Evidence map›Paper›PMID 41233852›Full record

ArticleBreast cancer research : BCR2025

Integrating bulk and single-cell RNA sequencing analysis to reveal characterization of mechanical stimulus-related genes and prognostic signatures in breast cancer.

Ze Yang, Haifeng Lou, Yuqiao Huang, Lingyun Guo, Yingfei Huang, Gao Zhu, Jingjia Li, Yindan Lin, Jiang Zhu, Yandi Sun

Abstract read
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Article in Breast cancer research : BCR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Ze Yang *School of Life Science, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China. zyang2015@zju.edu.cn.
Haifeng Lou *Department of Ultrasound, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
Yuqiao Huang *Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
Lingyun GuoCancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
Yingfei HuangCancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
Gao ZhuDepartment of Otolaryngology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China.
Jingjia LiZhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China.
Yindan LinDepartment of Toxicology and Cancer Biology, University of Kentucky College of Medicine, Lexington, KY, 40536, USA.
Jiang ZhuDepartment of Ultrasound, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China. zhujiang1046@zju.edu.cn.
Yandi SunSchool of Life Science, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China. 0621565@zju.edu.cn.

Funding

Natural Science Foundation of Zhejiang Province LZ22H180001the National Natural Science Foundation of China 32400633the National Natural Science Foundation of China 82272004the Research Project of Zhejiang Chinese Medical University 2024RCZXZK48
6 · The paper itself

Abstract

objectivesTo identify molecular clusters and establish a scoring model based on mechanical stimulus-related genes (MSRGs) for predicting the prognosis of breast cancer patients and understanding the role of mechanical stimuli in the breast tumor microenvironment (TME).

methodsWe utilized bulk and single-cell RNA sequencing analysis to characterize MSRGs associated with breast cancer prognosis. Unsupervised consensus molecular clustering was applied to identify distinct clusters based on overall survival-associated MSRGs from The Cancer Genome Atlas (TCGA) database. The scoring model was constructed by LASSO-Cox method and validated. Additionally, single-cell RNA sequencing analysis, along with in vitro and in vivo experiments, were conducted to further investigate the role of the model in breast cancer.

resultsWe identified 23 overall survival-associated MSRGs and established two molecular subgroups with distinct survival outcomes. A prognostic signature incorporating 15 MSRGs was developed and validated, demonstrating its predictive capability for overall survival of breast cancer patients. The nomogram integrating clinical characteristics and the mechanical stimulus-related risk score exhibited promising predictive accuracy. The low-risk group displayed an immune "hot" phenotype with increased immune cell infiltration, while the high-risk group exhibited resistance to conventional chemotherapy but potential sensitivity to Sepantronium bromide. By using the SCISSOR algorithm, we provide evidence at single-cell resolution for the impact of mechanical stimulation on tumor immune microenvironment. The in vivo and in vitro assays demonstrated that knockdown of TEX19 significantly suppressed breast tumor proliferation.

conclusionWe developed a pioneering prognostic signature incorporating MSRGs in breast cancer, with a particular focus on mechanical stimuli may influence breast cancer prognosis by remodeling the immune microenvironment. The findings highlighted the importance of personalized treatment strategies and provide new insights into the role of mechanical forces in breast tumor biology.

Indexed as

Biomarkers, TumorBreast NeoplasmsGene Expression Regulation, NeoplasticSingle-Cell AnalysisAnimalsCell Line, TumorFemaleGene Expression ProfilingHumansMiceNomogramsPrognosisSequence Analysis, RNATumor MicroenvironmentBiomarkers, TumorBreast cancerMechanical stimulusPrognostic signatureTumor immune microenvironment

Identifiers

PMID41233852
PMCPMC12616973

What Socratic holds

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LicenceCC BY
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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 Socratic graph.