Univerzita Pardubice Fakulta chemicko- technologická

Univerzita Pardubice

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English

Publikace detail

Mass spectrometry imaging in a spatial multi-omics context

Autoři: Idkowiak Jakub

Rok: 2023

Druh publikace: ostatní - přednáška nebo poster

Strana od-do: nestránkováno

Tituly:

Jazyk	Název	Abstrakt	Klíčová slova
eng	Mass spectrometry imaging in a spatial multi-omics context	Mass spectrometry imaging (MSI) has the ability to generate spatial distribution maps of metabolites, lipids, peptides, and drugs in intact tissues, and hence is highly complementary to other spatial omics approaches such as spatial transcriptomics (ST). Here, to link these distinct spatial omics datasets, we present a spatial multi-omics (SMO) integration pipeline and apply it to combine spatial lipidomics data obtained via MSI with ST to study complex human diseases, such as prostate cancer (PCa). To this end, prostate tumours and matched normal biopsies were selected from 8 high-risk PCa patients. ST (Visium, 10X Genomics) and MSI analysis (MALDI-2, Orbitrap Elite MS, Thermo Fisher Scientific) were performed on neighbouring frozen tissue sections along with single-nuclei RNAsequencing (snRNA-seq) (Chromium, 10X Genomics) on matched homogenised tissue sections for spot deconvolution. Based on a non-rigid co-registration algorithm and granularity matching, a shared spatial coordinate system for automated analysis of the integrated MSI and ST datasets was created. Unsupervised clustering analyses were performed to show that both spatial modalities contain complementary molecular information within specific histological areas, as annotated by an expert pathologist. This approach revealed unique correlations between lipids and gene expression profiles that are linked to discrete subpopulations of cells and histopathological disease states and uncovered molecularly different subregions of highgrade tumour regions and areas of cellular transformation not discernible by morphology alone. Our results indicate that the innovative SMO pipeline can provide unprecedented spatial molecular insight into the intricate interplay between different classes of molecules in complex diseases characterised by a high degree of spatial and molecular heterogeneity, and holds promise for applications in molecular pathology, target discovery, and other