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Chang YC, Gnann C, Steimbach RR, Bayer FP, Lechner S, Sakhteman A, Abele M, Zecha J, Trendel J, The M, Lundberg E, Miller AK, Kuster B. Decrypting lysine deacetylase inhibitor action and protein modifications by dose-resolved proteomics. Cell Rep 2024; 43:114272. [PMID: 38795348 DOI: 10.1016/j.celrep.2024.114272] [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: 12/19/2023] [Revised: 03/12/2024] [Accepted: 05/09/2024] [Indexed: 05/27/2024] Open
Abstract
Lysine deacetylase inhibitors (KDACis) are approved drugs for cutaneous T cell lymphoma (CTCL), peripheral T cell lymphoma (PTCL), and multiple myeloma, but many aspects of their cellular mechanism of action (MoA) and substantial toxicity are not well understood. To shed more light on how KDACis elicit cellular responses, we systematically measured dose-dependent changes in acetylation, phosphorylation, and protein expression in response to 21 clinical and pre-clinical KDACis. The resulting 862,000 dose-response curves revealed, for instance, limited cellular specificity of histone deacetylase (HDAC) 1, 2, 3, and 6 inhibitors; strong cross-talk between acetylation and phosphorylation pathways; localization of most drug-responsive acetylation sites to intrinsically disordered regions (IDRs); an underappreciated role of acetylation in protein structure; and a shift in EP300 protein abundance between the cytoplasm and the nucleus. This comprehensive dataset serves as a resource for the investigation of the molecular mechanisms underlying KDACi action in cells and can be interactively explored online in ProteomicsDB.
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Affiliation(s)
- Yun-Chien Chang
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Christian Gnann
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Raphael R Steimbach
- Cancer Drug Development, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany; Biosciences Faculty, Heidelberg University, Heidelberg, Baden-Württemberg, Germany
| | - Florian P Bayer
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Severin Lechner
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Amirhossein Sakhteman
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Miriam Abele
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Jana Zecha
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Jakob Trendel
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Matthew The
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA
| | - Aubry K Miller
- Cancer Drug Development, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany; German Cancer Consortium (DKTK), Heidelberg, Baden-Württemberg, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Bavaria, Germany; German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany.
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2
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Emery-Corbin SJ, Yousef JM, Adhikari S, Sumardy F, Nhu D, van Delft MF, Lessene G, Dziekan J, Webb AI, Dagley LF. Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient. Proteomics 2024:e2300644. [PMID: 38766901 DOI: 10.1002/pmic.202300644] [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: 12/19/2023] [Revised: 05/03/2024] [Accepted: 05/07/2024] [Indexed: 05/22/2024]
Abstract
Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay "CETSA") workflows typically employ multiplexing reagents reliant on data-dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA-MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA-DIA design has superior proteome coverage as compared to using tandem-mass tags (TMT) necessitating DDA-MS analysis. Importantly, we demonstrate our PISA-DIA approach has the quantitative and statistical rigor using A-1331852, a specific inhibitor of BCL-xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA-DIA workflow to identify BCL-xL. We assert our novel overlapping gradient PISA-DIA-MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.
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Affiliation(s)
- Samantha J Emery-Corbin
- Advanced Technology and Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - Jumana M Yousef
- Advanced Technology and Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - Subash Adhikari
- Advanced Technology and Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - Fransisca Sumardy
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
- ACRF Chemical Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
| | - Duong Nhu
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
- ACRF Chemical Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
| | - Mark F van Delft
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
- Blood Cells and Blood Cancer Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
| | - Guillaume Lessene
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
- ACRF Chemical Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Pharmacology and Therapeutics, University of Melbourne, Melbourne, Victoria, Australia
| | - Jerzy Dziekan
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
- Infection and Immunity Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
| | - Andrew I Webb
- Advanced Technology and Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - Laura F Dagley
- Advanced Technology and Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
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3
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Yin Y, Xu J, Ilyas I, Xu S. Bioactive Flavonoids in Protecting Against Endothelial Dysfunction and Atherosclerosis. Handb Exp Pharmacol 2024. [PMID: 38755351 DOI: 10.1007/164_2024_715] [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: 05/18/2024]
Abstract
Atherosclerosis is a common cardiovascular disease closely associated with factors such as hyperlipidaemia and chronic inflammation. Among them, endothelial dysfunction serves as a major predisposing factor. Vascular endothelial dysfunction is manifested by impaired endothelium-dependent vasodilation, enhanced oxidative stress, chronic inflammation, leukocyte adhesion and hyperpermeability, endothelial senescence, and endothelial-mesenchymal transition (EndoMT). Flavonoids are known for their antioxidant activity, eliminating oxidative stress induced by reactive oxygen species (ROS), thereby preventing the oxidation of low-density lipoprotein (LDL) cholesterol, reducing platelet aggregation, alleviating ischemic damage, and improving vascular function. Flavonoids have also been shown to possess anti-inflammatory activity and to protect the cardiovascular system. This review focuses on the protective effects of these naturally-occuring bioactive flavonoids against the initiation and progression of atherosclerosis through their effects on endothelial cells including, but not limited to, their antioxidant, anti-inflammatory, anti-thrombotic, and lipid-lowering properties. However, more clinical evidences are still needed to determine the exact role and optimal dosage of these compounds in the treatment of atherosclerosis.
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Affiliation(s)
- Yanjun Yin
- School of Pharmacy, Bengbu Medical University, Bengbu, China
| | - Jingjing Xu
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Iqra Ilyas
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Suowen Xu
- Department of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
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4
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Rosenberger G, Li W, Turunen M, He J, Subramaniam PS, Pampou S, Griffin AT, Karan C, Kerwin P, Murray D, Honig B, Liu Y, Califano A. Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis. Nat Commun 2024; 15:3909. [PMID: 38724493 PMCID: PMC11082183 DOI: 10.1038/s41467-024-47957-3] [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: 03/18/2023] [Accepted: 04/16/2024] [Indexed: 05/12/2024] Open
Abstract
Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.
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Affiliation(s)
- George Rosenberger
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Mikko Turunen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jing He
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Prem S Subramaniam
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sergey Pampou
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Aaron T Griffin
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Medical Scientist Training Program, Columbia University Irving Medical Center, New York, NY, USA
| | - Charles Karan
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- J.P. Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Patrick Kerwin
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Diana Murray
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Barry Honig
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA.
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA.
| | - Andrea Califano
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
- Chan Zuckerberg Biohub New York, New York, NY, USA.
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5
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Coorssen JR, Padula MP. Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience. Proteomes 2024; 12:14. [PMID: 38651373 PMCID: PMC11036260 DOI: 10.3390/proteomes12020014] [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: 03/17/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 04/25/2024] Open
Abstract
With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.
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Affiliation(s)
- Jens R. Coorssen
- Department of Biological Sciences, Faculty of Mathematics and Science, Brock University, St. Catharines, ON L2S 3A1, Canada
- Institute for Globally Distributed Open Research and Education (IGDORE), St. Catharines, ON L2N 4X2, Canada
| | - Matthew P. Padula
- School of Life Sciences and Proteomics, Lipidomics and Metabolomics Core Facility, Faculty of Science, University of Technology Sydney, Sydney, NSW 2007, Australia
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6
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Li Y, Liu X, Wang Y, Liu Z, Ye M, Wang H. [Deciphering cellular processes responding to lethality of 17 β-estradiol by quantitative phosphoproteomics]. Se Pu 2024; 42:333-344. [PMID: 38566422 PMCID: PMC10988567 DOI: 10.3724/sp.j.1123.2023.04025] [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: 04/25/2023] [Indexed: 04/04/2024] Open
Abstract
17β-Estradiol (E2), an important endocrine hormone in the mammalian body, participates in the regulation of the physiological functions of the reproductive system, mammary glands, bone, and cardiovascular system, among others. Paradoxically, despite the physiological actions of endogenous E2 (0.2-1.0 nmol/L), numerous clinical and experimental studies have demonstrated that high-dose E2 treatment can cause tumor regression and exert pro-apoptotic actions in multiple cell types; however, the underlying mechanism remains undescribed. In particular, little information of the cellular processes responding to the lethality of E2 is available. In the present study, we attempted to characterize the cellular processes responding to high-dose (μmol/L) E2 treatment using quantitative phosphoproteomics to obtain a better understanding of the regulatory mechanism of E2-induced cell death. First, the cell phenotype induced by high-dose E2 was determined by performing Cell Counting Kit-8 assay (CCK8), cell cytotoxicity analysis by trypan blue staining, and microscopic imaging on HeLa cells treated with 1-10 μmol/L E2 or dimethyl sulfoxide (DMSO) for 1-3 d. E2 inhibited cell proliferation and induced cell death in a dose- and time-dependent manner. Compared with the DMSO-treated HeLa cells, the cells treated with 5 μmol/L E2 for 2 d demonstrated >74% growth inhibition and approximately 50% cell death. Thus, these cells were used for quantitative phosphoproteomic analysis. Next, a solid-phase extraction (SPE)-based immobilized titanium ion affinity chromatography (Ti4+-IMAC) phosphopeptide-enrichment method coupled with data-independent acquisition (DIA)-based quantitative proteomics was employed for the in-depth screening of high-dose E2-regulated phosphorylation sites to investigate the intracellular processes responding to high-dose E2 treatment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified over 10000 phosphorylation sites regulated by E2 and DMSO in HeLa cells. In comparison with the DMSO-treated cells, the cells treated with 5 μmol/L E2 showed 537 upregulated phosphorylation sites and 387 downregulated phosphorylation sites, with a threshold of p<0.01 and |log2(fold change)|≥1. A total of 924 phosphorylation sites on 599 proteins were significantly regulated by high-dose E2, and these sites were subjected to enrichment analysis. In addition, 453 differently regulated phosphorylation sites on 325 proteins were identified only in the E2- or DMSO-treated cell samples. These phosphorylation sites may be phosphorylated or dephosphorylated in response to high-dose E2 stimulation and were subjected to parallel enrichment analyses. Taken together, 1218 phosphorylation sites on 741 proteins were significantly regulated by high-dose E2 treatment. The functional phosphoproteins in these two groups were then analyzed using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) to determine the biological processes in which they participate and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Consistent with the cell-phenotype data, cell cycle-related proteins were highly enriched in the two groups of E2-regulated phosphoproteins (p<0.05), indicating that high-dose E2 treatment can regulate cell proliferation. In addition, E2-regulated phosphoproteins were highly enriched in the cellular processes of ribosome biogenesis, nucleocytoplasmic transport, and messenger ribonucleic acid (mRNA) processing/splicing (p<0.05), indicating that the activation of these processes may contribute to high-dose E2-induced cell death. These results further confirm that high-dose E2 treatment inhibits protein translation and induces cell death. Furthermore, the significant upregulation of multiple phosphorylation sites associated with epidermal growth factor receptor (EGFR) and mitogen-activated protein kinases (MAPKs) MAPK1, MAPK4, and MAPK14 by high-dose E2 indicates that the EGFR and MAPK signaling pathways are likely involved in the regulation of E2-induced cell death. These phosphorylation sites likely play vital roles in E2-induced cell death in HeLa cells. Overall, our phosphoproteomic data could be a valuable resource for uncovering the regulatory mechanisms of E2 in the micromolar range.
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Affiliation(s)
- Yanan Li
- 1. School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- 2. State Key Laboratory of Environmental Chemistry and Eco-toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Xiaoyan Liu
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Yan Wang
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Zhen Liu
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Mingliang Ye
- 3. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Hailin Wang
- 1. School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- 2. State Key Laboratory of Environmental Chemistry and Eco-toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
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7
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Yang Z, Zheng Y, Gao Q. Lysine lactylation in the regulation of tumor biology. Trends Endocrinol Metab 2024:S1043-2760(24)00025-0. [PMID: 38395657 DOI: 10.1016/j.tem.2024.01.011] [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: 12/01/2023] [Revised: 01/24/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024]
Abstract
Lysine lactylation (Kla), a newly discovered post-translational modification (PTM) of lysine residues, is progressively revealing its crucial role in tumor biology. A growing body of evidence supports its capacity of transcriptional regulation through histone modification and modulation of non-histone protein function. It intricately participates in a myriad of events in the tumor microenvironment (TME) by orchestrating the transitions of immune states and augmenting tumor malignancy. Its preferential modification of metabolic proteins underscores its specific regulatory influence on metabolism. This review focuses on the effect and the probable mechanisms of Kla-mediated regulation of tumor metabolism, the upstream factors that determine Kla intensity, and its potential implications for the clinical diagnosis and treatment of tumors.
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Affiliation(s)
- Zijian Yang
- Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yingqi Zheng
- Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China; State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China.
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8
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Wu Q, Zheng J, Sui X, Fu C, Cui X, Liao B, Ji H, Luo Y, He A, Lu X, Xue X, Tan CSH, Tian R. High-throughput drug target discovery using a fully automated proteomics sample preparation platform. Chem Sci 2024; 15:2833-2847. [PMID: 38404368 PMCID: PMC10882491 DOI: 10.1039/d3sc05937e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/19/2023] [Indexed: 02/27/2024] Open
Abstract
Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.
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Affiliation(s)
- Qiong Wu
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Jiangnan Zheng
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
- Southern University of Science and Technology, Guangming Advanced Research Institute Shenzhen 518055 China
| | - Xintong Sui
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Changying Fu
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Xiaozhen Cui
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Bin Liao
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Hongchao Ji
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Yang Luo
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - An He
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Xue Lu
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Xinyue Xue
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
| | - Chris Soon Heng Tan
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
- Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology 1088 Xueyuan Road Shenzhen 518055 China
- Southern University of Science and Technology, Guangming Advanced Research Institute Shenzhen 518055 China
| | - Ruijun Tian
- Department of Chemistry, School of Science, Southern University of Science and Technology Shenzhen 518055 China
- Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology 1088 Xueyuan Road Shenzhen 518055 China
- Southern University of Science and Technology, Guangming Advanced Research Institute Shenzhen 518055 China
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9
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Joshi SK, Piehowski P, Liu T, Gosline SJC, McDermott JE, Druker BJ, Traer E, Tyner JW, Agarwal A, Tognon CE, Rodland KD. Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine. Annu Rev Pharmacol Toxicol 2024; 64:455-479. [PMID: 37738504 PMCID: PMC10950354 DOI: 10.1146/annurev-pharmtox-022723-113921] [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: 09/24/2023]
Abstract
Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.
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Affiliation(s)
- Sunil K Joshi
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Paul Piehowski
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Tao Liu
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Sara J C Gosline
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Jason E McDermott
- Pacific Northwest National Laboratory, Richland, Washington, USA
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, Oregon, USA
| | - Brian J Druker
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Elie Traer
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Jeffrey W Tyner
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, Oregon, USA
| | - Anupriya Agarwal
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, Oregon, USA
| | - Cristina E Tognon
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Karin D Rodland
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Pacific Northwest National Laboratory, Richland, Washington, USA
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10
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Li Y, Lyu J, Wang Y, Ye M, Wang H. Ligand Modification-Free Methods for the Profiling of Protein-Environmental Chemical Interactions. Chem Res Toxicol 2024; 37:1-15. [PMID: 38146056 DOI: 10.1021/acs.chemrestox.3c00282] [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: 12/27/2023]
Abstract
Adverse health outcomes caused by environmental chemicals are often initiated via their interactions with proteins. Essentially, one environmental chemical may interact with a number of proteins and/or a protein may interact with a multitude of environmental chemicals, forming an intricate interaction network. Omics-wide protein-environmental chemical interaction profiling (PECI) is of prominent importance for comprehensive understanding of these interaction networks, including the toxicity mechanisms of action (MoA), and for providing systematic chemical safety assessment. However, such information remains unknown for most environmental chemicals, partly due to their vast chemical diversity. In recent years, with the continuous efforts afforded, especially in mass spectrometry (MS) based omics technologies, several ligand modification-free methods have been developed, and new attention for systematic PECI profiling was gained. In this Review, we provide a comprehensive overview on these methodologies for the identification of ligand-protein interactions, including affinity interaction-based methods of affinity-driven purification, covalent modification profiling, and activity-based protein profiling (ABPP) in a competitive mode, physicochemical property changes assessment methods of ligand-directed nuclear magnetic resonance (ligand-directed NMR), MS integrated with equilibrium dialysis for the discovery of allostery systematically (MIDAS), thermal proteome profiling (TPP), limited proteolysis-coupled mass spectrometry (LiP-MS), stability of proteins from rates of oxidation (SPROX), and several intracellular downstream response characterization methods. We expect that the applications of these ligand modification-free technologies will drive a considerable increase in the number of PECI identified, facilitate unveiling the toxicological mechanisms, and ultimately contribute to systematic health risk assessment of environmental chemicals.
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Affiliation(s)
- Yanan Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- The State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jiawen Lyu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Yan Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Mingliang Ye
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
- State Key Laboratory of Medical Proteomics, Beijing, 102206, China
| | - Hailin Wang
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- The State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
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11
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Lee CY, The M, Meng C, Bayer FP, Putzker K, Müller J, Streubel J, Woortman J, Sakhteman A, Resch M, Schneider A, Wilhelm S, Kuster B. Illuminating phenotypic drug responses of sarcoma cells to kinase inhibitors by phosphoproteomics. Mol Syst Biol 2024; 20:28-55. [PMID: 38177929 PMCID: PMC10883282 DOI: 10.1038/s44320-023-00004-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 11/06/2023] [Accepted: 11/30/2023] [Indexed: 01/06/2024] Open
Abstract
Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect is particularly apparent in cancer entities such as sarcomas for which the oncogenic drivers are often not clear. To investigate more systematically how the cellular proteotypes of sarcoma cells shape their response to molecularly targeted drugs, we profiled the proteomes and phosphoproteomes of 17 sarcoma cell lines and screened the same against 150 cancer drugs. The resulting 2550 phenotypic profiles revealed distinct drug responses and the cellular activity landscapes derived from deep (phospho)proteomes (9-10,000 proteins and 10-27,000 phosphorylation sites per cell line) enabled several lines of analysis. For instance, connecting the (phospho)proteomic data with drug responses revealed known and novel mechanisms of action (MoAs) of KIs and identified markers of drug sensitivity or resistance. All data is publicly accessible via an interactive web application that enables exploration of this rich molecular resource for a better understanding of active signalling pathways in sarcoma cells, identifying treatment response predictors and revealing novel MoA of clinical KIs.
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Affiliation(s)
- Chien-Yun Lee
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Matthew The
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Chen Meng
- Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich, Freising, Germany
| | - Florian P Bayer
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Kerstin Putzker
- Chemical Biology Core Facility, EMBL Heidelberg, Heidelberg, Germany
| | - Julian Müller
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Johanna Streubel
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Julia Woortman
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Amirhossein Sakhteman
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Moritz Resch
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Annika Schneider
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Stephanie Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany.
- Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich, Freising, Germany.
- German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany.
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12
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Deng B, Vanagas L, Alonso AM, Angel SO. Proteomics Applications in Toxoplasma gondii: Unveiling the Host-Parasite Interactions and Therapeutic Target Discovery. Pathogens 2023; 13:33. [PMID: 38251340 PMCID: PMC10821451 DOI: 10.3390/pathogens13010033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/25/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024] Open
Abstract
Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID (BirA*-mediated proximity-dependent biotin identification), APEX (ascorbate peroxidase-mediated proximity labeling), and Y2H (yeast two hybrid), as well as various proteomics approaches, including single-cell analysis, DIA (data-independent acquisition), targeted, top-down, and plasma proteomics. Furthermore, we discuss bioinformatics and the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.
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Affiliation(s)
- Bin Deng
- Department of Biology and VBRN Proteomics Facility, University of Vermont, Burlington, VT 05405, USA
| | - Laura Vanagas
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
| | - Andres M. Alonso
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
| | - Sergio O. Angel
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
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13
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Thiery J, Fahrner M. Integration of proteomics in the molecular tumor board. Proteomics 2023:e2300002. [PMID: 38143279 DOI: 10.1002/pmic.202300002] [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: 07/24/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 12/26/2023]
Abstract
Cancer remains one of the most complex and challenging diseases in mankind. To address the need for a personalized treatment approach for particularly complex tumor cases, molecular tumor boards (MTBs) have been initiated. MTBs are interdisciplinary teams that perform in-depth molecular diagnostics to cooperatively and interdisciplinarily advise on the best therapeutic strategy. Current molecular diagnostics are routinely performed on the transcriptomic and genomic levels, aiming to identify tumor-driving mutations. However, these approaches can only partially capture the actual phenotype and the molecular key players of tumor growth and progression. Thus, direct investigation of the expressed proteins and activated signaling pathways provide valuable complementary information on the tumor-driving molecular characteristics of the tissue. Technological advancements in mass spectrometry-based proteomics enable the robust, rapid, and sensitive detection of thousands of proteins in minimal sample amounts, paving the way for clinical proteomics and the probing of oncogenic signaling activity. Therefore, proteomics is currently being integrated into molecular diagnostics within MTBs and holds promising potential in aiding tumor classification and identifying personalized treatment strategies. This review introduces MTBs and describes current clinical proteomics, its potential in precision oncology, and highlights the benefits of multi-omic data integration.
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Affiliation(s)
- Johanna Thiery
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
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14
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Stephenson EH, Higgins JMG. Pharmacological approaches to understanding protein kinase signaling networks. Front Pharmacol 2023; 14:1310135. [PMID: 38164473 PMCID: PMC10757940 DOI: 10.3389/fphar.2023.1310135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Protein kinases play vital roles in controlling cell behavior, and an array of kinase inhibitors are used successfully for treatment of disease. Typical drug development pipelines involve biological studies to validate a protein kinase target, followed by the identification of small molecules that effectively inhibit this target in cells, animal models, and patients. However, it is clear that protein kinases operate within complex signaling networks. These networks increase the resilience of signaling pathways, which can render cells relatively insensitive to inhibition of a single kinase, and provide the potential for pathway rewiring, which can result in resistance to therapy. It is therefore vital to understand the properties of kinase signaling networks in health and disease so that we can design effective multi-targeted drugs or combinations of drugs. Here, we outline how pharmacological and chemo-genetic approaches can contribute to such knowledge, despite the known low selectivity of many kinase inhibitors. We discuss how detailed profiling of target engagement by kinase inhibitors can underpin these studies; how chemical probes can be used to uncover kinase-substrate relationships, and how these tools can be used to gain insight into the configuration and function of kinase signaling networks.
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Affiliation(s)
| | - Jonathan M. G. Higgins
- Faculty of Medical Sciences, Biosciences Institute, Newcastle University, Newcastle uponTyne, United Kingdom
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15
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Bayer FP, Gander M, Kuster B, The M. CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose-response curves. Nat Commun 2023; 14:7902. [PMID: 38036588 PMCID: PMC10689459 DOI: 10.1038/s41467-023-43696-z] [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: 08/25/2023] [Accepted: 11/16/2023] [Indexed: 12/02/2023] Open
Abstract
Dose-response curves are key metrics in pharmacology and biology to assess phenotypic or molecular actions of bioactive compounds in a quantitative fashion. Yet, it is often unclear whether or not a measured response significantly differs from a curve without regulation, particularly in high-throughput applications or unstable assays. Treating potency and effect size estimates from random and true curves with the same level of confidence can lead to incorrect hypotheses and issues in training machine learning models. Here, we present CurveCurator, an open-source software that provides reliable dose-response characteristics by computing p-values and false discovery rates based on a recalibrated F-statistic and a target-decoy procedure that considers dataset-specific effect size distributions. The application of CurveCurator to three large-scale datasets enables a systematic drug mode of action analysis and demonstrates its scalable utility across several application areas, facilitated by a performant, interactive dashboard for fast data exploration.
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Affiliation(s)
- Florian P Bayer
- Proteomics and Bioanalytics, School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
| | - Manuel Gander
- Proteomics and Bioanalytics, School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
| | - Bernhard Kuster
- Proteomics and Bioanalytics, School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, 80336, Munich, Germany
| | - Matthew The
- Proteomics and Bioanalytics, School of Life Sciences, Technical University of Munich, 85354, Freising, Germany.
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16
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Shuken SR, McAlister GC, Barshop WD, Canterbury JD, Bergen D, Huang J, Huguet R, Paulo JA, Zabrouskov V, Gygi SP, Yu Q. Deep Proteomic Compound Profiling with the Orbitrap Ascend Tribrid Mass Spectrometer Using Tandem Mass Tags and Real-Time Search. Anal Chem 2023; 95:15180-15188. [PMID: 37811788 PMCID: PMC10785648 DOI: 10.1021/acs.analchem.3c01701] [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: 10/10/2023]
Abstract
Tandem mass tags (TMT) and tribrid mass spectrometers are a powerful combination for high-throughput proteomics with high quantitative accuracy. Increasingly, this technology is being used to map the effects of drugs on the proteome. However, the depth of proteomic profiling is still limited by sensitivity and speed. The new Orbitrap Ascend mass spectrometer was designed to address these limitations with a combination of hardware and software improvements. We evaluated the performance of the Ascend in multiple contexts including deep proteomic profiling. We found that the Ascend exhibited increased sensitivity, yielding higher signal-to-noise ratios than the Orbitrap Eclipse with shorter injection times. As a result, higher numbers of peptides and proteins were identified and quantified, especially with low sample input. TMT measurements had significantly improved signal-to-noise ratios, improving quantitative precision. In a fractionated 16plex sample that profiled proteomic differences across four human cell lines, the Ascend was able to quantify hundreds more proteins than the Eclipse, many of them low-abundant proteins, and the Ascend was able to quantify >8000 proteins in 30% less instrument time. We used the Ascend to analyze 8881 proteins in HCT116 cancer cells treated with covalent sulfolane/sulfolene inhibitors of peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1), a phosphorylation-specific peptidyl-prolyl cis-trans isomerase implicated in several cancers. We characterized these PIN1 inhibitors' effects on the proteome and identified discrepancies among the different compounds, which will facilitate a better understanding of the structure-activity relationship of this class of compounds. The Ascend was able to quantify statistically significant, potentially therapeutically relevant changes in proteins that the Eclipse could not detect.
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Affiliation(s)
- Steven R Shuken
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Graeme C McAlister
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - William D Barshop
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Jesse D Canterbury
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - David Bergen
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Jingjing Huang
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Romain Huguet
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - João A Paulo
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Vlad Zabrouskov
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Qing Yu
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
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17
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Hu LZ, Douglass E, Turunen M, Pampou S, Grunn A, Realubit R, Antolin AA, Wang ALE, Li H, Subramaniam P, Karan C, Alvarez M, Califano A. Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.08.561457. [PMID: 37873470 PMCID: PMC10592689 DOI: 10.1101/2023.10.08.561457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have implemented an efficient integrative experimental and computational framework leveraging the systematic generation and analysis of drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Protein activity-based analyses revealed highly reproducible, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide polypharmacology map, characterization of MoA-related drug clusters and off-target effects, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins. The proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, could help support more systematic and quantitative approaches to precision oncology.
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18
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Madsen RR, Toker A. PI3K signaling through a biochemical systems lens. J Biol Chem 2023; 299:105224. [PMID: 37673340 PMCID: PMC10570132 DOI: 10.1016/j.jbc.2023.105224] [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: 05/08/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/08/2023] Open
Abstract
Following 3 decades of extensive research into PI3K signaling, it is now evidently clear that the underlying network does not equate to a simple ON/OFF switch. This is best illustrated by the multifaceted nature of the many diseases associated with aberrant PI3K signaling, including common cancers, metabolic disease, and rare developmental disorders. However, we are still far from a complete understanding of the fundamental control principles that govern the numerous phenotypic outputs that are elicited by activation of this well-characterized biochemical signaling network, downstream of an equally diverse set of extrinsic inputs. At its core, this is a question on the role of PI3K signaling in cellular information processing and decision making. Here, we review the determinants of accurate encoding and decoding of growth factor signals and discuss outstanding questions in the PI3K signal relay network. We emphasize the importance of quantitative biochemistry, in close integration with advances in single-cell time-resolved signaling measurements and mathematical modeling.
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Affiliation(s)
- Ralitsa R Madsen
- MRC-Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, Scotland, United Kingdom.
| | - Alex Toker
- Department of Pathology and Cancer Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
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19
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Thomson TM. On the importance for drug discovery of a transnational Latin American database of natural compound structures. Front Pharmacol 2023; 14:1207559. [PMID: 37426821 PMCID: PMC10324963 DOI: 10.3389/fphar.2023.1207559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/15/2023] [Indexed: 07/11/2023] Open
Affiliation(s)
- Timothy M. Thomson
- Institute for Molecular Biology (IBMB-CSIC), Barcelona, Spain
- CIBER de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain
- Universidad Peruana Cayetano Heredia, Lima, Peru
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20
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Herbst SA, White FM. Decrypting the potency of anti-cancer therapeutics by using mass spectrometry to quantify post-translational modifications. CELL REPORTS METHODS 2023; 3:100483. [PMID: 37323574 PMCID: PMC10261922 DOI: 10.1016/j.crmeth.2023.100483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
In a recent issue of Science, Zecha et al.1 present decryptM, an approach aimed at defining the mechanisms of action of anti-cancer therapeutics through systems-level analysis of protein post-translational modifications (PTMs). By using a broad range of concentrations, decryptM generates drug response curves for each detected PTM, enabling identification of drug effects at different therapeutic doses.
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Affiliation(s)
- Sophie A. Herbst
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Center for Precision Cancer Medicine, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Forest M. White
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Center for Precision Cancer Medicine, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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21
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Crunkhorn S. Decrypting drug action at the level of PTMs. Nat Rev Drug Discov 2023; 22:355. [PMID: 37020011 DOI: 10.1038/d41573-023-00052-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
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