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

## TL;DR

This study introduces a new mass spectrometry method to compare proteins in normal and cancerous breast tissue, identifying potential biomarkers for breast cancer.

## Contribution

A novel label-free microLC–SWATH-MS method with immunoaffinity depletion of serum proteins for proteomic profiling of breast tissue and tumors.

## Key findings

- 158 proteins showed significant differences between tumor and normal breast tissue, including 59 upregulated and 23 downregulated proteins.
- Functional analysis linked these proteins to processes like ECM organization, focal adhesion, and metabolic pathways relevant to breast cancer.
- The method enabled robust proteomic profiling with a custom spectral library generated from immunoaffinity-depleted pooled samples.

## Abstract

Mass spectrometry (MS)-based proteomics can provide deep insights into protein-driven molecular processes and signaling pathways in breast cancer, thereby contributing to improvements in disease diagnosis, treatment, and prevention. This study focuses on the development of a label-free quantitative proteomic profiling approach for the analysis of fresh-frozen human normal breast tissue (BTIS) and breast tumor (BTUM) samples.

A pilot set of BTIS and BTUM samples obtained from eight patients diagnosed with luminal B (Lum B) or triple-negative breast cancer (TNBC) was analyzed using micro-liquid chromatography coupled to tandem mass spectrometry (microLC–MS/MS) in a data-independent acquisition sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mode. To expand proteome coverage during SWATH data extraction, an experimental spectral ion library was generated from the MS/MS spectra of a pooled sample comprising aliquots from all analyzed BTIS and BTUM samples. To expand the spectral library, the pooled sample was immunodepleted of the 14 most abundant serum proteins, enabling deeper proteome coverage.

A total of 562 proteins were identified at a false discovery rate (FDR) of <1%, of which 299 were successfully quantified across all samples. Among these, 158 proteins showed statistically significant differences (p < 0.05) between breast tumor and normal breast tissue samples, including 59 proteins that were upregulated and 23 that were downregulated by at least 1.5-fold. Functional enrichment analysis revealed that the quantified proteins were associated with cellular structures and compartments relevant to breast cancer biology, such as the extracellular matrix (ECM), extracellular exosomes, and nucleosomes. These proteins were also involved in biological processes implicated in disease development and progression, including ECM organization, focal adhesion, mRNA splicing via the spliceosome, interleukin-12-mediated signaling, platelet activation, and metabolic pathways related to amino acid metabolism and gluconeogenesis/glycolysis.

This proof-of-concept study demonstrates that the developed microLC–SWATH-MS approach, combined with a custom spectral library generated from pooled breast tissue and tumor samples immunoaffinity-depleted of 14 high-abundance serum proteins, enables robust and high-throughput proteomic profiling of breast tissue and tumors. Further expansion of high-quality spectral libraries may enhance proteome coverage and improve the clinical applicability of this approach. While the methodology supports the discovery of candidate biomarkers and therapeutic targets relevant to translational research and precision oncology, the biological conclusions drawn from this study should be interpreted with caution due to the limited sample size. Validation in larger patient cohorts using orthogonal methods will be required to confirm the potential clinical utility of the identified proteins.