Integrative analysis of transcriptomic landscape and urinary signature reveals prognostic biomarkers for clear cell renal cell carcinoma

Wei Zhang; Wenqiang Liu; Yiren Yang; Chengwu Xiao; Yutian Xiao; Xiaojie Tan; Qingyang Pang; Han Wu; Meimian Hua; Xiaolei Shi

doi:10.3389/fonc.2023.1102623

Integrative analysis of transcriptomic landscape and urinary signature reveals prognostic biomarkers for clear cell renal cell carcinoma

Front Oncol. 2023 Mar 24:13:1102623. doi: 10.3389/fonc.2023.1102623. eCollection 2023.

Authors

Affiliations

¹ Department of Urology, Changhai Hospital, Naval Medical University, Shanghai, China.
² Department of Epidemiology, Naval Medical University, Shanghai, China.

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT) have poor prognosis. We aimed to reveal features of ccRCC with VTT and develop a urine-based prognostic classifier to predict ccRCC prognosis through integrative analyses of transcriptomic landscape and urinary signature.

Methods: RNA sequencing was performed in five patients with ccRCC thrombus-tumor-normal tissue triples, while mass spectrometry was performed for urine samples from 12 ccRCC and 11 healthy controls. A urine-based classifier consisting of three proteins was developed to predict patients' survival and validated in an independent cohort.

Results: Transcriptomic analysis identified 856 invasion-associated differentially expressed genes (DEGs). Furthermore, proteomic analysis showed 133 differentially expressed proteins (DEPs). Integration of transcriptomic landscape and urinary signature reveals 6 urinary detectable proteins (VSIG4, C3, GAL3ST1, TGFBI, AKR1C3, P4HB) displaying abundance changes consistent with corresponding genes in transcriptomic profiling. According to TCGA database, VSIG4, TGFBI, and P4HB were significantly overexpressed in patients with shorter survival and might be independent prognostic factors for ccRCC (all p<0.05). A prognostic classifier consisting of the three DEPs highly associated with survival performed satisfactorily in predicting overall survival (HR=2.0, p<0.01) and disease-free survival (HR=1.6, p<0.001) of ccRCC patients. The ELISA analysis of urine samples from an independent cohort confirmed the satisfied predictive power of the classifier for pathological grade (AUC=0.795, p<0.001) and stage (AUC=0.894, p<0.001).

Conclusion: Based on integrative analyses of transcriptomic landscape and urinary signature, the urine-based prognostic classifier consisting of VSIG4, TGFBI, and P4HB has satisfied predictive power of ccRCC prognosis and may facilitate ccRCC molecular subtyping and treatment.

Keywords: biomarker; clear cell renal cell carcinoma; prognosis; urine; venous tumor thrombus.

Grants and funding

This work was sponsored by National Natural Science Foundation of China (XS 82203134, WZ 81802581), Naval Medical University Sailing Program (WZ 2021), Changhai Hospital Basic Medical Research Program (WZ 2021JCMS04), Shanghai Research Center of Genitourinary System Diseases Program (2022ZZ01011). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.