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PSMD2 过表达作为肾细胞癌接受免疫检查点抑制剂和酪氨酸激酶抑制剂治疗的耐药及预后生物标志物

英文原题:PSMD2 overexpression as a biomarker for resistance and prognosis in renal cell carcinoma treated with immune checkpoint and tyrosine kinase inhibitors.

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PSMD2 overexpression as a biomarker for resistance and prognosis in renal cell carcinoma treated with immune checkpoint and tyrosine kinase inhibitors.

PubMed 2024/09/02(内容时间) Cell Oncol (Dordr) Q1 · IF 5.6(JCR 2025)

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研究概要

PSMD2 表达升高与接受 ICI+TKI 治疗的 mRCC 患者的耐药和 PFS 缩短相关。高 PSMD2 水平还与 TIL(肿瘤浸润淋巴细胞)功能受损和耗竭增加相关。纳入 PSMD2 表达的 ML 模型可能有助于识别更可能从 ICI+TKI 中获益的患者。

研究思路结论见上方概要

整合免疫检查点抑制剂(ICIs)联合酪氨酸激酶抑制剂(TKIs)现已被推荐为转移性肾细胞癌(mRCC)的一线治疗方案。肿瘤中蛋白酶体26S亚基非ATP酶2(PSMD2)过表达与肿瘤进展相关。目前,mRCC尚缺乏用于ICI+TKI联合治疗的既定生物标志物。

本研究涉及来自两个接受ICI+TKI治疗的RCC患者队列(ZS-MRCC和JAVELIN-Renal-101)的RNA测序。我们利用免疫组织化学和流式细胞术,旨在评估高风险局部RCC样本中的免疫细胞浸润和功能。依据RECIST标准评估缓解和无进展生存期(PFS)。

PSMD2在晚期RCC中以及对ICI+TKI治疗无应答者中显著过表达。PSMD2过表达与ZS-MRCC和JAVELIN-101队列中较差的PFS相关。多因素Cox分析验证PSMD2为独立的PFS预测因子。PSMD2过表达与CD8+ T细胞减少相关,尤其是GZMB+ CD8+ T细胞,此外还伴有PD1+ CD4+ T细胞增加。另外,PSMD2水平高的肿瘤显示出T细胞耗竭水平增强和调节性T细胞存在增加。随后开发了一个基于PSMD2表达和其他筛选因素的机器学习(ML)模型,用于预测ICI+TKI的疗效。

展开英文摘要原文

Integrated immune checkpoint inhibitors (ICIs) plus tyrosine kinase inhibitors (TKIs) are now the recommended first-line therapy to manage renal cell carcinoma (mRCC). Proteasome 26S subunit non-ATPase 2 (PSMD2) overexpression in tumors has been correlated with tumor progression. Currently, mRCC lacks an established biomarker for the combination of ICI+TKI.

This study involved RNA sequencing of RCC patients from two cohorts treated with ICI+TKI (ZS-MRCC and JAVELIN-Renal-101). We utilized immunohistochemistry alongside flow cytometry, aiming at assessing immune cell infiltration and functionality in high-risk localized RCC samples. Response and progression-free survival (PFS) were evaluated relying upon RECIST criteria.

PSMD2 was significantly overexpressed in advanced RCC and among non-responders to ICI+TKI therapy. Overexpressed PSMD2 was correlated with poor PFS in the ZS-MRCC and JAVELIN-101 cohorts. Multivariate Cox analysis validated PSMD2 as an independent PFS predictor. PSMD2 overexpression was related to a reduction in CD8 + T cells, especially GZMB + CD8 + T cells, besides an increase in PD1 + CD4 + T cells. Additionally, tumors with high PSMD2 levels showed enhanced T cell exhaustion levels and a higher regulatory T cell presence. A Machine Learning (ML) model based on PSMD2 expression and other screened factors was subsequently developed to predict the effectiveness of ICI+TKI.

Elevated PSMD2 expression is linked to resistance and decreased PFS in mRCC patients undergoing ICI+TKI therapy. High PSMD2 levels are also associated with impaired function and increased exhaustion of tumor-infiltrating lymphocytes. An ML model incorporating PSMD2 expression could potentially identify patients who may have a higher likelihood of benefiting from ICI+TKI.

论文信息

作者
Xu X、Wang J、Wang Y、Zhu Y、Wang J、Guo J
单位
Department of Urology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China. xl.xu@hotmail.com.China
期刊
Cellular oncology (Dordrecht, Netherlands)2024 Oct
原文标识
PubMed 39222176 · DOI 10.1007/s13402-024-00977-z