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Truong JXM, Rao SR, Ryan FJ, Lynn DJ, Snel MF, Butler LM, Trim PJ. Spatial MS multiomics on clinical prostate cancer tissues. Anal Bioanal Chem 2024; 416:1745-1757. [PMID: 38324070 DOI: 10.1007/s00216-024-05178-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 02/08/2024]
Abstract
Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.
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Affiliation(s)
- Jacob X M Truong
- The University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia
- Freemasons Centre for Male Health and Wellbeing, University of Adelaide, North Terrace, Adelaide, South Australia, 5000, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), North Terrace, Adelaide, South Australia, 5000, Australia
| | - Sushma R Rao
- The University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia
| | - Feargal J Ryan
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia
- Flinders Health and Medical Research Institute, Flinders University, Bedford Park, South Australia, 5042, Australia
| | - David J Lynn
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia
- Flinders Health and Medical Research Institute, Flinders University, Bedford Park, South Australia, 5042, Australia
| | - Marten F Snel
- The University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia
| | - Lisa M Butler
- The University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia
- Freemasons Centre for Male Health and Wellbeing, University of Adelaide, North Terrace, Adelaide, South Australia, 5000, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), North Terrace, Adelaide, South Australia, 5000, Australia
| | - Paul J Trim
- The University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute (SAHMRI), North Terrace, Adelaide, South Australia, 5000, Australia.
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Hristova J, Svinarov D. Enhancing precision medicine through clinical mass spectrometry platform. BIOTECHNOL BIOTEC EQ 2022. [DOI: 10.1080/13102818.2022.2053342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Affiliation(s)
- Julieta Hristova
- Alexander University Hospital, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
| | - Dobrin Svinarov
- Alexander University Hospital, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
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3
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Alexovič M, Sabo J, Longuespée R. Microproteomic sample preparation. Proteomics 2021; 21:e2000318. [PMID: 33547857 DOI: 10.1002/pmic.202000318] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/23/2021] [Accepted: 01/27/2021] [Indexed: 12/11/2022]
Abstract
Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).
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Affiliation(s)
- Michal Alexovič
- Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P.J. Šafárik in Košice, Košice, Slovakia
| | - Ján Sabo
- Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P.J. Šafárik in Košice, Košice, Slovakia
| | - Rémi Longuespée
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
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Longuespée R, Ly A, Casadonte R, Schwamborn K, Kazdal D, Zgorzelski C, Bollwein C, Kriegsmann K, Weichert W, Kriegsmann J, Schirmacher P, Fresnais M, Oliveira C, Kriegsmann M. Identification of MALDI Imaging Proteolytic Peptides Using LC‐MS/MS‐Based Biomarker Discovery Data: A Proof of Concept. Proteomics Clin Appl 2018; 13:e1800158. [DOI: 10.1002/prca.201800158] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 11/09/2018] [Indexed: 01/10/2023]
Affiliation(s)
- Rémi Longuespée
- Institute of PathologyUniversity of Heidelberg 69120 Heidelberg Germany
| | - Alice Ly
- Bruker Daltonik GmbH 28359 Bremen Germany
| | | | | | - Daniel Kazdal
- Institute of PathologyUniversity of Heidelberg 69120 Heidelberg Germany
| | | | - Christine Bollwein
- Institute of PathologyTechnical University of Munich 81675 Munich Germany
| | - Katharina Kriegsmann
- Department of Internal Medicine VHematology, Oncology and RheumatologyUniversity of Heidelberg 69120 Heidelberg Germany
| | - Wilko Weichert
- Institute of PathologyTechnical University of Munich 81675 Munich Germany
| | | | - Peter Schirmacher
- Institute of PathologyUniversity of Heidelberg 69120 Heidelberg Germany
| | - Margaux Fresnais
- Department of Clinical Pharmacology and PharmacoepidemiologyUniversity of Heidelberg 69120 Heidelberg Germany
- German Cancer Research Center (DKFZ)—German Cancer Consortium (DKTK) 69120 Heidelberg Germany
| | | | - Mark Kriegsmann
- Institute of PathologyUniversity of Heidelberg 69120 Heidelberg Germany
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