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Pyroptosis-Related Gene Signature Predicts the Prognosis of ccRCC Using TCGA and Single-Cell RNA Seq Database
Ying Gan1, Zhenan Zhang1, Xiaofei Wang1
1Department of Urology, Peking University First Hospital, Beijing 100034, China.
Abstract:
Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal carcinoma, which is not sensitive to both radiotherapy and chemotherapy. The objective response rate of metastatic renal cancer to targeted drugs and immunotherapy is unsatisfactory. Pyroptosis, proven as an inflammatory form of programmed cell death, could be activated by some inflammasomes, while could create a tumor-suppressing environment by releasing inflammatory factors in the tumor. To explore indicators predicting the prognosis of ccRCC and the effect of antitumor therapy, we constructed a pyroptosis risk model containing 4 genes after 11 pyroptosis-related genes of 516 ccRCC cases in the TCGA database were scanned. Based on the risk score, 516 ccRCC cases were divided into two groups for functional enrichment analysis and immune profile to seek functional pathways and potential therapeutic targets. Besides, those results were verified in GSE29609 and single-cell transcriptomic data. The study suggests that the conducted pyroptosis model could predict the prognosis of ccRCC and reflect the immune microenvironment, which may help in immune checkpoint inhibitor treatment.
Insights
This study developed a 4-gene pyroptosis risk model to predict clear cell renal cell carcinoma (ccRCC) prognosis and immune microenvironment. This model may guide immunotherapy, including immune checkpoint inhibitors.
Area of Science:
- Oncology
- Immunology
- Molecular Biology
Background:
- Clear cell renal cell carcinoma (ccRCC) shows poor response to conventional therapies.
- Current targeted drugs and immunotherapies offer limited efficacy for metastatic ccRCC.
- Pyroptosis, an inflammatory programmed cell death, can induce a tumor-suppressing environment.
Purpose of the Study:
- To identify prognostic indicators for ccRCC.
- To evaluate the potential of pyroptosis-related genes in predicting ccRCC outcomes.
- To explore therapeutic targets for ccRCC, particularly in relation to the immune microenvironment.
Main Methods:
- Utilized TCGA database (516 ccRCC cases) to screen 11 pyroptosis-related genes.
- Constructed a 4-gene pyroptosis risk model based on prognostic significance.
- Performed functional enrichment and immune profiling analyses stratified by risk score.
- Validated findings using GSE29609 and single-cell transcriptomic data.
Main Results:
- Developed a robust 4-gene pyroptosis risk model with predictive power for ccRCC prognosis.
- The model effectively reflects the immune microenvironment characteristics of ccRCC.
- Identified potential functional pathways and therapeutic targets associated with pyroptosis.
- Validation confirmed the model's reliability across different datasets.
Conclusions:
- The pyroptosis risk model serves as a valuable tool for predicting ccRCC patient prognosis.
- The model offers insights into the ccRCC immune landscape, potentially guiding treatment strategies.
- This research supports the use of pyroptosis-related genes for developing novel ccRCC therapies, including immune checkpoint inhibitors.
