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利用多样化的细胞死亡相关特征预测肾透明细胞癌的预后和免疫治疗反应。

Leveraging diverse cell-death related signature predicts the prognosis and immunotherapy response in renal clear cell carcinoma.

机构信息

Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China.

Department of Endocrinology, Shenzhen University General Hospital, Shenzhen, Guangdong, China.

出版信息

Front Immunol. 2023 Dec 11;14:1293729. doi: 10.3389/fimmu.2023.1293729. eCollection 2023.

DOI:10.3389/fimmu.2023.1293729
PMID:38146369
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10749459/
Abstract

BACKGROUND

Modulation of programmed cell death in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects.

METHODS

We downloaded the data of clear cell renal cell carcinoma samples from The Cancer Genome Atlas and used a machine learning approach to build a new programmed cell death index (PCDI) through 13 programmed cell death-related genes. Based on PCDI, clinical features, tumor immune microenvironment, chemotherapy response and immunotherapy response were systematically analyzed.

RESULTS

PCDI consists of eight programmed cell death-related genes (TBX3, BID, TCIRG1, IDUA, KDR, PYCARD, IFNG and LRRK2). PCDI is a reliable predictor of survival in clear cell renal cell carcinoma patients and has been validated in multiple external datasets. We found that the high PCDI group showed higher levels of immune cell infiltration and better response to immunotherapy compared to the low PCDI group, and PCDI can also be used for prognostic prediction in a variety of cancers other than clear cell renal cell carcinoma. experiments demonstrated that knockdown of IDUA inhibited the proliferation and migration of clear cell renal cell carcinoma.

CONCLUSIONS

The PCDI identified in this study provides valuable insights into the clinical management of clear cell renal cell carcinoma by accurately evaluating the prognosis of patients with clear cell renal carcinoma and identifying the patient population that would benefit from immunotherapy.

摘要

背景

肿瘤细胞程序性细胞死亡的调节改变了肿瘤微环境和肿瘤浸润淋巴细胞的涌入,其诱导剂与免疫检查点抑制剂的联合使用在增强抗肿瘤作用方面发挥协同作用。

方法

我们从癌症基因组图谱中下载了透明细胞肾细胞癌样本的数据,并通过 13 个程序性细胞死亡相关基因,采用机器学习方法构建了一个新的程序性细胞死亡指数(PCDI)。基于 PCDI,系统分析了临床特征、肿瘤免疫微环境、化疗反应和免疫治疗反应。

结果

PCDI 由 8 个程序性细胞死亡相关基因(TBX3、BID、TCIRG1、IDUA、KDR、PYCARD、IFNG 和 LRRK2)组成。PCDI 是透明细胞肾细胞癌患者生存的可靠预测指标,并在多个外部数据集得到验证。我们发现,高 PCDI 组的免疫细胞浸润水平更高,对免疫治疗的反应更好,而低 PCDI 组则相反,并且 PCDI 还可以用于预测除透明细胞肾细胞癌以外的多种癌症的预后。实验表明,IDUA 的敲低抑制了透明细胞肾细胞癌的增殖和迁移。

结论

本研究中鉴定的 PCDI 通过准确评估透明细胞肾细胞癌患者的预后,并确定受益于免疫治疗的患者人群,为透明细胞肾细胞癌的临床管理提供了有价值的见解。

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