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Sun M, Otsuka Y, Okada M, Shimma S, Toyoda M. Probe oscillation control in tapping-mode scanning probe electrospray ionization for stabilization of mass spectrometry imaging. Analyst 2024; 149:4011-4019. [PMID: 38953117 DOI: 10.1039/d4an00712c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
Mass spectrometry imaging (MSI) is used for visualizing the distribution of components in solid samples, such as biological tissues, and requires a technique to ionize the components from local areas of the sample. Tapping-mode scanning probe electrospray ionization (t-SPESI) uses an oscillating capillary probe to extract components from a local area of a sample with a small volume of solvent and to perform electrospray ionization of those components at high speed. MSI can be conducted by scanning the sample surface with a capillary probe. To ensure stable extraction and ionization for MSI, the probe oscillation during measurements must be understood. In this study, we examined the changes in oscillation amplitude and phase due to the interaction between the oscillating probe and the brain tissue section when the probe tip was dynamically brought close to the sample surface. The changes in the probe oscillation depended on the oscillation frequency and polarity of the bias voltage applied to the solvent because an electrostatic force shifted the frequency of the probe oscillation. These findings suggest that controlling the probe oscillation frequency is important for stabilizing MSI by t-SPESI.
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Affiliation(s)
- Mengze Sun
- Department of Physics, Graduate School of Science, Osaka University, Japan.
| | - Yoichi Otsuka
- Department of Physics, Graduate School of Science, Osaka University, Japan.
- Forefront Research Center, Graduate School of Science, Osaka University, Japan
| | - Maki Okada
- Department of Physics, Graduate School of Science, Osaka University, Japan.
| | - Shuichi Shimma
- Department of Bioengineering, Graduate School of Engineering, Osaka University, Japan
| | - Michisato Toyoda
- Department of Physics, Graduate School of Science, Osaka University, Japan.
- Forefront Research Center, Graduate School of Science, Osaka University, Japan
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2
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Dudka I, Lundquist K, Wikström P, Bergh A, Gröbner G. Metabolomic profiles of intact tissues reflect clinically relevant prostate cancer subtypes. J Transl Med 2023; 21:860. [PMID: 38012666 PMCID: PMC10683247 DOI: 10.1186/s12967-023-04747-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 11/21/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis. METHODS A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity). RESULTS Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B. CONCLUSIONS The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.
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Affiliation(s)
- Ilona Dudka
- Department of Chemistry, Umeå University, Umeå, Sweden
| | | | - Pernilla Wikström
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden.
| | - Anders Bergh
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
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3
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Tomalty D, Giovannetti O, Velikonja L, Munday J, Kaufmann M, Iaboni N, Jamzad A, Rubino R, Fichtinger G, Mousavi P, Nicol CJB, Rudan JF, Adams MA. Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging. J Anat 2023; 243:758-769. [PMID: 37264225 PMCID: PMC10557387 DOI: 10.1111/joa.13909] [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: 03/15/2023] [Revised: 05/11/2023] [Accepted: 05/20/2023] [Indexed: 06/03/2023] Open
Abstract
Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a molecular imaging method that can be used to elucidate the small-molecule composition of tissues and map their spatial information using two-dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI-MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for which are known to carry various nerve fiber types were harvested from a fresh cadaveric donor: mixed, motor and sensory (sciatic and femoral); cutaneous, sensory (sural); and autonomic (vagus). Tissue samples were harvested to include the nerve bundles in addition to surrounding connective tissue. Samples were flash-frozen, embedded in optimal cutting temperature compound in cross-section, and sectioned at 14 μm. Following DESI-MSI analysis, identical tissue sections were stained with hematoxylin and eosin. In this proof-of-concept study, a combination of multivariate and univariate statistical methods was used to evaluate molecular differences between the nerve and adjacent tissue and between nerve subtypes. The acquired mass spectral profiles of the peripheral nerve samples presented trends in ion abundances that seemed to be characteristic of nerve tissue and spatially corresponded to the associated histology of the tissue sections. Principal component analysis (PCA) supported the separation of the samples into distinct nerve and adjacent tissue classes. This classification was further supported by the K-means clustering analysis, which showed separation of the nerve and background ions. Differences in ion expression were confirmed using ANOVA which identified statistically significant differences in ion expression between the nerve subtypes. The PCA plot suggested some separation of the nerve subtypes into four classes which corresponded with the nerve types. This was supported by the K-means clustering. Some overlap in classes was noted in these two clustering analyses. This study provides emerging evidence that DESI-MSI is an effective tool for metabolomic profiling of peripheral nerves. Our results suggest that peripheral nerves have molecular profiles that are distinct from the surrounding connective tissues and that DESI-MSI may be able to discriminate between nerve subtypes. DESI-MSI of peripheral nerves may be a valuable technique that could be used to improve our understanding of peripheral nerve anatomy and physiology. The ability to utilize ambient mass spectrometry techniques in real time could also provide an unprecedented advantage for surgical decision making, including in nerve-sparing procedures in the future.
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Affiliation(s)
- Diane Tomalty
- Department of Biomedical and Molecular SciencesQueen's UniversityKingstonOntarioCanada
| | - Olivia Giovannetti
- Department of Biomedical and Molecular SciencesQueen's UniversityKingstonOntarioCanada
| | - Leah Velikonja
- Department of Biomedical and Molecular SciencesQueen's UniversityKingstonOntarioCanada
| | - Jasica Munday
- Department of Biomedical and Molecular SciencesQueen's UniversityKingstonOntarioCanada
| | - Martin Kaufmann
- Department of SurgeryQueen's UniversityKingstonOntarioCanada
- Gastrointestinal Diseases Research UnitKingston Health Sciences CenterKingstonOntarioCanada
| | - Natasha Iaboni
- Department of Pathology and Molecular MedicineQueen's UniversityKingstonOntarioCanada
| | - Amoon Jamzad
- School of ComputingQueen's UniversityKingstonOntarioCanada
| | - Rachel Rubino
- Division of Cancer Biology and GeneticsQueen's Cancer Research InstituteKingstonOntarioCanada
| | | | - Parvin Mousavi
- School of ComputingQueen's UniversityKingstonOntarioCanada
| | - Christopher J. B. Nicol
- Department of Pathology and Molecular MedicineQueen's UniversityKingstonOntarioCanada
- Division of Cancer Biology and GeneticsQueen's Cancer Research InstituteKingstonOntarioCanada
| | - John F. Rudan
- Department of SurgeryQueen's UniversityKingstonOntarioCanada
| | - Michael A. Adams
- Department of Biomedical and Molecular SciencesQueen's UniversityKingstonOntarioCanada
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4
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Planque M, Igelmann S, Ferreira Campos AM, Fendt SM. Spatial metabolomics principles and application to cancer research. Curr Opin Chem Biol 2023; 76:102362. [PMID: 37413787 DOI: 10.1016/j.cbpa.2023.102362] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 05/07/2023] [Accepted: 06/06/2023] [Indexed: 07/08/2023]
Abstract
Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.
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Affiliation(s)
- Mélanie Planque
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Sebastian Igelmann
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Ana Margarida Ferreira Campos
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium.
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5
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Chen H, Li X, Li F, Li Y, Chen F, Zhang L, Ye F, Gong M, Bu H. Prediction of coexisting invasive carcinoma on ductal carcinoma in situ (DCIS) lesions by mass spectrometry imaging. J Pathol 2023; 261:125-138. [PMID: 37555360 DOI: 10.1002/path.6154] [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: 10/15/2022] [Revised: 05/16/2023] [Accepted: 06/07/2023] [Indexed: 08/10/2023]
Abstract
Due to limited biopsy samples, ~20% of DCIS lesions confirmed by biopsy are upgraded to invasive ductal carcinoma (IDC) upon surgical resection. Avoiding underestimation of IDC when diagnosing DCIS has become an urgent challenge in an era discouraging overtreatment of DCIS. In this study, the metabolic profiles of 284 fresh frozen breast samples, including tumor tissues and adjacent benign tissues (ABTs) and distant surrounding tissues (DSTs), were analyzed using desorption electrospray ionization-mass spectrometry (DESI-MS) imaging. Metabolomics analysis using DESI-MS data revealed significant differences in metabolite levels, including small-molecule antioxidants, long-chain polyunsaturated fatty acids (PUFAs) and phospholipids between pure DCIS and IDC. However, the metabolic profile in DCIS with invasive carcinoma components clearly shifts to be closer to adjacent IDC components. For instance, DCIS with invasive carcinoma components showed lower levels of antioxidants and higher levels of free fatty acids compared to pure DCIS. Furthermore, the accumulation of long-chain PUFAs and the phosphatidylinositols (PIs) containing PUFA residues may also be associated with the progression of DCIS. These distinctive metabolic characteristics may offer valuable indications for investigating the malignant potential of DCIS. By combining DESI-MS data with machine learning (ML) methods, various breast lesions were discriminated. Importantly, the pure DCIS components were successfully distinguished from the DCIS components in samples with invasion in postoperative specimens by a Lasso prediction model, achieving an AUC value of 0.851. In addition, pixel-level prediction based on DESI-MS data enabled automatic visualization of tissue properties across whole tissue sections. Summarily, DESI-MS imaging on histopathological sections can provide abundant metabolic information about breast lesions. By analyzing the spatial metabolic characteristics in tissue sections, this technology has the potential to facilitate accurate diagnosis and individualized treatment of DCIS by inferring the presence of IDC components surrounding DCIS lesions. © 2023 The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Hong Chen
- Department of Pathology and Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, PR China
- Key Laboratory of Transplant Engineering and Immunology of the National Health Commission, West China Hospital, Sichuan University, Chengdu, PR China
| | - Xin Li
- Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, PR China
| | - Fengling Li
- Department of Pathology and Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, PR China
- Department of Pathology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Yijie Li
- Department of Pathology and Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, PR China
- Key Laboratory of Transplant Engineering and Immunology of the National Health Commission, West China Hospital, Sichuan University, Chengdu, PR China
| | - Fei Chen
- Department of Pathology and Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, PR China
| | - Lu Zhang
- Image Processing and Parallel Computing Laboratory, School of Computer Science, Southwest Petroleum University, Chengdu, PR China
| | - Feng Ye
- Department of Pathology and Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, PR China
- Key Laboratory of Transplant Engineering and Immunology of the National Health Commission, West China Hospital, Sichuan University, Chengdu, PR China
| | - Meng Gong
- Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, PR China
| | - Hong Bu
- Department of Pathology and Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, PR China
- Department of Pathology, West China Hospital, Sichuan University, Chengdu, PR China
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Kumar BS. Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview. Mass Spectrom (Tokyo) 2023; 12:A0129. [PMID: 37789912 PMCID: PMC10542858 DOI: 10.5702/massspectrometry.a0129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 08/25/2023] [Indexed: 10/05/2023] Open
Abstract
Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.
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Affiliation(s)
- Bharath S. Kumar
- Correspondence to: Bharath S. Kumar, 21, B2, 27th Street, Nanganallur, Chennai, India, e-mail:
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7
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Kumar BS. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:3768-3784. [PMID: 37503728 DOI: 10.1039/d3ay00867c] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Tissue analysis, which is essential to histology and is considered the benchmark for the diagnosis and prognosis of many illnesses, including cancer, is significant. During surgery, the surgical margin of the tumor is assessed using the labor-intensive, challenging, and commonly subjective technique known as frozen section histopathology. In the biopsy section, large numbers of molecules can now be visualized at once (ion images) following recent developments in [MSI] mass spectrometry imaging under atmospheric conditions. This is vastly superior to and different from the single optical tissue image processing used in traditional histopathology. This review article will focus on the advancement of desorption electrospray ionization mass spectrometry imaging [DESI-MSI] technique, which is label-free and requires little to no sample preparation. Since the proportion of molecular species in normal and abnormal tissues is different, DESI-MSI can capture ion images of the distributions of lipids and metabolites on biopsy sections, which can provide rich diagnostic information. This is not a systematic review but a summary of well-known, cutting-edge and recent DESI-MSI applications in cancer research between 2018 and 2023.
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Affiliation(s)
- Bharath Sampath Kumar
- Independent Researcher, 21, B2, 27th Street, Nanganallur, Chennai 61, TamilNadu, India.
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8
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Kaufmann M, Iaboni N, Jamzad A, Hurlbut D, Ren KYM, Rudan JF, Mousavi P, Fichtinger G, Varma S, Caycedo-Marulanda A, Nicol CJB. Metabolically Active Zones Involving Fatty Acid Elongation Delineated by DESI-MSI Correlate with Pathological and Prognostic Features of Colorectal Cancer. Metabolites 2023; 13:metabo13040508. [PMID: 37110166 PMCID: PMC10141897 DOI: 10.3390/metabo13040508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 03/18/2023] [Accepted: 03/20/2023] [Indexed: 04/03/2023] Open
Abstract
Colorectal cancer (CRC) is the second leading cause of cancer deaths. Despite recent advances, five-year survival rates remain largely unchanged. Desorption electrospray ionization mass spectrometry imaging (DESI) is an emerging nondestructive metabolomics-based method that retains the spatial orientation of small-molecule profiles on tissue sections, which may be validated by ‘gold standard’ histopathology. In this study, CRC samples were analyzed by DESI from 10 patients undergoing surgery at Kingston Health Sciences Center. The spatial correlation of the mass spectral profiles was compared with histopathological annotations and prognostic biomarkers. Fresh frozen sections of representative colorectal cross sections and simulated endoscopic biopsy samples containing tumour and non-neoplastic mucosa for each patient were generated and analyzed by DESI in a blinded fashion. Sections were then hematoxylin and eosin (H and E) stained, annotated by two independent pathologists, and analyzed. Using PCA/LDA-based models, DESI profiles of the cross sections and biopsies achieved 97% and 75% accuracies in identifying the presence of adenocarcinoma, using leave-one-patient-out cross validation. Among the m/z ratios exhibiting the greatest differential abundance in adenocarcinoma were a series of eight long-chain or very-long-chain fatty acids, consistent with molecular and targeted metabolomics indicators of de novo lipogenesis in CRC tissue. Sample stratification based on the presence of lympovascular invasion (LVI), a poor CRC prognostic indicator, revealed the abundance of oxidized phospholipids, suggestive of pro-apoptotic mechanisms, was increased in LVI-negative compared to LVI-positive patients. This study provides evidence of the potential clinical utility of spatially-resolved DESI profiles to enhance the information available to clinicians for CRC diagnosis and prognosis.
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Affiliation(s)
- Martin Kaufmann
- Department of Surgery, Kingston Health Sciences Centre, Kingston, ON K7L 2V7, Canada
- Gastrointestinal Diseases Research Unit, Kingston Health Sciences Center, Kingston, ON K7L 2V7, Canada
| | - Natasha Iaboni
- Department of Pathology and Molecular Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, ON K7L 3N6, Canada
| | - Amoon Jamzad
- School of Computing, Queen’s University, Kingston, ON K7L 2N8, Canada
| | - David Hurlbut
- Department of Pathology and Molecular Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, ON K7L 3N6, Canada
| | - Kevin Yi Mi Ren
- Department of Pathology and Molecular Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, ON K7L 3N6, Canada
| | - John F. Rudan
- Department of Surgery, Kingston Health Sciences Centre, Kingston, ON K7L 2V7, Canada
| | - Parvin Mousavi
- School of Computing, Queen’s University, Kingston, ON K7L 2N8, Canada
| | - Gabor Fichtinger
- School of Computing, Queen’s University, Kingston, ON K7L 2N8, Canada
| | - Sonal Varma
- Department of Pathology and Molecular Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, ON K7L 3N6, Canada
| | - Antonio Caycedo-Marulanda
- Department of Surgery, Kingston Health Sciences Centre, Kingston, ON K7L 2V7, Canada
- Orlando Health Colon and Rectal Institute, Orlando, FL 32806, USA
| | - Christopher J. B. Nicol
- Department of Pathology and Molecular Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, ON K7L 3N6, Canada
- Queen’s Cancer Research Institute, Division of Cancer Biology and Genetics, Kingston, ON K7L 3N6, Canada
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Soudah T, Zoabi A, Margulis K. Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies. MASS SPECTROMETRY REVIEWS 2023; 42:751-778. [PMID: 34642958 DOI: 10.1002/mas.21736] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Revised: 09/16/2021] [Accepted: 09/21/2021] [Indexed: 06/13/2023]
Abstract
Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is one of the least specimen destructive ambient ionization mass spectrometry tissue imaging methods. It enables rapid simultaneous mapping, measurement, and identification of hundreds of molecules from an unmodified tissue sample. Over the years, since its first introduction as an imaging technique in 2005, DESI-MSI has been extensively developed as a tool for separating tissue regions of various histopathologic classes for diagnostic applications. Recently, DESI-MSI has also emerged as a versatile technique that enables drug discovery and can guide the efficient development of drug delivery systems. For example, it has been increasingly employed for uncovering unique patterns of in vivo drug distribution, the discovery of potentially treatable biochemical pathways, revealing novel druggable targets, predicting therapeutic sensitivity of diseased tissues, and identifying early tissue response to pharmacological treatment. These and other recent advances in implementing DESI-MSI as the tool for the development of novel therapies are highlighted in this review.
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Affiliation(s)
- Terese Soudah
- The Faculty of Medicine, The School of Pharmacy, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amani Zoabi
- The Faculty of Medicine, The School of Pharmacy, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Katherine Margulis
- The Faculty of Medicine, The School of Pharmacy, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel
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Zeković M, Bumbaširević U, Živković M, Pejčić T. Alteration of Lipid Metabolism in Prostate Cancer: Multifaceted Oncologic Implications. Int J Mol Sci 2023; 24:ijms24021391. [PMID: 36674910 PMCID: PMC9863986 DOI: 10.3390/ijms24021391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 01/12/2023] Open
Abstract
Cancer is increasingly recognized as an extraordinarily heterogeneous disease featuring an intricate mutational landscape and vast intra- and intertumor variability on both genetic and phenotypic levels. Prostate cancer (PCa) is the second most prevalent malignant disease among men worldwide. A single metabolic program cannot epitomize the perplexing reprogramming of tumor metabolism needed to sustain the stemness of neoplastic cells and their prominent energy-consuming functional properties, such as intensive proliferation, uncontrolled growth, migration, and invasion. In cancerous tissue, lipids provide the structural integrity of biological membranes, supply energy, influence the regulation of redox homeostasis, contribute to plasticity, angiogenesis and microenvironment reshaping, mediate the modulation of the inflammatory response, and operate as signaling messengers, i.e., lipid mediators affecting myriad processes relevant for the development of the neoplasia. Comprehensive elucidation of the lipid metabolism alterations in PCa, the underlying regulatory mechanisms, and their implications in tumorigenesis and the progression of the disease are gaining growing research interest in the contemporary urologic oncology. Delineation of the unique metabolic signature of the PCa featuring major aberrant pathways including de novo lipogenesis, lipid uptake, storage and compositional reprogramming may provide novel, exciting, and promising avenues for improving diagnosis, risk stratification, and clinical management of such a complex and heterogeneous pathology.
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Affiliation(s)
- Milica Zeković
- Centre of Research Excellence in Nutrition and Metabolism, Institute for Medical Research, National Institute of Republic of Serbia, University of Belgrade, 11000 Belgrade, Serbia
| | - Uros Bumbaširević
- Clinic of Urology, University Clinical Center of Serbia, 11000 Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia
| | - Marko Živković
- Clinic of Urology, University Clinical Center of Serbia, 11000 Belgrade, Serbia
| | - Tomislav Pejčić
- Clinic of Urology, University Clinical Center of Serbia, 11000 Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia
- Correspondence:
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11
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Gao SQ, Zhao JH, Guan Y, Tang YS, Li Y, Liu LY. Mass Spectrometry Imaging technology in metabolomics: a systematic review. Biomed Chromatogr 2022:e5494. [PMID: 36044038 DOI: 10.1002/bmc.5494] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/24/2022] [Accepted: 08/28/2022] [Indexed: 11/11/2022]
Abstract
Mass spectrometry imaging (MSI) is a powerful label-free analysis technique that can provide simultaneous spatial distribution of multiple compounds in a single experiment. By combining the sensitive and rapid screening of high-throughput mass spectrometry with spatial chemical information, metabolite analysis and morphological characteristics are presented in a single image. MSI can be used for qualitative and quantitative analysis of metabolic profiles and it can provide visual analysis of spatial distribution information of complex biological and microbial systems. Matrix assisted laser desorption ionization, laser ablation electrospray ionization and desorption electrospray ionization are commonly used in MSI. Here, we summarize and compare these three technologies, as well as the applications and prospects of MSI in metabolomics.
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Affiliation(s)
- Si-Qi Gao
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Jin-Hui Zhao
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Yue Guan
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Ying-Shu Tang
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Ying Li
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Li-Yan Liu
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
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12
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Zhong AB, Muti IH, Eyles SJ, Vachet RW, Sikora KN, Bobst CE, Calligaris D, Stopka SA, Agar JN, Wu CL, Mino-Kenudson MA, Agar NYR, Christiani DC, Kaltashov IA, Cheng LL. Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging. Front Mol Biosci 2022; 9:785232. [PMID: 35463966 PMCID: PMC9024335 DOI: 10.3389/fmolb.2022.785232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 03/02/2022] [Indexed: 11/22/2022] Open
Abstract
The status of metabolomics as a scientific branch has evolved from proof-of-concept to applications in science, particularly in medical research. To comprehensively evaluate disease metabolomics, multiplatform approaches of NMR combining with mass spectrometry (MS) have been investigated and reported. This mixed-methods approach allows for the exploitation of each individual technique's unique advantages to maximize results. In this article, we present our findings from combined NMR and MS imaging (MSI) analysis of human lung and prostate cancers. We further provide critical discussions of the current status of NMR and MS combined human prostate and lung cancer metabolomics studies to emphasize the enhanced metabolomics ability of the multiplatform approach.
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Affiliation(s)
- Anya B. Zhong
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Isabella H. Muti
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Stephen J. Eyles
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - Richard W. Vachet
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - Kristen N. Sikora
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - Cedric E. Bobst
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - David Calligaris
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Sylwia A. Stopka
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Jeffery N. Agar
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, United States
| | - Chin-Lee Wu
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | | | - Nathalie Y. R. Agar
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Dana-Farber Cancer Institute, Boston, MA, United States
| | - David C. Christiani
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Igor A. Kaltashov
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Leo L. Cheng
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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13
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Unravelling Prostate Cancer Heterogeneity Using Spatial Approaches to Lipidomics and Transcriptomics. Cancers (Basel) 2022; 14:cancers14071702. [PMID: 35406474 PMCID: PMC8997139 DOI: 10.3390/cancers14071702] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 03/11/2022] [Accepted: 03/21/2022] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Prostate cancer is a heterogenous disease in terms of disease aggressiveness and therapy response, leading to dilemmas in treatment decisions. This heterogeneity reflects the multifocal nature of prostate cancer and its diversity in cellular and molecular composition, necessitating spatial molecular approaches. Here in view of the emerging importance of rewired lipid metabolism as a source of biomarkers and therapeutic targets for prostate cancer, we highlight recent advancements in technologies that enable the spatial mapping of lipids and related metabolic pathways associated with prostate cancer development and progression. We also evaluate their potential for future implementation in treatment decision-making in the clinical management of prostate cancer. 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.
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14
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Fidelito G, Watt MJ, Taylor RA. Personalized Medicine for Prostate Cancer: Is Targeting Metabolism a Reality? Front Oncol 2022; 11:778761. [PMID: 35127483 PMCID: PMC8813754 DOI: 10.3389/fonc.2021.778761] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/21/2021] [Indexed: 02/06/2023] Open
Abstract
Prostate cancer invokes major shifts in gene transcription and metabolic signaling to mediate alterations in nutrient acquisition and metabolic substrate selection when compared to normal tissues. Exploiting such metabolic reprogramming is proposed to enable the development of targeted therapies for prostate cancer, yet there are several challenges to overcome before this becomes a reality. Herein, we outline the role of several nutrients known to contribute to prostate tumorigenesis, including fatty acids, glucose, lactate and glutamine, and discuss the major factors contributing to variability in prostate cancer metabolism, including cellular heterogeneity, genetic drivers and mutations, as well as complexity in the tumor microenvironment. The review draws from original studies employing immortalized prostate cancer cells, as well as more complex experimental models, including animals and humans, that more accurately reflect the complexity of the in vivo tumor microenvironment. In synthesizing this information, we consider the feasibility and potential limitations of implementing metabolic therapies for prostate cancer management.
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Affiliation(s)
- Gio Fidelito
- Department of Anatomy & Physiology, The University of Melbourne, Melbourne, VIC, Australia
| | - Matthew J. Watt
- Department of Anatomy & Physiology, The University of Melbourne, Melbourne, VIC, Australia
- *Correspondence: Renea A. Taylor, ; Matthew J. Watt,
| | - Renea A. Taylor
- Department of Physiology, Biomedicine Discovery Institute, Cancer Program, Monash University, Melbourne, VIC, Australia
- Prostate Cancer Research Program, Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
- *Correspondence: Renea A. Taylor, ; Matthew J. Watt,
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15
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Haroon M, Tahir M, Nawaz H, Majeed MI, Al-Saadi AA. Surface-enhanced Raman scattering (SERS) spectroscopy for prostate cancer diagnosis: A review. Photodiagnosis Photodyn Ther 2021; 37:102690. [PMID: 34921990 DOI: 10.1016/j.pdpdt.2021.102690] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/28/2021] [Accepted: 12/13/2021] [Indexed: 12/13/2022]
Abstract
The present review focuses on the diagnosis of prostate cancer using surface enhanced Raman scattering (SERS) spectroscopy. On the basis of literature search, SERS-based analysis for prostate cancer detection of different sample types is reported in the present study. Prostate cancer is responsible for nearly one-tenth of all cell cancer deaths among men. Significant efforts have been dedicated to establish precise and sensitive monitoring techniques to detect prostate cancer biomarkers in different types of body samples. Among the various spectro-analytical techniques investigated to achieve this objective, SERS spectroscopy has been proven as a promising approach that provides noticeable enhancements of the Raman sensitivity when the target biomolecules interact with a nanostructured surface. The purpose of this review is to give a brief overview of the SERS-basedapproach and other spectro-analytical strategies being used for the detection and quantification of prostate cancer biomarkers. The revolutionary development of SERS methods for the diagnosis of prostate cancer has been discussed in more details based on the reported literature. It has been noticed that the SERS-based immunoassay presents reliable results for the prostate cancer quantification. The EC-SERS, which integrates electrochemistry with the SERS model, could also offer a potential ultrasensitive strategy, although its application in prostate cancer analysis has been still limited.
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Affiliation(s)
- Muhammad Haroon
- Department of Chemistry, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
| | - Muhammad Tahir
- Department of Chemistry, University of Agriculture Faisalabad, Pakistan
| | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Pakistan
| | | | - Abdulaziz A Al-Saadi
- Department of Chemistry, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia; Interdisciplinary Research Center (IRC) in Refinery and Advanced Chemicals, Dhahran 31261, Saudi Arabia.
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16
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Hilton KLF, Manwani C, Boles JE, White LJ, Ozturk S, Garrett MD, Hiscock JR. The phospholipid membrane compositions of bacterial cells, cancer cell lines and biological samples from cancer patients. Chem Sci 2021; 12:13273-13282. [PMID: 34777745 PMCID: PMC8529332 DOI: 10.1039/d1sc03597e] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/21/2021] [Indexed: 12/24/2022] Open
Abstract
While cancer now impacts the health and well-being of more of the human population than ever before, the exponential rise in antimicrobial resistant (AMR) bacterial infections means AMR is predicted to become one of the greatest future threats to human health. It is therefore vital that novel therapeutic strategies are developed that can be used in the treatment of both cancer and AMR infections. Whether the target of a therapeutic agent be inside the cell or in the cell membrane, it must either interact with or cross this phospholipid barrier to elicit the desired cellular effect. Here we summarise findings from published research into the phospholipid membrane composition of bacterial and cancer cell lines and biological samples from cancer patients. These data not only highlight key differences in the membrane composition of these biological samples, but also the methods used to elucidate and report the results of this analogous research between the microbial and cancer fields.
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Affiliation(s)
- Kira L F Hilton
- School of Physical Sciences, University of Kent Canterbury Kent CT2 7NH UK
| | - Chandni Manwani
- School of Physical Sciences, University of Kent Canterbury Kent CT2 7NH UK
- School of Biosciences, University of Kent Canterbury Kent CT2 7NJ UK
| | - Jessica E Boles
- School of Physical Sciences, University of Kent Canterbury Kent CT2 7NH UK
| | - Lisa J White
- School of Physical Sciences, University of Kent Canterbury Kent CT2 7NH UK
| | - Sena Ozturk
- School of Physical Sciences, University of Kent Canterbury Kent CT2 7NH UK
| | | | - Jennifer R Hiscock
- School of Physical Sciences, University of Kent Canterbury Kent CT2 7NH UK
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17
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Singh R, Mills IG. The Interplay Between Prostate Cancer Genomics, Metabolism, and the Epigenome: Perspectives and Future Prospects. Front Oncol 2021; 11:704353. [PMID: 34660272 PMCID: PMC8511631 DOI: 10.3389/fonc.2021.704353] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 08/31/2021] [Indexed: 12/12/2022] Open
Abstract
Prostate cancer is a high-incidence cancer, often detected late in life. The prostate gland is an accessory gland that secretes citrate; an impaired citrate secretion reflects imbalances in the activity of enzymes in the TCA Cycle in mitochondria. Profiling studies on prostate tumours have identified significant metabolite, proteomic, and transcriptional modulations with an increased mitochondrial metabolic activity associated with localised prostate cancer. Here, we focus on the androgen receptor, c-Myc, phosphatase and tensin Homolog deleted on chromosome 10 (PTEN), and p53 as amongst the best-characterised genomic drivers of prostate cancer implicated in metabolic dysregulation and prostate cancer progression. We outline their impact on metabolic function before discussing how this may affect metabolite pools and in turn chromatin structure and the epigenome. We reflect on some recent literature indicating that mitochondrial mutations and OGlcNAcylation may also contribute to this crosstalk. Finally, we discuss the technological challenges of assessing crosstalk given the significant differences in the spatial sensitivity and throughput of genomic and metabolomic profiling approaches.
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Affiliation(s)
- Reema Singh
- Nuffield Department of Surgical Sciences John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Ian G Mills
- Nuffield Department of Surgical Sciences John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.,Patrick G Johnston Centre for Cancer Research, Queen's University of Belfast, Belfast, United Kingdom.,Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway.,Department of Clinical Science, University of Bergen, Bergen, Norway
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18
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Connolly L, Jamzad A, Kaufmann M, Farquharson CE, Ren K, Rudan JF, Fichtinger G, Mousavi P. Combined Mass Spectrometry and Histopathology Imaging for Perioperative Tissue Assessment in Cancer Surgery. J Imaging 2021; 7:203. [PMID: 34677289 PMCID: PMC8539093 DOI: 10.3390/jimaging7100203] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 09/28/2021] [Accepted: 09/30/2021] [Indexed: 12/16/2022] Open
Abstract
Mass spectrometry is an effective imaging tool for evaluating biological tissue to detect cancer. With the assistance of deep learning, this technology can be used as a perioperative tissue assessment tool that will facilitate informed surgical decisions. To achieve such a system requires the development of a database of mass spectrometry signals and their corresponding pathology labels. Assigning correct labels, in turn, necessitates precise spatial registration of histopathology and mass spectrometry data. This is a challenging task due to the domain differences and noisy nature of images. In this study, we create a registration framework for mass spectrometry and pathology images as a contribution to the development of perioperative tissue assessment. In doing so, we explore two opportunities in deep learning for medical image registration, namely, unsupervised, multi-modal deformable image registration and evaluation of the registration. We test this system on prostate needle biopsy cores that were imaged with desorption electrospray ionization mass spectrometry (DESI) and show that we can successfully register DESI and histology images to achieve accurate alignment and, consequently, labelling for future training. This automation is expected to improve the efficiency and development of a deep learning architecture that will benefit the use of mass spectrometry imaging for cancer diagnosis.
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Affiliation(s)
- Laura Connolly
- School of Computing, Queen’s University, Kingston, ON K7L 3N6, Canada; (A.J.); (C.E.F.); (G.F.); (P.M.)
| | - Amoon Jamzad
- School of Computing, Queen’s University, Kingston, ON K7L 3N6, Canada; (A.J.); (C.E.F.); (G.F.); (P.M.)
| | - Martin Kaufmann
- Department of Surgery, Queen’s University, Kingston, ON K7L 3N6, Canada; (M.K.); (J.F.R.)
| | - Catriona E. Farquharson
- School of Computing, Queen’s University, Kingston, ON K7L 3N6, Canada; (A.J.); (C.E.F.); (G.F.); (P.M.)
| | - Kevin Ren
- Department of Pathology and Molecular Medicine, Queen’s University, Kingston, ON K7L 3N6, Canada;
| | - John F. Rudan
- Department of Surgery, Queen’s University, Kingston, ON K7L 3N6, Canada; (M.K.); (J.F.R.)
| | - Gabor Fichtinger
- School of Computing, Queen’s University, Kingston, ON K7L 3N6, Canada; (A.J.); (C.E.F.); (G.F.); (P.M.)
| | - Parvin Mousavi
- School of Computing, Queen’s University, Kingston, ON K7L 3N6, Canada; (A.J.); (C.E.F.); (G.F.); (P.M.)
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19
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Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes. Cancers (Basel) 2021; 13:cancers13194829. [PMID: 34638309 PMCID: PMC8507874 DOI: 10.3390/cancers13194829] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 12/12/2022] Open
Abstract
Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.
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20
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Butler LM, Mah CY, Machiels J, Vincent AD, Irani S, Mutuku SM, Spotbeen X, Bagadi M, Waltregny D, Moldovan M, Dehairs J, Vanderhoydonc F, Bloch K, Das R, Stahl J, Kench JG, Gevaert T, Derua R, Waelkens E, Nassar ZD, Selth LA, Trim PJ, Snel MF, Lynn DJ, Tilley WD, Horvath LG, Centenera MM, Swinnen JV. Lipidomic profiling of clinical prostate cancer reveals targetable alterations in membrane lipid composition. Cancer Res 2021; 81:4981-4993. [PMID: 34362796 DOI: 10.1158/0008-5472.can-20-3863] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 06/07/2021] [Accepted: 08/03/2021] [Indexed: 12/24/2022]
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 (n=21), independent unmatched tissues (n=47), and primary prostate explants cultured with the clinical AR antagonist enzalutamide (n=43). Significant differences in lipid composition were detected and spatially visualized in tumors compared to matched benign samples. 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 samples, 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 first 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.
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Affiliation(s)
- Lisa M Butler
- South Australian Health and Medical Research Institute, University of Adelaide, School of Medicine and Freemasons Foundation Centre for Men's Health
| | - Chui Yan Mah
- South Australian Health and Medical Research Institute, University of Adelaide, Freemasons Foundation Centre for Men's Health and Adelaide Medical School
| | | | | | - Swati Irani
- South Australian Health and Medical Research Institute, University of Adelaide, School of Medicine and Freemasons Foundation Centre for Men's Health
| | - Shadrack M Mutuku
- South Australian Health and Medical Research Institute, University of Adelaide, School of Medicine and Freemasons Foundation Centre for Men's Health
| | | | | | | | - Max Moldovan
- Registry of Older Australians, South Australian Health and Medical Research Institute
| | - Jonas Dehairs
- Department of Oncology, KU Leuven - University of Leuven
| | | | - Katarzyna Bloch
- Department of Hematology and Oncology, Familial Cancer Program, Dartmouth–Hitchcock Medical Center
| | | | | | - James G Kench
- Tissue Pathology & Diagnostic Oncology, Royal Prince Alfred Hospital
| | | | - Rita Derua
- Laboratory of Protein Phosphorylation and Proteomics, Catholic University of Leuven
| | - Etienne Waelkens
- Laboratory of Protein Phosphorylation and Proteomics, Catholic University of Leuven
| | | | - Luke A Selth
- Flinders Health and Medical Research Institute, Flinders University
| | - Paul J Trim
- Proteomics, Metabolomics and MS Imaging Core Facility, South Australian Health & Medical Research Institute
| | - Marten F Snel
- Proteomics, Metabolomics and MS-Imaging Core Facility, South Australian Health & Medical Research Institute
| | - David J Lynn
- Precision Medicine, South Australian Health and Medical Research Institute
| | - Wayne D Tilley
- Dame Roma Mitchell Cancer Research Laboratories, University of Adelaide
| | - Lisa G Horvath
- Cancer Research Program, Garvan Institute of Medical Research
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21
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Tu A, Said N, Muddiman DC. Spatially resolved metabolomic characterization of muscle invasive bladder cancer by mass spectrometry imaging. Metabolomics 2021; 17:70. [PMID: 34287708 PMCID: PMC8893274 DOI: 10.1007/s11306-021-01819-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 07/09/2021] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Muscle invasive bladder cancer (MIBC) is an advanced stage of bladder cancer which poses a severe threat to life. Cancer development is usually accompanied by remarkable alterations in cell metabolism, and hence deep insights into MIBC at the metabolomic level can facilitate the understanding of the biochemical mechanisms involved in the cancer development and progression. METHODS In this proof-of-concept study, the optimal cutting temperature (OCT)-embedded MIBC samples were first washed with pure water to remove the polymer compounds which could cause severe signal suppression during mass spectrometry. Further, the tissue sections were analyzed by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI), providing an overview on the spatially resolved metabolomic profiles. RESULTS The MSI data enabled the discrimination between not only the cancerous and normal tissues, but also the subregions within a tissue section associated with different disease states. Using t-Distributed Stochastic Neighbor Embedding (t-SNE), the hyperdimensional MSI data was mapped into a two-dimensional space to visualize the spectral similarity, providing evidence that metabolomic alterations might have occurred outside the histopathological tumor border. Least absolute shrinkage and selection operator (LASSO) was further employed to classify sample pathology in a pixel-wise manner, yielding excellent prediction sensitivity and specificity up to 96% based on the statistically characteristic spectral features. CONCLUSION The results demonstrate great promise of IR-MALDESI MSI to identify molecular changes derived from cancer and unveil tumor heterogeneity, which can potentially promote the discovery of clinically relevant biomarkers and allow for applications in precision medicine.
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Affiliation(s)
- Anqi Tu
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Neveen Said
- Departments of Cancer Biology, Pathology, and Urology, Wake Forest University School of Medicine, Wake Forest Baptist Comprehensive Cancer Center, Winston Salem, NC, 27157, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA.
- Molecular Education, Technology and Research Innovation Center (METRIC), North Carolina State University, Raleigh, NC, 27695, USA.
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22
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Lopes Gonçalves JP, Bollwein C, Weichert W, Schwamborn K. Implementation of Mass Spectrometry Imaging in Pathology: Advances and Challenges. Clin Lab Med 2021; 41:173-184. [PMID: 34020758 DOI: 10.1016/j.cll.2021.03.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Mass spectrometry imaging (MSI) combines the excellence in molecular characterization of mass spectrometry with microscopic imaging capabilities of hematoxylin- and eosin-stained samples, enabling the precise location of several analytes in the tissue. Especially in the field of pathology, MSI may have an impactful role in tumor diagnosis, biomarker identification, prognostic prediction, and characterization of tumor margins during tumor resection procedures. This article discusses the recent developments in the field that are paving the way for this technology to become accepted as an analytical tool in the clinical setting, its current limitations, and future directions.
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Affiliation(s)
| | - Christine Bollwein
- Institute of Pathology, Technical University of Munich, Trogerstr. 18, 81675 Munich, Germany
| | - Wilko Weichert
- Institute of Pathology, Technical University of Munich, Trogerstr. 18, 81675 Munich, Germany
| | - Kristina Schwamborn
- Institute of Pathology, Technical University of Munich, Trogerstr. 18, 81675 Munich, Germany.
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23
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Tiwari S, Kajdacsy-Balla A, Whiteley J, Cheng G, Hewitt SM, Bhargava R. INFORM: INFrared-based ORganizational Measurements of tumor and its microenvironment to predict patient survival. SCIENCE ADVANCES 2021; 7:7/6/eabb8292. [PMID: 33536203 PMCID: PMC7857685 DOI: 10.1126/sciadv.abb8292] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 12/11/2020] [Indexed: 05/14/2023]
Abstract
The structure and organization of a tumor and its microenvironment are often associated with cancer outcomes due to spatially varying molecular composition and signaling. A persistent challenge is to use this physical and chemical spatial organization to understand cancer progression. Here, we present a high-definition infrared imaging-based organizational measurement framework (INFORM) that leverages intrinsic chemical contrast of tissue to label unique components of the tumor and its microenvironment. Using objective and automated computational methods, further, we determine organization characteristics important for prediction. We show that the tumor spatial organization assessed with this framework is predictive of overall survival in colon cancer that adds to capability from clinical variables such as stage and grade, approximately doubling the risk of death in high-risk individuals. Our results open an all-digital avenue for measuring and studying the association between tumor spatial organization and disease progression.
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Affiliation(s)
- Saumya Tiwari
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Andre Kajdacsy-Balla
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Joshua Whiteley
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | | | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Rohit Bhargava
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
- Departments of Electrical and Computer Engineering, Mechanical Science and Engineering, Chemical and Biomolecular Engineering and Chemistry, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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24
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Andersen MK, Høiem TS, Claes BSR, Balluff B, Martin-Lorenzo M, Richardsen E, Krossa S, Bertilsson H, Heeren RMA, Rye MB, Giskeødegård GF, Bathen TF, Tessem MB. Spatial differentiation of metabolism in prostate cancer tissue by MALDI-TOF MSI. Cancer Metab 2021; 9:9. [PMID: 33514438 PMCID: PMC7847144 DOI: 10.1186/s40170-021-00242-z] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 12/09/2020] [Indexed: 02/07/2023] Open
Abstract
Background Prostate cancer tissues are inherently heterogeneous, which presents a challenge for metabolic profiling using traditional bulk analysis methods that produce an averaged profile. The aim of this study was therefore to spatially detect metabolites and lipids on prostate tissue sections by using mass spectrometry imaging (MSI), a method that facilitates molecular imaging of heterogeneous tissue sections, which can subsequently be related to the histology of the same section. Methods Here, we simultaneously obtained metabolic and lipidomic profiles in different prostate tissue types using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MSI. Both positive and negative ion mode were applied to analyze consecutive sections from 45 fresh-frozen human prostate tissue samples (N = 15 patients). Mass identification was performed with tandem MS. Results Pairwise comparisons of cancer, non-cancer epithelium, and stroma revealed several metabolic differences between the tissue types. We detected increased levels of metabolites crucial for lipid metabolism in cancer, including metabolites involved in the carnitine shuttle, which facilitates fatty acid oxidation, and building blocks needed for lipid synthesis. Metabolites associated with healthy prostate functions, including citrate, aspartate, zinc, and spermine had lower levels in cancer compared to non-cancer epithelium. Profiling of stroma revealed higher levels of important energy metabolites, such as ADP, ATP, and glucose, and higher levels of the antioxidant taurine compared to cancer and non-cancer epithelium. Conclusions This study shows that specific tissue compartments within prostate cancer samples have distinct metabolic profiles and pinpoint the advantage of methodology providing spatial information compared to bulk analysis. We identified several differential metabolites and lipids that have potential to be developed further as diagnostic and prognostic biomarkers for prostate cancer. Spatial and rapid detection of cancer-related analytes showcases MALDI-TOF MSI as a promising and innovative diagnostic tool for the clinic. Supplementary Information The online version contains supplementary material available at 10.1186/s40170-021-00242-z.
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Affiliation(s)
- Maria K Andersen
- Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.
| | - Therese S Høiem
- Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Britt S R Claes
- Maastricht MultiModal Molecular Imaging institute (M4I), Maastricht University, Maastricht, The Netherlands
| | - Benjamin Balluff
- Maastricht MultiModal Molecular Imaging institute (M4I), Maastricht University, Maastricht, The Netherlands
| | - Marta Martin-Lorenzo
- Maastricht MultiModal Molecular Imaging institute (M4I), Maastricht University, Maastricht, The Netherlands
| | - Elin Richardsen
- Department of Medical Biology, UiT The Artic University of Norway, Tromsø, Norway.,Department of Clinical Pathology, University Hospital of North Norway, UNN, Tromsø, Norway
| | - Sebastian Krossa
- Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Helena Bertilsson
- Department of Clinical and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.,Department of Urology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging institute (M4I), Maastricht University, Maastricht, The Netherlands
| | - Morten B Rye
- Department of Clinical and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.,Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.,Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.,BioCore-Bioinformatics Core Facility, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Guro F Giskeødegård
- Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Trondheim, Norway. .,Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
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Neumann EK, Djambazova KV, Caprioli RM, Spraggins JM. Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:2401-2415. [PMID: 32886506 PMCID: PMC9278956 DOI: 10.1021/jasms.0c00232] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.
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Affiliation(s)
- Elizabeth K Neumann
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Katerina V Djambazova
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
| | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
- Department of Pharmacology, Vanderbilt University, 2220 Pierce Avenue, Nashville, Tennessee 37232, United States
- Department of Medicine, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Jeffrey M Spraggins
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
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26
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Tonry C, Finn S, Armstrong J, Pennington SR. Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management. Clin Proteomics 2020; 17:41. [PMID: 33292167 PMCID: PMC7678104 DOI: 10.1186/s12014-020-09305-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/11/2020] [Indexed: 12/12/2022] Open
Abstract
Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990's, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3-5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.
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Affiliation(s)
- Claire Tonry
- UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - Stephen Finn
- Department of Histopathology and Morbid Anatomy, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin 8, Ireland
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Butler LM, Perone Y, Dehairs J, Lupien LE, de Laat V, Talebi A, Loda M, Kinlaw WB, Swinnen JV. Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention. Adv Drug Deliv Rev 2020; 159:245-293. [PMID: 32711004 PMCID: PMC7736102 DOI: 10.1016/j.addr.2020.07.013] [Citation(s) in RCA: 285] [Impact Index Per Article: 71.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 07/02/2020] [Accepted: 07/16/2020] [Indexed: 02/06/2023]
Abstract
With the advent of effective tools to study lipids, including mass spectrometry-based lipidomics, lipids are emerging as central players in cancer biology. Lipids function as essential building blocks for membranes, serve as fuel to drive energy-demanding processes and play a key role as signaling molecules and as regulators of numerous cellular functions. Not unexpectedly, cancer cells, as well as other cell types in the tumor microenvironment, exploit various ways to acquire lipids and extensively rewire their metabolism as part of a plastic and context-dependent metabolic reprogramming that is driven by both oncogenic and environmental cues. The resulting changes in the fate and composition of lipids help cancer cells to thrive in a changing microenvironment by supporting key oncogenic functions and cancer hallmarks, including cellular energetics, promoting feedforward oncogenic signaling, resisting oxidative and other stresses, regulating intercellular communication and immune responses. Supported by the close connection between altered lipid metabolism and the pathogenic process, specific lipid profiles are emerging as unique disease biomarkers, with diagnostic, prognostic and predictive potential. Multiple preclinical studies illustrate the translational promise of exploiting lipid metabolism in cancer, and critically, have shown context dependent actionable vulnerabilities that can be rationally targeted, particularly in combinatorial approaches. Moreover, lipids themselves can be used as membrane disrupting agents or as key components of nanocarriers of various therapeutics. With a number of preclinical compounds and strategies that are approaching clinical trials, we are at the doorstep of exploiting a hitherto underappreciated hallmark of cancer and promising target in the oncologist's strategy to combat cancer.
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Affiliation(s)
- Lisa M Butler
- Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, SA 5005, Australia; South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
| | - Ylenia Perone
- Department of Surgery and Cancer, Imperial College London, Imperial Centre for Translational and Experimental Medicine, London, UK
| | - Jonas Dehairs
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Leslie E Lupien
- Program in Experimental and Molecular Medicine, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 037560, USA
| | - Vincent de Laat
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Ali Talebi
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Massimo Loda
- Pathology and Laboratory Medicine, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - William B Kinlaw
- The Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 03756, USA
| | - Johannes V Swinnen
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium.
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28
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29
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Mussap M, Loddo C, Fanni C, Fanos V. Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics. Expert Rev Clin Pharmacol 2020; 13:115-134. [PMID: 31958027 DOI: 10.1080/17512433.2020.1713750] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.
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Affiliation(s)
- Michele Mussap
- Laboratory Unit, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy
| | | | - Claudia Fanni
- Division of Pediatrics, Rovigo Hospital, Rovigo, Italy
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Neonatal Pathology and Neonatal Section, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy
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30
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Swiner DJ, Jackson S, Burris BJ, Badu-Tawiah AK. Applications of Mass Spectrometry for Clinical Diagnostics: The Influence of Turnaround Time. Anal Chem 2020; 92:183-202. [PMID: 31671262 PMCID: PMC7896279 DOI: 10.1021/acs.analchem.9b04901] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
This critical review discusses how the need for reduced clinical turnaround times has influenced chemical instrumentation. We focus on the development of modern mass spectrometry (MS) and its application in clinical diagnosis. With increased functionality that takes advantage of novel front-end modifications and computational capabilities, MS can now be used for non-traditional clinical analyses, including applications in clinical microbiology for bacteria differentiation and in surgical operation rooms. We summarize here recent developments in the field that have enabled such capabilities, which include miniaturization for point-of-care testing, direct complex mixture analysis via ambient ionization, chemical imaging and profiling, and systems integration.
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Affiliation(s)
- Devin J. Swiner
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210
| | - Sierra Jackson
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210
| | - Benjamin J. Burris
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210
| | - Abraham K. Badu-Tawiah
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210
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31
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Mah CY, Nassar ZD, Swinnen JV, Butler LM. Lipogenic effects of androgen signaling in normal and malignant prostate. Asian J Urol 2019; 7:258-270. [PMID: 32742926 PMCID: PMC7385522 DOI: 10.1016/j.ajur.2019.12.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 09/16/2019] [Accepted: 11/05/2019] [Indexed: 12/18/2022] Open
Abstract
Prostate cancer is an androgen-dependent cancer with unique metabolic features compared to many other solid tumors, and typically does not exhibit the “Warburg effect”. During malignant transformation, an early metabolic switch diverts the dependence of normal prostate cells on aerobic glycolysis for the synthesis of and secretion of citrate towards a more energetically favorable metabolic phenotype, whereby citrate is actively oxidised for energy and biosynthetic processes (i.e. de novo lipogenesis). It is now clear that lipid metabolism is one of the key androgen-regulated processes in prostate cells and alterations in lipid metabolism are a hallmark of prostate cancer, whereby increased de novo lipogenesis accompanied by overexpression of lipid metabolic genes are characteristic of primary and advanced disease. Despite recent advances in our understanding of altered lipid metabolism in prostate tumorigenesis and cancer progression, the intermediary metabolism of the normal prostate and its relationship to androgen signaling remains poorly understood. In this review, we discuss the fundamental metabolic relationships that are distinctive in normal versus malignant prostate tissues, and the role of androgens in the regulation of lipid metabolism at different stages of prostate tumorigenesis.
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Affiliation(s)
- Chui Yan Mah
- Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, Australia.,South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Zeyad D Nassar
- Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, Australia.,South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Johannes V Swinnen
- KU Leuven- University of Leuven, LKI- Leuven Cancer Institute, Department of Oncology, Laboratory of Lipid Metabolism and Cancer, Leuven, Belgium
| | - Lisa M Butler
- Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, Australia.,South Australian Health and Medical Research Institute, Adelaide, Australia
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