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肿瘤微环境中的CTSS与肾透明细胞癌的免疫逃逸和免疫治疗敏感性相关。

CTSS in the tumor microenvironment links immune escape and immunotherapy sensitivity in kidney renal clear cell carcinoma.

作者信息

Zhou Hanjing, Ying Jun, Xu Xuchun, Huang Jian

机构信息

Department of Nephrology, Jinhua Hospital of Zhejiang University, Jinhua, 321000, Zhejiang, China.

出版信息

Discov Oncol. 2025 Jul 29;16(1):1439. doi: 10.1007/s12672-025-03267-8.

Abstract

The tumor microenvironment (TME) of kidney renal clear cell carcinoma (KIRC) exhibits complex dynamics among immune, stromal, and malignant cells that drive immune escape (IE) mechanisms and influence clinical outcomes. Through single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis (hdWGCNA), we identified a crucial IE-related gene module most strongly associated with KIRC progression. Partitioning Around Medoids (PAM) clustering delineated two distinct IE patterns, with pattern one demonstrating prolonged patient survival. Employing advanced machine learning (ML) algorithms, we identified Cathepsin S (CTSS) as the most pivotal tumor suppressor, with elevated CTSS expression consistently predicting improved survival across multiple independent cohorts. Functional analyses revealed significant enrichment of CTSS in immune-regulatory pathways, including B/T cell activation and inflammatory activity. Mutation profiling uncovered distinct genomic alterations in 5q35.3 among CTSS-high tumors, while drug response prediction identified eight potential therapeutic agents (e.g., Navitoclax, Ibrutinib) exhibiting enhanced efficacy in these patients. Notably, CTSS expression strongly correlated with immune cell infiltration and established immunotherapy biomarkers, supporting its dual role as both a prognostic indicator and predictor of immune response. This study provides mechanistic insights into IE in KIRC and positions CTSS as a promising biomarker and therapeutic target for precision immunotherapy.

摘要

肾透明细胞癌(KIRC)的肿瘤微环境(TME)在免疫、基质和恶性细胞之间呈现出复杂的动态变化,这些变化驱动免疫逃逸(IE)机制并影响临床结果。通过单细胞RNA测序和高维加权基因共表达网络分析(hdWGCNA),我们确定了一个与KIRC进展最密切相关的关键IE相关基因模块。围绕中心点划分(PAM)聚类确定了两种不同的IE模式,模式一显示患者生存期延长。采用先进的机器学习(ML)算法,我们确定组织蛋白酶S(CTSS)为最关键的肿瘤抑制因子,CTSS表达升高始终预示着多个独立队列患者生存率的提高。功能分析表明,CTSS在免疫调节途径中显著富集,包括B/T细胞活化和炎症活性。突变分析揭示了CTSS高表达肿瘤中5q35.3存在明显的基因组改变,而药物反应预测确定了八种潜在治疗药物(如维托卡夫、依鲁替尼)在这些患者中显示出增强的疗效。值得注意的是,CTSS表达与免疫细胞浸润和既定的免疫治疗生物标志物密切相关,支持其作为预后指标和免疫反应预测指标的双重作用。本研究为KIRC中的IE提供了机制性见解,并将CTSS定位为精准免疫治疗的有前景的生物标志物和治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cd3/12307852/05c738376318/12672_2025_3267_Fig1_HTML.jpg

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