Open Access

ARTICLE

Solute carrier-related signature for assessing prognosis and immunity in patients with clear-cell renal cell carcinoma

WEI BAO^1,#, QIANGUANG HAN^2,#, XIAO GUAN³, ZIJIE WANG², MIN GU^1,2,*

1 Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
2 Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
3 Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China

* Corresponding Author: MIN GU. Email:

(This article belongs to this Special Issue: Transcriptome Analysis in Tumor Microenvironment and Tumor Heterogeneity)

Oncology Research 2023, 31(2), 181-192. https://doi.org/10.32604/or.2023.028051

Received 28 November 2022; Accepted 07 February 2023; Issue published 10 April 2023

Abstract

Background: Clear-cell renal cell carcinoma (ccRCC) is the most common malignant kidney cancer. However, the tumor microenvironment and crosstalk involved in metabolic reprogramming in ccRCC are not well-understood. Methods: We used The Cancer Genome Atlas to obtain ccRCC transcriptome data and clinical information. The E-MTAB-1980 cohort was used for external validation. The GENECARDS database contains the first 100 solute carrier (SLC)-related genes. The predictive value of SLC-related genes for ccRCC prognosis and treatment was assessed using univariate Cox regression analysis. An SLC-related predictive signature was developed through Lasso regression analysis and used to determine the risk profiles of patients with ccRCC. Patients in each cohort were separated into high- and low-risk groups based on their risk scores. The clinical importance of the signature was assessed through survival, immune microenvironment, drug sensitivity, and nomogram analyses using R software. Results: SLC25A23, SLC25A42, SLC5A1, SLC3A1, SLC25A37, SLC5A6, SLCO5A1, and SCP2 comprised the signatures of the eight SLC-related genes. Patients with ccRCC were separated into high- and low-risk groups based on the risk value in the training and validation cohorts; the high-risk group had a significantly worse prognosis (p < 0.001). The risk score was an independent predictive indicator of ccRCC in the two cohorts according to univariate and multivariate Cox regression (p < 0.05). Analysis of the immune microenvironment showed that immune cell infiltration and immune checkpoint gene expression differed between the two groups (p < 0.05). Drug sensitivity analysis showed that compared to the low-risk group, the high-risk group was more sensitive to sunitinib, nilotinib, JNK-inhibitor-VIII, dasatinib, bosutinib, and bortezomib (p < 0.001). Survival analysis and receiver operating characteristic curves were validated using the E-MTAB-1980 cohort. Conclusions: SLC-related genes have predictive relevance in ccRCC and play roles in the immunological milieu. Our results provide insight into metabolic reprogramming in ccRCC and identify promising treatment targets for ccRCC.

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Supplementary Material

Supplementary Material File

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