1
|
Stillger MN, Kurowski K, Bronsert P, Brombacher E, Kreutz C, Werner M, Tang L, Timme-Bronsert S, Schilling O. Neoadjuvant chemo- or chemo-radiation-therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass. Int J Cancer 2024; 154:2162-2175. [PMID: 38353498 DOI: 10.1002/ijc.34867] [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: 08/21/2023] [Revised: 11/08/2023] [Accepted: 12/20/2023] [Indexed: 04/14/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo-radiation (NCRT) therapy. We employed data-independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment-naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment-naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post-NCT and post-NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment-naïve PDAC. Further analyses on patient survival and protein expression identified treatment-specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment-naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.
Collapse
Affiliation(s)
- Maren N Stillger
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Konrad Kurowski
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, Core Facility for Histopathology and Digital Pathology, Medical Center-University of Freiburg, Freiburg, Germany
| | - Peter Bronsert
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, Core Facility for Histopathology and Digital Pathology, Medical Center-University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Eva Brombacher
- Faculty of Biology, University of Freiburg, Freiburg, Germany
- Faculty of Medicine and Medical Center, Institute of Medical Biometry and Statistics, University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Freiburg, Germany
| | - Clemens Kreutz
- Faculty of Medicine and Medical Center, Institute of Medical Biometry and Statistics, University of Freiburg, Freiburg, Germany
| | - Martin Werner
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, Core Facility for Histopathology and Digital Pathology, Medical Center-University of Freiburg, Freiburg, Germany
| | - Laura Tang
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Sylvia Timme-Bronsert
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Oliver Schilling
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, Core Facility for Histopathology and Digital Pathology, Medical Center-University of Freiburg, Freiburg, Germany
| |
Collapse
|
2
|
Fröhlich K, Fahrner M, Brombacher E, Seredynska A, Maldacker M, Kreutz C, Schmidt A, Schilling O. Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics. Mol Cell Proteomics 2024:100800. [PMID: 38880244 DOI: 10.1016/j.mcpro.2024.100800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 06/08/2024] [Accepted: 06/13/2024] [Indexed: 06/18/2024] Open
Abstract
Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.
Collapse
Affiliation(s)
- Klemens Fröhlich
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| | - Eva Brombacher
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Adrianna Seredynska
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Maximilian Maldacker
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Clemens Kreutz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Germany
| | - Alexander Schmidt
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| |
Collapse
|
3
|
Thiery J, Fahrner M. Integration of proteomics in the molecular tumor board. Proteomics 2024; 24:e2300002. [PMID: 38143279 DOI: 10.1002/pmic.202300002] [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: 07/24/2023] [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.
Collapse
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
| |
Collapse
|
4
|
Gu A, Li J, Qiu S, Hao S, Yue ZY, Zhai S, Li MY, Liu Y. Pancreatic cancer environment: from patient-derived models to single-cell omics. Mol Omics 2024; 20:220-233. [PMID: 38414408 DOI: 10.1039/d3mo00250k] [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: 02/29/2024]
Abstract
Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.
Collapse
Affiliation(s)
- Ao Gu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P. R. China.
| | - Jiatong Li
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P. R. China.
| | - Shimei Qiu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China
| | - Shenglin Hao
- Department of Functional Neurosurgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Zhu-Ying Yue
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P. R. China.
| | - Shuyang Zhai
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P. R. China.
| | - Meng-Yao Li
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P. R. China.
| | - Yingbin Liu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P. R. China.
| |
Collapse
|
5
|
Halstenbach T, Topitsch A, Schilling O, Iglhaut G, Nelson K, Fretwurst T. Mass spectrometry-based proteomic applications in dental implants research. Proteomics Clin Appl 2024; 18:e2300019. [PMID: 38342588 DOI: 10.1002/prca.202300019] [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: 07/21/2023] [Revised: 12/07/2023] [Accepted: 12/21/2023] [Indexed: 02/13/2024]
Abstract
Dental implants have been established as successful treatment options for missing teeth with steadily increasing demands. Today, the primary areas of research in dental implantology revolve around osseointegration, soft and hard tissue grafting as well as peri-implantitis diagnostics, prevention, and treatment. This review provides a comprehensive overview of the current literature on the application of MS-based proteomics in dental implant research, highlights how explorative proteomics provided insights into the biology of peri-implant soft and hard tissues and how proteomics facilitated the stratification between healthy and diseased implants, enabling the identification of potential new diagnostic markers. Additionally, this review illuminates technical aspects, and provides recommendations for future study designs based on the current evidence.
Collapse
Affiliation(s)
- Tim Halstenbach
- Department of Oral- and Craniomaxillofacial Surgery/Translational Implantology, Division of Regenerative Oral Medicine, Faculty of Medicine, Medical Center - University of Freiburg, Freiburg, Germany
| | - Annika Topitsch
- Department of Oral- and Craniomaxillofacial Surgery/Translational Implantology, Division of Regenerative Oral Medicine, Faculty of Medicine, Medical Center - University of Freiburg, Freiburg, Germany
- Institute of Surgical Pathology, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Oliver Schilling
- Institute of Surgical Pathology, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Gerhard Iglhaut
- Department of Oral- and Craniomaxillofacial Surgery/Translational Implantology, Division of Regenerative Oral Medicine, Faculty of Medicine, Medical Center - University of Freiburg, Freiburg, Germany
| | - Katja Nelson
- Department of Oral- and Craniomaxillofacial Surgery/Translational Implantology, Division of Regenerative Oral Medicine, Faculty of Medicine, Medical Center - University of Freiburg, Freiburg, Germany
| | - Tobias Fretwurst
- Department of Oral- and Craniomaxillofacial Surgery/Translational Implantology, Division of Regenerative Oral Medicine, Faculty of Medicine, Medical Center - University of Freiburg, Freiburg, Germany
| |
Collapse
|
6
|
Werner T, Fahrner M, Schilling O. Using proteomics for stratification and risk prediction in patients with solid tumors. PATHOLOGIE (HEIDELBERG, GERMANY) 2023; 44:176-182. [PMID: 37999758 DOI: 10.1007/s00292-023-01261-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/19/2023] [Indexed: 11/25/2023]
Abstract
Proteomics, the study of proteins and their functions, has greatly evolved due to advances in analytical chemistry and computational biology. Unlike genomics or transcriptomics, proteomics captures the dynamic and diverse nature of proteins, which play crucial roles in cellular processes. This is exemplified in cancer, where genomic and transcriptomic information often falls short in reflecting actual protein expression and interactions. Liquid chromatography-mass spectrometry (LC-MS) is pivotal in proteomic data generation, enabling high-throughput analysis of protein samples. The MS-based workflow involves protein digestion, chromatographic separation, ionization, and fragmentation, leading to peptide identification and quantification. Computational biostatistics, particularly using tools in R (R Foundation for Statistical Computing, Vienna, Austria; www.R-project.org ), aid in data analysis, revealing protein expression patterns and correlations with clinical variables. Proteomic studies can be explorative, aiming to characterize entire proteomes, or targeted, focusing on specific proteins of interest. The integration of proteomics with genomics addresses database limitations and enhances peptide identification. Case studies in intrahepatic cholangiocarcinoma, glioblastoma multiforme, and pancreatic ductal adenocarcinoma highlight proteomics' clinical applications, from subtyping cancers to identifying diagnostic markers. Moreover, proteomic data augment molecular tumor boards by providing deeper insights into pathway activities and genomic mutations, supporting personalized treatment decisions. Overall, proteomics contributes significantly to advancing our understanding of cellular biology and improving clinical care.
Collapse
Affiliation(s)
- Tilman Werner
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Centre Freiburg, University of Freiburg, Breisacher Str. 115a, 79106, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
| | - Matthias Fahrner
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Centre Freiburg, University of Freiburg, Breisacher Str. 115a, 79106, Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| | - Oliver Schilling
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Centre Freiburg, University of Freiburg, Breisacher Str. 115a, 79106, Freiburg, Germany.
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany.
| |
Collapse
|
7
|
Mullenger JL, Zeidler MP, Fragiadaki M. Evaluating the Molecular Properties and Function of ANKHD1, and Its Role in Cancer. Int J Mol Sci 2023; 24:12834. [PMID: 37629022 PMCID: PMC10454556 DOI: 10.3390/ijms241612834] [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: 07/12/2023] [Revised: 08/09/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
Ankyrin repeat and single KH domain-containing protein 1 (ANKHD1) is a large, scaffolding protein composed of two stretches of ankyrin repeat domains that mediate protein-protein interactions and a KH domain that mediates RNA or single-stranded DNA binding. ANKHD1 interacts with proteins in several crucial signalling pathways, including receptor tyrosine kinase, JAK/STAT, mechanosensitive Hippo (YAP/TAZ), and p21. Studies into the role of ANKHD1 in cancer cell lines demonstrate a crucial role in driving uncontrolled cellular proliferation and growth, enhanced tumorigenicity, cell cycle progression through the S phase, and increased epithelial-to-mesenchymal transition. Furthermore, at a clinical level, the increased expression of ANKHD1 has been associated with greater tumour infiltration, increased metastasis, and larger tumours. Elevated ANKHD1 resulted in poorer prognosis, more aggressive growth, and a decrease in patient survival in numerous cancer types. This review aims to gather the current knowledge about ANKHD1 and explore its molecular properties and functions, focusing on the protein's role in cancer at both a cellular and clinical level.
Collapse
Affiliation(s)
- Jordan L. Mullenger
- Department of Infection, Immunity, and Cardiovascular Disease, The University of Sheffield, Sheffield S10 2RX, UK;
- Department of Translational Medicine and Therapeutics, Queen Mary University London, London E1 4NS, UK
| | - Martin P. Zeidler
- School of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK;
| | - Maria Fragiadaki
- Department of Translational Medicine and Therapeutics, Queen Mary University London, London E1 4NS, UK
| |
Collapse
|
8
|
Lange PF, Schilling O, Huesgen PF. Positional proteomics: is the technology ready to study clinical cohorts? Expert Rev Proteomics 2023; 20:309-318. [PMID: 37869791 DOI: 10.1080/14789450.2023.2272046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/22/2023] [Indexed: 10/24/2023]
Abstract
INTRODUCTION Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.
Collapse
Affiliation(s)
- Philipp F Lange
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Michael Cuccione Childhood Cancer Research Program, BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Molecular Oncology, BC Cancer Research Centre, Vancouver, BC, Canada
| | - Oliver Schilling
- Institute of Surgical Pathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Pitter F Huesgen
- Central Institute for Engineering, Electronics and Analytics, ZEA-3, Forschungszentrum Jülich, Jülich, Germany
- Cologne Excellence Cluster on Stress Responses in Ageing-Associated Diseases, CECAD, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
- Institute of Biochemistry, Department for Chemistry, University of Cologne, Cologne, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| |
Collapse
|
9
|
Lima Silva WJ, Freitas de Freitas R. Assessing the performance of docking, FEP, and MM/GBSA methods on a series of KLK6 inhibitors. J Comput Aided Mol Des 2023:10.1007/s10822-023-00515-3. [PMID: 37378817 DOI: 10.1007/s10822-023-00515-3] [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: 03/30/2023] [Accepted: 06/21/2023] [Indexed: 06/29/2023]
Abstract
Kallikrein 6 (KLK6) is an attractive drug target for the treatment of neurological diseases and for various cancers. Herein, we explore the accuracy and efficiency of different computational methods and protocols to predict the free energy of binding (ΔGbind) for a series of 49 inhibitors of KLK6. We found that the performance of the methods varied strongly with the tested system. For only one of the three KLK6 datasets, the docking scores obtained with rDock were in good agreement (R2 ≥ 0.5) with experimental values of ΔGbind. A similar result was obtained with MM/GBSA (using the ff14SB force field) calculations based on single minimized structures. Improved binding affinity predictions were obtained with the free energy perturbation (FEP) method, with an overall MUE and RMSE of 0.53 and 0.68 kcal/mol, respectively. Furthermore, in a simulation of a real-world drug discovery project, FEP was able to rank the most potent compounds at the top of the list. These results indicate that FEP can be a promising tool for the structure-based optimization of KLK6 inhibitors.
Collapse
Affiliation(s)
- Wemenes José Lima Silva
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil
| | - Renato Freitas de Freitas
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
| |
Collapse
|
10
|
Siegel PM, Barta BA, Orlean L, Steenbuck ID, Cosenza-Contreras M, Wengenmayer T, Trummer G, Wolf D, Westermann D, Schilling O, Diehl P. The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study. J Transl Med 2023; 21:319. [PMID: 37173738 PMCID: PMC10176307 DOI: 10.1186/s12967-023-04174-8] [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: 03/03/2023] [Accepted: 04/30/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is applied in patients with refractory hemodynamic failure. Exposure of blood components to high shear stress and the large extracorporeal surfaces in the ECMO circuit trigger a complex inflammatory response syndrome and coagulopathy which are believed to worsen the already poor prognosis of these patients. Mass spectrometry-based proteomics allow a detailed characterization of the serum proteome as it provides the identity and concentration of large numbers of individual proteins at the same time. In this study, we aimed to characterize the serum proteome of patients receiving VA-ECMO. METHODS Serum samples were collected on day 1 and day 3 after initiation of VA-ECMO. Samples underwent immunoaffinity based depletion for the 14 most abundant serum proteins, in-solution digestion and PreOmics clean-up. A spectral library was built with multiple measurements of a master-mix sample using variable mass windows. Individual samples were measured in data independent acquisition (DIA) mode. Raw files were analyzed by DIA-neural network. Unique proteins were log transformed and quantile normalized. Differential expression analysis was conducted with the LIMMA-R package. ROAST was applied to generate gene ontology enrichment analyses. RESULTS Fourteen VA-ECMO patients and six healthy controls were recruited. Seven patients survived. Three hundred and fifty-one unique proteins were identified. One hundred and thirty-seven proteins were differentially expressed between VA-ECMO patients and controls. One hundred and forty-five proteins were differentially expressed on day 3 compared to day 1. Many of the differentially expressed proteins were involved in coagulation and the inflammatory response. The serum proteomes of survivors and non-survivors on day 3 differed from each other according to partial least-squares discriminant analysis (PLS-DA) and 48 proteins were differentially expressed. Many of these proteins have also been ascribed to processes in coagulation and inflammation (e.g., Factor IX, Protein-C, Kallikrein, SERPINA10, SEMA4B, Complement C3, Complement Factor D and MASP-1). CONCLUSION The serum proteome of VA-ECMO patients displays major changes compared to controls and changes from day 1 until day 3. Many changes in the serum proteome are related to inflammation and coagulation. Survivors and non-survivors can be differentiated according to their serum proteomes using PLS-DA analysis on day 3. Our results build the basis for future studies using mass-spectrometry based serum proteomics as a tool to identify novel prognostic biomarkers. TRIAL REGISTRATION DRKS00011106.
Collapse
Affiliation(s)
- Patrick Malcolm Siegel
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Bálint András Barta
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Lukas Orlean
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ines Derya Steenbuck
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Miguel Cosenza-Contreras
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Tobias Wengenmayer
- Interdisciplinary Medical Intensive Care (IMIT), Medical Center, University of Freiburg, Freiburg, Germany
| | - Georg Trummer
- Department of Cardiovascular Surgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Dennis Wolf
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dirk Westermann
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Philipp Diehl
- Department of Cardiology and Angiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| |
Collapse
|