Document Type
Article
Publication Date
1-1-2025
Abstract
Solid tumors present a formidable challenge in oncology, necessitating innovative approaches to improve therapeutic outcomes. Proteoglycans, multifaceted molecules within the tumor microenvironment, have garnered attention due to their diverse roles in cancer progression. Their unique ability to interact with specific membrane receptors, growth factors, and cytokines provides a promising avenue for the development of recombinant proteoglycan-based therapies that could enhance the precision and efficacy of cancer treatment. In this study, we performed a comprehensive analysis of the proteoglycan gene landscape in human breast carcinomas. Leveraging the available wealth of genomic and clinical data regarding gene expression in breast carcinoma and using a machine learning model, we identified a unique gene expression signature composed of five proteoglycans differentially modulated in the tumor tissue: Syndecan-1 and asporin (upregulated) and decorin, PRELP and podocan (downregulated). Additional query of the breast carcinoma data revealed that serglycin, previously shown to be increased in breast carcinoma patients and mouse models and to correlate with a poor prognosis, was indeed decreased in the vast majority of breast cancer patients and its levels inversely correlated with tumor progression and invasion. This proteoglycan gene signature could provide novel diagnostic capabilities in breast cancer biology and highlights the need for further utilization of publicly available datasets for the clinical validation of preclinical experimental results.
Recommended Citation
Buraschi, Simone; Pascal, Gabriel; Liberatore, Federico; and Iozzo, Renato V., "Comprehensive Investigation of Proteoglycan Gene Expression in Breast Cancer: Discovery of a Unique Proteoglycan Gene Signature Linked to the Malignant Phenotype" (2025). Department of Pathology, Anatomy, and Cell Biology Faculty Papers. Paper 487.
https://jdc.jefferson.edu/pacbfp/487
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
40066261
Language
English

Comments
This article is the author’s final published version in Proteoglycan Research, Volume 3, Issue 1, 2026, Article number e70014.
The published version is available at https://doi.org/10.1002/pgr2.70014. Copyright © 2025 The Author(s).