1
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Sun BB, Suhre K, Gibson BW. Promises and challenges of populational proteomics in health and disease. Mol Cell Proteomics 2024:100786. [PMID: 38761890 DOI: 10.1016/j.mcpro.2024.100786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 05/13/2024] [Accepted: 05/15/2024] [Indexed: 05/20/2024] Open
Abstract
Advances in proteomic assay technologies has significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvement in multiplexed protein assays have facilitated quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest ranging, and potentially the most disease relevant, blood circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with the affinity-based array platforms in terms of speed, cost and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remains considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations and data integration as population scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs and financing must be solved.
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Affiliation(s)
- Benjamin B Sun
- Human Genetics, Informatics and Predictive Sciences, Bristol-Myers Squibb, 02141, USA
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha 24144, Qatar; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Bradford W Gibson
- Pharmaceutical Chemistry, University of California, San Francisco, CA 94143, USA
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Pruszkowska-Przybylska P, Dupont ME, Jacobsen SB, Smerup M, Tfelt-Hansen J, Morling N, Andersen JD. Evaluation of DNAmAge in paired fresh, frozen, and formalin-fixed paraffin-embedded heart tissues. PLoS One 2024; 19:e0299557. [PMID: 38718072 PMCID: PMC11078437 DOI: 10.1371/journal.pone.0299557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 02/12/2024] [Indexed: 05/12/2024] Open
Abstract
The continued development in methylome analysis has enabled a more precise assessment of DNA methylation, but treatment of target tissue prior to analysis may affect DNA analysis. Prediction of age based on methylation levels in the genome (DNAmAge) has gained much interest in disease predisposition (biological age estimation), but also in chronological donor age estimation in crime case samples. Various epigenetic clocks were designed to predict the age. However, it remains unknown how the storage of the tissues affects the DNAmAge estimation. In this study, we investigated the storage method impact of DNAmAge by the comparing the DNAmAge of the two commonly used storage methods, freezing and formalin-fixation and paraffin-embedding (FFPE) to DNAmAge of fresh tissue. This was carried out by comparing paired heart tissue samples of fresh tissue, samples stored by freezing and FFPE to chronological age and whole blood samples from the same individuals. Illumina EPIC beadchip array was used for methylation analysis and the DNAmAge was evaluated with the following epigenetic clocks: Horvath, Hannum, Levine, Horvath skin+blood clock (Horvath2), PedBE, Wu, BLUP, EN, and TL. We observed differences in DNAmAge among the storage conditions. FFPE samples showed a lower DNAmAge compared to that of frozen and fresh samples. Additionally, the DNAmAge of the heart tissue was lower than that of the whole blood and the chronological age. This highlights caution when evaluating DNAmAge for FFPE samples as the results were underestimated compared with fresh and frozen tissue samples. Furthermore, the study also emphasizes the need for a DNAmAge model based on heart tissue samples for an accurate age estimation.
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Affiliation(s)
| | - Mikkel Eriksen Dupont
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stine Bøttcher Jacobsen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Morten Smerup
- Department of Cardiothoracic Surgery, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jacob Tfelt-Hansen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Niels Morling
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jeppe Dyrberg Andersen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Doll S, Schweizer L, Bollwein C, Steiger K, Pfarr N, Walker M, Wörtler K, Knebel C, von Eisenhart-Rothe R, Hartmann W, Weichert W, Mann M, Kuhn PH, Specht K. Proteomic Characterization of Undifferentiated Small Round Cell Sarcomas with EWSR1- and CIC::DUX4-Translocations Reveals Diverging Tumor Biology and Distinct Diagnostic Markers. Mod Pathol 2024:100511. [PMID: 38705279 DOI: 10.1016/j.modpat.2024.100511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 04/11/2024] [Accepted: 04/26/2024] [Indexed: 05/07/2024]
Abstract
Undifferentiated small round cell sarcomas of bone and soft tissue (USRS) are a group of tumors with heterogenic genomic alterations sharing similar morphology. In the present study, we performed a comparative large-scale proteomic analysis of USRS (n=42) with diverse genomic translocations including classic Ewing sarcomas with EWSR1::FLI1 fusions (n=24) or EWSR1::ERG - fusions (n=4), sarcomas with an EWSR1 - rearrangement (n=2), CIC::DUX4 fusion (n=8), as well as tumors classified as USRS with no genetic data available (n=4). Proteins extracted from formalin-fixed, paraffin-embedded (FFPE) pretherapeutic biopsies were analyzed qualitatively and quantitatively using shot gun mass spectrometry (MS). More than 8000 protein groups could be quantified using data-independent acquisition. Unsupervised hierarchical cluster analysis based on proteomic data allowed stratification of the 42 cases into distinct groups reflecting the different molecular genotypes. Protein signatures that significantly correlated with the respective genomic translocations were identified and used to generate a heatmap of all 42 sarcomas with assignment of cases with unknown molecular genetic data to either the EWSR1- or CIC-rearranged groups. MS-based prediction of sarcoma subtypes was molecularly confirmed in two cases where next-generation sequencing was technically feasible. MS also detected proteins routinely used in the immunohistochemical approach for the differential diagnosis of USRS. BCL11B highly expressed in Ewing sarcomas and Bach2 as well as ETS-1 highly expressed in CIC::DUX4-associated sarcomas, were among proteins identified by the present proteomic study and were chosen for immunohistochemical confirmation of MS data in our study cohort. Differential expression of these 3 markers in the two genetic groups were further validated in an independent cohort of n= 34 USRS. Finally, our proteomic results point towards diverging signaling pathways in the different USRS subgroups.
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Affiliation(s)
- Sophia Doll
- Max-Planck-Institute for Biochemistry, Am Klopferspitz 18A, Martinsried, Germany
| | - Lisa Schweizer
- Max-Planck-Institute for Biochemistry, Am Klopferspitz 18A, Martinsried, Germany
| | - Christine Bollwein
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany
| | - Katja Steiger
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany
| | - Nicole Pfarr
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany
| | - Maria Walker
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany
| | - Klaus Wörtler
- Musculoskeletal Radiology Section, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Carolin Knebel
- Department of Orthopaedic Surgery, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Ruediger von Eisenhart-Rothe
- Department of Orthopaedic Surgery, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | | | - Wilko Weichert
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany; German Cancer Consortium (DKTK), Partner-site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matthias Mann
- Max-Planck-Institute for Biochemistry, Am Klopferspitz 18A, Martinsried, Germany
| | - Peer-Hendrik Kuhn
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany
| | - Katja Specht
- Institute of Pathology, Technical University of Munich, 81675 Munich, Germany.
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4
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Topitsch A, Halstenbach T, Rothweiler R, Fretwurst T, Nelson K, Schilling O. Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone. J Proteome Res 2024; 23:1810-1820. [PMID: 38634750 DOI: 10.1021/acs.jproteome.4c00046] [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] [Indexed: 04/19/2024]
Abstract
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.
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Affiliation(s)
- Annika Topitsch
- Institute for Surgical Pathology, Faculty of Medicine, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Albertstraße 19a, 79104 Freiburg, Germany
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104 Freiburg, Germany
- Department of Oral and Maxillofacial Surgery/Translational Implantology, Faculty of Medicine, Medical Center - University of Freiburg, Hugstetter Straße 55, 79106 Freiburg, Germany
| | - Tim Halstenbach
- Department of Oral and Maxillofacial Surgery/Translational Implantology, Faculty of Medicine, Medical Center - University of Freiburg, Hugstetter Straße 55, 79106 Freiburg, Germany
| | - René Rothweiler
- Department of Oral and Maxillofacial Surgery/Translational Implantology, Faculty of Medicine, Medical Center - University of Freiburg, Hugstetter Straße 55, 79106 Freiburg, Germany
| | - Tobias Fretwurst
- Department of Oral and Maxillofacial Surgery/Translational Implantology, Faculty of Medicine, Medical Center - University of Freiburg, Hugstetter Straße 55, 79106 Freiburg, Germany
| | - Katja Nelson
- Department of Oral and Maxillofacial Surgery/Translational Implantology, Faculty of Medicine, Medical Center - University of Freiburg, Hugstetter Straße 55, 79106 Freiburg, Germany
| | - Oliver Schilling
- Institute for Surgical Pathology, Faculty of Medicine, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
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5
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Makhmut A, Qin D, Hartlmayr D, Seth A, Coscia F. An Automated and Fast Sample Preparation Workflow for Laser Microdissection Guided Ultrasensitive Proteomics. Mol Cell Proteomics 2024; 23:100750. [PMID: 38513891 PMCID: PMC11067455 DOI: 10.1016/j.mcpro.2024.100750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 03/23/2024] Open
Abstract
Spatial tissue proteomics integrating whole-slide imaging, laser microdissection, and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE robotic system, which has the capacity to process 192 samples in 3 h. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking, and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows 'on-the-fly' sample clean-up, particularly pertinent for laser microdissection workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell, and epithelial microregions of 4000 μm2 to a depth of ∼2000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.
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Affiliation(s)
- Anuar Makhmut
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Di Qin
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | | | | | - Fabian Coscia
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany.
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Xavier D, Lucas N, Williams SG, Koh JMS, Ashman K, Loudon C, Reddel R, Hains PG, Robinson PJ. Heat 'n Beat: A Universal High-Throughput End-to-End Proteomics Sample Processing Platform in under an Hour. Anal Chem 2024; 96:4093-4102. [PMID: 38427620 DOI: 10.1021/acs.analchem.3c04708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
Proteomic analysis by mass spectrometry of small (≤2 mg) solid tissue samples from diverse formats requires high throughput and comprehensive proteome coverage. We developed a nearly universal, rapid, and robust protocol for sample preparation, suitable for high-throughput projects that encompass most cell or tissue types. This end-to-end workflow extends from original sample to loading the mass spectrometer and is centered on a one-tube homogenization and digestion method called Heat 'n Beat (HnB). It is applicable to most tissues, regardless of how they were fixed or embedded. Sample preparation was divided into separate challenges. The initial sample washing and final peptide cleanup steps were adapted to three tissue sources: fresh frozen (FF), optimal cutting temperature (OCT) compound embedded (FF-OCT), and formalin-fixed paraffin embedded (FFPE). Third, for core processing, tissue disruption and lysis were decreased to a 7 min heat and homogenization treatment, and reduction, alkylation, and proteolysis were optimized into a single step. The refinements produced near doubled peptide yield when compared to our earlier method ABLE delivered a consistently high digestion efficiency of 85-90%, reported by ProteinPilot, and required only 38 min for core processing in a single tube, with the total processing time being 53-63 min. The robustness of HnB was demonstrated on six organ types, a cell line, and a cancer biopsy. Its suitability for high-throughput applications was demonstrated on a set of 1171 FF-OCT human cancer biopsies, which were processed for end-to-end completion in 92 h, producing highly consistent peptide yield and quality for over 3513 MS runs.
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Affiliation(s)
- Dylan Xavier
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Natasha Lucas
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Steven G Williams
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Jennifer M S Koh
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Keith Ashman
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Clare Loudon
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Roger Reddel
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Peter G Hains
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
| | - Phillip J Robinson
- ProCan, Faculty of Medicine and Health, The University of Sydney, Children's Medical Research Institute, Westmead, NSW 2145, Australia
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Johansen A, Sandve GKF, Ibsen JH, Lundin KEA, Sollid LM, Stamnaes J. Biopsy Proteome Scoring to Determine Mucosal Remodeling in Celiac Disease. Gastroenterology 2024:S0016-5085(24)00286-5. [PMID: 38467384 DOI: 10.1053/j.gastro.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/14/2024] [Accepted: 03/05/2024] [Indexed: 03/13/2024]
Abstract
BACKGROUND & AIMS Histologic evaluation of gut biopsy specimens is a cornerstone for diagnosis and management of celiac disease (CeD). Despite its wide use, the method depends on proper biopsy orientation, and it suffers from interobserver variability. Biopsy proteome measurement reporting on the tissue state can be obtained by mass spectrometry analysis of formalin-fixed paraffin-embedded tissue. Here we aimed to transform biopsy proteome data into numerical scores that give observer-independent measures of mucosal remodeling in CeD. METHODS A pipeline using glass-mounted formalin-fixed paraffin-embedded sections for mass spectrometry-based proteome analysis was established. Proteome data were converted to numerical scores using 2 complementary approaches: a rank-based enrichment score and a score based on machine-learning using logistic regression. The 2 scoring approaches were compared with each other and with histology analyzing 18 patients with CeD with biopsy specimens collected before and after treatment with a gluten-free diet as well as biopsy specimens from patients with CeD with varying degree of remission (n = 22). Biopsy specimens from individuals without CeD (n = 32) were also analyzed. RESULTS The method yielded reliable proteome scoring of both unstained and H&E-stained glass-mounted sections. The scores of the 2 approaches were highly correlated, reflecting that both approaches pick up proteome changes in the same biological pathways. The proteome scores correlated with villus height-to-crypt depth ratio. Thus, the method is able to score biopsy specimens with poor orientation. CONCLUSIONS Biopsy proteome scores give reliable observer and orientation-independent measures of mucosal remodeling in CeD. The proteomic method can readily be implemented by nonexpert laboratories in parallel to histology assessment and easily scaled for clinical trial settings.
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Affiliation(s)
- Anette Johansen
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Geir Kjetil F Sandve
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Informatics, The Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Jostein Holen Ibsen
- Department of Gastroenterology, Oslo University Hospital-Rikshospitalet, Oslo, Norway
| | - Knut E A Lundin
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Gastroenterology, Oslo University Hospital-Rikshospitalet, Oslo, Norway
| | - Ludvig M Sollid
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Immunology, Oslo University Hospital-Rikshospitalet, Oslo, Norway
| | - Jorunn Stamnaes
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Immunology, Oslo University Hospital-Rikshospitalet, Oslo, Norway.
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Dokanei S, Minai‐Tehrani D, Moghoofei M, Rostamian M. Investigating the relationship between Epstein-Barr virus infection and gastric cancer: A systematic review and meta-analysis. Health Sci Rep 2024; 7:e1976. [PMID: 38505684 PMCID: PMC10948593 DOI: 10.1002/hsr2.1976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 02/06/2024] [Accepted: 02/28/2024] [Indexed: 03/21/2024] Open
Abstract
Background and Aims Gastric cancer (GC) is a common cancer type worldwide, and various factors can be involved in its occurrence. One of these factors is Epstein-Barr virus (EBV) infection. In this regard, a systematic review and meta-analysis was conducted to achieve a better understanding of the EBV prevalence in GC samples. Methods English databases were searched and studies that reported the prevalence and etiological factors of EBV related to GC from July 2007 to November 2022 were retrieved. The reported data were selected based on the inclusion and exclusion criteria. The pooled prevalence of EBV infection with 95% confidence intervals was calculated. Quality assessment, heterogeneity testing, and publication bias assessment were also performed. The literature search showed 953 studies, of which 87 studies met our inclusion criteria and were used for meta-analysis. Results The pooled prevalence of EBV infection related to GC was estimated to be 9.5% (95% confidence interval [CI]: 8.2%-11%) in the general population. The prevalence of EBV infection related to GC by gender was 13.5% (95% CI: 11.1%-16.3%) in males and 7.6% (95% CI: 5.4%-10.6%) in females. No significant differences were observed in terms of geographical region. Out of the 87 studies included in the meta-analysis, the most common diagnostic test was in situ hybridization (58 cases). Conclusions Altogether, the results indicated that EBV infection is one of the important factors in the development of GC. However, this does not necessarily mean that EBV infection directly causes GC since other factors may also be involved in the development of GC. Therefore, it is recommended to conduct extensive epidemiological studies on various aspects of the relationship between this virus and GC, which can provide valuable information for understanding the relationship between EBV and GC.
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Affiliation(s)
- Saman Dokanei
- Faculty of Life Sciences and BiotechnologyShahid Beheshti University (GC)TehranIran
| | | | - Mohsen Moghoofei
- Department of Microbiology, Faculty of MedicineKermanshah University of Medical SciencesKermanshahIran
| | - Mosayeb Rostamian
- Infectious Diseases Research Center, Health InstituteKermanshah University of Medical SciencesKermanshahIran
- Student Research CommitteeKermanshah University of Medical SciencesKermanshahIran
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Patton A, Dermawan JK. Current updates in sarcoma biomarker discovery: emphasis on next-generation sequencing-based methods. Pathology 2024; 56:274-282. [PMID: 38185613 DOI: 10.1016/j.pathol.2023.10.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 10/25/2023] [Accepted: 10/29/2023] [Indexed: 01/09/2024]
Abstract
Soft tissue sarcomas comprise a heterogeneous group of neoplasms. Although soft tissue malignancies make up only 2% of adult cancers, classification based on histomorphology presents a diagnostic challenge. Characterisation of soft tissue sarcomas by molecular analysis is rapidly evolving to improve diagnostic accuracy and develop targeted therapies. This review highlights the advances in molecular techniques, including current next-generation sequencing-based assays (fusion detection by RNA sequencing, targeted/whole exome sequencing, microRNA profiling), as well as emerging methods (liquid biopsies, DNA methylation profiling, single-cell molecular profiling and next-generation immunohistochemistry) for future clinical applications.
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Affiliation(s)
- Ashley Patton
- Department of Pathology & Laboratory Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Josephine K Dermawan
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA.
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10
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Dieters-Castator DZ, Manzanillo P, Yang HY, Modak RV, Rardin MJ, Gibson BW. Magnetic Bead-Based Workflow for Sensitive and Streamlined Cell Surface Proteomics. J Proteome Res 2024; 23:618-632. [PMID: 38226771 DOI: 10.1021/acs.jproteome.3c00432] [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] [Indexed: 01/17/2024]
Abstract
Cell surface proteins represent an important class of molecules for therapeutic targeting and cellular phenotyping. However, their enrichment and detection via mass spectrometry-based proteomics remains challenging due to low abundance, post-translational modifications, hydrophobic regions, and processing requirements. To improve their identification, we optimized a Cell-Surface Capture (CSC) workflow that incorporates magnetic bead-based processing. Using this approach, we evaluated labeling conditions (biotin tags and catalysts), enrichment specificity (streptavidin beads), missed cleavages (lysis buffers), nonenzymatic deamidation (digestion and deglycosylation buffers), and data acquisition methods (DDA, DIA, and TMT). Our findings support the use of alkoxyamine-PEG4-biotin plus 5-methoxy-anthranilic acid, SDS/urea-based lysis buffers, single-pot solid-phased-enhanced sample-preparation (SP3), and streptavidin magnetic beads for maximal surfaceome coverage. Notably, with semiautomated processing, sample handling was simplified and between ∼600 and 900 cell surface N-glycoproteins were identified from only 25-200 μg of HeLa protein. CSC also revealed significant differences between in vitro monolayer cultures and in vivo tumor xenografts of murine CT26 colon adenocarcinoma samples that may aid in target identification for drug development. Overall, the improved efficiency of the magnetic-based CSC workflow identified both previously reported and novel N-glycosites with less material and high reproducibility that should help advance the field of surfaceomics by providing insight in cellular phenotypes not previously documented.
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Affiliation(s)
| | - Paolo Manzanillo
- Inflammation, Amgen Research, South San Francisco, California 94080, United States
| | - Han-Yin Yang
- Discovery Proteomics, Amgen Research, South San Francisco, California 94080, United States
| | - Rucha V Modak
- Inflammation, Amgen Research, South San Francisco, California 94080, United States
| | - Matthew J Rardin
- Discovery Proteomics, Amgen Research, South San Francisco, California 94080, United States
| | - Bradford W Gibson
- Discovery Proteomics, Amgen Research, South San Francisco, California 94080, United States
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11
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G Jagadeeshaprasad M, Zeng J, Zheng N. LC-MS bioanalysis of protein biomarkers and protein therapeutics in formalin-fixed paraffin-embedded tissue specimens. Bioanalysis 2024; 16:245-258. [PMID: 38226835 DOI: 10.4155/bio-2023-0210] [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] [Indexed: 01/17/2024] Open
Abstract
Formalin-fixed paraffin-embedded (FFPE) is a form of preservation and preparation for biopsy specimens. FFPE tissue specimens are readily available as part of oncology studies because they are often collected for disease diagnosis or confirmation. FFPE tissue specimens could be extremely useful for retrospective studies on protein biomarkers because the samples preserved in FFPE blocks could be stable for decades. However, LC-MS bioanalysis of FFPE tissues poses significant challenges. In this Perspective, we review the benefits and recent developments in LC-MS approach for targeted protein biomarker and protein therapeutic analysis using FFPE tissues and their clinical and translational applications. We believe that LC-MS bioanalysis of protein biomarkers in FFPE tissue specimens represents a great potential for its clinical applications.
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Affiliation(s)
| | - Jianing Zeng
- Department of Protein Sciences & Mass Spectrometry, Translational Medicine, Bristol Myers Squibb, Princeton, NJ 08543, USA
| | - Naiyu Zheng
- Department of Protein Sciences & Mass Spectrometry, Translational Medicine, Bristol Myers Squibb, Princeton, NJ 08543, USA
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12
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Yan HJ, Lin SC, Xu SH, Gao YB, Zhou BJ, Zhou R, Chen FM, Li FR. Proteomic analysis reveals LRPAP1 as a key player in the micropapillary pattern metastasis of lung adenocarcinoma. Heliyon 2024; 10:e23913. [PMID: 38226250 PMCID: PMC10788494 DOI: 10.1016/j.heliyon.2023.e23913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/13/2023] [Accepted: 12/15/2023] [Indexed: 01/17/2024] Open
Abstract
Objectives Lung adenocarcinomas have different prognoses depending on their histological growth patterns. Micropapillary growth within lung adenocarcinoma, particularly metastasis, is related to dismal prognostic outcome. Metastasis accounts for a major factor leading to mortality among lung cancer patients. Understanding the mechanisms underlying early stage metastasis can help develop novel treatments for improving patient survival. Methods Here, quantitative mass spectrometry was conducted for comparing protein expression profiles among various histological subtypes, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma (including acinar and micropapillary [MIP] types). To determine the mechanism of MIP-associated metastasis, we identified a protein that was highly expressed in MIP. The expression of the selected highly expressed MIP protein was verified via immunohistochemical (IHC) analysis and its function was validated by an in vitro migration assay. Results Proteomic data revealed that low-density lipoprotein receptor-related protein-associated protein 1 (LRPAP1) was highly expressed in MIP group, which was confirmed by IHC. The co-expressed proteins in this study, PSMD1 and HSP90AB1, have been reported to be highly expressed in different cancers and play an essential role in metastasis. We observed that LRPAP1 promoted lung cancer progression, including metastasis, invasion and proliferation in vitro and in vivo. Conclusion LRPAP1 is necessary for MIP-associated metastasis and is the candidate novel anti-metastasis therapeutic target.
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Affiliation(s)
- Hao-jie Yan
- Translational Medicine Collaborative Innovation Center, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), 518020, Shenzhen, China
- Post-doctoral Scientific Research Station of Basic Medicine, Jinan University, 510632, Guangzhou, China
- Guangdong Engineering Technology Research Center of Stem Cell and Cell Therapy, Shenzhen Key Laboratory of Stem Cell Research and Clinical Transformation, Shenzhen Immune Cell Therapy Public Service Platform, 518020, Shenzhen, China
| | - Sheng-cheng Lin
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 518172, Shenzhen, China
| | | | - Yu-biao Gao
- Translational Medicine Collaborative Innovation Center, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), 518020, Shenzhen, China
- Guangdong Engineering Technology Research Center of Stem Cell and Cell Therapy, Shenzhen Key Laboratory of Stem Cell Research and Clinical Transformation, Shenzhen Immune Cell Therapy Public Service Platform, 518020, Shenzhen, China
| | - Bao-jin Zhou
- Experiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, 201203, Shanghai, China
| | - Ruo Zhou
- Deepxomics Co., Ltd, 518112, Shenzhen, China
| | - Fu-ming Chen
- Translational Medicine Collaborative Innovation Center, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), 518020, Shenzhen, China
- Guangdong Engineering Technology Research Center of Stem Cell and Cell Therapy, Shenzhen Key Laboratory of Stem Cell Research and Clinical Transformation, Shenzhen Immune Cell Therapy Public Service Platform, 518020, Shenzhen, China
| | - Fu-rong Li
- Translational Medicine Collaborative Innovation Center, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), 518020, Shenzhen, China
- Guangdong Engineering Technology Research Center of Stem Cell and Cell Therapy, Shenzhen Key Laboratory of Stem Cell Research and Clinical Transformation, Shenzhen Immune Cell Therapy Public Service Platform, 518020, Shenzhen, China
- Institute of Health Medicine, Southern University of Science and Technology, 518055, Shenzhen, China
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Naimy S, Sølberg JBK, Kuczek DE, Løvendorf MB, Bzorek M, Litman T, Mund A, Rahbek Gjerdrum LM, Clark RA, Mann M, Dyring-Andersen B. Comparative quantitative proteomic analysis of melanoma subtypes, nevus-associated melanoma, and corresponding nevi. J Invest Dermatol 2024:S0022-202X(23)03211-6. [PMID: 38185415 DOI: 10.1016/j.jid.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 12/01/2023] [Accepted: 12/04/2023] [Indexed: 01/09/2024]
Abstract
A substantial part of cutaneous malignant melanomas develops from benign nevi. However, the precise molecular events driving the transformation from benign to malignant melanoma are not well understood. We used laser microdissection and mass spectrometry to analyze the proteomes of melanoma subtypes, including superficial spreading melanomas (SSM, n=17), nodular melanomas (NM, n=17), and acral melanomas (AM, n=15). Furthermore, we compared the proteomes of nevi cells and melanoma cells within the same specimens (nevus-associated melanoma (NAM, n=14)). In total, we quantified 7,935 proteins. Despite the genomic and clinical differences of the melanoma subtypes, our analysis revealed relatively similar proteomes, except for the upregulation of proteins involved in immune activation in NM vs AM. Examining NAM versus nevi, we found 1,725 differentially expressed proteins (FDR < 0.05). Among these proteins were 140 that overlapped with cancer hallmarks, tumor suppressors, and regulators of metabolism and cell cycle. Pathway analysis indicated aberrant activation of the PI3K-AKT-mTOR pathways and the Hippo-YAP pathway. Using a classifier, we identified six proteins capable of distinguishing melanoma from nevi samples. Our study represents a comprehensive comparative analysis of the proteome in melanoma subtypes and associated nevi, offering, to our knowledge, previously unreported insights into the biological behavior of these distinct entities.
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Affiliation(s)
- Soraya Naimy
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Department of Pathology, Copenhagen University Hospital, Zealand University Hospital, Roskilde, Denmark
| | - Julie B K Sølberg
- Department of Dermatology and Allergy, Copenhagen University Hospital - Herlev and Gentofte Hospital, Hellerup, Denmark
| | - Dorota E Kuczek
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Marianne Bengtson Løvendorf
- Department of Dermatology and Allergy, Copenhagen University Hospital - Herlev and Gentofte Hospital, Hellerup, Denmark; Leo Foundation Skin Immunology Research Center, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Michael Bzorek
- Department of Pathology, Copenhagen University Hospital, Zealand University Hospital, Roskilde, Denmark
| | - Thomas Litman
- Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Andreas Mund
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | | | - Rachael A Clark
- Department of Dermatology, Brigham and Women's Hospital and Harvard Medical School, Boston, US
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Beatrice Dyring-Andersen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Department of Dermatology and Allergy, Copenhagen University Hospital - Herlev and Gentofte Hospital, Hellerup, Denmark; Leo Foundation Skin Immunology Research Center, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
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14
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Wang YE, Zeng WL, Cao ST, Zou JP, Liu CT, Shi JM, Li J, Qiu F, Wang Y. Development of a sample preparation method for micro-proteomics analysis of the formaldehyde-fixed paraffin-embedded liver tissue samples. Talanta 2024; 266:125106. [PMID: 37639870 DOI: 10.1016/j.talanta.2023.125106] [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: 05/09/2023] [Revised: 08/16/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023]
Abstract
Liver micro-proteomics based on the routinely used formaldehyde-fixed paraffin-embedded (FFPE) samples is valuable for innovative research, but the technical approach for sample preparation is often challenging. In this study, we aimed to develop a method for sample preparation for micro-proteomics on using the FFPE liver samples. We collected 2000 individual cells per batch from FFPE liver slices with laser capture microdissection and used them as test samples. We used the microscale fresh-frozen liver samples or HepG2 cells as control samples. For the FFPE samples, we first established a procedure for protein extraction. 2 h incubation at 95 °C in alkaline amine buffer supplemented with 4% sodium dodecyl sulfate allows improved production, efficiency, and quality of protein extraction. Then, we developed a dedicated protocol HDMSP for the micro-concentrated (<0.05 μg/μL) protein preparation for mass spectrometry (MS) based analysis, in which 2 μg/μL carboxyl magnetic beads and 70% acetonitrile are used to induce protein precipitation. For the 0.01 μg/μL protein control samples, protein recovery rate (PRR) by HDMSP is 72.1%, while the PRR is 5.9% if using a standard method solid phase-enhanced sample preparation. For the FFPE samples, the HDMSP PRR is 88.8%, and the subsequent MS analysis demonstrates increased depth, robustness, and quantitation accuracy for HDMSP relative to the control of in-gel digestion. Moreover, the physicochemical properties and subcellular location of the FFPE liver micro-proteome are comparable to those of the fresh-frozen control samples processed with filter-aided sample preparation (FASP). HDMSP is also comparable to FASP in terms of reproducibility and physicochemical properties in liver subcellular proteomes, and meanwhile reduces the sample preparation time by 15.9% and the experimental cost by 30.8%. Overall, the new method is simple and highly effective for preparing the microscale FFPE liver protein samples for MS analysis. This study provides a useful solution for FFPE liver micro-proteomics.
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Affiliation(s)
- Yong-Er Wang
- Biomedical Research Center, Southern Medical University, Guangzhou, China; School of Pharmaceutical Science, Southern Medical University, Guangzhou, China
| | - Wei-Lan Zeng
- Biomedical Research Center, Southern Medical University, Guangzhou, China; School of Pharmaceutical Science, Southern Medical University, Guangzhou, China
| | - Sheng-Tian Cao
- Biomedical Research Center, Southern Medical University, Guangzhou, China; School of Pharmaceutical Science, Southern Medical University, Guangzhou, China
| | - Jun-Peng Zou
- Biomedical Research Center, Southern Medical University, Guangzhou, China; School of Pharmaceutical Science, Southern Medical University, Guangzhou, China
| | - Cui-Ting Liu
- Biomedical Research Center, Southern Medical University, Guangzhou, China
| | - Jun-Min Shi
- Biomedical Research Center, Southern Medical University, Guangzhou, China
| | - Jing Li
- Biomedical Research Center, Southern Medical University, Guangzhou, China
| | - Feng Qiu
- The Seventh Affiliated Hospital of Southern Medical University, Foshan, China.
| | - Yan Wang
- Biomedical Research Center, Southern Medical University, Guangzhou, China; School of Pharmaceutical Science, Southern Medical University, Guangzhou, China; The Seventh Affiliated Hospital of Southern Medical University, Foshan, China; School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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15
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Mar D, Babenko IM, Zhang R, Noble WS, Denisenko O, Vaisar T, Bomsztyk K. A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes. J Transl Med 2024; 104:100282. [PMID: 37924947 PMCID: PMC10872585 DOI: 10.1016/j.labinv.2023.100282] [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: 08/29/2023] [Revised: 10/23/2023] [Accepted: 10/27/2023] [Indexed: 11/06/2023] Open
Abstract
Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.
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Affiliation(s)
- Daniel Mar
- UW Medicine South Lake Union, University of Washington, Seattle, Washington; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington
| | - Ilona M Babenko
- Diabetes Institute, University of Washington, Seattle, Washington
| | - Ran Zhang
- Department of Genome Sciences, University of Washington, Seattle, Washington
| | - William Stafford Noble
- Department of Genome Sciences, University of Washington, Seattle, Washington; Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington
| | - Oleg Denisenko
- UW Medicine South Lake Union, University of Washington, Seattle, Washington
| | - Tomas Vaisar
- Diabetes Institute, University of Washington, Seattle, Washington
| | - Karol Bomsztyk
- UW Medicine South Lake Union, University of Washington, Seattle, Washington; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington; Matchstick Technologies, Inc, Kirkland, Washington.
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16
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Tüshaus J, Sakhteman A, Lechner S, The M, Mucha E, Krisp C, Schlegel J, Delbridge C, Kuster B. A region-resolved proteomic map of the human brain enabled by high-throughput proteomics. EMBO J 2023; 42:e114665. [PMID: 37916885 PMCID: PMC10690467 DOI: 10.15252/embj.2023114665] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 11/03/2023] Open
Abstract
Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).
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Affiliation(s)
- Johanna Tüshaus
- Proteomics and Bioanalytics, Department of Molecular Life Sciences, School of Life SciencesTechnical University of MunichMunichGermany
| | - Amirhossein Sakhteman
- Proteomics and Bioanalytics, Department of Molecular Life Sciences, School of Life SciencesTechnical University of MunichMunichGermany
| | - Severin Lechner
- Proteomics and Bioanalytics, Department of Molecular Life Sciences, School of Life SciencesTechnical University of MunichMunichGermany
| | - Matthew The
- Proteomics and Bioanalytics, Department of Molecular Life Sciences, School of Life SciencesTechnical University of MunichMunichGermany
| | - Eike Mucha
- Bruker Daltonics GmbH & Co. KGBremenGermany
| | | | - Jürgen Schlegel
- Department of Neuropathology, Klinikum Rechts der ISAR, School of MedicineTechnical University MunichMunichGermany
| | - Claire Delbridge
- Department of Neuropathology, Klinikum Rechts der ISAR, School of MedicineTechnical University MunichMunichGermany
| | - Bernhard Kuster
- Proteomics and Bioanalytics, Department of Molecular Life Sciences, School of Life SciencesTechnical University of MunichMunichGermany
- German Cancer Consortium (DKTK), Munich SiteHeidelbergGermany
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17
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Brouwer NP, Webbink L, Haddad TS, Rutgers N, van Vliet S, Wood CS, Jansen PW, Lafarge MW, de Wilt JH, Hugen N, Simmer F, Jamieson NB, Tauriello DV, Kölzer VH, Vermeulen M, Nagtegaal ID. Transcriptomics and proteomics reveal distinct biology for lymph node metastases and tumour deposits in colorectal cancer. J Pathol 2023; 261:401-412. [PMID: 37792663 DOI: 10.1002/path.6196] [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: 06/08/2023] [Revised: 07/12/2023] [Accepted: 08/02/2023] [Indexed: 10/06/2023]
Abstract
Both lymph node metastases (LNMs) and tumour deposits (TDs) are included in colorectal cancer (CRC) staging, although knowledge regarding their biological background is lacking. This study aimed to compare the biology of these prognostic features, which is essential for a better understanding of their role in CRC spread. Spatially resolved transcriptomic analysis using digital spatial profiling was performed on TDs and LNMs from 10 CRC patients using 1,388 RNA targets, for the tumour cells and tumour microenvironment. Shotgun proteomics identified 5,578 proteins in 12 different patients. Differences in RNA and protein expression were analysed, and spatial deconvolution was performed. Image-based consensus molecular subtype (imCMS) analysis was performed on all TDs and LNMs included in the study. Transcriptome and proteome profiles identified distinct clusters for TDs and LNMs in both the tumour and tumour microenvironment segment, with upregulation of matrix remodelling, cell adhesion/motility, and epithelial-mesenchymal transition (EMT) in TDs (all p < 0.05). Spatial deconvolution showed a significantly increased abundance of fibroblasts, macrophages, and regulatory T-cells (p < 0.05) in TDs. Consistent with a higher fibroblast and EMT component, imCMS classified 62% of TDs as poor prognosis subtype CMS4 compared to 36% of LNMs (p < 0.05). Compared to LNMs, TDs have a more invasive state involving a distinct tumour microenvironment and upregulation of EMT, which are reflected in a more frequent histological classification of TDs as CMS4. These results emphasise the heterogeneity of locoregional spread and the fact that TDs should merit more attention both in future research and during staging. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Nelleke Pm Brouwer
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Loth Webbink
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Tariq S Haddad
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Natasja Rutgers
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Shannon van Vliet
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Colin S Wood
- Wolfson Wohl Cancer Research Centre, School of Cancer Sciences, University of Glasgow, UK
- Academic Unit of Surgery, Glasgow Royal Infirmary, University of Glasgow, UK
| | - Pascal Wtc Jansen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, The Netherlands
| | - Maxime W Lafarge
- Department of Pathology and Molecular Pathology, University and University Hospital of Zürich, Zürich, Switzerland
| | - Johannes Hw de Wilt
- Department of Surgery, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Niek Hugen
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Femke Simmer
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Nigel B Jamieson
- Wolfson Wohl Cancer Research Centre, School of Cancer Sciences, University of Glasgow, UK
- Academic Unit of Surgery, Glasgow Royal Infirmary, University of Glasgow, UK
| | - Daniele Vf Tauriello
- Department of Medical Biosciences, Research Institute for Medical Innovation, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Viktor H Kölzer
- Department of Pathology and Molecular Pathology, University and University Hospital of Zürich, Zürich, Switzerland
| | - Michiel Vermeulen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, The Netherlands
- The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Iris D Nagtegaal
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
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18
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Cho A, Ahn J, Kim A, Lee JH, Ryu HS, Kim KM, Yi EC. Proteomics analysis of an individual formalin-fixed paraffin-embedded tissue section using isobaric-tag amplification. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2023; 37:e9616. [PMID: 37817342 DOI: 10.1002/rcm.9616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 10/12/2023]
Abstract
RATIONALE The comprehensive analysis of formalin-fixed paraffin-embedded (FFPE) tissues is essential for retrospective clinical studies. However, detecting low-abundance proteins and obtaining proteome-scale data from FFPE samples pose analytical challenges in mass spectrometry-based proteomics. To overcome this challenge, our study focuses on implementing an isobaric labeling approach to improve the detection of low-abundance target proteins in FFPE tissues, thereby enhancing the qualitative and quantitative analysis. METHODS We employed an isobaric labeling approach utilizing synthetic peptides or proteins to enable the qualitative and quantitative measurement of target proteins in FFPE tissue samples. To achieve this, we incorporated tandem mass tag (TMT)-labeled recombinant proteins or synthetic peptides into TMT-labeled metastatic breast cancer FFPE tissues. Through this strategy, we successfully detect coexisting CD276 (B7-H3) and CD147 proteins while identifying over 6000 proteins using targeted analysis of individual FFPE tissue sections. RESULTS Our findings provide compelling evidence that the incorporation of isobaric labeling, along with the inclusion of TMT-labeled peptides or proteins, greatly enhances the detection of target proteins in FFPE tissue samples. By employing this approach, we were able to obtain robust qualitative measurements of CD276 and CD147 proteins, showcasing its effectiveness in identifying more than 6000 proteins in FFPE samples. CONCLUSIONS The integration of an isobaric labeling approach, in conjunction with synthetic peptides or proteins, presents a valuable strategy for enhancing the detection and validation of target proteins in FFPE tissue analysis. This technique holds immense potential in retrospective clinical studies, as it enables comprehensive analysis of low-abundance proteins and facilitating proteome-scale investigations in FFPE samples. By leveraging this methodology, researchers can unlock new insights into disease mechanisms and advance our understanding of complex biological processes.
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Affiliation(s)
- Ara Cho
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Jinsung Ahn
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Andrew Kim
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Jeong Hyun Lee
- Division of Biomedical Convergence, College of Biomedical Science, Kangwon National University, Chuncheon, Republic of Korea
| | - Han Suk Ryu
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kristine M Kim
- Division of Biomedical Convergence, College of Biomedical Science, Kangwon National University, Chuncheon, Republic of Korea
- Department of Bio-Health Convergence, Kangwon National University, Chuncheon, Republic of Korea
| | - Eugene C Yi
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine, Seoul National University, Seoul, Republic of Korea
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19
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Davis S, Scott C, Oetjen J, Charles PD, Kessler BM, Ansorge O, Fischer R. Deep topographic proteomics of a human brain tumour. Nat Commun 2023; 14:7710. [PMID: 38001067 PMCID: PMC10673928 DOI: 10.1038/s41467-023-43520-8] [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: 03/01/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023] Open
Abstract
The spatial organisation of cellular protein expression profiles within tissue determines cellular function and is key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially-resolved, quantitative proteomics of tissue that generates maps of protein abundance across tissue slices derived from a human atypical teratoid-rhabdoid tumour at three spatial resolutions, the highest being 40 µm, to reveal distinct abundance patterns of thousands of proteins. We employ spatially-aware algorithms that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with spatial abundance patterns and correlate proteins in the context of tissue heterogeneity and cellular features such as extracellular matrix or proximity to blood vessels. We identify PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response-driven, spatially-organised protein networks of the extracellular tumour matrix. Overall, we demonstrate spatially-aware deep proteo-phenotyping of tissue heterogeneity, to re-define understanding tissue biology and pathology at the molecular level.
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Affiliation(s)
- Simon Davis
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
| | - Connor Scott
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Janina Oetjen
- Bruker Daltonics GmbH & Co. KG, Fahrenheitstraße 4, 28359, Bremen, Germany
| | - Philip D Charles
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
| | - Benedikt M Kessler
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
| | - Olaf Ansorge
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Roman Fischer
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK.
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK.
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20
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Makhmut A, Qin D, Fritzsche S, Nimo J, König J, Coscia F. A framework for ultra-low-input spatial tissue proteomics. Cell Syst 2023; 14:1002-1014.e5. [PMID: 37909047 DOI: 10.1016/j.cels.2023.10.003] [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: 06/01/2023] [Revised: 08/03/2023] [Accepted: 10/06/2023] [Indexed: 11/02/2023]
Abstract
Spatial proteomics combining microscopy-based cell phenotyping with ultrasensitive mass-spectrometry-based proteomics is an emerging and powerful concept to study cell function and heterogeneity in (patho)physiology. However, optimized workflows that preserve morphological information for phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected tissue are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low-input archival material. Benchmarking in murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions. Applied to human tonsil, we profiled 146 microregions including T and B lymphocyte niches and quantified cell-type-specific markers, cytokines, and transcription factors. These data also highlighted proteome dynamics within activated germinal centers, illuminating sites undergoing B cell proliferation and somatic hypermutation. This approach has broad implications in biomedicine, including early disease profiling and drug target and biomarker discovery. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Anuar Makhmut
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Di Qin
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Sonja Fritzsche
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Jose Nimo
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Janett König
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Fabian Coscia
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany.
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21
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Kitata RB, Yang JC, Chen YJ. Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape. MASS SPECTROMETRY REVIEWS 2023; 42:2324-2348. [PMID: 35645145 DOI: 10.1002/mas.21781] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/17/2021] [Accepted: 01/21/2022] [Indexed: 06/15/2023]
Abstract
The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.
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Affiliation(s)
| | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
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22
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Wamsley NT, Wilkerson EM, Guan L, LaPak KM, Schrank TP, Holmes BJ, Sprung RW, Gilmore PE, Gerndt SP, Jackson RS, Paniello RC, Pipkorn P, Puram SV, Rich JT, Townsend RR, Zevallos JP, Zolkind P, Le QT, Goldfarb D, Major MB. Targeted Proteomic Quantitation of NRF2 Signaling and Predictive Biomarkers in HNSCC. Mol Cell Proteomics 2023; 22:100647. [PMID: 37716475 PMCID: PMC10587640 DOI: 10.1016/j.mcpro.2023.100647] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 09/11/2023] [Accepted: 09/13/2023] [Indexed: 09/18/2023] Open
Abstract
The NFE2L2 (NRF2) oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion, and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry-based targeted proteomics assay based on internal standard-triggered parallel reaction monitoring to quantify 69 NRF2 pathway components and targets, as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved an existing internal standard-triggered parallel reaction monitoring acquisition algorithm, called SureQuant, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded HNSCCs, NRF2 signaling intensity positively correlated with NRF2-activating mutations and with SOX2 protein expression. Protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus infection status. CDKN2A (p16) protein expression positively correlated with the human papilloma virus oncogenic E7 protein and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or formalin-fixed paraffin-embedded archived tissues in under 90 min.
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Affiliation(s)
- Nathan T Wamsley
- Department of Cell Biology and Physiology, Washington University in St Louis, St Louis, Missouri, USA
| | - Emily M Wilkerson
- Department of Cell Biology and Physiology, Washington University in St Louis, St Louis, Missouri, USA
| | - Li Guan
- Department of Radiation Oncology, Stanford University, Stanford, California, USA
| | - Kyle M LaPak
- Department of Cell Biology and Physiology, Washington University in St Louis, St Louis, Missouri, USA
| | - Travis P Schrank
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Brittany J Holmes
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - Robert W Sprung
- Department of Medicine, Washington University School of Medicine, St Louis, Missouri, USA
| | - Petra Erdmann Gilmore
- Department of Medicine, Washington University School of Medicine, St Louis, Missouri, USA
| | - Sophie P Gerndt
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Ryan S Jackson
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Randal C Paniello
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Patrik Pipkorn
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Sidharth V Puram
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Jason T Rich
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Reid R Townsend
- Department of Medicine, Washington University School of Medicine, St Louis, Missouri, USA
| | - José P Zevallos
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Paul Zolkind
- Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA
| | - Quynh-Thu Le
- Department of Radiation Oncology, Stanford University, Stanford, California, USA
| | - Dennis Goldfarb
- Department of Cell Biology and Physiology, Washington University in St Louis, St Louis, Missouri, USA; Institute for Informatics, Washington University in St Louis, St Louis, Missouri, USA.
| | - Michael B Major
- Department of Cell Biology and Physiology, Washington University in St Louis, St Louis, Missouri, USA; Department of Otolaryngology/Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri, USA.
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23
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Montero-Calle A, Garranzo-Asensio M, Rejas-González R, Feliu J, Mendiola M, Peláez-García A, Barderas R. Benefits of FAIMS to Improve the Proteome Coverage of Deteriorated and/or Cross-Linked TMT 10-Plex FFPE Tissue and Plasma-Derived Exosomes Samples. Proteomes 2023; 11:35. [PMID: 37987315 PMCID: PMC10661291 DOI: 10.3390/proteomes11040035] [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: 07/19/2023] [Revised: 09/20/2023] [Accepted: 10/20/2023] [Indexed: 11/22/2023] Open
Abstract
The proteome characterization of complex, deteriorated, or cross-linked protein mixtures as paired clinical FFPE or exosome samples isolated from low plasma volumes (250 µL) might be a challenge. In this work, we aimed at investigating the benefits of FAIMS technology coupled to the Orbitrap Exploris 480 mass spectrometer for the TMT quantitative proteomics analyses of these complex samples in comparison to the analysis of protein extracts from cells, frozen tissue, and exosomes isolated from large volume plasma samples (3 mL). TMT experiments were performed using a two-hour gradient LC-MS/MS with or without FAIMS and two compensation voltages (CV = -45 and CV = -60). In the TMT experiments of cells, frozen tissue, or exosomes isolated from large plasma volumes (3 mL) with FAIMS, a limited increase in the number of identified and quantified proteins accompanied by a decrease in the number of peptides identified and quantified was observed. However, we demonstrated here a noticeable improvement (>100%) in the number of peptide and protein identifications and quantifications for the plasma exosomes isolated from low plasma volumes (250 µL) and FFPE tissue samples in TMT experiments with FAIMS in comparison to the LC-MS/MS analysis without FAIMS. Our results highlight the potential of mass spectrometry analyses with FAIMS to increase the depth into the proteome of complex samples derived from deteriorated, cross-linked samples and/or those where the material was scarce, such as FFPE and plasma-derived exosomes from low plasma volumes (250 µL), which might aid in the characterization of their proteome and proteoforms and in the identification of dysregulated proteins that could be used as biomarkers.
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Affiliation(s)
- Ana Montero-Calle
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
| | - María Garranzo-Asensio
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
| | - Raquel Rejas-González
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
| | - Jaime Feliu
- Translational Oncology Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain;
- Center for Biomedical Research in the Cancer Network (CIBERONC), Instituto de Salud Carlos III, 28046 Madrid, Spain;
| | - Marta Mendiola
- Center for Biomedical Research in the Cancer Network (CIBERONC), Instituto de Salud Carlos III, 28046 Madrid, Spain;
- Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain;
| | - Alberto Peláez-García
- Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain;
| | - Rodrigo Barderas
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
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24
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Nordmann TM, Schweizer L, Metousis A, Thielert M, Rodriguez E, Rahbek-Gjerdrum LM, Stadler PC, Bzorek M, Mund A, Rosenberger FA, Mann M. A Standardized and Reproducible Workflow for Membrane Glass Slides in Routine Histology and Spatial Proteomics. Mol Cell Proteomics 2023; 22:100643. [PMID: 37683827 PMCID: PMC10565769 DOI: 10.1016/j.mcpro.2023.100643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/28/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023] Open
Abstract
Defining the molecular phenotype of single cells in situ is key for understanding tissue architecture in health and disease. Advanced imaging platforms have recently been joined by spatial omics technologies, promising unparalleled insights into the molecular landscape of biological samples. Furthermore, high-precision laser microdissection (LMD) of tissue on membrane glass slides is a powerful method for spatial omics technologies and single-cell type spatial proteomics in particular. However, current histology protocols have not been compatible with glass membrane slides and LMD for automated staining platforms and routine histology procedures. This has prevented the combination of advanced staining procedures with LMD. In this study, we describe a novel method for handling glass membrane slides that enables automated eight-color multiplexed immunofluorescence staining and high-quality imaging followed by precise laser-guided extraction of single cells. The key advance is the glycerol-based modification of heat-induced epitope retrieval protocols, termed "G-HIER." We find that this altered antigen-retrieval solution prevents membrane distortion. Importantly, G-HIER is fully compatible with current antigen retrieval workflows and mass spectrometry-based proteomics and does not affect proteome depth or quality. To demonstrate the versatility of G-HIER for spatial proteomics, we apply the recently introduced deep visual proteomics technology to perform single-cell type analysis of adjacent suprabasal and basal keratinocytes of human skin. G-HIER overcomes previous incompatibility of standard and advanced staining protocols with membrane glass slides and enables robust integration with routine histology procedures, high-throughput multiplexed imaging, and sophisticated downstream spatial omics technologies.
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Affiliation(s)
- Thierry M Nordmann
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Lisa Schweizer
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Andreas Metousis
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Marvin Thielert
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Edwin Rodriguez
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | | | - Michael Bzorek
- Department of Pathology, Zealand University Hospital, Roskilde, Denmark
| | - Andreas Mund
- Proteomics Program, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Florian A Rosenberger
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
| | - Matthias Mann
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Proteomics Program, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
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25
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Schweizer L, Schaller T, Zwiebel M, Karayel Ö, Müller‐Reif JB, Zeng W, Dintner S, Nordmann TM, Hirschbühl K, Märkl B, Claus R, Mann M. Quantitative multiorgan proteomics of fatal COVID-19 uncovers tissue-specific effects beyond inflammation. EMBO Mol Med 2023; 15:e17459. [PMID: 37519267 PMCID: PMC10493576 DOI: 10.15252/emmm.202317459] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 07/11/2023] [Accepted: 07/14/2023] [Indexed: 08/01/2023] Open
Abstract
SARS-CoV-2 may directly and indirectly damage lung tissue and other host organs, but there are few system-wide, untargeted studies of these effects on the human body. Here, we developed a parallelized mass spectrometry (MS) proteomics workflow enabling the rapid, quantitative analysis of hundreds of virus-infected FFPE tissues. The first layer of response to SARS-CoV-2 in all tissues was dominated by circulating inflammatory molecules. Beyond systemic inflammation, we differentiated between systemic and true tissue-specific effects to reflect distinct COVID-19-associated damage patterns. Proteomic changes in the lungs resembled those of diffuse alveolar damage (DAD) in non-COVID-19 patients. Extensive organ-specific changes were also evident in the kidneys, liver, and lymphatic and vascular systems. Secondary inflammatory effects in the brain were related to rearrangements in neurotransmitter receptors and myelin degradation. These MS-proteomics-derived results contribute substantially to our understanding of COVID-19 pathomechanisms and suggest strategies for organ-specific therapeutic interventions.
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Affiliation(s)
- Lisa Schweizer
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Tina Schaller
- Pathology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Maximilian Zwiebel
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Özge Karayel
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- Present address:
Department of Physiological ChemistryGenentechSouth San FranciscoUSA
| | | | - Wen‐Feng Zeng
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | | | - Thierry M Nordmann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Klaus Hirschbühl
- Hematology and Oncology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Bruno Märkl
- Pathology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Rainer Claus
- Pathology, Medical FacultyUniversity of AugsburgAugsburgGermany
- Hematology and Oncology, Medical FacultyUniversity of AugsburgAugsburgGermany
| | - Matthias Mann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
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26
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Pai MGJ, Biswas D, Verma A, Srivastava S. A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy. Expert Rev Proteomics 2023; 20:381-395. [PMID: 37970632 DOI: 10.1080/14789450.2023.2283498] [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: 07/07/2023] [Accepted: 11/01/2023] [Indexed: 11/17/2023]
Abstract
INTRODUCTION Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation. AREAS COVERED This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches. EXPERT OPINION Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.
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Affiliation(s)
- Medha Gayathri J Pai
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Deeptarup Biswas
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Ayushi Verma
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
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27
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Bech JM, Terkelsen T, Bartels AS, Coscia F, Doll S, Zhao S, Zhang Z, Brünner N, Lindebjerg J, Madsen GI, Fang X, Mann M, Afonso Moreira JM. Proteomic Profiling of Colorectal Adenomas Identifies a Predictive Risk Signature for Development of Metachronous Advanced Colorectal Neoplasia. Gastroenterology 2023; 165:121-132.e5. [PMID: 36966943 DOI: 10.1053/j.gastro.2023.03.208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/09/2023] [Accepted: 03/14/2023] [Indexed: 04/17/2023]
Abstract
BACKGROUND & AIMS Colonic adenomatous polyps, or adenomas, are frequent precancerous lesions and the origin of most cases of colorectal adenocarcinoma. However, we know from epidemiologic studies that although most colorectal cancers (CRCs) originate from adenomas, only a small fraction of adenomas (3%-5%) ever progress to cancer. At present, there are no molecular markers to guide follow-up surveillance programs. METHODS We profiled, by mass spectrometry-based proteomics combined with machine learning analysis, a selected cohort of formalin-fixed, paraffin-embedded high-grade (HG) adenomas with long clinical follow-up, collected as part of the Danish national screening program. We grouped subjects in the cohort according to their subsequent history of findings: a nonmetachronous advanced neoplasia group (G0), with no new HG adenomas or CRCs up to 10 years after polypectomy, and a metachronous advanced neoplasia group (G1) where individuals developed a new HG adenoma or CRC within 5 years of diagnosis. RESULTS We generated a proteome dataset from 98 selected HG adenoma samples, including 20 technical replicates, of which 45 samples belonged to the nonmetachronous advanced neoplasia group and 53 to the metachronous advanced neoplasia group. The clear distinction of these 2 groups seen in a uniform manifold approximation and projection plot indicated that the information contained within the abundance of the ∼5000 proteins was sufficient to predict the future occurrence of HG adenomas or development of CRC. CONCLUSIONS We performed an in-depth analysis of quantitative proteomic data from 98 resected adenoma samples using various novel algorithms and statistical packages and found that their proteome can predict development of metachronous advanced lesions and progression several years in advance.
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Affiliation(s)
- Jacob Mathias Bech
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark; Sino-Danish Center for Education and Research, Aarhus University, Aarhus, Denmark
| | - Thilde Terkelsen
- Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Fabian Coscia
- Spatial Proteomics Group, Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association, Berlin, Germany; Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Siqi Zhao
- Beijing Institute of Genomics, China National Center for Bioinformation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Zhaojun Zhang
- Beijing Institute of Genomics, China National Center for Bioinformation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Nils Brünner
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Jan Lindebjerg
- Department of Pathology, Lillebaelt Hospital, Vejle Hospital, Vejle, Denmark
| | | | - Xiangdong Fang
- Beijing Institute of Genomics, China National Center for Bioinformation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Matthias Mann
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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28
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Li Q, Mu L, Yang X, Wang G, Liang J, Wang S, Zhang H, Li Z. Discovery of Oogenesis Biomarkers from Mouse Oocytes Using a Single-Cell Proteomics Approach. J Proteome Res 2023. [PMID: 37154469 DOI: 10.1021/acs.jproteome.3c00157] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
We established an efficient and simplified single-cell proteomics (ES-SCP) workflow to realize proteomics profiling at the single-oocyte level. With the ES-SCP workflow, we constructed a deep coverage proteome library during oocyte maturation, which contained more than 6000 protein groups, and identified and quantified more than 4000 protein groups from a pool of only 15 oocytes at germinal vesicle (GV), GV breakdown (GVBD), and metaphase II (MII) stages. More than 1500 protein groups can be identified from single oocytes. We found that marker proteins including maternal factors and mRNA regulators, such as ZAR1, TLE6, and BTG4, showed significant variations in abundance during oocyte maturation, and it was discovered that maternal mRNA degradation was indispensable during oocyte maturation. Proteomics analysis from single oocytes revealed that changes in antioxidant factors, maternal factors, mRNA stabilization, and energy metabolism were the factors that affect the oocyte quality during ovary aging. Our data laid the foundation for future innovations in assisted reproduction.
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Affiliation(s)
- Qian Li
- State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Lu Mu
- State Key Laboratory of Farm Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Xuebing Yang
- State Key Laboratory of Farm Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Ge Wang
- State Key Laboratory of Farm Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Jing Liang
- State Key Laboratory of Farm Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Shaolin Wang
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China
| | - Hua Zhang
- State Key Laboratory of Farm Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Zhen Li
- State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing 100193, China
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Azimi A, Patrick E, Teh R, Kim J, Fernandez-Penas P. Proteomic profiling of cutaneous melanoma explains the aggressiveness of distant organ metastasis. Exp Dermatol 2023. [PMID: 37082900 DOI: 10.1111/exd.14814] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/05/2023] [Accepted: 04/07/2023] [Indexed: 04/22/2023]
Abstract
Despite recent developments in managing metastatic melanomas, patients' overall survival remains low. Therefore, the current study aims to understand better the proteome-wide changes associated with melanoma metastasis that will assist with identifying targeted therapies. The latest development in mass spectrometry-based proteomics, together with extensive bioinformatics analysis, was used to investigate the molecular changes in 60 formalin-fixed and paraffin-embedded samples of primary and lymph nodes (LN) and distant organ metastatic melanomas. A total of 4631 proteins were identified, of which 72 and 453 were significantly changed between the LN and distant organ metastatic melanomas compared to the primary lesions (adj. p-value <0.05). An increase in proteins such as SLC9A3R1, CD20 and GRB2 and a decrease in CST6, SERPINB5 and ARG1 were associated with regional LN metastasis. By contrast, increased metastatic activities in distant organ metastatic melanomas were related to higher levels of CEACAM1, MC1R, AKT1 and MMP3-9 and decreased levels of CDKN2A, SDC1 and SDC4 proteins. Furthermore, machine learning analysis classified the lesions with up to 92% accuracy based on their metastatic status. The findings from this study provide up to date proteome-level information about the progression of melanomas to regional LN and distant organs, leading to the identification of protein signatures with potential for clinical translation.
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Affiliation(s)
- Ali Azimi
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
| | - Ellis Patrick
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- School of Mathematics and Statistics, Faculty of Science, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Rachel Teh
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
| | - Jennifer Kim
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- Department of Tissue Pathology and Diagnostic Oncology, Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales, Australia
| | - Pablo Fernandez-Penas
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
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Messner CB, Demichev V, Wang Z, Hartl J, Kustatscher G, Mülleder M, Ralser M. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 2023; 23:e2200013. [PMID: 36349817 DOI: 10.1002/pmic.202200013] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/11/2022]
Abstract
There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.
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Affiliation(s)
- Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Vadim Demichev
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ziyue Wang
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Hartl
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, Scotland, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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Mar D, Babenko IM, Zhang R, Noble WS, Denisenko O, Vaisar T, Bomsztyk K. MultiomicsTracks96: A high throughput PIXUL-Matrix-based toolbox to profile frozen and FFPE tissues multiomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.533031. [PMID: 36993219 PMCID: PMC10055122 DOI: 10.1101/2023.03.16.533031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Background The multiome is an integrated assembly of distinct classes of molecules and molecular properties, or "omes," measured in the same biospecimen. Freezing and formalin-fixed paraffin-embedding (FFPE) are two common ways to store tissues, and these practices have generated vast biospecimen repositories. However, these biospecimens have been underutilized for multi-omic analysis due to the low throughput of current analytical technologies that impede large-scale studies. Methods Tissue sampling, preparation, and downstream analysis were integrated into a 96-well format multi-omics workflow, MultiomicsTracks96. Frozen mouse organs were sampled using the CryoGrid system, and matched FFPE samples were processed using a microtome. The 96-well format sonicator, PIXUL, was adapted to extract DNA, RNA, chromatin, and protein from tissues. The 96-well format analytical platform, Matrix, was used for chromatin immunoprecipitation (ChIP), methylated DNA immunoprecipitation (MeDIP), methylated RNA immunoprecipitation (MeRIP), and RNA reverse transcription (RT) assays followed by qPCR and sequencing. LC-MS/MS was used for protein analysis. The Segway genome segmentation algorithm was used to identify functional genomic regions, and linear regressors based on the multi-omics data were trained to predict protein expression. Results MultiomicsTracks96 was used to generate 8-dimensional datasets including RNA-seq measurements of mRNA expression; MeRIP-seq measurements of m6A and m5C; ChIP-seq measurements of H3K27Ac, H3K4m3, and Pol II; MeDIP-seq measurements of 5mC; and LC-MS/MS measurements of proteins. We observed high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles (ChIP-seq: H3K27Ac, H3K4m3, Pol II; MeDIP-seq: 5mC) was able to recapitulate and predict organ-specific super-enhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic expression profiles can be more accurately predicted by the full suite of multi-omics data, compared to using epigenomic, transcriptomic, or epitranscriptomic measurements individually. Conclusions The MultiomicsTracks96 workflow is well suited for high dimensional multi-omics studies - for instance, multiorgan animal models of disease, drug toxicities, environmental exposure, and aging as well as large-scale clinical investigations involving the use of biospecimens from existing tissue repositories.
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Fu Q, Murray CI, Karpov OA, Van Eyk JE. Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis. MASS SPECTROMETRY REVIEWS 2023; 42:873-886. [PMID: 34786750 DOI: 10.1002/mas.21750] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 10/11/2021] [Accepted: 10/27/2021] [Indexed: 06/13/2023]
Abstract
Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.
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Affiliation(s)
- Qin Fu
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Christopher I Murray
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Oleg A Karpov
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Jennifer E Van Eyk
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
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Barnabas G, Goebeler V, Tsui J, Bush JW, Lange PF. ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues. Anal Chem 2023; 95:3291-3299. [PMID: 36724070 PMCID: PMC9933881 DOI: 10.1021/acs.analchem.2c04264] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/17/2023] [Indexed: 02/02/2023]
Abstract
Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies, but protein extraction and subsequent sample processing steps have been shown to be challenging for mass spectrometry (MS) analysis. Streamlined high-throughput sample preparation workflows are essential for efficient peptide extraction from complex clinical specimens such as fresh frozen tissues or FFPE. Overall, proteome analysis has gained significant improvements in the instrumentation, acquisition methods, sample preparation workflows, and analysis pipelines, yet even the most recent FFPE workflows remain complex and are not readily scalable. Here, we present an optimized workflow for automated sonication-free acid-assisted proteome (ASAP) extraction from FFPE sections. ASAP enables efficient protein extraction from FFPE specimens, achieving similar proteome coverage as established methods using expensive sonicators, resulting in reduced sample processing time. The broad applicability of ASAP on archived pediatric tumor FFPE specimens resulted in high-quality data with increased proteome coverage and quantitative reproducibility. Our study demonstrates the practicality and superiority of the ASAP workflow as a streamlined, time- and cost-effective pipeline for high-throughput FFPE proteomics of clinical specimens.
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Affiliation(s)
- Georgina
D. Barnabas
- Department
of Pathology, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Michael
Cuccione Childhood Cancer Research Program, BC Children’s Hospital and Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Verena Goebeler
- Department
of Pediatrics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Michael
Cuccione Childhood Cancer Research Program, BC Children’s Hospital and Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Janice Tsui
- Department
of Pathology, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Michael
Cuccione Childhood Cancer Research Program, BC Children’s Hospital and Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Jonathan W. Bush
- Department
of Pathology, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Philipp F. Lange
- Department
of Pathology, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Michael
Cuccione Childhood Cancer Research Program, BC Children’s Hospital and Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
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Thorsen ASF, Riber LPS, Rasmussen LM, Overgaard M. A targeted multiplex mass spectrometry method for quantitation of abundant matrix and cellular proteins in formalin-fixed paraffin embedded arterial tissue. J Proteomics 2023; 272:104775. [PMID: 36414230 DOI: 10.1016/j.jprot.2022.104775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/30/2022] [Accepted: 11/17/2022] [Indexed: 11/20/2022]
Abstract
Assessment of proteins in formalin-fixed paraffin-embedded (FFPE) tissue traditionally hinges on immunohistochemistry and immunoblotting. These methods are far from optimal for quantitative studies and not suitable for large-scale testing of multiple protein panels. In this study, we developed and optimised a novel targeted isotope dilution mass spectrometry (MS)-based method for FFPE samples, designed to quantitate 17 matrix and cytosolic proteins abundantly present in arterial tissue. Our new method was developed on FFPE human tissue samples of the internal thoracic artery obtained from coronary artery bypass graft (CABG) operations. The workflow has a limit of 60 samples per day. Assay precision improved by normalisation to both beta-actin and smooth muscle actin with inter-assay coefficients of variation (CV) ranging from 5.3% to 31.9%. To demonstrate clinical utility of the assay we analysed 40 FFPE artery specimens from two groups of patients with or without type 2 diabetes. We observed increased levels of collagen type IV α1 and α2 in patients with diabetes. The assay is scalable for larger cohorts and advantageous for pathophysiological studies in diabetes and the method is easily convertible to analysis of other proteins in FFPE artery samples. SIGNIFICANCE: This article presents a novel robust and precise targeted mass spectrometry assay for relative quantitation of a panel of abundant matrix and cellular arterial proteins in archived formalin-fixed paraffin-embedded arterial samples. We demonstrate its utility in pathophysiological studies of cardiovascular disease in diabetes.
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Affiliation(s)
- Anne-Sofie Faarvang Thorsen
- Department of Clinical Biochemistry and Center for Individualised Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark; Steno Diabetes Center Odense (SDCO), Odense, Denmark
| | - Lars Peter Schødt Riber
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark; Department of Cardiac, Thoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark
| | - Lars Melholt Rasmussen
- Department of Clinical Biochemistry and Center for Individualised Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Martin Overgaard
- Department of Clinical Biochemistry and Center for Individualised Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
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Yang L, Fan W, Xu Y. Chameleon-like microbes promote microecological differentiation of Daqu. Food Microbiol 2023; 109:104144. [DOI: 10.1016/j.fm.2022.104144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/31/2022] [Accepted: 09/12/2022] [Indexed: 11/28/2022]
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Hepker M, Clabaugh G, Jin H, Kanthasamy AG. New protocol for kinetic assay seeding ability recovery "KASAR" from formalin-fixed paraffin-embedded tissues. Front Mol Biosci 2023; 10:1087982. [PMID: 36793788 PMCID: PMC9922999 DOI: 10.3389/fmolb.2023.1087982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 01/19/2023] [Indexed: 01/31/2023] Open
Abstract
The real-time quaking-induced conversion (RT-QuIC) alpha-synuclein (aSyn) protein kinetic seeding assay has been very useful for detecting pathological aggregates in various synucleinopathies including Parkinson's disease (PD). This biomarker assay relies on fresh frozen tissue to effectively seed and amplify aSyn aggregating protein. With vast repositories of formalin-fixed paraffin-embedded (FFPE) tissues, it is paramount to harness the power of kinetic assays to unlock the diagnostic potential of archived FFPE biospecimens. However, the major challenge posed by significantly reduced amplification of formalin-fixed tissues in the assay suggests that formalin fixation deterred monomer interaction with the sample seed and depressed subsequent protein aggregation. To overcome this challenge, we developed a kinetic assay seeding ability recovery (KASAR) protocol to maintain the integrity of the tissue and seeding protein. For this, we implemented a series of heating steps with the brain tissue suspended in a buffer composed of 500 mM tris-HCl (pH 7.5) and 0.02% SDS after the standard deparaffinization of the tissue sections. Initially, samples from seven human brain samples, including four samples from patients diagnosed with dementia with Lewy bodies (DLB) and three samples from healthy controls without DLB, were compared to fresh frozen samples under three different, but clinically common sample storage conditions: formalin-fixed, FFPE, and FFPE slices cut 5 µm thick. The KASAR protocol was able to recover seeding activity for all positive samples in all storage conditions. Next, 28 FFPE samples from the submandibular gland (SMG) of patients diagnosed with PD, incidental Lewy body disease (ILBD), or healthy controls were tested with 93% of results replicating when blinded. With samples of only a few milligrams, this protocol recovered the same quality of seeding in formalin-fixed tissue as fresh frozen tissue. Moving forward, protein aggregate kinetic assays, in conjunction with the KASAR protocol, can be used to understand and diagnose neurodegenerative diseases more comprehensively. Overall, our KASAR protocol unlocks and restores the seeding ability of formalin-fixed paraffin-embedded tissues for the amplification of biomarker protein aggregates in kinetic assays.
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Affiliation(s)
- Monica Hepker
- Parkinson Disorders Research Laboratory, Iowa Center for Advanced Neurotoxicology, Department of Biomedical Sciences, Iowa State University, Ames, IA, United States
| | - Griffin Clabaugh
- Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of GA, Athens, GA, United States
| | - Huajun Jin
- Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of GA, Athens, GA, United States
| | - Anumantha G. Kanthasamy
- Parkinson Disorders Research Laboratory, Iowa Center for Advanced Neurotoxicology, Department of Biomedical Sciences, Iowa State University, Ames, IA, United States,Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of GA, Athens, GA, United States,*Correspondence: Anumantha G. Kanthasamy,
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Development of a Laser Microdissection-Coupled Quantitative Shotgun Lipidomic Method to Uncover Spatial Heterogeneity. Cells 2023; 12:cells12030428. [PMID: 36766770 PMCID: PMC9913738 DOI: 10.3390/cells12030428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/21/2023] [Accepted: 01/24/2023] [Indexed: 01/31/2023] Open
Abstract
Lipid metabolic disturbances are associated with several diseases, such as type 2 diabetes or malignancy. In the last two decades, high-performance mass spectrometry-based lipidomics has emerged as a valuable tool in various fields of biology. However, the evaluation of macroscopic tissue homogenates leaves often undiscovered the differences arising from micron-scale heterogeneity. Therefore, in this work, we developed a novel laser microdissection-coupled shotgun lipidomic platform, which combines quantitative and broad-range lipidome analysis with reasonable spatial resolution. The multistep approach involves the preparation of successive cryosections from tissue samples, cross-referencing of native and stained images, laser microdissection of regions of interest, in situ lipid extraction, and quantitative shotgun lipidomics. We used mouse liver and kidney as well as a 2D cell culture model to validate the novel workflow in terms of extraction efficiency, reproducibility, and linearity of quantification. We established that the limit of dissectible sample area corresponds to about ten cells while maintaining good lipidome coverage. We demonstrate the performance of the method in recognizing tissue heterogeneity on the example of a mouse hippocampus. By providing topological mapping of lipid metabolism, the novel platform might help to uncover region-specific lipidomic alterations in complex samples, including tumors.
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Pu J, Xue C, Huo S, Shen Q, Qu Y, Yang X, An B, Angel TE, Chen Z, Mehl JT, Tang H, Yang E, Sikorski TW, Qu J. Highly Accurate and Robust Absolute Quantification of Target Proteins in Formalin-Fixed Paraffin-Embedded (FFPE) Tissues by LC-MS. Anal Chem 2023; 95:924-934. [PMID: 36534410 PMCID: PMC10581745 DOI: 10.1021/acs.analchem.2c03473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Accurate, absolute liquid chromatography-mass spectrometry (LC-MS)-based quantification of target proteins in formalin-fixed paraffin-embedded (FFPE) tissues would greatly expand sample availability for pharmaceutical/clinical investigations but remains challenging owing to the following issues: (i) efficient/quantitative recovery of target signature peptides from FFPE tissues is essential but an optimal procedure for targeted, absolute quantification is lacking; (ii) most FFPE samples are long-term-stored; severe immunohistochemistry (IHC) signal losses of target proteins during storage were widely reported, while the effect of storage on LC-MS-based methods was unknown; and (iii) the proper strategy to prepare calibration/quality-control samples to ensure accurate targeted protein analysis in FFPE tissues remained elusive. Using targeted quantification of monoclonal antibody (mAb), antigen, and 40 tissue markers in FFPE tissues as a model system, we extensively investigate those issues and develope an LC-MS-based strategy enabling accurate and precise targeted protein quantification in FFPE samples. First, we demonstrated a surfactant cocktail-based procedure (f-SEPOD), providing high/reproducible recovery of target signature peptides from FFPE tissues. Second, a heat-accelerated degradation study within a roughly estimated 5 year storage period recapitulated the loss of protein IHC signals while LC-MS signals of all targets remained constant. This indicates that the storage of FFPE tissues mainly causes decreased immunoreactivity but unlikely chemical degradation of proteins, which strongly suggests that the storage of FFPE tissues does not cause significant quantitative bias for LC-MS-based methods. Third, while a conventional spike-and-extract approach for calibration caused substantial negative biases, a novel approach, using FFPE-treated calibration standards, enabled accurate and precise quantification. With the pipeline, we conducted the first-ever pharmacokinetics measurement of mAb and its target in FFPE tissues, where time courses by FFPE vs fresh tissues showed excellent correlation.
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Affiliation(s)
- Jie Pu
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York 14214, United States
| | - Chao Xue
- Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, New York 14214, United States
| | - Shihan Huo
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York 14214, United States
| | - Qingqing Shen
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York 14214, United States
| | - Yang Qu
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York 14214, United States; New York State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, New York 14203, United States
| | - Xinxin Yang
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York 14214, United States
| | - Bo An
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States
| | - Thomas E. Angel
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States
| | - Zhuo Chen
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States
| | - John T. Mehl
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States
| | - Huaping Tang
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States
| | - Eric Yang
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States
| | - Timothy W. Sikorski
- Bioanalysis, Immunogenicity & Biomarkers, In-Vitro/In-Vivo Translation, R&D Research, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States; Phone: (610) 270-4978
| | - Jun Qu
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York 14214, United States; New York State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, New York 14203, United States
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Obi EN, Tellock DA, Thomas GJ, Veenstra TD. Biomarker Analysis of Formalin-Fixed Paraffin-Embedded Clinical Tissues Using Proteomics. Biomolecules 2023; 13:biom13010096. [PMID: 36671481 PMCID: PMC9855471 DOI: 10.3390/biom13010096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 01/06/2023] Open
Abstract
The relatively recent developments in mass spectrometry (MS) have provided novel opportunities for this technology to impact modern medicine. One of those opportunities is in biomarker discovery and diagnostics. Key developments in sample preparation have enabled a greater range of clinical samples to be characterized at a deeper level using MS. While most of these developments have focused on blood, tissues have also been an important resource. Fresh tissues, however, are difficult to obtain for research purposes and require significant resources for long-term storage. There are millions of archived formalin-fixed paraffin-embedded (FFPE) tissues within pathology departments worldwide representing every possible tissue type including tumors that are rare or very small. Owing to the chemical technique used to preserve FFPE tissues, they were considered intractable to many newer proteomics techniques and primarily only useful for immunohistochemistry. In the past couple of decades, however, researchers have been able to develop methods to extract proteins from FFPE tissues in a form making them analyzable using state-of-the-art technologies such as MS and protein arrays. This review will discuss the history of these developments and provide examples of how they are currently being used to identify biomarkers and diagnose diseases such as cancer.
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40
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Cox J. Prediction of peptide mass spectral libraries with machine learning. Nat Biotechnol 2023; 41:33-43. [PMID: 36008611 DOI: 10.1038/s41587-022-01424-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/11/2022] [Indexed: 01/21/2023]
Abstract
The recent development of machine learning methods to identify peptides in complex mass spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods for peptide identification, such as search engines and experimental spectral libraries, are being superseded by deep learning models that allow the fragmentation spectra of peptides to be predicted from their amino acid sequence. These new approaches, including recurrent neural networks and convolutional neural networks, use predicted in silico spectral libraries rather than experimental libraries to achieve higher sensitivity and/or specificity in the analysis of proteomics data. Machine learning is galvanizing applications that involve large search spaces, such as immunopeptidomics and proteogenomics. Current challenges in the field include the prediction of spectra for peptides with post-translational modifications and for cross-linked pairs of peptides. Permeation of machine-learning-based spectral prediction into search engines and spectrum-centric data-independent acquisition workflows for diverse peptide classes and measurement conditions will continue to push sensitivity and dynamic range in proteomics applications in the coming years.
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Affiliation(s)
- Jürgen Cox
- Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.
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41
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Bader JM, Deigendesch N, Misch M, Mann M, Koch A, Meissner F. Proteomics separates adult-type diffuse high-grade gliomas in metabolic subgroups independent of 1p/19q codeletion and across IDH mutational status. Cell Rep Med 2022; 4:100877. [PMID: 36584682 PMCID: PMC9873829 DOI: 10.1016/j.xcrm.2022.100877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 07/15/2022] [Accepted: 12/07/2022] [Indexed: 12/30/2022]
Abstract
High-grade adult-type diffuse gliomas are malignant neuroepithelial tumors with poor survival rates in combined chemoradiotherapy. The current WHO classification is based on IDH1/2 mutational and 1p/19q codeletion status. Glioma proteome alterations remain undercharacterized despite their promise for a better molecular patient stratification and therapeutic target identification. Here, we use mass spectrometry to characterize 42 formalin-fixed, paraffin-embedded (FFPE) samples from IDH-wild-type (IDHwt) gliomas, IDH-mutant (IDHmut) gliomas with and without 1p/19q codeletion, and non-neoplastic controls. Based on more than 5,500 quantified proteins and 5,000 phosphosites, gliomas separate by IDH1/2 mutational status but not by 1p/19q status. Instead, IDHmut gliomas split into two proteomic subtypes with widespread perturbations, including aerobic/anaerobic energy metabolism. Validations with three independent glioma proteome datasets confirm these subgroups and link the IDHmut subtypes to the established proneural and classic/mesenchymal subtypes in IDHwt glioma. This demonstrates common phenotypic subtypes across the IDH status with potential therapeutic implications for patients with IDHmut gliomas.
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Affiliation(s)
- Jakob Maximilian Bader
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Nikolaus Deigendesch
- Pathology, Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland
| | - Martin Misch
- Department of Neurosurgery, Charité, Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, and Humboldt-Universität zu Berlin, Berlin Institute of Health, 13353 Berlin, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany,Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Arend Koch
- Department of Neuropathology, Charité, Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, and Humboldt-Universität zu Berlin, Berlin Institute of Health, 13353 Berlin, Germany.
| | - Felix Meissner
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany; Department of Systems Immunology and Proteomics, Institute of Innate Immunity, University Hospital Bonn, 53127 Bonn, Germany.
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Schoffman H, Levin Y, Itzhaki-Alfia A, Tselekovits L, Gonen L, Vainer GW, Hout-Siloni G, Barshack I, Cohen ZR, Margalit N, Shahar T. Comparison of matched formalin-fixed paraffin embedded and fresh frozen meningioma tissue reveals bias in proteomic profiles. Proteomics 2022; 22:e2200085. [PMID: 36098096 DOI: 10.1002/pmic.202200085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 08/26/2022] [Accepted: 08/26/2022] [Indexed: 12/29/2022]
Abstract
Tissue biopsies are most commonly archived in a paraffin block following tissue fixation with formaldehyde (FFPE) or as fresh frozen tissue (FFT). While both methods preserve biological samples, little is known about how they affect the quantifiable proteome. We performed a 'bottom-up' proteomic analysis (N = 20) of short and long-term archived FFPE surgical samples of human meningiomas and compared them to matched FFT specimens. FFT facilitated a similar number of proteins assigned by MetaMorpheus compared with matched FFPE specimens (5378 vs. 5338 proteins, respectively (p = 0.053), regardless of archival time. However, marked differences in the proteome composition were apparent between FFPE and FFT specimens. Twenty-three percent of FFPE-derived peptides and 8% of FFT-derived peptides contained at least one chemical modification. Methylation and formylation were most prominent in FFPE-derived peptides (36% and 17% of modified FFPE peptides, respectively) while, most of phosphorylation and iron modifications appeared in FFT-derived peptides (p < 0.001). A mean 14% (± 2.9) of peptides identified in FFPE contained at least one modified Lysine residue. Importantly, larger proteins were significantly overrepresented in FFT specimens, while FFPE specimens were enriched with smaller proteins.
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Affiliation(s)
- Hanan Schoffman
- Laboratory of Molecular Neuro Oncology, Neurosurgery Department, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Yishai Levin
- de Botton Institute for Protein Profiling, The Nancy and Stephen Grand Israel National Center for Personalized Medicine, Weizmann Institute of Science, Rehovot, Israel
| | | | - Lea Tselekovits
- Laboratory of Molecular Neuro Oncology, Neurosurgery Department, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Lior Gonen
- Neurosurgery Department, Shaare Zedek Medical Center, Hebrew University Medical School, Jerusalem, Israel
| | - Gilad Wolf Vainer
- Department of Pathology, Hadassah Hebrew University Medical School, Jerusalem, Israel
| | - Goni Hout-Siloni
- Department of Pathology, Sheba Medical Center, Ramat Gan, Israel
| | - Iris Barshack
- Department of Pathology, Sheba Medical Center, Ramat Gan, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Zvi R Cohen
- Department of Neurosurgery, Sheba Medical Center, Ramat Gan, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Nevo Margalit
- Neurosurgery Department, Shaare Zedek Medical Center, Hebrew University Medical School, Jerusalem, Israel
| | - Tal Shahar
- Laboratory of Molecular Neuro Oncology, Neurosurgery Department, Shaare Zedek Medical Center, Jerusalem, Israel.,Neurosurgery Department, Shaare Zedek Medical Center, Hebrew University Medical School, Jerusalem, Israel
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43
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Woo J, Schoenfeld M, Sun X, Iraguha T, Zhou Z, Zhang Q. Mouse Paneth Cell-Enriched Proteome Enabled by Laser Capture Microdissection. J Proteome Res 2022; 21:2435-2442. [PMID: 36153828 PMCID: PMC9671084 DOI: 10.1021/acs.jproteome.2c00311] [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] [Indexed: 11/30/2022]
Abstract
Paneth cells are antimicrobial peptide-secreting cells located at the base of the crypts of the small intestine. The proteome of Paneth cells is not well defined because of their coexistence with stem cells, making it difficult to culture Paneth cells alone in vitro. Using a simplified toluidine blue O method for staining mouse intestinal tissue, laser capture microdissection (LCM) to isolate cells from the crypt region, and surfactant-assisted one-pot protein digestion, we identified more than 1300 proteins from crypts equivalent to 18,000 cells. Compared with the proteomes of villi and smooth muscle regions, the crypt proteome is highly enriched in defensins, lysozymes, and other antimicrobial peptides that are characteristic of Paneth cells. The sensitivity of the LCM-based proteomics approach was also assessed using a smaller number of cell equivalent tissues: a comparable proteomic coverage can be achieved with 3600 cells. This work is the first proteomics study of intestinal tissue enriched with Paneth cells. The simplified workflow enables profiling of Paneth cell-associated pathological changes at the proteome level directly from frozen intestinal tissue. It may also be useful for proteomics studies of other spatially resolved cell types from other tissues.
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Affiliation(s)
- Jongmin Woo
- Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC 28081
| | - Madeline Schoenfeld
- Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC 28081
| | - Xinguo Sun
- Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC 28081
| | - Thierry Iraguha
- Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC 28081
| | - Zhanxiang Zhou
- Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC 28081
- Department of Nutrition, University of North Carolina at Greensboro, Greensboro, NC 27402
| | - Qibin Zhang
- Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC 28081
- Department of Chemistry & Biochemistry, University of North Carolina at Greensboro, Greensboro, NC 27402
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44
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Poulos RC, Cai Z, Robinson PJ, Reddel RR, Zhong Q. Opportunities for pharmacoproteomics in biomarker discovery. Proteomics 2022; 23:e2200031. [PMID: 36086888 DOI: 10.1002/pmic.202200031] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/30/2022] [Accepted: 09/06/2022] [Indexed: 11/08/2022]
Abstract
Proteomic data are a uniquely valuable resource for drug response prediction and biomarker discovery because most drugs interact directly with proteins in target cells rather than with DNA or RNA. Recent advances in mass spectrometry and associated processing methods have enabled the generation of large-scale proteomic datasets. Here we review the significant opportunities that currently exist to combine large-scale proteomic data with drug-related research, a field termed pharmacoproteomics. We describe successful applications of drug response prediction using molecular data, with an emphasis on oncology. We focus on technical advances in data-independent acquisition mass spectrometry (DIA-MS) that can facilitate the discovery of protein biomarkers for drug responses, alongside the increased availability of big biomedical data. We spotlight new opportunities for machine learning in pharmacoproteomics, driven by the combination of these large datasets and improved high-performance computing. Finally, we explore the value of pre-clinical models for pharmacoproteomic studies and the accompanying challenges of clinical validation. We propose that pharmacoproteomics offers the potential for novel discovery and innovation within the cancer landscape. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Rebecca C Poulos
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Zhaoxiang Cai
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Roger R Reddel
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Qing Zhong
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
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45
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Mukherjee A, Ghosh S, Biswas D, Rao A, Shetty P, Epari S, Moiyadi A, Srivastava S. Clinical Proteomics for Meningioma: An Integrated Workflow for Quantitative Proteomics and Biomarker Validation in Formalin-Fixed Paraffin-Embedded Tissue Samples. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:512-520. [PMID: 36036964 DOI: 10.1089/omi.2022.0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.
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Affiliation(s)
- Arijit Mukherjee
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Susmita Ghosh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Deeptarup Biswas
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Aishwarya Rao
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | | | | | | | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
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46
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Boys EL, Liu J, Robinson PJ, Reddel RR. Clinical applications of mass spectrometry-based proteomics in cancer: where are we? Proteomics 2022; 23:e2200238. [PMID: 35968695 DOI: 10.1002/pmic.202200238] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/07/2022] [Accepted: 08/09/2022] [Indexed: 11/12/2022]
Abstract
Tumor tissue processing methodologies in combination with data-independent acquisition mass spectrometry (DIA-MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS-based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA-MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi-omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Emma L Boys
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Jia Liu
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.,The Kinghorn Cancer Centre, St Vincent's Hospital, Darlinghurst, NSW, Australia.,School of Clinical Medicine, St Vincent's Campus, University of New South Wales, Sydney, NSW, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Roger R Reddel
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
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47
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Nwosu AJ, Misal SA, Truong T, Carson RH, Webber KGI, Axtell NB, Liang Y, Johnston SM, Virgin KL, Smith EG, Thomas GV, Morgan T, Price JC, Kelly RT. In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 μm. J Proteome Res 2022; 21:2237-2245. [PMID: 35916235 PMCID: PMC9767749 DOI: 10.1021/acs.jproteome.2c00409] [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: 11/29/2022]
Abstract
Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories to cost-effectively preserve valuable specimens for later study. With the rapid growth of spatial proteomics, FFPE tissues can serve as a more accessible alternative to more commonly used frozen tissues. However, extracting proteins from FFPE tissues is challenging due to cross-links formed between proteins and formaldehyde. Here, we have adapted the nanoPOTS sample processing workflow, which was previously applied to single cells and fresh-frozen tissues, to profile protein expression from FFPE tissues. Following the optimization of extraction solvents, times, and temperatures, we identified an average of 1312 and 3184 high-confidence master proteins from 10 μm thick FFPE-preserved mouse liver tissue squares having lateral dimensions of 50 and 200 μm, respectively. The observed proteome coverage for FFPE tissues was on average 88% of that achieved for similar fresh-frozen tissues. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. This modified nanodroplet processing in one pot for trace samples (nanoPOTS) and fully automated processing in one pot for trace sample (autoPOTS) workflows provides the greatest coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues. Data are available via ProteomeXchange with identifier PXD029729.
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Affiliation(s)
- Andikan J Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Santosh A Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Richard H Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Nathaniel B Axtell
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kenneth L Virgin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ethan G Smith
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - George V Thomas
- Knight Cancer Center, Oregon Health & Science University, Portland, Oregon 97239, United States
| | - Terry Morgan
- Department of Pathology, Oregon Health & Science University, Portland, Oregon 97239, United States
| | - John C Price
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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48
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Kwon Y, Piehowski PD, Zhao R, Sontag RL, Moore RJ, Burnum-Johnson KE, Smith RD, Qian WJ, Kelly RT, Zhu Y. Hanging drop sample preparation improves sensitivity of spatial proteomics. LAB ON A CHIP 2022; 22:2869-2877. [PMID: 35838077 PMCID: PMC9320080 DOI: 10.1039/d2lc00384h] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
Spatial proteomics holds great promise for revealing tissue heterogeneity in both physiological and pathological conditions. However, one significant limitation of most spatial proteomics workflows is the requirement of large sample amounts that blurs cell-type-specific or microstructure-specific information. In this study, we developed an improved sample preparation approach for spatial proteomics and integrated it with our previously-established laser capture microdissection (LCM) and microfluidics sample processing platform. Specifically, we developed a hanging drop (HD) method to improve the sample recovery by positioning a nanowell chip upside-down during protein extraction and tryptic digestion steps. Compared with the commonly-used sitting-drop method, the HD method keeps the tissue pixel away from the container surface, and thus improves the accessibility of the extraction/digestion buffer to the tissue sample. The HD method can increase the MS signal by 7 fold, leading to a 66% increase in the number of identified proteins. An average of 721, 1489, and 2521 proteins can be quantitatively profiled from laser-dissected 10 μm-thick mouse liver tissue pixels with areas of 0.0025, 0.01, and 0.04 mm2, respectively. The improved system was further validated in the study of cell-type-specific proteomes of mouse uterine tissues.
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Affiliation(s)
- Yumi Kwon
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Paul D Piehowski
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Rui Zhao
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Ryan L Sontag
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Kristin E Burnum-Johnson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Ryan T Kelly
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
- Department of Chemistry and Biochemistry, Brigham Young University, C100 BNSN, Provo, UT 84602, USA
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
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49
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Kaufmann M, Schaupp AL, Sun R, Coscia F, Dendrou CA, Cortes A, Kaur G, Evans HG, Mollbrink A, Navarro JF, Sonner JK, Mayer C, DeLuca GC, Lundeberg J, Matthews PM, Attfield KE, Friese MA, Mann M, Fugger L. Identification of early neurodegenerative pathways in progressive multiple sclerosis. Nat Neurosci 2022; 25:944-955. [PMID: 35726057 DOI: 10.1038/s41593-022-01097-3] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/16/2022] [Indexed: 11/08/2022]
Abstract
Progressive multiple sclerosis (MS) is characterized by unrelenting neurodegeneration, which causes cumulative disability and is refractory to current treatments. Drug development to prevent disease progression is an urgent clinical need yet is constrained by an incomplete understanding of its complex pathogenesis. Using spatial transcriptomics and proteomics on fresh-frozen human MS brain tissue, we identified multicellular mechanisms of progressive MS pathogenesis and traced their origin in relation to spatially distributed stages of neurodegeneration. By resolving ligand-receptor interactions in local microenvironments, we discovered defunct trophic and anti-inflammatory intercellular communications within areas of early neuronal decline. Proteins associated with neuronal damage in patient samples showed mechanistic concordance with published in vivo knockdown and central nervous system (CNS) disease models, supporting their causal role and value as potential therapeutic targets in progressive MS. Our findings provide a new framework for drug development strategies, rooted in an understanding of the complex cellular and signaling dynamics in human diseased tissue that facilitate this debilitating disease.
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Affiliation(s)
- Max Kaufmann
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Anna-Lena Schaupp
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Rosa Sun
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Neurosurgery, Queen Elizabeth Hospital, Birmingham, UK
| | - Fabian Coscia
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Spatial Proteomics Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Calliope A Dendrou
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adrian Cortes
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Gurman Kaur
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hayley G Evans
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Annelie Mollbrink
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - José Fernández Navarro
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Jana K Sonner
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Christina Mayer
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Gabriele C DeLuca
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Kathrine E Attfield
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Manuel A Friese
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias Mann
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK.
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50
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Yang L, Weng S, Qian X, Wang M, Ying W. Strategy for Microscale Extraction and Proteome Profiling of Peripheral Blood Mononuclear Cells. Anal Chem 2022; 94:8827-8832. [PMID: 35699231 DOI: 10.1021/acs.analchem.1c05365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Peripheral blood mononuclear cells (PBMCs) play vital roles in physiological and pathological processes and represent a rich source for disease monitoring. Typical molecular profiling on PBMCs involves the sorting of cell subsets and thus requires a large volume of peripheral blood (PB), which impedes the clinical practicability of omics tools in PBMC measurements. It would be clinically invaluable to develop a convenient approach for preparing PBMCs from small volumes of PB and for deep proteome profiling of PBMCs. To this end, here, we designed an apparatus (PBMC-mCap) for microscale enrichment and proteome analysis of PBMCs, which pushed the needed PB volume from the normal 2 mL or higher to 100 μL or lower, comparable to the volume of a drop of finger blood. A PBMC-specific mass spectra library containing 8869 proteins and 121,956 peptides was further built, which, in combination with the optimized data-independent acquisition strategy, helped to identify 6000 and 6500 proteins from PBMCs with 100 μL and 1 mL of PB as initial materials, respectively. Further application of the strategy for PBMC proteomes revealed a steady difference between gender (male vs female) and upon stimulus (COVID-19 vaccination). For the latter, we observed differentially expressed genes and pathways involving the activation of immune cells, including the NF-κB pathway, inflammation response, and antiviral response. Our strategy for the proteome analysis of microscale PBMCs may provide a convenient clinical toolkit for disease diagnosis and healthy state monitoring.
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Affiliation(s)
- Li Yang
- School of Basic Medical Science, Anhui Medical University, Hefei 230032, China.,State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing 102206, China
| | - Shuang Weng
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing 102206, China
| | - Xiaohong Qian
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing 102206, China
| | - Mingchao Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing 102206, China
| | - Wantao Ying
- School of Basic Medical Science, Anhui Medical University, Hefei 230032, China.,State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing 102206, China
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