A novel endothelial-related prognostic index by integrating single-cell and bulk RNA sequencing data for patients with kidney renal clear cell carcinoma

Deng-Xiong Li; Qing-Xin Yu; Chui-Xuan Zeng; Lu-Xia Ye; Yi-Qing Guo; Jun-Fei Liu; Hai-Hong Zheng; Dechao Feng; Wuran Wei

doi:10.3389/fgene.2023.1096491

A novel endothelial-related prognostic index by integrating single-cell and bulk RNA sequencing data for patients with kidney renal clear cell carcinoma

Front Genet. 2023 Mar 10:14:1096491. doi: 10.3389/fgene.2023.1096491. eCollection 2023.

Authors

Deng-Xiong Li¹, Qing-Xin Yu², Chui-Xuan Zeng³, Lu-Xia Ye², Yi-Qing Guo², Jun-Fei Liu², Hai-Hong Zheng², Dechao Feng¹, Wuran Wei¹

Affiliations

¹ Department of Urology, West China Hospital, Institute of Urology, Sichuan University, Chengdu, Sichuan, China.
² Department of Pathology, Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang, China.
³ Department of Urology, Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China.

Abstract

Background: Endothelial cells in the tumor microenvironment play an important role in the development of kidney renal clear cell carcinoma (KIRC). We wanted to further identify the function of endothelial cells in KIRC patients by integrating single-cell and bulk RNA sequencing data. Methods: Online databases provide the original data of this study. An endothelial-related prognostic index (ERPI) was constructed and validated by R version 3.6.3 and relative packages. Results: The ERPI consisted of three genes (CCND1, MALL, and VWF). Patients with high ERPI scores were significantly correlated with worse prognosis than those with low ERPI scores in the TCGA training group, TCGA test group, and GSE29609 group. A positive correlation was identified between the ERPI score and poor clinical features. The results of functional analysis indicated that ERPI was significantly associated with immune-related activities. We suggested that patients with high ERPI scores were more likely to benefit from immunotherapy based on the results of immune checkpoints, tumor microenvironment, stemness index, and TCIA, while patients with low ERPI scores were sensitive to gemcitabine, docetaxel, paclitaxel, axitinib, pazopanib, sorafenib, and temsirolimus according to the results of the "pRRophetic" algorithm. Therefore, this ERPI may help doctors choose the optimal treatment for patients with KIRC. Conclusion: By integrating single-cell and bulk RNA sequencing data from KIRC patients, we successfully identified the key genes from the perspective of endothelial cells in the tumor microenvironment and constructed ERPIs that had positive implications in precision medicine.

Keywords: endothelial cells; kidney renal clear cell carcinoma; precision medicine; single-cell; tumor microenvironment.

Grants and funding

This program was supported by the National Key Research and Development Program of China (2021YFC2009303), Project of Health Commission of Sichuan Province (21PJ041) and the Key Research and Development Support Plan of Chengdu Science and Technology Bureau (2022-YF05-01568-SN). The funders had no role in the study design, data collection or analysis, preparation of the manuscript, or the decision to publish.