1
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Grooms AJ, Burris BJ, Badu-Tawiah AK. Mass spectrometry for metabolomics analysis: Applications in neonatal and cancer screening. MASS SPECTROMETRY REVIEWS 2024; 43:683-712. [PMID: 36524560 PMCID: PMC10272294 DOI: 10.1002/mas.21826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 11/18/2022] [Accepted: 11/24/2022] [Indexed: 06/17/2023]
Abstract
Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body.
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Affiliation(s)
- Alexander J Grooms
- Department of Chemistry and Biochemistry, The Ohio State University, Ohio, Columbus, USA
| | - Benjamin J Burris
- Department of Chemistry and Biochemistry, The Ohio State University, Ohio, Columbus, USA
| | - Abraham K Badu-Tawiah
- Department of Chemistry and Biochemistry, The Ohio State University, Ohio, Columbus, USA
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2
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Mohsen JJ, Martel AA, Slavoff SA. Microproteins-Discovery, structure, and function. Proteomics 2023; 23:e2100211. [PMID: 37603371 PMCID: PMC10841188 DOI: 10.1002/pmic.202100211] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/03/2023] [Accepted: 08/10/2023] [Indexed: 08/22/2023]
Abstract
Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles.
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Affiliation(s)
- Jessica J. Mohsen
- Department of Chemistry, Yale University, New Haven, CT, USA
- Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT, USA
| | - Alina A. Martel
- Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT, USA
| | - Sarah A. Slavoff
- Department of Chemistry, Yale University, New Haven, CT, USA
- Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
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3
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Wisztorski M, Aboulouard S, Roussel L, Duhamel M, Saudemont P, Cardon T, Narducci F, Robin YM, Lemaire AS, Bertin D, Hajjaji N, Kobeissy F, Leblanc E, Fournier I, Salzet M. Fallopian tube lesions as potential precursors of early ovarian cancer: a comprehensive proteomic analysis. Cell Death Dis 2023; 14:644. [PMID: 37775701 PMCID: PMC10541450 DOI: 10.1038/s41419-023-06165-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 09/08/2023] [Accepted: 09/20/2023] [Indexed: 10/01/2023]
Abstract
Ovarian cancer is the leading cause of death from gynecologic cancer worldwide. High-grade serous carcinoma (HGSC) is the most common and deadliest subtype of ovarian cancer. While the origin of ovarian tumors is still debated, it has been suggested that HGSC originates from cells in the fallopian tube epithelium (FTE), specifically the epithelial cells in the region of the tubal-peritoneal junction. Three main lesions, p53 signatures, STILs, and STICs, have been defined based on the immunohistochemistry (IHC) pattern of p53 and Ki67 markers and the architectural alterations of the cells, using the Sectioning and Extensively Examining the Fimbriated End Protocol. In this study, we performed an in-depth proteomic analysis of these pre-neoplastic epithelial lesions guided by mass spectrometry imaging and IHC. We evaluated specific markers related to each preneoplastic lesion. The study identified specific lesion markers, such as CAVIN1, Emilin2, and FBLN5. We also used SpiderMass technology to perform a lipidomic analysis and identified the specific presence of specific lipids signature including dietary Fatty acids precursors in lesions. Our study provides new insights into the molecular mechanisms underlying the progression of ovarian cancer and confirms the fimbria origin of HGSC.
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Affiliation(s)
- Maxence Wisztorski
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
| | - Soulaimane Aboulouard
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
| | - Lucas Roussel
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
| | - Marie Duhamel
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
| | - Philippe Saudemont
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
| | - Tristan Cardon
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
| | - Fabrice Narducci
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
- Department of Gynecology Oncology, Oscar Lambret Cancer Center, 59020, Lille, France
| | - Yves-Marie Robin
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
- Department of Gynecology Oncology, Oscar Lambret Cancer Center, 59020, Lille, France
| | - Anne-Sophie Lemaire
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
- Department of Gynecology Oncology, Oscar Lambret Cancer Center, 59020, Lille, France
| | - Delphine Bertin
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
- Department of Gynecology Oncology, Oscar Lambret Cancer Center, 59020, Lille, France
| | - Nawale Hajjaji
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France
- Medical Oncology Department, Oscar Lambret Cancer Center, 59020, Lille, France
| | - Firas Kobeissy
- Department of Neurobiology, Center for Neurotrauma, Multiomics & Biomarkers (CNMB), MorehouseSchool of Medicine, Atlanta, GA, 30310, USA
- Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Eric Leblanc
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France.
- Department of Gynecology Oncology, Oscar Lambret Cancer Center, 59020, Lille, France.
| | - Isabelle Fournier
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France.
- Institut Universitaire de France, 75000, Paris, France.
| | - Michel Salzet
- Univ.Lille, Inserm, CHU Lille, U-1192 - Laboratoire Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000, Lille, France.
- Institut Universitaire de France, 75000, Paris, France.
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4
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Tabb DL, Jeong K, Druart K, Gant MS, Brown KA, Nicora C, Zhou M, Couvillion S, Nakayasu E, Williams JE, Peterson HK, McGuire MK, McGuire MA, Metz TO, Chamot-Rooke J. Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection. J Proteome Res 2023. [PMID: 37235544 DOI: 10.1021/acs.jproteome.2c00673] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Generating top-down tandem mass spectra (MS/MS) from complex mixtures of proteoforms benefits from improvements in fractionation, separation, fragmentation, and mass analysis. The algorithms to match MS/MS to sequences have undergone a parallel evolution, with both spectral alignment and match-counting approaches producing high-quality proteoform-spectrum matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification (ProSight PD, TopPIC, MSPathFinderT, and pTop) in their yield of PrSMs while controlling false discovery rate. We evaluated deconvolution engines (ThermoFisher Xtract, Bruker AutoMSn, Matrix Science Mascot Distiller, TopFD, and FLASHDeconv) in both ThermoFisher Orbitrap-class and Bruker maXis Q-TOF data (PXD033208) to produce consistent precursor charges and mass determinations. Finally, we sought post-translational modifications (PTMs) in proteoforms from bovine milk (PXD031744) and human ovarian tissue. Contemporary identification workflows produce excellent PrSM yields, although approximately half of all identified proteoforms from these four pipelines were specific to only one workflow. Deconvolution algorithms disagree on precursor masses and charges, contributing to identification variability. Detection of PTMs is inconsistent among algorithms. In bovine milk, 18% of PrSMs produced by pTop and TopMG were singly phosphorylated, but this percentage fell to 1% for one algorithm. Applying multiple search engines produces more comprehensive assessments of experiments. Top-down algorithms would benefit from greater interoperability.
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Affiliation(s)
- David L Tabb
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| | - Kyowon Jeong
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen 72076, Germany
| | - Karen Druart
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| | - Megan S Gant
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| | - Kyle A Brown
- School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin 53705, United States
| | - Carrie Nicora
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Mowei Zhou
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Sneha Couvillion
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ernesto Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Janet E Williams
- Department of Animal, Veterinary, and Food Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Haley K Peterson
- Department of Animal, Veterinary, and Food Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Michelle K McGuire
- Margaret Ritchie School of Family and Consumer Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Mark A McGuire
- Department of Animal, Veterinary, and Food Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Julia Chamot-Rooke
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
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5
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de Jong E, Kocer A. Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers. MEMBRANES 2023; 13:409. [PMID: 37103836 PMCID: PMC10142483 DOI: 10.3390/membranes13040409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 06/19/2023]
Abstract
Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.
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6
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Nickerson JL, Baghalabadi V, Rajendran SRCK, Jakubec PJ, Said H, McMillen TS, Dang Z, Doucette AA. Recent advances in top-down proteome sample processing ahead of MS analysis. MASS SPECTROMETRY REVIEWS 2023; 42:457-495. [PMID: 34047392 DOI: 10.1002/mas.21706] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 04/21/2021] [Accepted: 05/06/2021] [Indexed: 06/12/2023]
Abstract
Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.
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Affiliation(s)
| | - Venus Baghalabadi
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Subin R C K Rajendran
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
- Verschuren Centre for Sustainability in Energy and the Environment, Sydney, Nova Scotia, Canada
| | - Philip J Jakubec
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Hammam Said
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Teresa S McMillen
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Ziheng Dang
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Alan A Doucette
- Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada
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7
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Mallah K, Zibara K, Kerbaj C, Eid A, Khoshman N, Ousseily Z, Kobeissy A, Cardon T, Cizkova D, Kobeissy F, Fournier I, Salzet M. Neurotrauma investigation through spatial omics guided by mass spectrometry imaging: Target identification and clinical applications. MASS SPECTROMETRY REVIEWS 2023; 42:189-205. [PMID: 34323300 DOI: 10.1002/mas.21719] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/04/2021] [Accepted: 07/11/2021] [Indexed: 06/13/2023]
Abstract
Traumatic brain injury (TBI) represents one of the major public health concerns worldwide due to the increase in TBI incidence as a result of injuries from daily life accidents such as sports and motor vehicle transportation as well as military-related practices. This type of central nervous system trauma is known to predispose patients to several neurological disorders such as Parkinson's disease, Alzheimer's disease, chronic trauamatic encephalopathy, and age-related Dementia. Recently, several proteomic and lipidomic platforms have been applied on different TBI studies to investigate TBI-related mechanisms that have broadened our understanding of its distinct neuropathological complications. In this study, we provide an updated comprehensive overview of the current knowledge and novel perspectives of the spatially resolved microproteomics and microlipidomics approaches guided by mass spectrometry imaging used in TBI studies and its applications in the neurotrauma field. In this regard, we will discuss the use of the spatially resolved microproteomics and assess the different microproteomic sampling methods such as laser capture microdissection, parafilm assisted microdissection, and liquid microjunction extraction as accurate and precise techniques in the field of neuroproteomics. Additionally, we will highlight lipid profiling applications and their prospective potentials in characterizing molecular processes involved in the field of TBI. Specifically, we will discuss the phospholipid metabolism acting as a precursor for proinflammatory molecules such as eicosanoids. Finally, we will survey the current state of spatial neuroproteomics and microproteomics applications and present the various studies highlighting their findings in these fields.
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Affiliation(s)
- Khalil Mallah
- Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, South Carolina, USA
- PRASE, Lebanese University, Beirut, Lebanon
- Univ.Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
| | - Kazem Zibara
- PRASE, Lebanese University, Beirut, Lebanon
- Department of Biology, Faculty of Sciences-I, Lebanese University, Beirut, Lebanon
| | - Coline Kerbaj
- Department of Biology, Faculty of Sciences-I, Lebanese University, Beirut, Lebanon
| | - Ali Eid
- Department of Basic Medical Sciences, QU Health, Qatar University, Doha, Qatar
| | - Nour Khoshman
- Department of Biology, Faculty of Sciences-I, Lebanese University, Beirut, Lebanon
| | - Zahraa Ousseily
- Department of Biology, Faculty of Sciences-I, Lebanese University, Beirut, Lebanon
| | - Abir Kobeissy
- Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Tristan Cardon
- Univ.Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
| | - Dasa Cizkova
- Univ.Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
- Center for Experimental and Clinical Regenerative Medicine, University of Veterinary Medicine and Pharmacy in Košice, Košice, Slovakia
| | - Firas Kobeissy
- Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Isabelle Fournier
- Univ.Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
- Institut Universitaire de France, Paris, France
| | - Michel Salzet
- Univ.Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
- Institut Universitaire de France, Paris, France
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8
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Guo A, Chen Z, Li F, Luo Q. Delineating regions of interest for mass spectrometry imaging by multimodally corroborated spatial segmentation. Gigascience 2022; 12:giad021. [PMID: 37039115 PMCID: PMC10087011 DOI: 10.1093/gigascience/giad021] [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: 12/26/2022] [Revised: 02/17/2023] [Accepted: 03/13/2023] [Indexed: 04/12/2023] Open
Abstract
Mass spectrometry imaging (MSI), which localizes molecules in a tag-free, spatially resolved manner, is a powerful tool for the understanding of underlying biochemical mechanisms of biological phenomena. When analyzing MSI data, it is essential to delineate regions of interest (ROIs) that correspond to tissue areas of different anatomical or pathological labels. Spatial segmentation, obtained by clustering MSI pixels according to their mass spectral similarities, is a popular approach to automate ROI definition. However, how to select the number of clusters (#Clusters), which determines the granularity of segmentation, remains to be resolved, and an inappropriate #Clusters may lead to ROIs not biologically real. Here we report a multimodal fusion strategy to enable an objective and trustworthy selection of #Clusters by utilizing additional information from corresponding histology images. A deep learning-based algorithm is proposed to extract "histomorphological feature spectra" across an entire hematoxylin and eosin image. Clustering is then similarly performed to produce histology segmentation. Since ROIs originating from instrumental noise or artifacts would not be reproduced cross-modally, the consistency between histology and MSI segmentation becomes an effective measure of the biological validity of the results. So, #Clusters that maximize the consistency is deemed as most probable. We validated our strategy on mouse kidney and renal tumor specimens by producing multimodally corroborated ROIs that agreed excellently with ground truths. Downstream analysis based on the said ROIs revealed lipid molecules highly specific to tissue anatomy or pathology. Our work will greatly facilitate MSI-mediated spatial lipidomics, metabolomics, and proteomics research by providing intelligent software to automatically and reliably generate ROIs.
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Affiliation(s)
- Ang Guo
- Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhiyu Chen
- Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fang Li
- Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Qian Luo
- Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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9
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Mass spectrometry imaging in gynecological cancers: the best is yet to come. Cancer Cell Int 2022; 22:414. [PMID: 36536419 PMCID: PMC9764543 DOI: 10.1186/s12935-022-02832-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022] Open
Abstract
Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.
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10
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Zhang Y, Yang L, Zhang Y, Liang Y, Zhao H, Li Y, Cai G, Wu Z, Li Z. Identification of Important Factors Causing Developmental Arrest in Cloned Pig Embryos by Embryo Biopsy Combined with Microproteomics. Int J Mol Sci 2022; 23:ijms232415975. [PMID: 36555617 PMCID: PMC9783476 DOI: 10.3390/ijms232415975] [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: 11/02/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
The technique of pig cloning holds great promise for the livestock industry, life science, and biomedicine. However, the prenatal death rate of cloned pig embryos is extremely high, resulting in a very low cloning efficiency. This limits the development and application of pig cloning. In this study, we utilized embryo biopsy combined with microproteomics to identify potential factors causing the developmental arrest in cloned pig embryos. We verified the roles of two potential regulators, PDCD6 and PLK1, in cloned pig embryo development. We found that siRNA-mediated knockdown of PDCD6 reduced mRNA and protein expression levels of the pro-apoptotic gene, CASP3, in cloned pig embryos. PDCD6 knockdown also increased the cleavage rate and blastocyst rate of cloned porcine embryos. Overexpression of PLK1 via mRNA microinjection also improved the cleavage rate of cloned pig embryos. This study provided a new strategy to identify key factors responsible for the developmental defects in cloned pig embryos. It also helped establish new methods to improve pig cloning efficiency, specifically by correcting the expression pattern of PDCD6 and PLK1 in cloned pig embryos.
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Affiliation(s)
- Yuxing Zhang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Liusong Yang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Yiqian Zhang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Yalin Liang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Huaxing Zhao
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Yanan Li
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou 510642, China
- Correspondence: (Z.W.); (Z.L.)
| | - Zicong Li
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Guangzhou 510030, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510030, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou 510642, China
- Correspondence: (Z.W.); (Z.L.)
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11
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Mohaupt P, Roucou X, Delaby C, Vialaret J, Lehmann S, Hirtz C. The alternative proteome in neurobiology. Front Cell Neurosci 2022; 16:1019680. [PMID: 36467612 PMCID: PMC9712206 DOI: 10.3389/fncel.2022.1019680] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 11/02/2022] [Indexed: 10/13/2023] Open
Abstract
Translation involves the biosynthesis of a protein sequence following the decoding of the genetic information embedded in a messenger RNA (mRNA). Typically, the eukaryotic mRNA was considered to be inherently monocistronic, but this paradigm is not in agreement with the translational landscape of cells, tissues, and organs. Recent ribosome sequencing (Ribo-seq) and proteomics studies show that, in addition to currently annotated reference proteins (RefProt), other proteins termed alternative proteins (AltProts), and microproteins are encoded in regions of mRNAs thought to be untranslated or in transcripts annotated as non-coding. This experimental evidence expands the repertoire of functional proteins within a cell and potentially provides important information on biological processes. This review explores the hitherto overlooked alternative proteome in neurobiology and considers the role of AltProts in pathological and healthy neuromolecular processes.
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Affiliation(s)
- Pablo Mohaupt
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Xavier Roucou
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Constance Delaby
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Jérôme Vialaret
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Sylvain Lehmann
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Christophe Hirtz
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
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12
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Hajjaji N, Aboulouard S, Cardon T, Bertin D, Robin YM, Fournier I, Salzet M. Path to Clonal Theranostics in Luminal Breast Cancers. Front Oncol 2022; 11:802177. [PMID: 35096604 PMCID: PMC8793283 DOI: 10.3389/fonc.2021.802177] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 12/06/2021] [Indexed: 12/18/2022] Open
Abstract
Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString®) and CDx (Foundation One®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.
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Affiliation(s)
- Nawale Hajjaji
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France.,Breast Cancer Unit, Oscar Lambret Center, Lille, France
| | - Soulaimane Aboulouard
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
| | - Tristan Cardon
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France
| | - Delphine Bertin
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France.,Breast Cancer Unit, Oscar Lambret Center, Lille, France
| | - Yves-Marie Robin
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France.,Breast Cancer Unit, Oscar Lambret Center, Lille, France
| | - Isabelle Fournier
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France.,Institut universitaire de France, Paris, France
| | - Michel Salzet
- Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France.,Institut universitaire de France, Paris, France
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13
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Luu GT, Sanchez LM. Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study. INTERNATIONAL JOURNAL OF MASS SPECTROMETRY 2021; 469:116679. [PMID: 34744497 PMCID: PMC8570641 DOI: 10.1016/j.ijms.2021.116679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Ovarian cancer is one of the leading causes of cancer related deaths affecting United States women. Early-stage detection of ovarian cancer has been linked to increased survival, however, current screening methods, such as biomarker testing, have proven to be ineffective in doing so. Therefore, further developments are necessary to be able to achieve positive patient prognosis. Ongoing efforts are being made in biomarker discovery towards clinical applications in screening for early-stage ovarian cancer. In this perspective, we discuss and provide examples for several workflows employing mass spectrometry-based proteomics towards protein biomarker discovery and characterization in the context of ovarian cancer; workflows include protein identification and characterization as well as intact protein profiling. We also discuss the opportunities to merge these workflows for a multiplexed approach for biomarkers. Lastly, we provide our insight as to future developments that may serve to enhance biomarker discovery workflows while also considering translational potential.
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Affiliation(s)
- Gordon T Luu
- Department of Chemistry and Biochemistry, University of California Santa Cruz, 1156 High St. Santa Cruz, CA, 95064
| | - Laura M Sanchez
- Department of Chemistry and Biochemistry, University of California Santa Cruz, 1156 High St. Santa Cruz, CA, 95064
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14
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Innovation in drug toxicology: Application of mass spectrometry imaging technology. Toxicology 2021; 464:153000. [PMID: 34695509 DOI: 10.1016/j.tox.2021.153000] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 09/21/2021] [Accepted: 10/18/2021] [Indexed: 01/19/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful molecular imaging technology that can obtain qualitative, quantitative, and location information by simultaneously detecting and mapping endogenous or exogenous molecules in biological tissue slices without specific chemical labeling or complex sample pretreatment. This article reviews the progress made in MSI and its application in drug toxicology research, including the tissue distribution of toxic drugs and their metabolites, the target organs (liver, kidney, lung, eye, and central nervous system) of toxic drugs, the discovery of toxicity-associated biomarkers, and explanations of the mechanisms of drug toxicity when MSI is combined with the cutting-edge omics methodologies. The unique advantages and broad prospects of this technology have been fully demonstrated to further promote its wider use in the field of pharmaceutical toxicology.
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15
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Koudelka T, Winkels K, Kaleja P, Tholey A. Shedding light on both ends: An update on analytical approaches for N- and C-terminomics. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2021; 1869:119137. [PMID: 34626679 DOI: 10.1016/j.bbamcr.2021.119137] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 08/27/2021] [Accepted: 09/06/2021] [Indexed: 02/04/2023]
Abstract
Though proteases were long regarded as nonspecific degradative enzymes, over time, it was recognized that they also hydrolyze peptide bonds very specifically with a limited substrate pool. This irreversible posttranslational modification modulates the fate and activity of many proteins, making proteolytic processing a master switch in the regulation of e.g., the immune system, apoptosis and cancer progression. N- and C-terminomics, the identification of protein termini, has become indispensable in elucidating protease substrates and therefore protease function. Further, terminomics has the potential to identify yet unknown proteoforms, e.g. formed by alternative splicing or the recently discovered alternative ORFs. Different strategies and workflows have been developed that achieve higher sensitivity, a greater depth of coverage or higher throughput. In this review, we summarize recent developments in both N- and C-terminomics and include the potential of top-down proteomics which inherently delivers information on both ends of analytes in a single analysis.
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Affiliation(s)
- Tomas Koudelka
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Konrad Winkels
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Patrick Kaleja
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Andreas Tholey
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.
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16
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Drelich L, Aboulouard S, Franck J, Salzet M, Fournier I, Wisztorski M. Toward High Spatially Resolved Proteomics Using Expansion Microscopy. Anal Chem 2021; 93:12195-12203. [PMID: 34449217 DOI: 10.1021/acs.analchem.0c05372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Expansion microscopy (EM) is an emerging approach for morphological examination of biological specimens at nanoscale resolution using conventional optical microscopy. To achieve physical separation of cell structures, tissues are embedded in a swellable polymer and expanded several fold in an isotropic manner. This work shows the development and optimization of physical tissue expansion as a new method for spatially resolved large-scale proteomics. Herein we established a novel method to enlarge the tissue section to be compatible with manual microdissection on regions of interest and MS-based proteomic analysis. A major issue in expansion microscopy is the loss of protein information during the mechanical homogenization phase due to the use of proteinase K. For isotropic expansion, different homogenization agents were investigated, both to maximize protein identification and to minimize protein diffusion. Best results were obtained with SDS for homogenization. Using our modified protocol, we were able to enlarge a tissue section more than 3-fold and identified up to 655 proteins from 1 mm in size after expansion, equivalent to 330 μm in their real size corresponding thus to an average of 260 cells. This approach can be performed easily without any expensive sampling instrument. We demonstrated the compatibility of sample preparation for expansion microscopy and proteomic study in a spatial context.
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Affiliation(s)
- Lauranne Drelich
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, 59000, France
| | - Soulaimane Aboulouard
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, 59000, France
| | - Julien Franck
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, 59000, France
| | - Michel Salzet
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, 59000, France.,Institut Universitaire de France (IUF), Paris, 75000, France
| | - Isabelle Fournier
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, 59000, France.,Institut Universitaire de France (IUF), Paris, 75000, France
| | - Maxence Wisztorski
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, 59000, France
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17
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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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18
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Gagnon M, Savard M, Jacques JF, Bkaily G, Geha S, Roucou X, Gobeil F. Potentiation of B2 receptor signaling by AltB2R, a newly identified alternative protein encoded in the human bradykinin B2 receptor gene. J Biol Chem 2021; 296:100329. [PMID: 33497625 PMCID: PMC7949122 DOI: 10.1016/j.jbc.2021.100329] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 01/12/2021] [Accepted: 01/21/2021] [Indexed: 12/27/2022] Open
Abstract
Recent functional and proteomic studies in eukaryotes (www.openprot.org) predict the translation of alternative open reading frames (AltORFs) in mature G-protein-coupled receptor (GPCR) mRNAs, including that of bradykinin B2 receptor (B2R). Our main objective was to determine the implication of a newly discovered AltORF resulting protein, termed AltB2R, in the known signaling properties of B2R using complementary methodological approaches. When ectopically expressed in HeLa cells, AltB2R presented predominant punctate cytoplasmic/perinuclear distribution and apparent cointeraction with B2R at plasma and endosomal/vesicular membranes. The presence of AltB2R increases intracellular [Ca2+] and ERK1/2-MAPK activation (via phosphorylation) following B2R stimulation. Moreover, HEK293A cells expressing mutant B2R lacking concomitant expression of AltB2R displayed significantly decreased maximal responses in agonist-stimulated Gαq-Gαi2/3-protein coupling, IP3 generation, and ERK1/2-MAPK activation as compared with wild-type controls. Conversely, there was no difference in cell-surface density as well as ligand-binding properties of B2R and in efficiencies of cognate agonists at promoting B2R internalization and β-arrestin 2 recruitment. Importantly, both AltB2R and B2R proteins were overexpressed in prostate and breast cancers, compared with their normal counterparts suggesting new associative roles of AltB2R in these diseases. Our study shows that BDKRB2 is a dual-coding gene and identifies AltB2R as a novel positive modulator of some B2R signaling pathways. More broadly, it also supports a new, unexpected alternative proteome for GPCRs, which opens new frontiers in fields of GPCR biology, diseases, and drug discovery.
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Affiliation(s)
- Maxime Gagnon
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, Québec, Canada; Institute of Pharmacology, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Martin Savard
- Department of Pharmacology & Physiology, Université de Sherbrooke, Sherbrooke, Québec, Canada; Institute of Pharmacology, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Jean-François Jacques
- Department of Pharmacology & Physiology, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Ghassan Bkaily
- Department of Immunology & Cellular Biology, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Sameh Geha
- Department of Pathology, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
| | - Xavier Roucou
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, Québec, Canada; Institute of Pharmacology, Université de Sherbrooke, Sherbrooke, Québec, Canada.
| | - Fernand Gobeil
- Department of Pharmacology & Physiology, Université de Sherbrooke, Sherbrooke, Québec, Canada; Institute of Pharmacology, Université de Sherbrooke, Sherbrooke, Québec, Canada.
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19
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Cardon T, Fournier I, Salzet M. SARS-Cov-2 Interactome with Human Ghost Proteome: A Neglected World Encompassing a Wealth of Biological Data. Microorganisms 2020; 8:E2036. [PMID: 33352703 PMCID: PMC7766365 DOI: 10.3390/microorganisms8122036] [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: 11/12/2020] [Revised: 12/16/2020] [Accepted: 12/17/2020] [Indexed: 11/17/2022] Open
Abstract
Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics have led to a massive identification of proteins translated from mRNAs of alternative ORF (AltORFs), in addition to the predicted proteins issued from the reference ORF or from ncRNAs. These alternative proteins (AltProts) are not represented in the conventional protein databases and this "ghost proteome" was not considered until recently. Some of these proteins are functional and there is growing evidence that they are involved in central functions in physiological and physiopathological context. Based on our experience with AltProts, we were interested in finding out their interaction with the viral protein coming from the SARS-CoV-2 virus, responsible for the 2020 COVID-19 outbreak. Thus, we have scrutinized the recently published data by Krogan and coworkers (2020) on the SARS-CoV-2 interactome with host cells by affinity purification in co-immunoprecipitation (co-IP) in the perspective of drug repurposing. The initial work revealed the interaction between 332 human cellular reference proteins (RefProts) with the 27 viral proteins. Re-interrogation of this data using 23 viral targets and including AltProts, followed by enrichment of the interaction networks, leads to identify 218 RefProts (in common to initial study), plus 56 AltProts involved in 93 interactions. This demonstrates the necessity to take into account the ghost proteome for discovering new therapeutic targets, and establish new therapeutic strategies. Missing the ghost proteome in the drug metabolism and pharmacokinetic (DMPK) drug development pipeline will certainly be a major limitation to the establishment of efficient therapies.
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Affiliation(s)
- Tristan Cardon
- Inserm U1192, University Lille, CHU Lille, Laboratory Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Isabelle Fournier
- Inserm U1192, University Lille, CHU Lille, Laboratory Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
- Institut Universitaire de France, 75000 Paris, France
| | - Michel Salzet
- Inserm U1192, University Lille, CHU Lille, Laboratory Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
- Institut Universitaire de France, 75000 Paris, France
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20
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Krishnan R, Murugiah M, Lakshmi, NP, Mahalingam S. Guanine nucleotide binding protein like-1 (GNL1) promotes cancer cell proliferation and survival through AKT/p21 CIP1 signaling cascade. Mol Biol Cell 2020; 31:2904-2919. [PMID: 33147101 PMCID: PMC7927199 DOI: 10.1091/mbc.e20-04-0267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 10/14/2020] [Accepted: 10/27/2020] [Indexed: 12/03/2022] Open
Abstract
Human guanine nucleotide binding protein like 1 (GNL1) is an evolutionary conserved putative nucleolar GTPase belonging to the HSR1_MMR1 subfamily of GTPases. GNL1 was found to be highly up-regulated in various cancers. Here, we report for the first time that GNL1 inhibits apoptosis by modulating the expression of Bcl2 family of proteins and the cleavage of caspases 7 and 8. Furthermore, GNL1 protects colon cancer cells from chemo-drug-induced apoptosis. Interestingly, GNL1 up-regulates the expression of p53 and its transcriptional target, p21 but the up-regulation of p21 was found to be p53 dependent as well as independent mechanisms. Our results further demonstrate that GNL1 promotes cell growth and survival by inducing cytoplasmic retention and stabilization of p21 through AKT-mediated phosphorylation. In addition, GNL1 failed to inhibit apoptosis under p21 knockdown conditions which suggests the critical role of p21 in GNL1-mediated cell survival. Finally, an inverse correlation of GNL1, p21, and AKT expression in primary colon and breast cancer with patient survival suggests their critical role in tumorigenesis. Collectively, our study reveals that GNL1 executes its antiapoptotic function by a novel mechanism and suggests that it may function as a regulatory component of the PI3K/AKT/p21 signaling network to promote cell proliferation and survival in cancers.
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Affiliation(s)
- Rehna Krishnan
- Laboratory of Molecular Cell Biology, National Cancer Tissue Biobank, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology-Madras, Chennai 600 036, India
| | - Mariappan Murugiah
- Laboratory of Molecular Cell Biology, National Cancer Tissue Biobank, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology-Madras, Chennai 600 036, India
| | - Naga Padma Lakshmi,
- Laboratory of Molecular Cell Biology, National Cancer Tissue Biobank, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology-Madras, Chennai 600 036, India
| | - Sundarasamy Mahalingam
- Laboratory of Molecular Cell Biology, National Cancer Tissue Biobank, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology-Madras, Chennai 600 036, India
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21
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Cardon T, Fournier I, Salzet M. Shedding Light on the Ghost Proteome. Trends Biochem Sci 2020; 46:239-250. [PMID: 33246829 DOI: 10.1016/j.tibs.2020.10.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 01/19/2023]
Abstract
Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics has led to the identification of proteins translated from alternative open reading frames (AltORFs) in mRNAs. AltORFs are found in addition to predicted reference ORFs and noncoding RNA. Alternative proteins are not represented in the conventional protein databases, and this 'Ghost proteome' was not considered until recently. Some of these proteins are functional, and there is growing evidence that they are involved in central functions in physiological and physiopathological contexts. Here, we review how this Ghost proteome fills the gap in our understanding of signaling pathways, establishes new markers of pathologies, and highlights therapeutic targets.
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Affiliation(s)
- Tristan Cardon
- Laboratoire Protéomique, Réponse Inflammatoire Spectrométrie de Masse (PRISM), Inserm U1192, University of Lille, CHU Lille, F-59000 Lille, France.
| | - Isabelle Fournier
- Laboratoire Protéomique, Réponse Inflammatoire Spectrométrie de Masse (PRISM), Inserm U1192, University of Lille, CHU Lille, F-59000 Lille, France; Institut Universitaire de France, Paris, France.
| | - Michel Salzet
- Laboratoire Protéomique, Réponse Inflammatoire Spectrométrie de Masse (PRISM), Inserm U1192, University of Lille, CHU Lille, F-59000 Lille, France; Institut Universitaire de France, Paris, France.
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22
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Vergara D, Verri T, Damato M, Trerotola M, Simeone P, Franck J, Fournier I, Salzet M, Maffia M. A Hidden Human Proteome Signature Characterizes the Epithelial Mesenchymal Transition Program. Curr Pharm Des 2020; 26:372-375. [PMID: 31995001 DOI: 10.2174/1381612826666200129091610] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 01/27/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Molecular changes associated with the initiation of the epithelial to mesenchymal transition (EMT) program involve alterations of large proteome-based networks. The role of protein products mapping to non-coding genomic regions is still unexplored. OBJECTIVE The goal of this study was the identification of an alternative protein signature in breast cancer cellular models with a distinct expression of EMT markers. METHODS We profiled MCF-7 and MDA-MB-231 cells using liquid-chromatography mass/spectrometry (LCMS/ MS) and interrogated the OpenProt database to identify novel predicted isoforms and novel predicted proteins from alternative open reading frames (AltProts). RESULTS Our analysis revealed an AltProt and isoform protein signature capable of classifying the two breast cancer cell lines. Among the most highly expressed alternative proteins, we observed proteins potentially associated with inflammation, metabolism and EMT. CONCLUSION Here, we present an AltProts signature associated with EMT. Further studies will be needed to define their role in cancer progression.
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Affiliation(s)
- Daniele Vergara
- Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy
| | - Tiziano Verri
- Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy
| | - Marina Damato
- Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy
| | - Marco Trerotola
- Department of Medical, Oral and Biotechnological Sciences, "G.d'Annunzio" University of Chieti-Pescara, Italy
| | - Pasquale Simeone
- Department of Medicine and Aging Sciences, "G.d'Annunzio" University of Chieti-Pescara, Italy; Laboratory of Cytomorphology, Center for Advanced Studies and Technology (CAST), "G.d'Annunzio" University of Chieti-Pescara, Italy
| | - Julien Franck
- University of Lille, Inserm, U-1192, Laboratoire Proteomique, Reponse Inflammatoire et Spectrometrie de Masse-PRISM, F-59000, Lille, France
| | - Isabelle Fournier
- University of Lille, Inserm, U-1192, Laboratoire Proteomique, Reponse Inflammatoire et Spectrometrie de Masse-PRISM, F-59000, Lille, France
| | - Michel Salzet
- University of Lille, Inserm, U-1192, Laboratoire Proteomique, Reponse Inflammatoire et Spectrometrie de Masse-PRISM, F-59000, Lille, France
| | - Michele Maffia
- Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy
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23
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Cardon T, Franck J, Coyaud E, Laurent EMN, Damato M, Maffia M, Vergara D, Fournier I, Salzet M. Alternative proteins are functional regulators in cell reprogramming by PKA activation. Nucleic Acids Res 2020; 48:7864-7882. [PMID: 32324228 PMCID: PMC7641301 DOI: 10.1093/nar/gkaa277] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 04/06/2020] [Accepted: 04/21/2020] [Indexed: 12/28/2022] Open
Abstract
It has been recently shown that many proteins are lacking from reference databases used in mass spectrometry analysis, due to their translation templated on alternative open reading frames. This questions our current understanding of gene annotation and drastically expands the theoretical proteome complexity. The functions of these alternative proteins (AltProts) still remain largely unknown. We have developed a large-scale and unsupervised approach based on cross-linking mass spectrometry (XL-MS) followed by shotgun proteomics to gather information on the functional role of AltProts by mapping them back into known signalling pathways through the identification of their reference protein (RefProt) interactors. We have identified and profiled AltProts in a cancer cell reprogramming system: NCH82 human glioma cells after 0, 16, 24 and 48 h Forskolin stimulation. Forskolin is a protein kinase A activator inducing cell differentiation and epithelial–mesenchymal transition. Our data show that AltMAP2, AltTRNAU1AP and AltEPHA5 interactions with tropomyosin 4 are downregulated under Forskolin treatment. In a wider perspective, Gene Ontology and pathway enrichment analysis (STRING) revealed that RefProts associated with AltProts are enriched in cellular mobility and transfer RNA regulation. This study strongly suggests novel roles of AltProts in multiple essential cellular functions and supports the importance of considering them in future biological studies.
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Affiliation(s)
- Tristan Cardon
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Julien Franck
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Etienne Coyaud
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Estelle M N Laurent
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Marina Damato
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France.,Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Michele Maffia
- Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Daniele Vergara
- Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Isabelle Fournier
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France.,Institut Universitaire de France (IUF),75005 Paris, France
| | - Michel Salzet
- Univ. Lille, Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), F-59000 Lille, France.,Institut Universitaire de France (IUF),75005 Paris, France
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24
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Patel SK, George B, Rai V. Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology. Front Pharmacol 2020; 11:1177. [PMID: 32903628 PMCID: PMC7438594 DOI: 10.3389/fphar.2020.01177] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 07/20/2020] [Indexed: 12/13/2022] Open
Abstract
The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.
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Affiliation(s)
- Sandip Kumar Patel
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
- Buck Institute for Research on Aging, Novato, CA, United States
| | - Bhawana George
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vineeta Rai
- Department of Entomology & Plant Pathology, North Carolina State University, Raleigh, NC, United States
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25
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Jayathirtha M, Dupree EJ, Manzoor Z, Larose B, Sechrist Z, Neagu AN, Petre BA, Darie CC. Mass Spectrometric (MS) Analysis of Proteins and Peptides. Curr Protein Pept Sci 2020; 22:92-120. [PMID: 32713333 DOI: 10.2174/1389203721666200726223336] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 05/12/2020] [Accepted: 05/28/2020] [Indexed: 01/09/2023]
Abstract
The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.
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Affiliation(s)
- Madhuri Jayathirtha
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY, United States
| | - Emmalyn J Dupree
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY, United States
| | - Zaen Manzoor
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY, United States
| | - Brianna Larose
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY, United States
| | - Zach Sechrist
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY, United States
| | - Anca-Narcisa Neagu
- Laboratory of Animal Histology, Faculty of Biology, "Alexandru Ioan Cuza" University of Iasi, Iasi, Romania
| | - Brindusa Alina Petre
- Laboratory of Biochemistry, Department of Chemistry, Al. I. Cuza University of Iasi, Iasi, Romania, Center for Fundamental Research and Experimental Development in Translation Medicine - TRANSCEND, Regional Institute of Oncology, Iasi, Romania
| | - Costel C Darie
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY, United States
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26
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Eggeling F, Hoffmann F. Microdissection—An Essential Prerequisite for Spatial Cancer Omics. Proteomics 2020; 20:e2000077. [DOI: 10.1002/pmic.202000077] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/12/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Ferdinand Eggeling
- Department of OtorhinolaryngologyMALDI Imaging and Core Unit Proteome AnalysisDFG Core Unit Jena Biophotonic and Imaging Laboratory (JBIL)Jena University Hospital Am Klinikum 1 Jena 07747 Germany
| | - Franziska Hoffmann
- Department of OtorhinolaryngologyMALDI Imaging and Core Unit Proteome AnalysisDFG Core Unit Jena Biophotonic and Imaging Laboratory (JBIL)Jena University Hospital Am Klinikum 1 Jena 07747 Germany
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27
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Li N, Nie H, Jiang L, Ruan G, Du F, Liu H. Recent advances of ambient ionization mass spectrometry imaging in clinical research. J Sep Sci 2020; 43:3146-3163. [PMID: 32573988 DOI: 10.1002/jssc.202000273] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 05/03/2020] [Accepted: 05/06/2020] [Indexed: 02/06/2023]
Abstract
The structural information and spatial distribution of molecules in biological tissues are closely related to the potential molecular mechanisms of disease origin, transfer, and classification. Ambient ionization mass spectrometry imaging is an effective tool that provides molecular images while describing in situ information of biomolecules in complex samples, in which ionization occurs at atmospheric pressure with the samples being analyzed in the native state. Ambient ionization mass spectrometry imaging can directly analyze tissue samples at a fairly high resolution to obtain molecules in situ information on the tissue surface to identify pathological features associated with a disease, resulting in the wide applications in pharmacy, food science, botanical research, and especially clinical research. Herein, novel ambient ionization techniques, such as techniques based on spray and solid-liquid extraction, techniques based on plasma desorption, techniques based on laser desorption ablation, and techniques based on acoustic desorption were introduced, and the data processing of ambient ionization mass spectrometry imaging was briefly reviewed. Besides, we also highlight recent applications of this imaging technology in clinical researches and discuss the challenges in this imaging technology and the perspectives on the future of the clinical research.
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Affiliation(s)
- Na Li
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
| | - Honggang Nie
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
| | - Liping Jiang
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
| | - Guihua Ruan
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
| | - Fuyou Du
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
- College of Biological and Environmental Engineering, Changsha University, Changsha, P. R. China
| | - Huwei Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
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28
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Wang K, Donnarumma F, Pettit ME, Szot CW, Solouki T, Murray KK. MALDI imaging directed laser ablation tissue microsampling for data independent acquisition proteomics. JOURNAL OF MASS SPECTROMETRY : JMS 2020; 55:e4475. [PMID: 31726477 DOI: 10.1002/jms.4475] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 10/25/2019] [Accepted: 11/07/2019] [Indexed: 06/10/2023]
Abstract
A multimodal workflow for mass spectrometry imaging was developed that combines MALDI imaging with protein identification and quantification by liquid chromatography tandem mass spectrometry (LC-MS/MS). Thin tissue sections were analyzed by MALDI imaging, and the regions of interest (ROI) were identified using a smoothing and edge detection procedure. A midinfrared laser at 3-μm wavelength was used to remove the ROI from the brain tissue section after MALDI mass spectrometry imaging (MALDI MSI). The captured material was processed using a single-pot solid-phase-enhanced sample preparation (SP3) method and analyzed by LC-MS/MS using ion mobility (IM) enhanced data independent acquisition (DIA) to identify and quantify proteins; more than 600 proteins were identified. Using a modified database that included isoform and the post-translational modifications chain, loss of the initial methionine, and acetylation, 14 MALDI MSI peaks were identified. Comparison of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the identified proteins was achieved through an evolutionary relationships classification system.
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Affiliation(s)
- Kelin Wang
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, United States
| | - Fabrizio Donnarumma
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, United States
| | - Michael E Pettit
- Department of Chemistry and Biochemistry, Baylor University, Waco, TX, 76706, United States
| | - Carson W Szot
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, United States
| | - Touradj Solouki
- Department of Chemistry and Biochemistry, Baylor University, Waco, TX, 76706, United States
| | - Kermit K Murray
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, United States
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29
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Pagliusi Jr. M, Brandão A, Zanetti G, Bonet I, Sartori C, Vieira A. Using the Parafilm-assisted Microdissection (PAM) Method to Sample Rodent Nucleus Accumbens. Bio Protoc 2020; 10:e3836. [DOI: 10.21769/bioprotoc.3836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 10/28/2020] [Accepted: 10/12/2020] [Indexed: 11/02/2022] Open
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30
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Cardon T, Hervé F, Delcourt V, Roucou X, Salzet M, Franck J, Fournier I. Optimized Sample Preparation Workflow for Improved Identification of Ghost Proteins. Anal Chem 2019; 92:1122-1129. [PMID: 31829555 DOI: 10.1021/acs.analchem.9b04188] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Large scale proteomic strategies rely on database interrogation. Thus, only referenced proteins can be identified. Recently, Alternative Proteins (AltProts) translated from nonannotated Alternative Open reading frame (AltORFs) were discovered using customized databases. Because of their small size which confers them peptide-like physicochemical properties, they are more difficult to detect using standard proteomics strategies. In this study, we tested different preparation workflows for improving the identification of AltProts in NCH82 human glioma cell line. The highest number of identified AltProts was achieved with RIPA buffer or boiling water extraction followed by acetic acid precipitation.
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Affiliation(s)
- Tristan Cardon
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France
| | - Flore Hervé
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France
| | - Vivian Delcourt
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France.,Department of Biochemistry , Université de Sherbrooke , Quebec , Sherbrooke , Canada
| | - Xavier Roucou
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France.,Department of Biochemistry , Université de Sherbrooke , Quebec , Sherbrooke , Canada
| | - Michel Salzet
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France.,Institut Universitaire de France (IUF) , Paris , France
| | - Julien Franck
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France
| | - Isabelle Fournier
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM) , Université de Lille , F-59000 Lille , France.,Institut Universitaire de France (IUF) , Paris , France
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31
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Cardon T, Salzet M, Franck J, Fournier I. Nuclei of HeLa cells interactomes unravel a network of ghost proteins involved in proteins translation. Biochim Biophys Acta Gen Subj 2019; 1863:1458-1470. [PMID: 31128158 DOI: 10.1016/j.bbagen.2019.05.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 04/18/2019] [Accepted: 05/14/2019] [Indexed: 11/29/2022]
Abstract
Ghost proteins are issued from alternative Open Reading Frames (ORFs) and are missing a genome annotation. Indeed, historical filters applied for the detection of putative translated ORFs led to a wrong classification of transcripts considered as non-coding although translated proteins can be detected by proteomics. This Ghost (also called Alternative) proteome was neglected, and one major issue is to identify the implication of the Ghost proteins in the biological processes. In this context, we aimed to identify the protein-protein interactions (PPIs) of the Ghost proteins. For that, we re-explored a cross-link MS study performed on nuclei of HeLa cells using cross-linking mass spectrometry (XL-MS) associated with the HaltOrf database. Among 1679 cross-link interactions identified, 292 are involving Ghost Proteins. Forty-Four of these Ghost proteins are found to interact with 7 Reference proteins related to ribonucleoproteins, ribosome subunits and zinc finger proteins network. We, thus, have focused our attention on the heterotrimer between the RE/poly(U)-binding/degradation factor 1 (AUF1), the Ribosomal protein 10 (RPL10) and AltATAD2. Using I-Tasser software we performed docking models from which we could suggest the attachment of AUF1 on the external part of RPL10 and the interaction of AltATAD2 on the RPL10 region interacting with 5S ribosomal RNA as a mechanism of regulation of the ribosome. Taken together, these results reveal the importance of Ghost Proteins within known protein interaction networks.
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Affiliation(s)
- Tristan Cardon
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France
| | - Michel Salzet
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France.
| | - Julien Franck
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France.
| | - Isabelle Fournier
- Inserm, U1192 - Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France.
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32
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Han J, Permentier H, Bischoff R, Groothuis G, Casini A, Horvatovich P. Imaging of protein distribution in tissues using mass spectrometry: An interdisciplinary challenge. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.12.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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33
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Neagu AN. Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1140:55-98. [PMID: 31347042 DOI: 10.1007/978-3-030-15950-4_4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.
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Affiliation(s)
- Anca-Narcisa Neagu
- Laboratory of Animal Histology, Faculty of Biology, "Alexandru Ioan Cuza" University of Iasi, Iasi, Romania.
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34
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Orlando E, Aebersold R. On the contribution of mass spectrometry-based platforms to the field of personalized oncology. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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35
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Barré FPY, Claes BSR, Dewez F, Peutz-Kootstra C, Munch-Petersen HF, Grønbæk K, Lund AH, Heeren RMA, Côme C, Cillero-Pastor B. Specific Lipid and Metabolic Profiles of R-CHOP-Resistant Diffuse Large B-Cell Lymphoma Elucidated by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging and in Vivo Imaging. Anal Chem 2018; 90:14198-14206. [PMID: 30422637 PMCID: PMC6328237 DOI: 10.1021/acs.analchem.8b02910] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
![]()
Diffuse
large B-cell lymphoma (DLBCL) is the most common B-cell
non-Hodgkin lymphoma. To treat this aggressive disease, R-CHOP, a
combination of immunotherapy (R; rituximab) and chemotherapy (CHOP;
cyclophosphamide, doxorubicin, vincristine, and prednisone), remains
the most commonly used regimen for newly diagnosed DLBCLs. However,
up to one-third of patients ultimately becomes refractory to initial
therapy or relapses after treatment, and the high mortality rate highlights
the urgent need for novel therapeutic approaches based upon selective
molecular targets. In order to understand the molecular mechanisms
underlying relapsed DLBCL, we studied differences in the lipid and
metabolic composition of nontreated and R-CHOP-resistant tumors, using
a combination of in vivo DLBCL xenograft models and mass spectrometry
imaging. Together, these techniques provide information regarding
analyte composition and molecular distributions of therapy-resistant
and sensitive areas. We found specific lipid and metabolic profiles
for R-CHOP-resistant tumors, such as a higher presence of phosphatidylinositol
and sphingomyelin fragments. In addition, we investigated intratumor
heterogeneity and identified specific lipid markers of viable and
necrotic areas. Furthermore, we could monitor metabolic changes and
found reduced adenosine triphosphate and increased adenosine monophosphate
in the R-CHOP-resistant tumors. This work highlights the power of
combining in vivo imaging and MSI to track molecular signatures in
DLBCL, which has potential application for other diseases.
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Affiliation(s)
- Florian P Y Barré
- The Maastricht Multimodal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry , Maastricht University , 6229 ER Maastricht , The Netherlands
| | - Britt S R Claes
- The Maastricht Multimodal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry , Maastricht University , 6229 ER Maastricht , The Netherlands
| | - Frédéric Dewez
- The Maastricht Multimodal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry , Maastricht University , 6229 ER Maastricht , The Netherlands
| | - Carine Peutz-Kootstra
- Department of Pathology , Maastricht University Medical Center, Cardiovascular Research Institute Maastricht , 6229 HX Maastricht , The Netherlands
| | - Helga F Munch-Petersen
- Department of Haematology and Department of Pathology , Rigshospitalet , 2100 Copenhagen , Denmark
| | - Kirsten Grønbæk
- Epigenomlaboratoriet, Rigshospitalet Dept. 3733 , Bartholin Institute , Copenhagen Biocenter, 2200 Copenhagen , Denmark.,Biotech Research and Innovation Centre (BRIC) , University of Copenhagen , 2200 Copenhagen , Denmark
| | - Anders H Lund
- Biotech Research and Innovation Centre (BRIC) , University of Copenhagen , 2200 Copenhagen , Denmark
| | - Ron M A Heeren
- The Maastricht Multimodal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry , Maastricht University , 6229 ER Maastricht , The Netherlands
| | - Christophe Côme
- Epigenomlaboratoriet, Rigshospitalet Dept. 3733 , Bartholin Institute , Copenhagen Biocenter, 2200 Copenhagen , Denmark.,Biotech Research and Innovation Centre (BRIC) , University of Copenhagen , 2200 Copenhagen , Denmark
| | - Berta Cillero-Pastor
- The Maastricht Multimodal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry , Maastricht University , 6229 ER Maastricht , The Netherlands
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36
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Hoffmann F, Umbreit C, Krüger T, Pelzel D, Ernst G, Kniemeyer O, Guntinas-Lichius O, Berndt A, von Eggeling F. Identification of Proteomic Markers in Head and Neck Cancer Using MALDI-MS Imaging, LC-MS/MS, and Immunohistochemistry. Proteomics Clin Appl 2018; 13:e1700173. [PMID: 30411850 DOI: 10.1002/prca.201700173] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 10/29/2018] [Indexed: 12/12/2022]
Abstract
PURPOSE The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. EXPERIMENTAL DESIGN MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC). RESULTS In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. CONCLUSIONS AND CLINICAL RELEVANCE The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.
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Affiliation(s)
- Franziska Hoffmann
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Claudia Umbreit
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.,Institute of Forensic Medicine, Section Pathology, Jena University Hospital, Jena, Germany
| | - Thomas Krüger
- Department of Molecular and Applied Microbiology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany
| | - Daniela Pelzel
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Günther Ernst
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Olaf Kniemeyer
- Department of Molecular and Applied Microbiology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany
| | | | - Alexander Berndt
- Institute of Forensic Medicine, Section Pathology, Jena University Hospital, Jena, Germany
| | - Ferdinand von Eggeling
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.,Institute of Physical Chemistry, Friedrich Schiller University, Jena, Germany
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37
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Swiatly A, Plewa S, Matysiak J, Kokot ZJ. Mass spectrometry-based proteomics techniques and their application in ovarian cancer research. J Ovarian Res 2018; 11:88. [PMID: 30270814 PMCID: PMC6166298 DOI: 10.1186/s13048-018-0460-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 09/20/2018] [Indexed: 12/26/2022] Open
Abstract
Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008-2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. Main difficulties concern both complexity and heterogeneity of ovarian cancer and drawbacks of the mass spectrometry strategies. This review summarizes challenges, capabilities, and promises of the mass spectrometry-based proteomics techniques in ovarian cancer management.
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Affiliation(s)
- Agata Swiatly
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
| | - Szymon Plewa
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
| | - Zenon J. Kokot
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
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38
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Interplay between human nucleolar GNL1 and RPS20 is critical to modulate cell proliferation. Sci Rep 2018; 8:11421. [PMID: 30061673 PMCID: PMC6065441 DOI: 10.1038/s41598-018-29802-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 07/13/2018] [Indexed: 12/29/2022] Open
Abstract
Human Guanine nucleotide binding protein like 1 (GNL1) belongs to HSR1_MMR1 subfamily of nucleolar GTPases. Here, we report for the first time that GNL1 promotes cell cycle and proliferation by inducing hyperphosphorylation of retinoblastoma protein. Using yeast two-hybrid screening, Ribosomal protein S20 (RPS20) was identified as a functional interacting partner of GNL1. Results from GST pull-down and co-immunoprecipitation assays confirmed that interaction between GNL1 and RPS20 was specific. Further, GNL1 induced cell proliferation was altered upon knockdown of RPS20 suggesting its critical role in GNL1 function. Interestingly, cell proliferation was significantly impaired upon expression of RPS20 interaction deficient GNL1 mutant suggest that GNL1 interaction with RPS20 is critical for cell growth. Finally, the inverse correlation of GNL1 and RPS20 expression in primary colon and gastric cancers with patient survival strengthen their critical importance during tumorigenesis. Collectively, our data provided evidence that cross-talk between GNL1 and RPS20 is critical to promote cell proliferation.
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39
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Garza KY, Feider CL, Klein DR, Rosenberg JA, Brodbelt JS, Eberlin LS. Desorption Electrospray Ionization Mass Spectrometry Imaging of Proteins Directly from Biological Tissue Sections. Anal Chem 2018; 90:7785-7789. [PMID: 29800516 DOI: 10.1021/acs.analchem.8b00967] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Analysis of large biomolecules including proteins has proven challenging using ambient ionization mass spectrometry imaging techniques. Here, we have successfully optimized desorption electrospray ionization mass spectrometry (DESI-MS) to detect intact proteins directly from tissue sections and further integrated DESI-MS to a high field asymmetric waveform ion mobility (FAIMS) device for protein imaging. Optimized DESI-FAIMS-MS parameters were used to image mouse kidney, mouse brain, and human ovarian and breast tissue samples, allowing detection of 11, 16, 14, and 16 proteoforms, respectively. Identification of protein species detected by DESI-MS was performed on-tissue by top-down ultraviolet photodissociation (UVPD) and collision induced dissociation (CID) as well as using tissue extracts by bottom-up CID and top-down UVPD. Our results demonstrate that DESI-MS imaging is suitable for the analysis of the distribution of proteins within biological tissue sections.
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Affiliation(s)
- Kyana Y Garza
- Department of Chemistry , The University of Texas at Austin , Austin , Texas 78712 , United States
| | - Clara L Feider
- Department of Chemistry , The University of Texas at Austin , Austin , Texas 78712 , United States
| | - Dustin R Klein
- Department of Chemistry , The University of Texas at Austin , Austin , Texas 78712 , United States
| | - Jake A Rosenberg
- Department of Chemistry , The University of Texas at Austin , Austin , Texas 78712 , United States
| | - Jennifer S Brodbelt
- Department of Chemistry , The University of Texas at Austin , Austin , Texas 78712 , United States
| | - Livia S Eberlin
- Department of Chemistry , The University of Texas at Austin , Austin , Texas 78712 , United States
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40
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Xia L, Tan S, Zhou Y, Lin J, Wang H, Oyang L, Tian Y, Liu L, Su M, Wang H, Cao D, Liao Q. Role of the NFκB-signaling pathway in cancer. Onco Targets Ther 2018; 11:2063-2073. [PMID: 29695914 PMCID: PMC5905465 DOI: 10.2147/ott.s161109] [Citation(s) in RCA: 270] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Cancer is a group of cells that malignantly grow and proliferate uncontrollably. At present, treatment modes for cancer mainly comprise surgery, chemotherapy, radiotherapy, molecularly targeted therapy, gene therapy, and immunotherapy. However, the curative effects of these treatments have been limited thus far by specific characteristics of tumors. Abnormal activation of signaling pathways is involved in tumor pathogenesis and plays critical roles in growth, progression, and relapse of cancers. Targeted therapies against effectors in oncogenic signaling have improved the outcomes of cancer patients. NFκB is an important signaling pathway involved in pathogenesis and treatment of cancers. Excessive activation of the NFκB-signaling pathway has been documented in various tumor tissues, and studies on this signaling pathway for targeted cancer therapy have become a hot topic. In this review, we update current understanding of the NFκB-signaling pathway in cancer.
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Affiliation(s)
- Longzheng Xia
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Shiming Tan
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Yujuan Zhou
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Jingguan Lin
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Heran Wang
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Linda Oyang
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Yutong Tian
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Lu Liu
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Min Su
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Hui Wang
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
| | - Deliang Cao
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
- Department of Medical Microbiology, Immunology, and Cell Biology, Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, USA
| | - Qianjin Liao
- Hunan Key Laboratory of Translational Radiation Oncology, Hunan Cancer Hospital and Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha, Hunan, China
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