Líf - og heilbrigðisvísindaráðstefna Háskóla Íslands 2023

Metabolomics profiling of breast cancer tissue microarrays by mass spectrometry imaging

Valdís Gunnarsdóttir Þormar, Yuchen Xiang, Jón Gunnlaugur Jónasson, Zoltan Takats, Margrét Þorsteinsdottir and Sigriður Klara Böðvarsdóttir

Introduction: As breast cancer (BC) is the most common cancer worldwide and the second leading cause of cancer-related deaths among women, the challenges of timely detection and the diverse nature of BC complicate treatment effectiveness and patient outcomes. There is a critical need for improved disease characterisation techniques in BC to enhance prognosis and tailor treatment options more effectively. In this study, we utilise metabolomics fingerprinting to analyse formalin-fixed and paraffin-embedded (FFPE) tissue microarray (TMA) samples from a precisely defined Icelandic BC cohort. By correlating BC subtypes and immunohistochemical (IHC) analysis with their metabolomics profiles, we aim to develop a new tissue diagnostic tool. This tool has the potential to complement routine clinical IHC analysis, which currently dictates adjuvant treatment decisions.

Methods: Metabolomics profiling, using desorption electrospray ionization mass spectrometry imaging (DESI-MSI), was performed on FFPE TMAs from 222 BC patients and 32 adjacent normal tissues for diagnostic evaluation. The DESI-MSI analysis has already demonstrated the capability to differentiate between tumour and normal breast tissues through their metabolomics signatures. To refine and enhance these findings, the DESI-MSI data is undergoing re-processing using a revised pipeline designed to detect a broader range of metabolites in the study cohort.

Results: This research is ongoing and our goal is to deepen our understanding of the metabolomics phenotypes of these BC patients by integrating mass spectral data with BC subtypes, protein expressions, histological and genetic mutations, and relevant patient demographics. Preliminary results indicate significant DESI-MSI metabolites when analysing BC subgroups among BRCA2 mutation carriers.

 

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