ArticleBreast cancer (Dove Medical Press)2024
A Novel Peroxisome-Related Gene Signature Predicts Breast Cancer Prognosis and Correlates with T Cell Suppression.
Article in Breast cancer (Dove Medical Press), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Early Epigenetic and Metabolic Responses to the Adipocyte Secretome Reveal Stress-Adaptive States in Triple-Negative Breast Cancer.bioRxiv : the preprint server for biology · 2026Article
- The multifaceted roles of the ACSL family in cancer: Metabolic reprogramming, ferroptosis regulation and tumour immune microenvironment remodelling.Clinical and translational medicine · 2026Review
- Remodeling of Metabolic and Secretory Organelles During Oncogenic and Oncomodulatory Viral Infections.Viruses · 2026Review
- Peroxisomal activity drives aggressive bladder cancer phenotypes and reveals erythorbic acid as a potential therapeutic modulator.Frontiers in oncology · 2026Article
- Type I collagen promotes triple-negative breast cancer progression through a UBE2V1-ACSL5 regulatory axis.Frontiers in oncology · 2026Article
- Assessment of chemical risk factor for breast cancer based on gene expression profiles.Scientific reports · 2025Article
- FNDC5 and ACOX1 as Biomarkers of Peroxisomal Activity with Contrast Outcomes in Colon Adenocarcinoma.Biological procedures online · 2025Article
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Authors and funding
4 authors.
Funding
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Abstract
Background: Peroxisomes are increasingly linked to cancer development, yet the prognostic role of peroxisome-related genes (PRGs) in breast cancer remains unclear. Objective: This study aimed to construct a prognostic model based on PRG expression in breast cancer to clarify their prognostic value and clinical implications. Methods: Transcriptomic data from TCGA and GEO were used for training and validation cohorts. TME characteristics were analyzed with ESTIMATE, MCP-counter, and CIBERSORT algorithms. qPCR validated mRNA expression levels of risk genes, and data analysis was conducted in R. Results: Univariate and multivariate Cox regression identified a 7-gene PRG risk signature (ACBD5, ACSL5, DAO, NOS2, PEX3, PEX10, and SLC27A2) predicting breast cancer prognosis in training (n=1069), internal validation (n=327), and external validation (merged from four GEO datasets, n=640) datasets. While basal and Her2 subtypes had higher risk scores than luminal subtypes, a significant prognostic impact of the PRG risk signature was seen only in luminal subtypes. The high-risk subgroup exhibited a higher frequency of focal synonymous copy number alterations (SCNAs), arm-level amplifications and deletions, and single nucleotide variations. These increased genomic aberrations were associated with greater immune suppression and reduced CD8+ T cell infiltration. Bulk RNA sequencing and single-cell analyses revealed distinct expression patterns of peroxisome-related genes (PRGs) in the breast cancer TME: PEX3 was primarily expressed in malignant and stromal cells, while ACSL5 showed high expression in T cells. Additionally, the PRG risk signature demonstrated efficacy comparable to that of well-known biomarkers for predicting immunotherapy responses. Drug sensitivity analysis revealed that the PRG high-risk subgroup was sensitive to inhibitors of BCL-2 family proteins (BCL-2, BCL-XL, and MCL1) and other kinases (PLK1, PLK1, BTK, CHDK1, and EGFR). Conclusion: The PRG risk signature serves as a promising biomarker for evaluating peroxisomal activity, prognosis, and responsiveness to immunotherapy in breast cancer.
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