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基于 TCGA 和单细胞 RNA 测序数据库的焦亡相关基因特征预测 ccRCC 的预后。

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

机构信息

Department of Urology, Peking University First Hospital, Beijing 100034, China.

出版信息

J Healthc Eng. 2022 Oct 30;2022:8224618. doi: 10.1155/2022/8224618. eCollection 2022.

DOI:10.1155/2022/8224618
PMID:36349258
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9637477/
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.

摘要

透明细胞肾细胞癌(ccRCC)是最常见的肾癌类型,对放疗和化疗均不敏感。转移性肾细胞癌对靶向药物和免疫疗法的客观缓解率并不理想。细胞焦亡已被证实为一种炎症形式的程序性细胞死亡,可以被一些炎性小体激活,同时在肿瘤中释放炎症因子可创造出肿瘤抑制环境。为了探索预测 ccRCC 预后和抗肿瘤治疗效果的指标,我们在 TCGA 数据库中扫描了 516 例 ccRCC 病例的 11 个与细胞焦亡相关的基因后,构建了一个包含 4 个基因的细胞焦亡风险模型。基于风险评分,将 516 例 ccRCC 病例分为两组进行功能富集分析和免疫特征分析,以寻找功能途径和潜在的治疗靶点。此外,还在 GSE29609 和单细胞转录组数据中对这些结果进行了验证。该研究表明,所构建的细胞焦亡模型可以预测 ccRCC 的预后,并反映免疫微环境,这可能有助于免疫检查点抑制剂的治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/9d3131387341/JHE2022-8224618.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/7bde541929aa/JHE2022-8224618.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/5f99ae741d45/JHE2022-8224618.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/a1fb05b527af/JHE2022-8224618.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/f2d469d57b14/JHE2022-8224618.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/8818836e717d/JHE2022-8224618.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/9d3131387341/JHE2022-8224618.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/7bde541929aa/JHE2022-8224618.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/fa2bcb32aff5/JHE2022-8224618.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/5f99ae741d45/JHE2022-8224618.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/a1fb05b527af/JHE2022-8224618.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/f2d469d57b14/JHE2022-8224618.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/8818836e717d/JHE2022-8224618.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3598/9637477/9d3131387341/JHE2022-8224618.007.jpg

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