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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月29日

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  • Hanjing Zhou,
  • Jun Ying,
  • Xuchun Xu,
  • Jian Huang

摘要

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.