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pmid:36349258

Pyroptosis-Related Gene Signature Predicts the Prognosis of ccRCC Using TCGA and Single-Cell RNA Seq Database.

Ying Gan · Zhenan Zhang · Xiaofei Wang · Aolin Li · Yu Fan · Qian Zhang

Journal of healthcare engineering · 2022 doi:10.1155/2022/8224618

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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title
Pyroptosis-Related Gene Signature Predicts the Prognosis of ccRCC Using TCGA and Single-Cell RNA Seq Database.
doi
10.1155/2022/8224618
pmid
36349258
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Ying Gan
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Zhenan Zhang
[2]
Xiaofei Wang
[3]
Aolin Li
[4]
Yu Fan
[5]
Qian Zhang
journal
Journal of healthcare engineering
year
2022
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.
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Multivariate Cox regression analyses were used for the pyroptosis risk model establishment (Supplementary Table S1).
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sections[11] "3.2. Construction and Evaluation of the Pyroptosis Risk Model" paragraph 2
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Multivariate Cox regression analyses were used for the pyroptosis risk model establishment (Supplementary Table S1).
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The risk model had an accuracy of 0.674 (95% CI: 0.624–0.724) in the TCGA cohort (Figure 4(b)).
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The risk model had an accuracy of 0.674 (95% CI: 0.624–0.724) in the TCGA cohort (Figure 4(b)).
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sections[11] "3.2. Construction and Evaluation of the Pyroptosis Risk Model" paragraph 3
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The risk model had an accuracy of 0.674 (95% CI: 0.624–0.724) in the TCGA cohort (Figure 4(b)).
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Complete file
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