Development and validation of a ubiquitin-proteasome system gene signature for prognostic prediction and immune microenvironment evaluation in hepatocellular carcinoma

泛素-蛋白酶体系统基因特征的开发和验证,用于肝细胞癌的预后预测和免疫微环境评估

阅读:4
作者:Zhi-Yang Liu #, Yi-He Li #, Qing-Kun Zhang #, Bo-Wen Li, Lin Xin

Background

The ubiquitin proteasome has a major role in the development of many tumors. However, the prognostic importance of ubiquitin proteasome-system genes (UPSGs) in hepatocellular carcinoma (HCC) is not fully defined.

Conclusion

We created a 3-UPSGs signature to estimate the prognosis of HCC and to assist in individualized treatment.

Methods

The TCGA and ICGC datasets were utilized to obtain transcriptional profiling data as well as clinicopathological information about HCC. The 3-UPSGs signature for the TCGA cohort was developed via univariate and LASSO Cox regression analyses. Differential expression of genes was demonstrated by qRT-PCR and immunohistochemistry (IHC). Biological pathways were studied using GSVA and GSEA. Six algorithms were used to compare immune infiltration between the two risk groups. Furthermore, drug sensitivity was measured using the "pRRophetic" R package. The predictive capacity of the 3-UPSGs signature for sensitivity to immunotherapy was also explored. Moreover, we performed a pan-cancer analysis of the 3-UPSGs signature.

Results

A risk model containing 3 UPSGs (DCAF13, CDC20 and PSMB5) was developed. IHC and qRT-PCR results showed that signature genes were significantly overexpressed in HCC tissues. The high-risk group had a worse prognosis, with a higher clinicopathological grade, higher levels of tumor mutation burden (TMB), elevated levels of immune checkpoint (IC) expression, as well as increased sensitivity to immunotherapy. The two risk groups also differ in their sensitivity to chemotherapeutic drugs. Furthermore, the three UPSGs may play crucial roles in the progression of multiple types of cancers.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。