Comparative profiling of whole-cell and exosome samples reveals protein signatures that stratify breast cancer subtypes

• Published in: Cellular and molecular life sciences : CMLS 2024-12, Vol.81 (1), p.363
• Main Authors: Andreu, Zoraida, Hidalgo, Marta R., Masiá, Esther, Romera-Giner, Sergio, Malmierca-Merlo, Pablo, López-Guerrero, José A., García-García, Francisco, Vicent, María J.
• Format: Article
• Language: English
• Subjects: Angiogenesis; Biochemistry; Biomarkers; Biomarkers, Tumor - metabolism; Biomedical and Life Sciences; Biomedicine; Biopsy; Breast cancer; Breast Neoplasms - classification; Breast Neoplasms - genetics; Breast Neoplasms - metabolism; Breast Neoplasms - pathology; Cell Biology; Cell Line, Tumor; Drug resistance; Exosomes; Exosomes - metabolism; Extracellular vesicles; Female; Humans; Invasiveness; Life Sciences; Medical research; Metastases; Metastasis; Mutation; Original Article; Protein expression; Proteins; Proteome - metabolism; Proteomics; Proteomics - methods; Research centers; Webs (structural)
• ISSN: 1420-682X; 1420-9071; 1420-9071
• DOI: 10.1007/s00018-024-05403-z

Identifying novel breast cancer biomarkers will improve patient stratification, enhance therapeutic outcomes, and help develop non-invasive diagnostics. We compared the proteomic profiles of whole-cell and exosomal samples of representative breast cancer cell subtypes to evaluate the potential of extracellular vesicles as non-invasive disease biomarkers in liquid biopsies. Overall, differentially-expressed proteins in whole-cell and exosome samples (which included markers for invasion, metastasis, angiogenesis, and drug resistance) effectively discriminated subtypes; furthermore, our results confirmed that the proteomic profile of exosomes reflects breast cancer cell-of-origin, which underscores their potential as disease biomarkers. Our study will contribute to identifying biomarkers that support breast cancer patient stratification and developing novel therapeutic strategies. We include an open, interactive web tool to explore the data as a molecular resource that can explain the role of these protein signatures in breast cancer classification. Graphical Abstract ( A ) We quantified proteomic profiles of breast cancer cells (BCCs) and breast cancer-derived exosomes (BCDEs) samples from four breast cancer cell lines representative of common breast cancer subtypes – Her2-positive (Her2, MDA-MB-453), Luminal A (LA, MCF7), Luminal B (LB, ZR-75), and triple-negative (TN, MDA-MB-231). ( B ) We independently performed four comparisons for BCCs and BCDEs, comparing each cell line against the remaining three. ( C ) We identified differentially-expressed proteins (DEPs) for BCCs and BCDEs, defined protein signatures, and functionally analyzed resulting networks. Through pathway inference analysis (PIA), we identified Kyoto Encyclopedia of genes and genomes (KEGG) subpaths and biological Gene Ontology (GO) terms that displayed differential activation. ( D ) We validated our proteomic signature using the Cancer Genome Atlas (TCGA) and the Cancer Proteome Atlas (TCPA) databases, verified that differentially-activated pathways in BCDEs caused a corresponding response in receptor cells, and confirmed that the BCDE proteomic signature reflects their cell-of-origin and identifies candidate disease biomarkers in liquid biopsies