Evidence map›Paper›PMID 40730712›Full record

ArticleDiscover oncology2025

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

Hanjing Zhou, Jun Ying, Xuchun Xu, Jian Huang

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hanjing ZhouDepartment of Nephrology, Jinhua Hospital of Zhejiang University, Jinhua, 321000, Zhejiang, China.
Jun YingDepartment of Nephrology, Jinhua Hospital of Zhejiang University, Jinhua, 321000, Zhejiang, China.
Xuchun XuDepartment of Nephrology, Jinhua Hospital of Zhejiang University, Jinhua, 321000, Zhejiang, China.
Jian HuangDepartment of Nephrology, Jinhua Hospital of Zhejiang University, Jinhua, 321000, Zhejiang, China. zjjhzxyyhj@163.com.

Funding

Key science and technology project in Jinhua City 2021-3-073
6 · The paper itself

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.

Indexed as

CTSSImmune escapeImmunotherapyKIRCMachine learning

Identifiers

PMID40730712
PMCPMC12307852

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.