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Wenk D, Zuo C, Kislinger T, Sepiashvili L. Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers. Clin Proteomics 2024; 21:6. [PMID: 38287260 PMCID: PMC10826105 DOI: 10.1186/s12014-024-09452-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 01/14/2024] [Indexed: 01/31/2024] Open
Abstract
Routine measurement of cancer biomarkers is performed for early detection, risk classification, and treatment monitoring, among other applications, and has substantially contributed to better clinical outcomes for patients. However, there remains an unmet need for clinically validated assays of cancer protein biomarkers. Protein tumor markers are of particular interest since proteins carry out the majority of biological processes and thus dynamically reflect changes in cancer pathophysiology. Mass spectrometry-based targeted proteomics is a powerful tool for absolute peptide and protein quantification in biological matrices with numerous advantages that make it attractive for clinical applications in oncology. The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) based methodologies has allowed laboratories to overcome challenges associated with immunoassays that are more widely used for tumor marker measurements. Yet, clinical implementation of targeted proteomics methodologies has so far been limited to a few cancer markers. This is due to numerous challenges associated with paucity of robust validation studies of new biomarkers and the labor-intensive and operationally complex nature of LC-MS/MS workflows. The purpose of this review is to provide an overview of targeted proteomics applications in cancer, workflows used in targeted proteomics, and requirements for clinical validation and implementation of targeted proteomics assays. We will also discuss advantages and challenges of targeted MS-based proteomics assays for clinical cancer biomarker analysis and highlight some recent developments that will positively contribute to the implementation of this technique into clinical laboratories.
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Affiliation(s)
- Deborah Wenk
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Charlotte Zuo
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Thomas Kislinger
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
- Princess Margaret Cancer Research Tower, Room 9-807, 101 College Street, Toronto, ON, M5G 1L7, Canada.
| | - Lusia Sepiashvili
- Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, 555 University Ave, Rm 3606, Toronto, ON, M5G 1X8, Canada.
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada.
- Sickkids Research Institute, Toronto, ON, Canada.
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Yang P, Bi Q, Li Y, Liao J, Ding Y, Huang D, Luo X, Huang Y, Yao C, Zhang J, Wei W, Li Z, Meng J, Guo D. Identification of Five Gelatins Based on Marker Peptides from Type I Collagen by Mass Spectrum in Multiple Reaction Monitoring Mode. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:5851-5860. [PMID: 37010496 DOI: 10.1021/acs.jafc.3c00151] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
In this study, a novel pseudo-targeted peptidomics strategy, integrating the transition list generated by an in-house software (Pep-MRMer) and the retention time transfer by high-abundance ion-based retention time calibration (HAI-RT-cal), was developed to screen marker peptides of gelatins from five closely related animal species, including porcine, bovine, horse, mule, and donkey. Five marker peptides were screened from the molecular phenotypic differences of type I collagen. Furthermore, a simple and robust 10 min multiple reaction monitoring (MRM) method was established and performed well in distinguishing different gelatins, particularly in discerning horse-hide gelatin (HHG) and mule-hide gelatin (MHG) from donkey-hide gelatin (DHG). The market investigation revealed the serious adulteration of DHG. Meantime, the pseudo-targeted peptidomics could be used to screen marker peptides of other gelatin foods.
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Affiliation(s)
- Peilei Yang
- Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, People's Republic of China
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Qirui Bi
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Yun Li
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Jingmei Liao
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Yelin Ding
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Dongdong Huang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, People's Republic of China
| | - Xiaoxiao Luo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Yong Huang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Changliang Yao
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Jianqing Zhang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Wenlong Wei
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Zhenwei Li
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
| | - Jiang Meng
- Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, People's Republic of China
| | - Dean Guo
- Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, People's Republic of China
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, People's Republic of China
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Kasahara K, Narumi R, Nagayama S, Masuda K, Esaki T, Obama K, Tomonaga T, Sakai Y, Shimizu Y, Adachi J. A large-scale targeted proteomics of plasma extracellular vesicles shows utility for prognosis prediction subtyping in colorectal cancer. Cancer Med 2022; 12:7616-7626. [PMID: 36394150 PMCID: PMC10067095 DOI: 10.1002/cam4.5442] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/03/2022] [Accepted: 11/02/2022] [Indexed: 11/18/2022] Open
Abstract
PURPOSE The pathogenesis of cancers depends on the molecular background of each individual patient. Therefore, verifying as many biomarkers as possible and clarifying their relationships with each disease status would be very valuable. We performed a large-scale targeted proteomics analysis of plasma extracellular vesicles (EVs) that may affect tumor progression and/or therapeutic resistance. EXPERIMENTAL DESIGN Plasma EVs from 59 were collected patients with colorectal cancer (CRC) and 59 healthy controls (HC) in cohort 1, and 150 patients with CRC in cohort 2 for the large-scale targeted proteomics analysis of 457 proteins as candidate CRC markers. The Mann-Whitney-Wilcoxon test and random forest model were applied in cohort 1 to select promising markers. Consensus clustering was applied to classify patients with CRC in cohort 2. The Kaplan-Meier method and Cox regression analysis were performed to identify potential molecular factors contributing to the overall survival (OS) of patients. RESULTS In the analysis of cohort 1, 99 proteins were associated with CRC. The analysis of cohort 2 revealed two clusters showing significant differences in OS (p = 0.017). Twelve proteins, including alpha-1-acid glycoprotein 1 (ORM1), were suggested to be associated with the identified CRC subtypes, and ORM1 was shown to significantly contribute to OS, suggesting that ORM1 might be one of the factors closely related to the OS. CONCLUSIONS The study identified two novel subtypes of CRC, which exhibit differences in OS, as well as important biomarker proteins that are closely related to the identified subtypes. Liquid biopsy assessment with targeted proteomics analysis was proposed to be crucial for predicting the CRC prognosis.
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Affiliation(s)
- Keiko Kasahara
- Department of SurgeryKyoto University Graduate School of MedicineKyotoJapan
- Laboratory of Proteome ResearchNational Institutes of Biomedical Innovation, Health and NutritionOsakaJapan
- Laboratory of Proteomics for Drug DiscoveryCenter for Drug Design Research, National Institute of Biomedical Innovation, Health and NutritionOsakaJapan
| | - Ryohei Narumi
- Laboratory of Proteome ResearchNational Institutes of Biomedical Innovation, Health and NutritionOsakaJapan
- Laboratory of Proteomics for Drug DiscoveryCenter for Drug Design Research, National Institute of Biomedical Innovation, Health and NutritionOsakaJapan
- Laboratory of Clinical and Analytical ChemistryCollaborative Research Center for Health and Medicine, National Institute of Biomedical Innovation, Health and NutritionOsakaJapan
| | - Satoshi Nagayama
- Department of Gastroenterological SurgeryGastroenterological Center, Cancer Institute Hospital, Japanese Foundation for Cancer ResearchTokyoJapan
- Department of SurgeryUji‐Tokusyukai Medical CenterKyotoJapan
| | - Keiko Masuda
- Laboratory for Cell‐Free Protein SynthesisRIKEN Center for Biosystems Dynamics ResearchOsakaJapan
| | - Tsuyoshi Esaki
- The Center for Data Science Education and ResearchShiga UniversityShigaJapan
| | - Kazutaka Obama
- Department of SurgeryKyoto University Graduate School of MedicineKyotoJapan
| | - Takeshi Tomonaga
- Laboratory of Proteome ResearchNational Institutes of Biomedical Innovation, Health and NutritionOsakaJapan
- Laboratory of Proteomics for Drug DiscoveryCenter for Drug Design Research, National Institute of Biomedical Innovation, Health and NutritionOsakaJapan
| | | | - Yoshihiro Shimizu
- Laboratory for Cell‐Free Protein SynthesisRIKEN Center for Biosystems Dynamics ResearchOsakaJapan
| | - Jun Adachi
- Laboratory of Proteome ResearchNational Institutes of Biomedical Innovation, Health and NutritionOsakaJapan
- Laboratory of Proteomics for Drug DiscoveryCenter for Drug Design Research, National Institute of Biomedical Innovation, Health and NutritionOsakaJapan
- Laboratory of Clinical and Analytical ChemistryCollaborative Research Center for Health and Medicine, National Institute of Biomedical Innovation, Health and NutritionOsakaJapan
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Kulyyassov A, Fresnais M, Longuespée R. Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives. Proteomics 2021; 21:e2100153. [PMID: 34591362 DOI: 10.1002/pmic.202100153] [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: 06/25/2021] [Revised: 09/08/2021] [Accepted: 09/24/2021] [Indexed: 12/25/2022]
Abstract
Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.
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Affiliation(s)
| | - Margaux Fresnais
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Rémi Longuespée
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
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Proteomic approaches to investigate gammaherpesvirus biology and associated tumorigenesis. Adv Virus Res 2020; 109:201-254. [PMID: 33934828 DOI: 10.1016/bs.aivir.2020.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The DNA viruses, Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV), are members of the gammaherpesvirus subfamily, a group of viruses whose infection is associated with multiple malignancies, including cancer. The primary host for these viruses is humans and, like all herpesviruses, infection with these pathogens is lifelong. Due to the persistence of gammaherpesvirus infection and the potential for cancer formation in infected individuals, there is a driving need to understand not only the biology of these viruses and how they remain undetected in host cells but also the mechanism(s) by which tumorigenesis occurs. One of the methods that has provided much insight into these processes is proteomics. Proteomics is the study of all the proteins that are encoded by a genome and allows for (i) identification of existing and novel proteins derived from a given genome, (ii) interrogation of protein-protein interactions within a system, and (iii) discovery of druggable targets for the treatment of malignancies. In this chapter, we explore how proteomics has contributed to our current understanding of gammaherpesvirus biology and their oncogenic processes, as well as the clinical applications of proteomics for the detection and treatment of gammaherpesvirus-associated cancers.
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Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona. Nat Commun 2020; 11:3662. [PMID: 32699280 PMCID: PMC7376165 DOI: 10.1038/s41467-020-17033-7] [Citation(s) in RCA: 170] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 06/02/2020] [Indexed: 02/08/2023] Open
Abstract
Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids. Varying the physicochemical properties of engineered NPs translates to distinct protein corona patterns enabling differential and reproducible interrogation of biological samples, including deep sampling of the plasma proteome. Spike experiments confirm a linear signal response. The median coefficient of variation was 22%. We screened 43 NPs and selected a panel of 5, which detect more than 2,000 proteins from 141 plasma samples using a 96-well automated workflow in a pilot non-small cell lung cancer classification study. Our streamlined workflow combines depth of coverage and throughput with precise quantification based on unique interactions between proteins and NPs engineered for deep and scalable quantitative proteomic studies. Large-scale, unbiased proteomics studies of biological samples like plasma are constrained by the complexity of the proteome. Herein, the authors develop a highly parallel protein quantitation platform leveraging multi nanoparticle protein coronas for deep proteome sampling and biomarker discovery.
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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: 160] [Impact Index Per Article: 40.0] [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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Sobsey CA, Ibrahim S, Richard VR, Gaspar V, Mitsa G, Lacasse V, Zahedi RP, Batist G, Borchers CH. Targeted and Untargeted Proteomics Approaches in Biomarker Development. Proteomics 2020; 20:e1900029. [DOI: 10.1002/pmic.201900029] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 10/10/2019] [Indexed: 01/24/2023]
Affiliation(s)
- Constance A. Sobsey
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - Sahar Ibrahim
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - Vincent R. Richard
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - Vanessa Gaspar
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - Georgia Mitsa
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - Vincent Lacasse
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - René P. Zahedi
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
| | - Gerald Batist
- Gerald Bronfman Department of OncologyJewish General HospitalMcGill University Montreal Quebec H4A 3T2 Canada
| | - Christoph H. Borchers
- Segal Cancer Proteomics CentreLady Davis InstituteJewish General HospitalMcGill University Montreal Quebec H3T 1E2 Canada
- Gerald Bronfman Department of OncologyJewish General HospitalMcGill University Montreal Quebec H4A 3T2 Canada
- Department of Data Intensive Science and EngineeringSkolkovo Institute of Science and TechnologySkolkovo Innovation Center Moscow 143026 Russia
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Cantor DI, Cheruku HR, Westacott J, Shin JS, Mohamedali A, Ahn SB. Proteomic investigations into resistance in colorectal cancer. Expert Rev Proteomics 2020; 17:49-65. [PMID: 31914823 DOI: 10.1080/14789450.2020.1713103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction: Despite advances in screening and treatment options, colorectal cancer (CRC) remains one of the most prevalent and lethal cancer subtypes. Resistance to cytotoxic or targeted therapy has remained a constant challenge to the treatment and long-term management of patients, attracting intense worldwide investigation since the 1950s. Through extensive investigations into the proteomic mechanisms and functions that convey resistance to therapy/s, researchers have become able to implicate alterations in several signaling pathways that provide and sustain resistance to treatment.Areas covered: In this review, we summarize how protein alterations are associated with resistance to therapy, with particular emphasis on CRC. An overview of the mechanisms of therapeutic resistance is described, highlighting recent studies which endeavor to elucidate the proteomic changes that are associated with the acquisition and promulgation of therapeutic resistance.Expert opinion: While cancers such as CRC have been intensively studied for decades, unresponsiveness and the resistance to therapy remain critical obstacles in the treatment of patients. Due to the inherent biological and clinical heterogeneity of individual CRCs, proteomic methods stand to become powerful tools to provide biological insights that may guide therapeutic strategies with the ultimate goal of refining emergent immunotherapeutic treatments.
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Affiliation(s)
- David I Cantor
- Australian Proteome Analysis Facility, Macquarie University, Sydney, Australia
| | | | - Jack Westacott
- Faculty of Science and Engineering, Macquarie University, Sydney, Australia
| | - Joo-Shik Shin
- Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and Faculty of Medicine, University of Sydney, Sydney, Australia
| | - Abidali Mohamedali
- Faculty of Science and Engineering, Macquarie University, Sydney, Australia
| | - Seong Boem Ahn
- Faculty of Health and Medical Sciences, Macquarie University, Sydney, Australia
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Kontostathi G, Makridakis M, Zoidakis J, Vlahou A. Applications of multiple reaction monitoring targeted proteomics assays in human plasma. Expert Rev Mol Diagn 2019; 19:499-515. [PMID: 31057016 DOI: 10.1080/14737159.2019.1615448] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.
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Affiliation(s)
- Georgia Kontostathi
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Manousos Makridakis
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Jerome Zoidakis
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Antonia Vlahou
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
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Abstract
INTRODUCTION Cancer is often diagnosed at late stages when the chance of cure is relatively low and although research initiatives in oncology discover many potential cancer biomarkers, few transition to clinical applications. This review addresses the current landscape of cancer biomarker discovery and translation with a focus on proteomics and beyond. Areas covered: The review examines proteomic and genomic techniques for cancer biomarker detection and outlines advantages and challenges of integrating multiple omics approaches to achieve optimal sensitivity and address tumor heterogeneity. This discussion is based on a systematic literature review and direct participation in translational studies. Expert commentary: Identifying aggressive cancers early on requires improved sensitivity and implementation of biomarkers representative of tumor heterogeneity. During the last decade of genomic and proteomic research, significant advancements have been made in next generation sequencing and mass spectrometry techniques. This in turn has led to a dramatic increase in identification of potential genomic and proteomic cancer biomarkers. However, limited successes have been shown with translation of these discoveries into clinical practice. We believe that the integration of these omics approaches is the most promising molecular tool for comprehensive cancer evaluation, early detection and transition to Precision Medicine in oncology.
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Affiliation(s)
- Ventzislava A Hristova
- a Department of Pathology , Johns Hopkins University School of Medicine , Baltimore , MD , USA
| | - Daniel W Chan
- a Department of Pathology , Johns Hopkins University School of Medicine , Baltimore , MD , USA
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Duan B, Bai J, Qiu J, Wang J, Tong C, Wang X, Miao J, Li Z, Li W, Yang J, Huang C. Histone-lysine N-methyltransferase SETD7 is a potential serum biomarker for colorectal cancer patients. EBioMedicine 2018; 37:134-143. [PMID: 30361067 PMCID: PMC6284455 DOI: 10.1016/j.ebiom.2018.10.036] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 10/04/2018] [Accepted: 10/11/2018] [Indexed: 01/14/2023] Open
Abstract
Background There is an urgent need for the identification of new, clinically useful biomarkers of CRC to enhance diagnostic and prognostic capabilities. Methods We performed proteomic profiling on serum samples from paired pre- and post-operative CRC patients, colorectal polyps patients and healthy controls using an approach combining magnetic bead-based weak cation exchange and matrix-assisted laser desorption ionization-time of flight mass spectrometry. We next performed liquid chromatography-electrospray ionization-tandem mass spectrometry to identify the proteins and selected potential biomarker based on bioinformatics analysis of the TCGA and GEO dataset. We examined SETD7 expression in serum and tissue samples by ELISA and immunohistochemistry respectively and explored the biological function of SETD7 in vitro. Findings 85 differentially expressed peptides were identified. Five peptides showing the most significant changes in abundance across paired pre- and post-operation CRC patients, colorectal polyps patients and healthy controls were identified as peptide regions of FGA, MUC5AC and SETD7. Bioinformatics analysis suggested that the up-regulation of SETD7 in CRC is relatively specific. Validation studies showed that SETD7 expression increased from healthy controls to those with colorectal polyps and finally CRC patients, and decreased after surgery. The sensitivity and specificity of SETD7 were 92.17% and 81.08%, with a high diagnostic value (AUC = 0.9477). In addition, SETD7 expression was significantly correlated with tumor stage and microsatellite instability. Knockdown of SETD7 inhibited cancer cell proliferation, induced G1/S cell cycle arrest and increased apoptosis. Interpretation Our data indicate that SETD7 could serve as a potential diagnostic and prognostic biomarker for CRC.
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Affiliation(s)
- Baojun Duan
- Key Laboratory of Environment and Disease-Related Gene, Ministry of Education, Department of Cell Biology and Genetics, School of Basic Medical sciences, Xi'an Jiaotong University, Health Science Center, Shaanxi, Xi'an 710061, China; Department of Medical Oncology of Shaanxi Provincial People's Hospital, Shaanxi, Xi'an 710068, China
| | - Jun Bai
- Department of Medical Oncology of Shaanxi Provincial People's Hospital, Shaanxi, Xi'an 710068, China
| | - Jian Qiu
- Department of General Surgery of Shaanxi Provincial People's Hospital, Shaanxi, Xi'an 710068, China
| | - Jianhua Wang
- Department of General Surgery of Shaanxi Provincial People's Hospital, Shaanxi, Xi'an 710068, China
| | - Cong Tong
- Department of General Surgery of Shaanxi Provincial People's Hospital, Shaanxi, Xi'an 710068, China
| | - Xiaofei Wang
- Key Laboratory of Environment and Disease-Related Gene, Ministry of Education, Department of Cell Biology and Genetics, School of Basic Medical sciences, Xi'an Jiaotong University, Health Science Center, Shaanxi, Xi'an 710061, China
| | - Jiyu Miao
- Key Laboratory of Environment and Disease-Related Gene, Ministry of Education, Department of Cell Biology and Genetics, School of Basic Medical sciences, Xi'an Jiaotong University, Health Science Center, Shaanxi, Xi'an 710061, China
| | - Zongfang Li
- National & Local Joint Engineering Research Center of Biodiagnostics and Biotherapy, the Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an 710004, China
| | - Wensheng Li
- Department of Pathology of Shaanxi Provincial People's Hospital, Shaanxi, Xi'an 710068, China
| | - Juan Yang
- Key Laboratory of Environment and Disease-Related Gene, Ministry of Education, Department of Cell Biology and Genetics, School of Basic Medical sciences, Xi'an Jiaotong University, Health Science Center, Shaanxi, Xi'an 710061, China.
| | - Chen Huang
- Key Laboratory of Environment and Disease-Related Gene, Ministry of Education, Department of Cell Biology and Genetics, School of Basic Medical sciences, Xi'an Jiaotong University, Health Science Center, Shaanxi, Xi'an 710061, China.
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