Evidence map›Paper›PMID 41324818›Full record

ArticleDiscover oncology2025

FREM1 serves as a novel therapeutic target in breast cancer through basement membrane-based prognostic modeling with integrated bioinformatics and experimental validation.

Chao Li, Pingming Gong, Junfeng Hu, Chengyu Luo

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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.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chao LiDepartment of General Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
Pingming GongDepartment of General Surgery, Beijing Luhe Hospital, Capital Medical University, Beijing, 101149, China.
Junfeng HuDepartment of General Surgery, Beijing Luhe Hospital, Capital Medical University, Beijing, 101149, China.
Chengyu LuoDepartment of General Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China. luochengyu@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer remains the leading cause of cancer-related mortality in women worldwide, with metastatic disease posing significant therapeutic challenges. While immunotherapy has shown promise, tumor immune evasion limits its efficacy. The basement membrane (BM), a specialized extracellular matrix structure, plays a crucial yet understudied role in breast cancer progression and immune modulation. This study aims to investigate the prognostic value and therapeutic potential of BM-related genes in breast cancer.

methodsWe integrated transcriptomic data from TCGA and GEO databases to construct a BM-related gene signature. Unsupervised clustering stratified patients into molecular subtypes, while differential expression analysis identified key BM-associated genes. Functional enrichment analyses (GO, KEGG, GSEA) elucidated biological pathways, and immune microenvironment characterization was performed using ESTIMATE and CIBERSORT. Machine learning approaches pinpointed critical BM-related genes, which were subsequently validated through in vitro experiments.

resultsBreast cancer patients were classified into high- and low-BM groups, with the low-BM cohort exhibiting worse prognosis. Pathway analysis revealed significant enrichment in immune regulation, ECM remodeling, and cytokine signaling. FREM1 emerged as a top protective gene through machine learning. Experimental validation in breast cancer cell lines showed that FREM1 expression was significantly lower in tumor cells compared to normal cells. Upon overexpression of FREM1 in breast cancer cell lines, as confirmed by both qPCR and Western blot, we observed a significant reduction in tumor cell proliferation, migration, and invasion. These findings suggest that FREM1 overexpression impairs the aggressiveness of breast cancer cells, reinforcing its potential as a tumor suppressor.

conclusionOur study establishes BM-related genes as novel prognostic biomarkers and therapeutic targets in breast cancer. FREM1 in particular functions as a tumor suppressor by inhibiting cancer cell proliferation, migration, and invasion, highlighting its potential for therapeutic exploitation. These findings provide critical insights into BM-mediated tumor progression and suggest new avenues for targeted breast cancer therapy.

Identifiers

PMID41324818
PMCPMC12770021

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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.