A novel proteomic mass spectrometry-based approach to reveal functionally heterogeneous tumor clones in breast cancer metastases and identify clone-specific drug targets.

Abstract

e13063 Background: Breast cancer mortality is expected to rise by almost 30% by 2030 worldwide, mainly due to the occurrence of distant metastases. The development of drugs specifically targeted at tumor drivers has not yet curbed resistance to treatment, which prevents metastases curability. There is a need for new molecular approaches to tackle metastases complex biology, particularly tumor heterogeneity, a main determinant of resistance. The aim of this study was to use a proteomic mass spectrometry-based approach to reveal functionally heterogeneous’ tumor subpopulations in breast cancer metastases, and identify clone specific drug targets. Methods: Metastasis biopsies (n = 21) were collected retrospectively from patients with advanced breast cancer treated at Oscar Lambret Cancer Center (Lille, France). Tumor heterogeneity was analyzed directly on FFPE tissue sections using MALDI mass spectrometry imaging (MSI) on a RapifleX Tissuetyper. Unsupervised spatial segmentation was performed to reveal tumor subpopulations with distinct proteomic profiles within each metastasis. The full proteomic characterization of these tumor clones was further performed with spatially resolved proteomic mass spectrometry. Results: MSI revealed that breast cancer metastases contained 2 to 5 functionally distinct tumor clones (proteomic clones). Although the clone profiles within a metastasis were correlated, unsupervised hierarchical clustering showed a clear distinction between them and specific proteomic signatures. Enrichment analysis showed that differentially expressed proteins were involved in a variety of biological processes or pathways including regulation of histone acetylation, extracellular matrix degradation, DNA repair, NOTCH pathway, estrogen-responsive target genes or exocytosis. The evolution of the proteomic clones profile during disease progression was also determined by comparison of paired biopsies. To identify the candidate treatments best fitted to metastasis heterogeneity, the specific proteomic signatures of the clones were matched against a druggable genome database. It was possible to unveil candidate drug targets personalized to each metastasis functional clone. Conclusions: MALDI mass spectrometry imaging combined with spatially resolved proteomics has the potential to tackle breast cancer metastases heterogeneity, and identify candidate drug targets specific to functional clones to personalize treatments.