Identification and Verification of Immune Subtype-Related lncRNAs in Clear Cell Renal Cell Carcinoma

Zhifeng Wang; Zihao Chen; Tengyun Guo; Menglin Hou; Junpeng Wang; Yanping Guo; Tao Du; Xiaoli Zhang; Ning Wang; Degang Ding; Xiqing Li

doi:10.3389/fonc.2022.888502

Identification and Verification of Immune Subtype-Related lncRNAs in Clear Cell Renal Cell Carcinoma

Front Oncol. 2022 Jun 2:12:888502. doi: 10.3389/fonc.2022.888502. eCollection 2022.

Authors

Zhifeng Wang¹, Zihao Chen², Tengyun Guo³, Menglin Hou⁴, Junpeng Wang¹, Yanping Guo⁵, Tao Du¹, Xiaoli Zhang¹, Ning Wang¹, Degang Ding¹, Xiqing Li⁶

Affiliations

¹ Department of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China.
² Department of Urology, Southern Medical University, Guangzhou, China.
³ Department of Neurosurgery, Daping Hospital, Army Medical University, Chongqing, China.
⁴ Department of Oncology, Graduate School of Guilin Medical University, Guilin, China.
⁵ Department of Pathology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China.
⁶ Department of Oncology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China.

Abstract

Background: According to clinical study results, immune checkpoint blockade (ICB) treatment enhances the survival outcome of patients with clear cell renal cell carcinoma (ccRCC). Previous research has divided ccRCC patients into immune subtypes with distinct ICB response rates. However, the study on the association between lncRNAs and ccRCC immune subtypes is lacking.

Methods: Differentially expressed lncRNAs/mRNAs between two major immune subgroups were calculated. A weighted gene co-expression network analysis (WGCNA) was conducted to establish the lncRNA-mRNA co-expression network and select the key lncRNAs. Then, prognostic lncRNAs were selected from the network by the bioinformatics method. Next, the risk-score was estimated by lncRNA expression and their coefficients. Finally, a nomogram based on lncRNAs and clinical parameters was created to predict the prognosis of ccRCC.

Results: LncRNAs and mRNAs associated with ccRCC immune subtypes were identified. The lncRNAs and mRNAs from a gene module closely linked to the immune subtype were used to construct a network. The KEGG pathways enriched in the network were related to immune system activation processes. These 8 lncRNAs (AL365361.1, LINC01934, AC090152.1, PCED1B-AS1, LINC00426, AC007728.2, AC243829.4, and LINC00158) were found to be positively correlated with immune cells of the tumor microenvironment. The C-index of the nomogram was 0.777, and the calibration curve data suggests that the nomogram has a high degree of discriminating capacity.

Conclusion: In summary, we discovered core lncRNAs linked with immune subtypes and created corresponding lncRNA-mRNA networks. These lncRNAs are anticipated to have predictive significance for ccRCC and may provide insight into novel biomarkers for the disease.

Keywords: LncRNA; ccRCC; co-expression network; immune subtype; nomogram.