Investigating chemoresistance in triple negative breast cancer, by imaging-guided MS-proteomics

Triple negative breast cancer (TNBC) is an aggressive disease whose standard treatment is neoadjuvant platinum-based chemotherapy. However, chemoresistance and relapse are common for this cancer subtype. While it is clear that the understanding the tumor microenvironment (TME) is essential for improving chemotherapeutic efficacy, systematic analyses with high spatial and phenotypic resolution have remained limited.

My aim is to better understand the TME of TNBC with cell-type and spatial resolution by expanding the Deep Visual Proteomics framework.

We analyzed a cohort of 90+ patient biopsies, before and after chemotherapy, to characterize key biomarkers predictive of the variable treatment outcomes. We performed multiplex imaging with a tissue-specific panel of 25+ markers to identify the majority of cell types of the TME. Images are stitched, registered, segmented, and cells classified with a Nextflow pipeline --- taking advantage of its transparency and replicability. Analyzing the spatial distribution of all cells allowed us to categorize distinct cellular niches; this perspective has the potential to identify novel associations between cellular distributions and diverse treatment outcomes.

Lastly, these analyses will enable the prioritization of the most interesting cellular phenotypes, which will be collected by laser microdissection for deep proteomic profiling by mass spectrometry (4000+ proteins), characterizing their global, functional states. These multimodal data provide us with unique insights into spatially and cell-type resolved proteomic changes induced by chemotherapy of TNBC, potentially identifying novel response markers that could improve clinical decision making in the long term.