A label-free microLC-SWATH-MS methodology with immunoaffinity depletion of high abundant serum proteins for quantitative proteomic comparison of fresh-frozen human normal breast tissue and tumor clinical specimens

Katarzyna Macur^1*Aleksandra Ewa Bogucka²Anna Fel-Tukalska³Jarosław Skokowski^4,5Stanisław Ołdziej⁶Paulina Czaplewska⁷

• ¹Intercollegiate Faculty of Biotechnology University of Gdańsk and Medical University of Gdańsk, Core Facility Laboratories, University of Gdańsk, Gdańsk, Poland
• ²Department of Physiology, Medical University of Gdańsk, Gdańsk, Poland
• ³Intercollegiate Faculty of Biotechnology University of Gdańsk and Medical University of Gdańsk, Laboratory of Biopolymer Structure, University of Gdańsk, Gdańsk, Poland
• ⁴Faculty of Medicine, Academy of Applied Medical and Social Sciences – AMiSNS (Akademia Medycznych i Społecznych Nauk Stosowanych), 52-300, Elbląg, Poland
• ⁵Clinical Department of General Surgery and Surgical Oncology, Saint Wojciech” Hospital, “Copernicus” Health Center, 80-000 Gdańsk, Poland
• ⁶Intercillegiate Faculty of Biotechnology University of Gdańsk and Medical University of Gdańsk, Laboratory of Biopolymer Structure, University of Gdańsk, Gdańsk, Poland
• ⁷Intercollegiate Faculty of Biotechnology University of Gdańska and Medical University of Gdańsk, Core Facility Laboratories, University of Gdańsk, Gdańsk, Poland

Background: Mass spectrometry (MS)–based proteomics provides valuable insights into protein-driven molecular mechanisms and signaling pathways in breast cancer, with potential applications in diagnosis, treatment, and prevention. This study aimed to develop a label-free quantitative proteomic workflow for the analysis of fresh-frozen human normal breast tissue (BTIS) and breast tumor (BTUM) samples. Methods: A pilot cohort of BTIS and BTUM samples from eight patients diagnosed with luminal B (LumB) or triple-negative breast cancer (TNBC) was analyzed using micro–liquid chromatography coupled to tandem mass spectrometry (microLC–MS/MS) in data-independent acquisition SWATH mode. To maximize proteome coverage during SWATH data extraction, a custom spectral ion library was generated from a pooled sample containing aliquots of all BTIS and BTUM specimens. To further enhance depth of coverage, the pooled sample was immunodepleted of the 14 most abundant serum proteins prior to library generation. Results: In total, 562 proteins were identified at a false discovery rate (FDR) <1%, of which 299 were consistently quantified across all samples. Comparative analysis revealed 158 proteins with statistically significant differences (p < 0.05) between BTUM and BTIS samples, including 59 upregulated and 23 downregulated proteins with fold changes ≥1.5. Functional enrichment analysis showed that the quantified proteins were associated with key cellular compartments relevant to breast cancer biology, including the extracellular matrix, extracellular exosomes, and nucleosomes. Enriched biological processes included extracellular matrix organization, focal adhesion, mRNA splicing via the spliceosome, interleukin-12–mediated signaling, platelet activation, and metabolic pathways related to amino acid metabolism and glycolysis/gluconeogenesis. Conclusions: This proof-of-concept study demonstrates that a microLC–SWATH-MS workflow combined with a custom, immunodepleted spectral library enables robust and high-throughput proteomic profiling of breast tissue and tumors. While the approach supports the discovery of candidate biomarkers and therapeutic targets, biological interpretations are limited by the small sample size and require validation in larger cohorts using orthogonal methods.