The work presented in this thesis demonstrates the great potential of using mass spectrometry-based quantitative (phospho)proteomics technologies to study and characterize proteins and their signaling networks in cancer research.
More specifically, using breast cancer as a model system, we show that proteomics is a very powerful tool offering great opportunities to discover novel protein biomarker signatures and unravel the molecular mechanisms and protein interaction networks involved in cancer treatment, progression and metastasis. Overall, three main research projects are presented in this thesis.
In the first project, we explored the biomarker potential of breast cancer-derived extracellular vesicles (EVs) by comparing the (phospho)proteome profiles of different breast (cancer) cell lines, with a special emphasis on the TNBC and HER2 subtypes. We showed that the EV proteomes nicely clustered based on their respective subtypes, revealing subtype-specific protein clusters that reflect BC etiology.
In the second project, we attempted to understand the mechanisms of drug synergy, when EGFR and ROCK inhibitors are combined for the treatment of TNBC tumors. We performed a deep proteomic and phosphoproteomic profiling to identify proteins and pathways altered upon single and combination treatments and found autophagy as a mechanism implicated in the cells’ response to combinatorial treatment.
Finally, in the third project, we aimed to gain insight into the molecular mechanisms regulating the function of the oncogenic transcription factor Fra-1 in metastasis by exploring the nature of Fra-1 protein complexes in breast cancer cells. Our analysis revealed next to known Fra-1 interactors, several novel potentially interesting interaction partners.