Evidence map›Paper›PMID 41003895›Full record

ArticleDiscover oncology2025

Multi-omics analysis reveals the prognostic value and immunomodulatory role of CTSW in breast cancer.

Xvliang Liu, Zeli Yin, Pengju Xi, Liming Wang, Jiakai Mao

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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Unveiling the Immune Mechanisms of Hypertension With Single-Cell Transcriptome-Wide Mendelian Randomization.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xvliang Liu *Department of General Surgery, Division of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Zeli Yin *Engineering Research Center for New Materials and Precision Treatment Technology of Malignant Tumors Therapy, The Second Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China.
Pengju Xi *Department of General Surgery, Division of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Liming WangDepartment of General Surgery, Division of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China. wangbcc259@163.com.
Jiakai MaoDepartment of General Surgery, Division of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.

Funding

Innovative Teams Project in Key Areas of Dalian 2021RT01Liaoning Province Talent Plan project YXMJ-JC-04National Natural Science Foundation of China 81972749the Science and Technology Project of Liaoning 2021JH2/10300020United Foundation for Dalian Institute of Chemical Physics, Chinese Academy of Sciences and the Second Hospital of Dalian Medical University DMU-2&DICP UN202301
6 · The paper itself

Abstract

backgroundThe inherent complexity and biological heterogeneity of breast cancer pose substantial challenges to the development of effective personalized therapies. The exploration of novel biomarkers, particularly those linked to the tumor immune microenvironment (TME), presents promising opportunities. This study employed a multi-omics framework to investigate the potential regulatory role of cysteine proteases in breast cancer, aiming to identify and characterize novel prognostic markers and strategic therapeutic targets.

methodsWe employed a comprehensive in silico analysis utilizing transcriptomic, methylomic, quantitative trait locus, and genome-wide association studies data. Differentially expressed genes (DEGs) were identified using established statistical tools. Their prognostic significance was assessed through Cox regression and Kaplan-Meier survival analyses. Mendelian randomization (MR) was used to infer potential causal relationships between gene expression and breast cancer risk. Functional enrichment analysis and immune infiltration assessment were performed to elucidate the biological context of DEGs. Single-cell RNA sequencing data provided high-resolution insights into the TME, and protein-protein interaction networks identified key biological pathways.

findingsCTSW emerged as a gene of critical prognostic significance. High CTSW expression was strongly correlated with improved patient survival across breast cancer subtypes. Causal inference via MR provided strong genetic evidence supporting a protective role for CTSW against breast cancer risk. Functional enrichment analysis implicated CTSW in key immune-related pathways, including T-cell activation. Crucially, single-cell analysis revealed that CTSW expression was not only enriched in activated CD8 + T cells but its intrinsic per-cell expression was highest within the triple negative breast cancer (TNBC) subtype, suggesting CTSW reflects the functional quality, not merely the quantity, of T-cell infiltration. This heightened expression in activated CD8 + T cells was strongly associated with a better prognosis. Finally, DNA methylation analysis suggested that epigenetic silencing contributes to CTSW's downregulation in breast cancer. INTERPRETATIONS: This study underscores the pivotal role of CTSW in breast cancer immunology, positioning it as a key indicator of a potent anti-tumor immune response within the TME. Collectively, our findings establish a robust, data-driven hypothesis that CTSW's high expression, particularly in TNBC, reflects a favorable, functionally active immune state. This comprehensive in silico investigation substantiates CTSW's potential as a prognostic biomarker and provides a strong rationale for its future experimental validation as a therapeutic target.

Indexed as

Breast cancerCTSWMendelian randomizationMulti-omics

Identifiers

PMID41003895
PMCPMC12474806

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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.