Evidence map›Paper›PMID 40879787›Full record

ArticleFunctional & integrative genomics2025

MZB1-Driven Endoplasmic reticulum stress model as a predictor of breast cancer progression and survival.

Purong Zhang, Rui Wang, Yuying Wang, Ning Zhang, Ke Luo

Abstract read
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In one paragraph

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

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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

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Purong ZhangDepartment of Breast Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Sichuan, Chengdu, China.
Rui WangCollege of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
Yuying WangDepartment of Breast Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Sichuan, Chengdu, China.
Ning ZhangDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277, Jiefang Avenue, Wuhan, 430030, Hubei, China. zhangning_uh@hust.edu.cn.
Ke LuoThe Breast Disease Center, The Affiliated Hospital of Guizhou Medical University, No. 28, Guiyi street, Guiyang, 550001, Guizhou, China. 18984385211@163.com.

Funding

Beijing Medical Award Foundation YXJL-2021-0092-0333Sichuan Science and Technology Program 2023YFS0103
6 · The paper itself

Abstract

Endoplasmic reticulum (ER) stress and its associated unfolded protein response (UPR) have been demonstrated to play a crucial role in cancer's progression, but their prognostic significance in breast cancer (BC) remains unclear. In this study, a reliable ER-related gene signature was developed for the purpose of predicting BC prognosis and investigating the associated immune landscape. By utilizing public datasets and analytical methods, we developed a 16 ER-related gene risk signature and verified its efficacy in predicting prognosis in independent patient groups. Patients in the high-risk group exhibited significantly poorer survival rates. Single-cell analysis revealed that the low-risk group exhibited stronger immune interactions. Conversely, the high-risk group exhibiting elevated immune checkpoints may signify an immunosuppressive microenvironment or heightened sensitivity to immune checkpoint inhibitor therapy. In vitro and vivo experiments confirmed that knocking down the expression of Marginal Zone B And B1 Cell Specific Protein (MZB1) significantly inhibited the proliferation, invasion, and tumorigenesis of breast cancer. The 16 ER-related gene signature is capable of effectively categorizing breast cancer patients into different risk levels, thereby providing a basis for personalized therapy. MZB1 has been identified as a significant regulatory factor, suggesting its potential as a target for the treatment of breast cancer.

Indexed as

Breast NeoplasmsEndoplasmic Reticulum StressAnimalsBiomarkers, TumorCell Line, TumorCell ProliferationDisease ProgressionFemaleGene Expression Regulation, NeoplasticHumansMicePrognosisTumor MicroenvironmentUnfolded Protein ResponseBiomarkers, TumorBreast cancerEndoplasmic reticulum stressMachine learningMZB1Tumor microenvironment

Identifiers

PMID40879787
PMCPMC12397153

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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.