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Fröhlich K, Fahrner M, Brombacher E, Seredynska A, Maldacker M, Kreutz C, Schmidt A, Schilling O. Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics. Mol Cell Proteomics 2024:100800. [PMID: 38880244 DOI: 10.1016/j.mcpro.2024.100800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 06/08/2024] [Accepted: 06/13/2024] [Indexed: 06/18/2024] Open
Abstract
Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.
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Affiliation(s)
- Klemens Fröhlich
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| | - Eva Brombacher
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Adrianna Seredynska
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Maximilian Maldacker
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Clemens Kreutz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Germany
| | - Alexander Schmidt
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
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2
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Dressler FF, Diedrichs F, Sabtan D, Hinrichs S, Krisp C, Gemoll T, Hennig M, Mackedanz P, Schlotfeldt M, Voß H, Offermann A, Kirfel J, Roesch MC, Struck JP, Kramer MW, Merseburger AS, Gratzke C, Schoeb DS, Miernik A, Schlüter H, Wetterauer U, Zubarev R, Perner S, Wolf P, Végvári Á. Proteomic analysis of the urothelial cancer landscape. Nat Commun 2024; 15:4513. [PMID: 38802361 PMCID: PMC11130393 DOI: 10.1038/s41467-024-48096-5] [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: 09/02/2023] [Accepted: 04/22/2024] [Indexed: 05/29/2024] Open
Abstract
Urothelial bladder cancer (UC) has a wide tumor biological spectrum with challenging prognostic stratification and relevant therapy-associated morbidity. Most molecular classifications relate only indirectly to the therapeutically relevant protein level. We improve the pre-analytics of clinical samples for proteome analyses and characterize a cohort of 434 samples with 242 tumors and 192 paired normal mucosae covering the full range of UC. We evaluate sample-wise tumor specificity and rank biomarkers by target relevance. We identify robust proteomic subtypes with prognostic information independent from histopathological groups. In silico drug prediction suggests efficacy of several compounds hitherto not in clinical use. Both in silico and in vitro data indicate predictive value of the proteomic clusters for these drugs. We underline that proteomics is relevant for personalized oncology and provide abundance and tumor specificity data for a large part of the UC proteome ( www.cancerproteins.org ).
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Affiliation(s)
- Franz F Dressler
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
| | - Falk Diedrichs
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Deema Sabtan
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Sofie Hinrichs
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Christoph Krisp
- Section Mass Spectrometry and Proteomics, Campus Forschung N27 00.008, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Timo Gemoll
- Section for Translational Surgical Oncology and Biobanking, Department of Surgery, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Martin Hennig
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Paulina Mackedanz
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Mareile Schlotfeldt
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Hannah Voß
- Section Mass Spectrometry and Proteomics, Campus Forschung N27 00.008, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Anne Offermann
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Jutta Kirfel
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Marie C Roesch
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Julian P Struck
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Department of Urology, Faculty of Health Sciences Brandenburg, Brandenburg Medical School Theodor Fontane, Brandenburg, Germany
| | - Mario W Kramer
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Axel S Merseburger
- Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Christian Gratzke
- Department of Urology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dominik S Schoeb
- Department of Urology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Arkadiusz Miernik
- Department of Urology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Hartmut Schlüter
- Section Mass Spectrometry and Proteomics, Campus Forschung N27 00.008, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ulrich Wetterauer
- Department of Urology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Medicine, Faculty of Medicine and Dentistry, Danube Private University, 3500, Krems, Austria
| | - Roman Zubarev
- Division of Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- The National Medical Research Center for Endocrinology, Moscow, Russia
- Department of Pharmacological & Technological Chemistry, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Sven Perner
- Institute of Pathology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Institute of Pathology, Research Center Borstel, Leibniz Lung Center, Borstel, Germany
- Center for Precision Oncology, Tuebingen, Germany
| | - Philipp Wolf
- Department of Urology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ákos Végvári
- Division of Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
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Dabaj I, Ducatez F, Marret S, Bekri S, Tebani A. Neuromuscular disorders in the omics era. Clin Chim Acta 2024; 553:117691. [PMID: 38081447 DOI: 10.1016/j.cca.2023.117691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/30/2023] [Accepted: 12/02/2023] [Indexed: 12/18/2023]
Abstract
Neuromuscular disorders encompass a spectrum of conditions characterized by primary lesions within the peripheral nervous system, which include the anterior horn cell, peripheral nerve, neuromuscular junction, and muscle. In pediatrics, most of these disorders are linked to genetic causes. Despite the considerable progress, the diagnosis of these disorders remains a challenging due to wide clinical presentation, disease heterogeneity and rarity. It is noteworthy that certain neuromuscular disorders, once deemed untreatable, can now be effectively managed through novel therapies. Biomarkers emerge as indispensable tools, serving as objective measures that not only refine diagnostic accuracy but also provide guidance for therapeutic decision-making and the ongoing monitoring of long-term outcomes. Herein a comprehensive review of biomarkers in neuromuscular disorders is provided. We highlight the role of omics-based technologies that further characterize neuromuscular pathophysiology as well as identify potential therapeutic targets to guide treatment strategies.
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Affiliation(s)
- Ivana Dabaj
- Normandie Univ, UNIROUEN, INSERM U1245, Nord/Est/Ile de France Neuromuscular Reference Center CHU Rouen, Department of Neonatalogy, Pediatric Intensive Care, and Neuropediatrics, F-76000 Rouen, France.
| | - Franklin Ducatez
- Normandie Univ, UNIROUEN, INSERM U1245, Nord/Est/Ile de France Neuromuscular Reference Center CHU Rouen, Department of Neonatalogy, Pediatric Intensive Care, and Neuropediatrics, F-76000 Rouen, France
| | - Stéphane Marret
- Normandie Univ, UNIROUEN, INSERM U1245, Nord/Est/Ile de France Neuromuscular Reference Center CHU Rouen, Department of Neonatalogy, Pediatric Intensive Care, and Neuropediatrics, F-76000 Rouen, France
| | - Soumeya Bekri
- Normandie Univ, UNIROUEN, INSERM U1245, CHU Rouen, Department of Metabolic Biochemistry, F-76000 Rouen, France
| | - Abdellah Tebani
- Normandie Univ, UNIROUEN, INSERM U1245, CHU Rouen, Department of Metabolic Biochemistry, F-76000 Rouen, France
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4
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Werner T, Fahrner M, Schilling O. Using proteomics for stratification and risk prediction in patients with solid tumors. PATHOLOGIE (HEIDELBERG, GERMANY) 2023; 44:176-182. [PMID: 37999758 DOI: 10.1007/s00292-023-01261-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/19/2023] [Indexed: 11/25/2023]
Abstract
Proteomics, the study of proteins and their functions, has greatly evolved due to advances in analytical chemistry and computational biology. Unlike genomics or transcriptomics, proteomics captures the dynamic and diverse nature of proteins, which play crucial roles in cellular processes. This is exemplified in cancer, where genomic and transcriptomic information often falls short in reflecting actual protein expression and interactions. Liquid chromatography-mass spectrometry (LC-MS) is pivotal in proteomic data generation, enabling high-throughput analysis of protein samples. The MS-based workflow involves protein digestion, chromatographic separation, ionization, and fragmentation, leading to peptide identification and quantification. Computational biostatistics, particularly using tools in R (R Foundation for Statistical Computing, Vienna, Austria; www.R-project.org ), aid in data analysis, revealing protein expression patterns and correlations with clinical variables. Proteomic studies can be explorative, aiming to characterize entire proteomes, or targeted, focusing on specific proteins of interest. The integration of proteomics with genomics addresses database limitations and enhances peptide identification. Case studies in intrahepatic cholangiocarcinoma, glioblastoma multiforme, and pancreatic ductal adenocarcinoma highlight proteomics' clinical applications, from subtyping cancers to identifying diagnostic markers. Moreover, proteomic data augment molecular tumor boards by providing deeper insights into pathway activities and genomic mutations, supporting personalized treatment decisions. Overall, proteomics contributes significantly to advancing our understanding of cellular biology and improving clinical care.
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Affiliation(s)
- Tilman Werner
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Centre Freiburg, University of Freiburg, Breisacher Str. 115a, 79106, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
| | - Matthias Fahrner
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Centre Freiburg, University of Freiburg, Breisacher Str. 115a, 79106, Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| | - Oliver Schilling
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Centre Freiburg, University of Freiburg, Breisacher Str. 115a, 79106, Freiburg, Germany.
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany.
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Mundt F, Albrechtsen NJW, Mann SP, Treit P, Ghodgaonkar-Steger M, O’Flaherty M, Raijmakers R, Vizcaíno JA, Heck AJ, Mann M. Foresight in clinical proteomics: current status, ethical considerations, and future perspectives. OPEN RESEARCH EUROPE 2023; 3:59. [PMID: 37645494 PMCID: PMC10446044 DOI: 10.12688/openreseurope.15810.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/26/2023] [Indexed: 08/31/2023]
Abstract
With the advent of robust and high-throughput mass spectrometric technologies and bioinformatics tools to analyze large data sets, proteomics has penetrated broadly into basic and translational life sciences research. More than 95% of FDA-approved drugs currently target proteins, and most diagnostic tests are protein-based. The introduction of proteomics to the clinic, for instance to guide patient stratification and treatment, is already ongoing. Importantly, ethical challenges come with this success, which must also be adequately addressed by the proteomics and medical communities. Consortium members of the H2020 European Union-funded proteomics initiative: European Proteomics Infrastructure Consortium-providing access (EPIC-XS) met at the Core Technologies for Life Sciences (CTLS) conference to discuss the emerging role and implementation of proteomics in the clinic. The discussion, involving leaders in the field, focused on the current status, related challenges, and future efforts required to make proteomics a more mainstream technology for translational and clinical research. Here we report on that discussion and provide an expert update concerning the feasibility of clinical proteomics, the ethical implications of generating and analyzing large-scale proteomics clinical data, and recommendations to ensure both ethical and effective implementation in real-world applications.
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Affiliation(s)
- Filip Mundt
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicolai J. Wewer Albrechtsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, University Hospital, Bispebjerg Hospital, Bispebjerg, Denmark
| | | | - Peter Treit
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
| | | | - Martina O’Flaherty
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Reinout Raijmakers
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Albert J.R. Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
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Birhanu AG. Mass spectrometry-based proteomics as an emerging tool in clinical laboratories. Clin Proteomics 2023; 20:32. [PMID: 37633929 PMCID: PMC10464495 DOI: 10.1186/s12014-023-09424-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 08/03/2023] [Indexed: 08/28/2023] Open
Abstract
Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.
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Lange PF, Schilling O, Huesgen PF. Positional proteomics: is the technology ready to study clinical cohorts? Expert Rev Proteomics 2023; 20:309-318. [PMID: 37869791 DOI: 10.1080/14789450.2023.2272046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/22/2023] [Indexed: 10/24/2023]
Abstract
INTRODUCTION Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.
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Affiliation(s)
- Philipp F Lange
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Michael Cuccione Childhood Cancer Research Program, BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Molecular Oncology, BC Cancer Research Centre, Vancouver, BC, Canada
| | - Oliver Schilling
- Institute of Surgical Pathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Pitter F Huesgen
- Central Institute for Engineering, Electronics and Analytics, ZEA-3, Forschungszentrum Jülich, Jülich, Germany
- Cologne Excellence Cluster on Stress Responses in Ageing-Associated Diseases, CECAD, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
- Institute of Biochemistry, Department for Chemistry, University of Cologne, Cologne, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
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Urachal carcinoma: The journey so far and the road ahead. Pathol Res Pract 2023; 243:154379. [PMID: 36821941 DOI: 10.1016/j.prp.2023.154379] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/15/2023] [Accepted: 02/16/2023] [Indexed: 02/19/2023]
Abstract
Urachal carcinoma, a rare cancer arising from urachus, accounts for about 1% of bladder cancer. The diagnosis at stage I shows about 63% 5-year survival whereas only 8% of the patients at stage IV shows a 5-year survival. Above 90% of urachal carcinomas are adenocarcinomas and most of the urachal carcinoma cases are invasive, showing a high resemblance to adenocarcinoma of various origins, making it hard for a conclusive diagnosis. Even though inconclusive, immunohistochemistry can play a significant role in identifying urachal carcinoma. Most cases show the biomarkers CK20 and CDX2, whereas CK7 and β-catenin are expressed at a lesser frequency. Due to the few cases available, there is a lack of evidence regarding specific markers differentiating urachal carcinoma from colorectal or primary bladder adenocarcinomas. In addition to immunohistochemistry, genomic characterization is emerging to play a role in the classification and treatment of the disease. Urachal carcinoma has been reported to have a molecular level similarity with colorectal malignancies regarding certain gene expressions. The TP53 mutations inactivating the tumor suppressor can probably be explored as a possible target in treating urachal carcinoma. Additionally, certain targets identified in gastric and breast cancer along with anti-HER2 treatment strategies can be explored. Immuno-oncology utilizes immune checkpoint inhibitors for the treatment of MSI-H tumors whereas a combination of tyrosine kinase inhibitors along with immune checkpoint inhibitors are being studied to treat MSI stable tumors. The article is an in-depth overview of urachal carcinoma addressing the current landscape with an emphasis on the future scenario.
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A knowledge graph to interpret clinical proteomics data. Nat Biotechnol 2022; 40:692-702. [PMID: 35102292 PMCID: PMC9110295 DOI: 10.1038/s41587-021-01145-6] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 11/01/2021] [Indexed: 12/14/2022]
Abstract
Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making. A knowledge graph platform integrates proteomics with other omics data and biomedical databases.
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10
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Morelli AP, Tortelli TC, Mancini MCS, Pavan ICB, Silva LGS, Severino MB, Granato DC, Pestana NF, Ponte LGS, Peruca GF, Pauletti BA, Dos Santos DFG, de Moura LP, Bezerra RMN, Leme AFP, Chammas R, Simabuco FM. STAT3 contributes to cisplatin resistance, modulating EMT markers, and the mTOR signaling in lung adenocarcinoma. Neoplasia 2021; 23:1048-1058. [PMID: 34543857 PMCID: PMC8453219 DOI: 10.1016/j.neo.2021.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 08/10/2021] [Accepted: 08/18/2021] [Indexed: 12/29/2022]
Abstract
Lung cancer is the second leading cause of cancer death worldwide and is strongly associated with cisplatin resistance. The transcription factor signal transducer and activator of transcription 3 (STAT3) is constitutively activated in cancer cells and coordinates critical cellular processes as survival, self-renewal, and inflammation. In several types of cancer, STAT3 controls the development, immunogenicity, and malignant behavior of tumor cells while it dictates the responsiveness to radio- and chemotherapy. It is known that STAT3 phosphorylation at Ser727 by mechanistic target of rapamycin (mTOR) is necessary for its maximal activation, but the crosstalk between STAT3 and mTOR signaling in cisplatin resistance remains elusive. In this study, using a proteomic approach, we revealed important targets and signaling pathways altered in cisplatin-resistant A549 lung adenocarcinoma cells. STAT3 had increased expression in a resistance context, which can be associated with a poor prognosis. STAT3 knockout (SKO) resulted in a decreased mesenchymal phenotype in A549 cells, observed by clonogenic potential and by the expression of epithelial-mesenchymal transition markers. Importantly, SKO cells did not acquire the mTOR pathway overactivation induced by cisplatin resistance. Consistently, SKO cells were more responsive to mTOR inhibition by rapamycin and presented impairment of the feedback activation loop in Akt. Therefore, rapamycin was even more potent in inhibiting the clonogenic potential in SKO cells and sensitized to cisplatin treatment. Mechanistically, STAT3 partially coordinated the cisplatin resistance phenotype via the mTOR pathway in non-small cell lung cancer. Thus, our findings reveal important targets and highlight the significance of the crosstalk between STAT3 and mTOR signaling in cisplatin resistance. The synergic inhibition of STAT3 and mTOR potentially unveil a potential mechanism of synthetic lethality to be explored for human lung cancer treatment.
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Affiliation(s)
- Ana Paula Morelli
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Tharcísio Citrângulo Tortelli
- Centro de Investigação Translacional em Oncologia, Departamento de Radiologia e Oncologia, Faculdade de Medicina da Universidade de São Paulo and Instituto do Câncer do Estado de São Paulo, São Paulo, SP, Brazil
| | - Mariana Camargo Silva Mancini
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Isadora Carolina Betim Pavan
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil; Laboratory of Signaling Mechanisms, School of Pharmaceutical Sciences, State University of Campinas, Campinas, SP, Brazil
| | - Luiz Guilherme Salvino Silva
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Matheus Brandemarte Severino
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Daniela Campos Granato
- Laboratório Nacional de Biociências (LNBio), Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), Campinas, Brazil
| | - Nathalie Fortes Pestana
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Luis Gustavo Saboia Ponte
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Guilherme Francisco Peruca
- Exercise Cell Biology Laboratory, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Bianca Alves Pauletti
- Laboratório Nacional de Biociências (LNBio), Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), Campinas, Brazil
| | | | - Leandro Pereira de Moura
- Exercise Cell Biology Laboratory, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Rosângela Maria Neves Bezerra
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil
| | - Adriana Franco Paes Leme
- Laboratório Nacional de Biociências (LNBio), Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), Campinas, Brazil
| | - Roger Chammas
- Centro de Investigação Translacional em Oncologia, Departamento de Radiologia e Oncologia, Faculdade de Medicina da Universidade de São Paulo and Instituto do Câncer do Estado de São Paulo, São Paulo, SP, Brazil
| | - Fernando Moreira Simabuco
- Multidisciplinary Laboratory of Food and Health, School of Applied Sciences, State University of Campinas, Limeira, SP, Brazil.
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11
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Prakash A, Mahoney KE, Orsburn BC. Cloud Computing Based Immunopeptidomics Utilizing Community Curated Variant Libraries Simplifies and Improves Neo-Antigen Discovery in Metastatic Melanoma. Cancers (Basel) 2021; 13:3754. [PMID: 34359654 PMCID: PMC8345142 DOI: 10.3390/cancers13153754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 11/17/2022] Open
Abstract
Unique peptide neo-antigens presented on the cell surface are attractive targets for researchers in nearly all areas of personalized medicine. Cells presenting peptides with mutated or other non-canonical sequences can be utilized for both targeted therapies and diagnostics. Today's state-of-the-art pipelines utilize complementary proteogenomic approaches where RNA or ribosomal sequencing data helps to create libraries from which tandem mass spectrometry data can be compared. In this study, we present an alternative approach whereby cloud computing is utilized to power neo-antigen searches against community curated databases containing more than 7 million human sequence variants. Using these expansive databases of high-quality sequences as a reference, we reanalyze the original data from two previously reported studies to identify neo-antigen targets in metastatic melanoma. Using our approach, we identify 79 percent of the non-canonical peptides reported by previous genomic analyses of these files. Furthermore, we report 18-fold more non-canonical peptides than previously reported. The novel neo-antigens we report herein can be corroborated by secondary analyses such as high predicted binding affinity, when analyzed by well-established tools such as NetMHC. Finally, we report 738 non-canonical peptides shared by at least five patient samples, and 3258 shared across the two studies. This illustrates the depth of data that is present, but typically missed by lower statistical power proteogenomic approaches. This large list of shared peptides across the two studies, their annotation, non-canonical origin, as well as MS/MS spectra from the two studies are made available on a web portal for community analysis.
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Affiliation(s)
- Amol Prakash
- Optys Tech Corporation, Shrewsbury, MA 01545, USA;
| | - Keira E. Mahoney
- Department of Chemistry, University of Virginia, Charlottesville, VA 22904-4319, USA;
| | - Benjamin C. Orsburn
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
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12
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Ma P, Jia G, Song Z. Monobenzone, a Novel and Potent KDM1A Inhibitor, Suppresses Migration of Gastric Cancer Cells. Front Pharmacol 2021; 12:640949. [PMID: 33935733 PMCID: PMC8084583 DOI: 10.3389/fphar.2021.640949] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 03/19/2021] [Indexed: 12/12/2022] Open
Abstract
Lysine-specific demethylase1 (KDM1A) is generally highly expressed in various cancer tissues, and promotes the initiation and development of cancers via diverse cellular signaling pathways. Therefore, KDM1A is a promising drug target in many cancers, and it is crucial to find effective KDM1A inhibitors, while none of them has entered into market. With the help of compound library, monobenzone, a local depigmentor using as a treating over-pigmentation in clinic, was characterized as an effective KDM1A inhibitor (IC50 = 0.4507 μM), which may competitively inhibit KDM1A reversibly. Further cellular study confirmed that monobenzone could inhibit the proliferation of gastric cancer cell lines MGC-803 and BGC-823 with IC50 as 7.82 ± 0.55 μM and 6.99 ± 0.51 μM, respectively, and erase the substrate of KDM1A, H3K4me1/2 and H3K9 me2, and inhibit the migration of gastric cancer cell by reversing epithelial–mesenchymal transition (EMT). As the structure of monobenzone is very simple and small, this study provides a novel backbone for the further optimization of KDM1A inhibitor and gives monobenzone potential new application.
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Affiliation(s)
- Peizhi Ma
- Department of Pharmacy, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Gang Jia
- Department of Oncology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zhiyu Song
- Department of Pharmacy, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
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13
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Son M, Kim H, Han D, Kim Y, Huh I, Han Y, Hong SM, Kwon W, Kim H, Jang JY, Kim Y. A Clinically Applicable 24-Protein Model for Classifying Risk Subgroups in Pancreatic Ductal Adenocarcinomas using Multiple Reaction Monitoring-Mass Spectrometry. Clin Cancer Res 2021; 27:3370-3382. [PMID: 33593883 DOI: 10.1158/1078-0432.ccr-20-3513] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 01/12/2021] [Accepted: 02/12/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Pancreatic ductal adenocarcinoma (PDAC) subtypes have been identified using various methodologies. However, it is a challenge to develop classification system applicable to routine clinical evaluation. We aimed to identify risk subgroups based on molecular features and develop a classification model that was more suited for clinical applications. EXPERIMENTAL DESIGN We collected whole dissected specimens from 225 patients who underwent surgery at Seoul National University Hospital [Seoul, Republic of Korea (South)], between October 2009 and February 2018. Target proteins with potential relevance to tumor progression or prognosis were quantified with robust quality controls. We used hierarchical clustering analysis to identify risk subgroups. A random forest classification model was developed to predict the identified risk subgroups, and the model was validated using transcriptomic datasets from external cohorts (N = 700), with survival analysis. RESULTS We identified 24 protein features that could classify the four risk subgroups associated with patient outcomes: stable, exocrine-like; activated, and extracellular matrix (ECM) remodeling. The "stable" risk subgroup was characterized by proteins that were associated with differentiation and tumor suppressors. "Exocrine-like" tumors highly expressed pancreatic enzymes. Two high-risk subgroups, "activated" and "ECM remodeling," were enriched in terms such as cell cycle, angiogenesis, immunocompetence, tumor invasion metastasis, and metabolic reprogramming. The classification model that included these features made prognoses with relative accuracy and precision in multiple cohorts. CONCLUSIONS We proposed PDAC risk subgroups and developed a classification model that may potentially be useful for routine clinical implementations, at the individual level. This clinical system may improve the accuracy of risk prediction and treatment guidelines.See related commentary by Thakur and Singh, p. 3272.
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Affiliation(s)
- Minsoo Son
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Hongbeom Kim
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Dohyun Han
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea (South)
| | - Yoseop Kim
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Iksoo Huh
- College of Nursing and Research Institute of Nursing Science, Seoul National University, Seoul, Republic of Korea (South)
| | - Youngmin Han
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Seung-Mo Hong
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (South)
| | - Wooil Kwon
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Haeryoung Kim
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Jin-Young Jang
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South).
| | - Youngsoo Kim
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea (South).
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14
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Ngo B, Kim E, Osorio-Vasquez V, Doll S, Bustraan S, Liang RJ, Luengo A, Davidson SM, Ali A, Ferraro GB, Fischer GM, Eskandari R, Kang DS, Ni J, Plasger A, Rajasekhar VK, Kastenhuber ER, Bacha S, Sriram RK, Stein BD, Bakhoum SF, Snuderl M, Cotzia P, Healey JH, Mainolfi N, Suri V, Friedman A, Manfredi M, Sabatini DM, Jones DR, Yu M, Zhao JJ, Jain RK, Keshari KR, Davies MA, Vander Heiden MG, Hernando E, Mann M, Cantley LC, Pacold ME. Limited Environmental Serine and Glycine Confer Brain Metastasis Sensitivity to PHGDH Inhibition. Cancer Discov 2020; 10:1352-1373. [PMID: 32571778 PMCID: PMC7483776 DOI: 10.1158/2159-8290.cd-19-1228] [Citation(s) in RCA: 142] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 04/15/2020] [Accepted: 06/17/2020] [Indexed: 12/19/2022]
Abstract
A hallmark of metastasis is the adaptation of tumor cells to new environments. Metabolic constraints imposed by the serine and glycine-limited brain environment restrict metastatic tumor growth. How brain metastases overcome these growth-prohibitive conditions is poorly understood. Here, we demonstrate that 3-phosphoglycerate dehydrogenase (PHGDH), which catalyzes the rate-limiting step of glucose-derived serine synthesis, is a major determinant of brain metastasis in multiple human cancer types and preclinical models. Enhanced serine synthesis proved important for nucleotide production and cell proliferation in highly aggressive brain metastatic cells. In vivo, genetic suppression and pharmacologic inhibition of PHGDH attenuated brain metastasis, but not extracranial tumor growth, and improved overall survival in mice. These results reveal that extracellular amino acid availability determines serine synthesis pathway dependence, and suggest that PHGDH inhibitors may be useful in the treatment of brain metastasis. SIGNIFICANCE: Using proteomics, metabolomics, and multiple brain metastasis models, we demonstrate that the nutrient-limited environment of the brain potentiates brain metastasis susceptibility to serine synthesis inhibition. These findings underscore the importance of studying cancer metabolism in physiologically relevant contexts, and provide a rationale for using PHGDH inhibitors to treat brain metastasis.This article is highlighted in the In This Issue feature, p. 1241.
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Affiliation(s)
- Bryan Ngo
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Eugenie Kim
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
| | - Victoria Osorio-Vasquez
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
| | - Sophia Doll
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Sophia Bustraan
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
| | - Roger J Liang
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Alba Luengo
- Koch Institute for Integrative Cancer Research, Cambridge, Massachusetts
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Shawn M Davidson
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey
| | - Ahmed Ali
- Koch Institute for Integrative Cancer Research, Cambridge, Massachusetts
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Gino B Ferraro
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Grant M Fischer
- Departments of Translational Molecular Pathology, Melanoma Medical Oncology, Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Roozbeh Eskandari
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Diane S Kang
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California Norris Comprehensive Cancer Center, Keck School of Medicine, Los Angeles, California
| | - Jing Ni
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Ariana Plasger
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | | | - Edward R Kastenhuber
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Sarah Bacha
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Roshan K Sriram
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Benjamin D Stein
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Samuel F Bakhoum
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Matija Snuderl
- Department of Pathology, New York University Langone Health, New York, New York
| | - Paolo Cotzia
- Department of Pathology, New York University Langone Health, New York, New York
| | - John H Healey
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - Vipin Suri
- Raze Therapeutics, Cambridge, Massachusetts
| | | | | | - David M Sabatini
- Whitehead Institute for Biomedical Research, Cambridge, Massachusetts
- Howard Hughes Medical Institute, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Broad Institute, Cambridge, Massachusetts
| | - Drew R Jones
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
- Metabolomics Core Resource Laboratory, NYU Langone Health, New York, New York
| | - Min Yu
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jean J Zhao
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
- Broad Institute, Cambridge, Massachusetts
| | - Rakesh K Jain
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Kayvan R Keshari
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michael A Davies
- Departments of Translational Molecular Pathology, Melanoma Medical Oncology, Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Matthew G Vander Heiden
- Koch Institute for Integrative Cancer Research, Cambridge, Massachusetts
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute, Cambridge, Massachusetts
| | - Eva Hernando
- Department of Pathology, New York University Langone Health, New York, New York
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
- Faculty of Health and Medical Sciences, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Lewis C Cantley
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York.
| | - Michael E Pacold
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York.
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15
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Mäkelä R, Arjonen A, Härmä V, Rintanen N, Paasonen L, Paprotka T, Rönsch K, Kuopio T, Kononen J, Rantala JK. Ex vivo modelling of drug efficacy in a rare metastatic urachal carcinoma. BMC Cancer 2020; 20:590. [PMID: 32576176 PMCID: PMC7313172 DOI: 10.1186/s12885-020-07092-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 06/19/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Ex vivo drug screening refers to the out-of-body assessment of drug efficacy in patient derived vital tumor cells. The purpose of these methods is to enable functional testing of patient specific efficacy of anti-cancer therapeutics and personalized treatment strategies. Such approaches could prove powerful especially in context of rare cancers for which demonstration of novel therapies is difficult due to the low numbers of patients. Here, we report comparison of different ex vivo drug screening methods in a metastatic urachal adenocarcinoma, a rare and aggressive non-urothelial bladder malignancy that arises from the remnant embryologic urachus in adults. METHODS To compare the feasibility and results obtained with alternative ex vivo drug screening techniques, we used three different approaches; enzymatic cell viability assay of 2D cell cultures and image-based cytometry of 2D and 3D cell cultures in parallel. Vital tumor cells isolated from a biopsy obtained in context of a surgical debulking procedure were used for screening of 1160 drugs with the aim to evaluate patterns of efficacy in the urachal cancer cells. RESULTS Dose response data from the enzymatic cell viability assay and the image-based assay of 2D cell cultures showed the best consistency. With 3D cell culture conditions, the proliferation rate of the tumor cells was slower and potency of several drugs was reduced even following growth rate normalization of the responses. MEK, mTOR, and MET inhibitors were identified as the most cytotoxic targeted drugs. Secondary validation analyses confirmed the efficacy of these drugs also with the new human urachal adenocarcinoma cell line (MISB18) established from the patient's tumor. CONCLUSIONS All the tested ex vivo drug screening methods captured the patient's tumor cells' sensitivity to drugs that could be associated with the oncogenic KRASG12V mutation found in the patient's tumor cells. Specific drug classes however resulted in differential dose response profiles dependent on the used cell culture method indicating that the choice of assay could bias results from ex vivo drug screening assays for selected drug classes.
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Affiliation(s)
- Rami Mäkelä
- Misvik Biology Ltd, Karjakatu 35 B, FI-20520, Turku, Finland
| | - Antti Arjonen
- Misvik Biology Ltd, Karjakatu 35 B, FI-20520, Turku, Finland.,Brinter Ltd, Turku, Finland
| | - Ville Härmä
- Misvik Biology Ltd, Karjakatu 35 B, FI-20520, Turku, Finland.,University of Sheffield, Sheffield, UK
| | - Nina Rintanen
- Central Finland Health Care District, Jyväskylä, Finland
| | | | - Tobias Paprotka
- Eurofins Genomics Europe Sequencing GmbH, Constance, Germany
| | - Kerstin Rönsch
- Eurofins Genomics Europe Sequencing GmbH, Constance, Germany
| | - Teijo Kuopio
- Central Finland Health Care District, Jyväskylä, Finland
| | - Juha Kononen
- Central Finland Health Care District, Jyväskylä, Finland.,Docrates Hospital, Helsinki, Finland
| | - Juha K Rantala
- Misvik Biology Ltd, Karjakatu 35 B, FI-20520, Turku, Finland. .,University of Sheffield, Sheffield, UK.
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16
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Chen J, Zhao J, Ding J, Wang Z, Du J, Wu C. Knocking down LSD1 inhibits the stemness features of colorectal cancer stem cells. ACTA ACUST UNITED AC 2020; 53:e9230. [PMID: 32520208 PMCID: PMC7279696 DOI: 10.1590/1414-431x20209230] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 01/29/2020] [Indexed: 12/12/2022]
Abstract
As a top leading cause of cancer death in many countries, colorectal cancer (CRC) has drawn increasing attention to the study of the pathological mechanism. According to the “cancer stem cell hypothesis”, malignancies originate from a small fraction of cancer cells that show self-renewal properties to initiate and sustain tumor growth and tumor metastasis. Therefore, these cancer stem cells (CSC) probably play important roles in tumor recurrence, metastasis, and drug resistance. Previous research reported that lysine-specific histone demethylase 1 (LSD1) maintains cancer stemness through up-regulating stemness markers SOX2 and OCT4. CD133 is believed to be the most robust surface marker for CRC stem cells, however the regulatory effect of LSD1 on stemness of CD133+ CRC has never been reported. In this study, our objectives included: 1) to isolate pure CD133+ and CD133− cells from SW620 cell line; 2) to investigate the effect of LSD1 on the characteristics of CD133+ stem cancer cells by knocking down the target gene. Results suggested that the SW620 cell line had both CD133+ and CD133− subsets. The CD133+ subset exhibited more CSC-like characteristics compared with the CD133− subset with higher viability, colony formation rate, migration and invasion rate, resistance to anti-cancer drugs, and apoptosis in vitro. The CD133+ also induced faster tumor formation and larger tumors in vivo. In the LSD1-knockdown CD133+ cells, the CSC-like characteristics had been all weakened. We conclude that LSD1 was important for CSCs to maintain their “stemness” features, which could be a potential therapeutic target of CRC.
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Affiliation(s)
- J Chen
- Department of Gastrointestinal Surgery, Guizhou Provincial Bijie City Qixingguan District People's Hospital, Bijie, China
| | - Jianyong Zhao
- Department of Gastrointestinal Surgery, Guizhou Provincial Staff Hospital, Guiyang, China
| | - J Ding
- Department of Gastrointestinal Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Ziwei Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiyi Du
- Department of Gastrointestinal Surgery, The First People's Hospital of Guiyang, Guiyang, China
| | - Chenchang Wu
- Department of Gastrointestinal Surgery, Guizhou Provincial Bijie City Qixingguan District People's Hospital, Bijie, China
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17
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Macklin A, Khan S, Kislinger T. Recent advances in mass spectrometry based clinical proteomics: applications to cancer research. Clin Proteomics 2020; 17:17. [PMID: 32489335 PMCID: PMC7247207 DOI: 10.1186/s12014-020-09283-w] [Citation(s) in RCA: 150] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 05/15/2020] [Indexed: 02/07/2023] Open
Abstract
Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.
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Affiliation(s)
- Andrew Macklin
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Shahbaz Khan
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Thomas Kislinger
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
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18
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Szilagyi GT, Nawrocki AM, Eros K, Schmidt J, Fekete K, Elkjaer ML, Hyrlov KH, Larsen MR, Illes Z, Gallyas F. Proteomic changes during experimental de- and remyelination in the corpus callosum. PLoS One 2020; 15:e0230249. [PMID: 32272486 PMCID: PMC7145428 DOI: 10.1371/journal.pone.0230249] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 02/25/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND In the cuprizone model of multiple sclerosis, de- and remyelination can be studied without major interference from the adaptive immune responses. Since previous proteomic studies did not focus on the corpus callosum, where cuprizone causes the most pronounced demyelination, we performed a bottom up proteomic analysis on this brain region. METHODS Eight week-old mice treated with 0.2% cuprizone, for 4 weeks and controls (C) were sacrificed after termination of the treatment (4wD), and 2 (2dR) or 14 (2wR) days later. Homogenates of dissected corpus callosum were analysed by quantitative proteomics. For data processing, clustering, gene ontology analysis, and regulatory network prediction, we used Perseus, PANTHER and Ingenuity Pathway Analysis softwares, respectively. RESULTS We identified 4886 unmodified, single- or multi phosphorylated and/or gycosylated (PTM) proteins. Out of them, 191 proteins were differentially regulated in at least one experimental group. We found 57 proteins specific for demyelination, 27 for early- and 57 for late remyelinationwhile 36 proteins were affected in two, and 23 proteins in all three groups. Phosphorylation represented 92% of the post translational modifications among differentially regulated modified (PTM) proteins with decreased level, while it was only 30% of the PTM proteins with increased level. Gene ontology analysis could not classify the demyelination specific proteins into any biological process category, while allocated the remyelination specific ones to nervous system development and myelination as the most specific subcategory. We also identified a protein network in experimental remyelination, and the gene orthologues of the network were differentially expressed in remyelinating multiple sclerosis brain lesions consistent with an early remyelination pattern. CONCLUSION Proteomic analysis seems more informative for remyelination than demyelination in the cuprizone model.
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Affiliation(s)
- Gabor T. Szilagyi
- Department of Biochemistry and Medical Chemistry, University of Pécs Medical School, Pécs, Hungary
| | - Arkadiusz M. Nawrocki
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Krisztian Eros
- Department of Biochemistry and Medical Chemistry, University of Pécs Medical School, Pécs, Hungary
- Szentagothai Research Centre, University of Pécs, Pécs, Hungary
- Nuclear-Mitochondrial Interactions Research Group, Hungarian Academy of Sciences, Budapest, Hungary
| | - Janos Schmidt
- Department of Biochemistry and Medical Chemistry, University of Pécs Medical School, Pécs, Hungary
| | - Katalin Fekete
- Department of Biochemistry and Medical Chemistry, University of Pécs Medical School, Pécs, Hungary
| | - Maria L. Elkjaer
- Department of Neurology, Odense University Hospital, Odense, Denmark
| | - Kirsten H. Hyrlov
- Department of Neurology, Odense University Hospital, Odense, Denmark
| | - Martin R. Larsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Zsolt Illes
- Department of Neurology, Odense University Hospital, Odense, Denmark
- Institute of Clinical Research, BRIDGE University of Southern Denmark, Odense, Denmark
- Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
| | - Ferenc Gallyas
- Department of Biochemistry and Medical Chemistry, University of Pécs Medical School, Pécs, Hungary
- Szentagothai Research Centre, University of Pécs, Pécs, Hungary
- Nuclear-Mitochondrial Interactions Research Group, Hungarian Academy of Sciences, Budapest, Hungary
- * E-mail:
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19
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Herholt A, Galinski S, Geyer PE, Rossner MJ, Wehr MC. Multiparametric Assays for Accelerating Early Drug Discovery. Trends Pharmacol Sci 2020; 41:318-335. [PMID: 32223968 DOI: 10.1016/j.tips.2020.02.005] [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: 12/13/2019] [Revised: 02/21/2020] [Accepted: 02/27/2020] [Indexed: 02/07/2023]
Abstract
Drug discovery campaigns are hampered by substantial attrition rates largely due to a lack of efficacy and safety reasons associated with candidate drugs. This is true in particular for genetically complex diseases, where insufficient knowledge of the modulatory actions of candidate drugs on targets and entire target pathways further adds to the problem of attrition. To better profile compound actions on targets, potential off-targets, and disease-linked pathways, new innovative technologies need to be developed that can elucidate the complex cellular signaling networks in health and disease. Here, we discuss progress in genetically encoded multiparametric assays and mass spectrometry (MS)-based proteomics, which both represent promising toolkits to profile multifactorial actions of drug candidates in disease-relevant cellular systems to promote drug discovery and personalized medicine.
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Affiliation(s)
- Alexander Herholt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany
| | - Sabrina Galinski
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany
| | - Philipp E Geyer
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Planegg, Germany; NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; OmicEra Diagnostics GmbH, Am Klopferspitz 19, 82152, Planegg, Germany
| | - Moritz J Rossner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany
| | - Michael C Wehr
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany.
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Abstract
PURPOSE OF REVIEW The aim of this review is to sum up the state of the art of urachal carcinoma (UC) in order to easily guide clinicians. RECENT FINDINGS UC is a rare and aggressive disease with consequent few data about diagnosis and treatment. Dates are mainly based on retrospective trial and case reports with limited prospective trial. Clinical presentation is not specific, often with urinary symptoms. Diagnosis is mainly based on CT scan and MRI, useful to evaluate local invasion and nodal status and to detect the presence of distant metastases. Therefore, biopsy is needed to obtain histological confirmation. Surgery is the gold standard for localized disease, while different chemotherapy schemes have been used in metastatic setting. Novel findings based on mutational analysis of the tumor include the use of biological treatment, such as cetuximab, and immunotherapy, such as atezolizumab, with satisfactory responses, suggesting that personalized treatment could be the most suitable option for UC.
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Law HCH, Lagundžin D, Clement EJ, Qiao F, Wagner ZS, Krieger KL, Costanzo-Garvey D, Caffrey TC, Grem JL, DiMaio DJ, Grandgenett PM, Cook LM, Fisher KW, Yu F, Hollingsworth MA, Woods NT. The Proteomic Landscape of Pancreatic Ductal Adenocarcinoma Liver Metastases Identifies Molecular Subtypes and Associations with Clinical Response. Clin Cancer Res 2019; 26:1065-1076. [PMID: 31848187 DOI: 10.1158/1078-0432.ccr-19-1496] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 10/19/2019] [Accepted: 12/11/2019] [Indexed: 12/16/2022]
Abstract
PURPOSE Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease that can be separated into distinct subtypes based on molecular signatures. Identifying PDAC subtype-specific therapeutic vulnerabilities is necessary to develop precision medicine approaches to treat PDAC. EXPERIMENTAL DESIGN A total of 56 PDAC liver metastases were obtained from the UNMC Rapid Autopsy Program and analyzed with quantitative proteomics. PDAC subtypes were identified by principal component analysis based on protein expression profiling. Proteomic subtypes were further characterized by the associated clinical information, including but not limited to survival analysis, drug treatment response, and smoking and drinking status. RESULTS Over 3,960 proteins were identified and used to delineate four distinct PDAC microenvironment subtypes: (i) metabolic; (ii) progenitor-like; (iii) proliferative; and (iv) inflammatory. PDAC risk factors of alcohol and tobacco consumption correlate with subtype classifications. Enhanced survival is observed in FOLFIRINOX treated metabolic and progenitor-like subtypes compared with the proliferative and inflammatory subtypes. In addition, TYMP, PDCD6IP, ERAP1, and STMN showed significant association with patient survival in a subtype-specific manner. Gemcitabine-induced alterations in the proteome identify proteins, such as serine hydroxymethyltransferase 1, associated with drug resistance. CONCLUSIONS These data demonstrate that proteomic analysis of clinical PDAC liver metastases can identify molecular signatures unique to disease subtypes and point to opportunities for therapeutic development to improve the treatment of PDAC.
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Affiliation(s)
- Henry C-H Law
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Dragana Lagundžin
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Emalie J Clement
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Fangfang Qiao
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Zachary S Wagner
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Kimiko L Krieger
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Diane Costanzo-Garvey
- Department of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, Omaha Nebraska
| | - Thomas C Caffrey
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Jean L Grem
- Internal Medicine, Division of Hematology Oncology, University of Nebraska Medical Center, Omaha Nebraska
| | - Dominick J DiMaio
- Department of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, Omaha Nebraska
| | - Paul M Grandgenett
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Leah M Cook
- Department of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, Omaha Nebraska
| | - Kurt W Fisher
- Department of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, Omaha Nebraska
| | - Fang Yu
- Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha Nebraska
| | - Michael A Hollingsworth
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska
| | - Nicholas T Woods
- Eppley Institute for Research in Cancer, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska.
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Doll S, Gnad F, Mann M. The Case for Proteomics and Phospho-Proteomics in Personalized Cancer Medicine. Proteomics Clin Appl 2019; 13:e1800113. [PMID: 30790462 PMCID: PMC6519247 DOI: 10.1002/prca.201800113] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 02/01/2019] [Indexed: 02/06/2023]
Abstract
The concept of personalized medicine is predominantly been pursued through genomic and transcriptomic technologies, leading to the identification of multiple mutations in a large variety of cancers. However, it has proven challenging to distinguish driver and passenger mutations and to deal with tumor heterogeneity and resistant clonal populations. More generally, these heterogeneous mutation patterns do not in themselves predict the tumor phenotype. Analysis of the expressed proteins in a tumor and their modification states reveals if and how these mutations are translated to the functional level. It is already known that proteomic changes including posttranslational modifications are crucial drivers of oncogenesis, but proteomics technology has only recently become comparable in depth and accuracy to RNAseq. These advances also allow the rapid and highly sensitive analysis of formalin-fixed and paraffin-embedded biobank tissues, on both the proteome and phosphoproteome levels. In this perspective, pioneering mass spectrometry-based proteomic studies are highlighted that pave the way toward clinical implementation. It is argued that proteomics and phosphoproteomics could provide the missing link to make omics analysis actionable in the clinic.
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Affiliation(s)
- Sophia Doll
- Department of Proteomics and Signal TransductionMax Planck Institute of Biochemistry82152MartinsriedGermany
- NNF Center for Protein ResearchFaculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark
| | - Florian Gnad
- Department of Bioinformatics and Computational BiologyCell Signaling Technology Inc01923DanversMAUSA
| | - Matthias Mann
- Department of Proteomics and Signal TransductionMax Planck Institute of Biochemistry82152MartinsriedGermany
- NNF Center for Protein ResearchFaculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark
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Lorentzian A, Uzozie A, Lange PF. Origins and clinical relevance of proteoforms in pediatric malignancies. Expert Rev Proteomics 2019; 16:185-200. [PMID: 30700156 DOI: 10.1080/14789450.2019.1575206] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Cancer changes the proteome in complex ways that reach well beyond simple changes in protein abundance. Genomic and transcriptional variations and post-translational protein modification create functional variants of a protein, known as proteoforms. Childhood cancers have fewer genomic alterations but show equally dramatic phenotypic changes as malignant cells in adults. Therefore, unraveling the complexities of the proteome is even more important in pediatric malignancies. Areas covered: In this review, the biological origins of proteoforms and technological advancements in the study of proteoforms are discussed. Particular emphasis is given to their implication in childhood malignancies and the critical role of cancer-specific proteoforms for the next generation of cancer therapies and diagnostics. Expert opinion: Recent advancements in technology have led to a better understanding of the underlying mechanisms of tumorigenesis. This has been critical for the development of more effective and less harmful treatments that are based on direct targeting of altered proteins and deregulated pathways. As proteome coverage and the ability to detect complex proteoforms increase, the most need for change is in data compilation and database availability to mediate high-level data analysis and allow for better functional annotation of proteoforms.
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Affiliation(s)
- Amanda Lorentzian
- a Department of Cell and Developmental Biology , University of British Columbia , Vancouver , BC , Canada.,b Michael Cuccione Childhood Cancer Research Program , BC Children's Hospital Research Institute , Vancouver , BC , Canada
| | - Anuli Uzozie
- b Michael Cuccione Childhood Cancer Research Program , BC Children's Hospital Research Institute , Vancouver , BC , Canada.,c Department of Pathology and Laboratory Medicine , University of British Columbia , Vancouver , BC , Canada
| | - Philipp F Lange
- a Department of Cell and Developmental Biology , University of British Columbia , Vancouver , BC , Canada.,b Michael Cuccione Childhood Cancer Research Program , BC Children's Hospital Research Institute , Vancouver , BC , Canada.,c Department of Pathology and Laboratory Medicine , University of British Columbia , Vancouver , BC , Canada
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