell-to-cell communication, neovascularization, cancer metastasis, and drug resistance, which all play an important role in the occurrence and progression of hepatocellular carcinoma (HCC). Because there are few mechanistic studies about the function of exosomes in HCC, the goals of this study were to identify exosome-related genes in HCC, to establish a reliable prognostic model for HCC, and to explore underlying mechanisms. Methods: The exoRBase and The Cancer Genome Atlas (TCGA) databases were used to analyze differentially expressed genes (DEGs). Cox regression and least absolute shrinkage and selection operator analyses were used to identify DEGs closely related to the overall survival of patients with HCC. An exosome-related prognostic model was then constructed in TCGA and validated in the International Cancer Genome Consortium database. A nomogram was developed to predict survival. CIBERSORT was used to estimate the abundance of different types of immune cells. Immunotherapy-related DEGs were used to predict the effect of immunotherapy. Results: Forty-eight exosome-related DEGs were obtained; of them, five [exportin 1 (XPO1), lysosomal thiol reductase (IFI30), F-box protein 16 (FBXO16), calmodulin 1 (CALM1), MORC family CW-type zinc finger 3 (MORC3)] were selected to construct a predictive model. Patients with HCC were then divided into low- and high-risk groups using the best cut-off value, as determined by the X-tile software. Prognosis was significantly poorer in the high-risk than in the low-risk group (P=0.009; hazard ratio =2.65). Features related to exosomes were found to positively regulate immune response. Further analysis showed a higher risk score was associated with higher expression of immune checkpoint molecules, including programmed death ligand 1 (PD-L1), programmed death ligand 2 (PD-L2), T cell Ig and ITIM domain (TIGIT), and indoleamine-2,3-dioxygenase 1 (IDO1). Conclusions: This study has identified a novel signature based on exosome-related genes that has potential as a prognostic biomarker for HCC. Our research provides an immunological perspective for the development of precision treatment for HCC.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据