ORCID Profile
0000-0002-1510-967X
Current Organisation
KU Leuven
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Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22428964.V1
Abstract: Results of lipid association analyses
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22428967
Abstract: Patient and s le clinical characteristics
Publisher: Wiley
Date: 04-12-2021
Abstract: Matrix‐assisted laser/desorption ionisation‐mass spectrometry imaging (MALDI‐MSI) enables label‐free imaging of biomolecules in biological tissues. However, many molecules remain undetected due to their poor ionisation efficiencies. These poor ionisation efficiencies practically limit spatial resolution. Herein, we address this challenge for aromatic antioxidants by reporting an innovative approach involving sequential matrix‐assisted laser desorption and two‐photon ionisation of desorbed neutrals. It is shown that ion yields increase with reduced s ling areas obtained using sub‐threshold primarily laser fluence. This counterintuitive observation could arise from a reduction in radical/ion neutralisation reactions within the sparse plume and/or favorable molecular desorption under low fluence conditions. The utility of this approach is demonstrated for imaging tocopherols and ubiquinols in mouse brain and prostate cancer tissue. This can pave the way for improved sensitivity in MSI experiments at cellular and sub‐cellular resolutions.
Publisher: MDPI AG
Date: 27-03-2022
Abstract: Due to advances in the detection and management of prostate cancer over the past 20 years, most cases of localised disease are now potentially curable by surgery or radiotherapy, or amenable to active surveillance without treatment. However, this has given rise to a new dilemma for disease management the inability to distinguish indolent from lethal, aggressive forms of prostate cancer, leading to substantial overtreatment of some patients and delayed intervention for others. Driving this uncertainty is the critical deficit of novel targets for systemic therapy and of validated biomarkers that can inform treatment decision-making and to select and monitor therapy. In part, this lack of progress reflects the inherent challenge of undertaking target and biomarker discovery in clinical prostate tumours, which are cellularly heterogeneous and multifocal, necessitating the use of spatial analytical approaches. In this review, the principles of mass spectrometry-based lipid imaging and complementary gene-based spatial omics technologies, their application to prostate cancer and recent advancements in these technologies are considered. We put in perspective studies that describe spatially-resolved lipid maps and metabolic genes that are associated with prostate tumours compared to benign tissue and increased risk of disease progression, with the aim of evaluating the future implementation of spatial lipidomics and complementary transcriptomics for prognostication, target identification and treatment decision-making for prostate cancer.
Publisher: American Association for Cancer Research (AACR)
Date: 06-08-2021
DOI: 10.1158/0008-5472.CAN-20-3863
Abstract: This study identifies malignancy and treatment-associated changes in lipid composition of clinical prostate cancer tissues, suggesting that mediators of these lipidomic changes could be targeted using existing metabolic agents.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22428964
Abstract: Results of lipid association analyses
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22428970.V1
Abstract: Supplementary Figures S1-S6
Publisher: Cold Spring Harbor Laboratory
Date: 28-08-2023
DOI: 10.1101/2023.08.28.555056
Abstract: Recent advances in spatial omics methods are revolutionising biomedical research by enabling detailed molecular analyses of cells and their interactions in their native state. As most technologies capture only a specific type of molecules, there is an unmet need to enable integration of multiple spatial-omics datasets. This, however, presents several challenges as these analyses typically operate on separate tissue sections at disparate spatial resolutions. Here, we established a spatial multi-omics integration pipeline enabling co-registration and granularity matching, and applied it to integrate spatial transcriptomics, mass spectrometry-based lipidomics, single nucleus RNA-seq and histomorphological information from human prostate cancer patient s les. This approach revealed unique correlations between lipids and gene expression profiles that are linked to distinct cell populations and histopathological disease states and uncovered molecularly different subregions not discernible by morphology alone. By its ability to correlate datasets that span across the biomolecular and spatial scale, the application of this novel spatial multi-omics integration pipeline provides unprecedented insight into the intricate interplay between different classes of molecules in a tissue context. In addition, it has unique hypothesis-generating potential, and holds promise for applications in molecular pathology, biomarker and target discovery and other tissue-based research fields.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22428970
Abstract: Supplementary Figures S1-S6
Publisher: Springer Science and Business Media LLC
Date: 02-02-2023
Publisher: Springer Science and Business Media LLC
Date: 09-02-2021
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.C.6513199.V1
Abstract: Abstract Dysregulated lipid metabolism is a prominent feature of prostate cancer that is driven by androgen receptor (AR) signaling. Here we used quantitative mass spectrometry to define the “lipidome” in prostate tumors with matched benign tissues ( i n /i = 21), independent unmatched tissues ( i n /i = 47), and primary prostate explants cultured with the clinical AR antagonist enzalutamide ( i n /i = 43). Significant differences in lipid composition were detected and spatially visualized in tumors compared with matched benign s les. Notably, tumors featured higher proportions of monounsaturated lipids overall and elongated fatty acid chains in phosphatidylinositol and phosphatidylserine lipids. Significant associations between lipid profile and malignancy were validated in unmatched s les, and phospholipid composition was characteristically altered in patient tissues that responded to AR inhibition. Importantly, targeting tumor-related lipid features via inhibition of acetyl-CoA carboxylase 1 significantly reduced cellular proliferation and induced apoptosis in tissue explants. This characterization of the prostate cancer lipidome in clinical tissues reveals enhanced fatty acid synthesis, elongation, and desaturation as tumor-defining features, with potential for therapeutic targeting. Significance: This study identifies malignancy and treatment-associated changes in lipid composition of clinical prostate cancer tissues, suggesting that mediators of these lipidomic changes could be targeted using existing metabolic agents. /
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22428967.V1
Abstract: Patient and s le clinical characteristics
No related grants have been discovered for Xander Spotbeen.