Quantitative Proteomics of Breast Benign and Malignant Tumors Reveals a Malignancy Signature

Abstract

Abstract The distinction between benign and malignant breast tumors is a challenge in clinical settings. While omic studies have contributed to discovering genetic and proteomic signatures in breast cancer, the molecular differences between benign and malignant tumors remain less studied. This pilot study aimed to investigate proteomic differences between both type of tumors to identify protein signatures indicative of malignancy. The relevance of our findings was assessed using published proteomics and transcriptomic datasets. Using SWATH-based mass spectrometry, we quantified 1,221 proteins in benign (n = 10) and malignant (n = 5) breast tumors. Protein-protein interaction (PPI)-based networks and enrichment analyses revealed dysregulation in pathways associated with extracellular matrix organization, platelet degranulation, innate immune system, and RNA metabolism. Through unsupervised analysis, a four-protein signature (OGN, LUM, DCN, and COL14A1) associated with the extracellular matrix emerged, differentiating between benign and malignant tumors. This protein dysregulation pattern was consistently verified in cancerous versus non-cancerous breast tissue across diverse proteomics and transcriptomics datasets. Notably, the dysregulation magnitude was higher in breast cancer subtypes with poor prognosis, such as Basal-Like and HER2 compared to Luminal A. These findings suggest a potential role for the identified signature in discerning malignant from non-cancerous breast tissue, offering valuable insights into enhancing diagnostic precision.