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

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: SLC25A23SLC25A42SLC5A1SLC3A1SLC25A37SLC5A6SLCO5A1, 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.

 

Comments:

The provided background describes a study conducted on clear-cell renal cell carcinoma (ccRCC), which is the most common malignant kidney cancer. The study aimed to understand the tumor microenvironment and the metabolic reprogramming involved in ccRCC. The researchers utilized data from The Cancer Genome Atlas (TCGA) and the E-MTAB-1980 cohort for external validation.

The focus of the study was on solute carrier (SLC)-related genes, which are involved in transporting various molecules across cellular membranes. The researchers obtained the first 100 SLC-related genes from the GENECARDS database. They performed univariate Cox regression analysis to assess the predictive value of these genes for ccRCC prognosis and treatment.

To develop a predictive signature, the researchers employed Lasso regression analysis using the identified SLC-related genes. The resulting signature consisted of eight genes: SLC25A23, SLC25A42, SLC5A1, SLC3A1, SLC25A37, SLC5A6, SLCO5A1, and SCP2. These genes were used to determine the risk profiles of ccRCC patients. Patients were divided into high- and low-risk groups based on their risk scores.

The study found that patients in the high-risk group had significantly worse prognosis compared to the low-risk group (p < 0.001). The risk score derived from the signature was identified as an independent predictive indicator for ccRCC in both the training and validation cohorts, as confirmed by univariate and multivariate Cox regression analysis (p < 0.05).

Furthermore, the researchers analyzed the immune microenvironment and found differences in immune cell infiltration and immune checkpoint gene expression between the high- and low-risk groups (p < 0.05). Drug sensitivity analysis revealed that the high-risk group was more sensitive to certain drugs such as sunitinib, nilotinib, JNK-inhibitor-VIII, dasatinib, bosutinib, and bortezomib, compared to the low-risk group (p < 0.001).

The findings of this study provide insights into the metabolic reprogramming involved in ccRCC and identify potential treatment targets. The SLC-related genes were shown to have predictive relevance in ccRCC, and their association with the immunological milieu suggests their involvement in immune responses. The results were validated using the E-MTAB-1980 cohort, further strengthening the significance of the findings.

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