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Skerniskyte J, Mulet C, André AC, Anderson MC, Injarabian L, Buck A, Prade VM, Sansonetti PJ, Reibel-Foisset S, Walch AK, Lebel M, Lykkesfeldt J, Marteyn BS. Ascorbate deficiency increases progression of shigellosis in guinea pigs and mice infection models. Gut Microbes 2023; 15:2271597. [PMID: 37876025 PMCID: PMC10730169 DOI: 10.1080/19490976.2023.2271597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/12/2023] [Indexed: 10/26/2023] Open
Abstract
Shigella spp. are the causative agents of bacterial dysentery and shigellosis, mainly in children living in developing countries. The study of Shigella entire life cycle in vivo and the evaluation of vaccine candidates' protective efficacy have been hampered by the lack of a suitable animal model of infection. None of the studies evaluated so far (rabbit, guinea pig, mouse) allowed the recapitulation of full shigellosis symptoms upon Shigella oral challenge. Historical reports have suggested that dysentery and scurvy are both metabolic diseases associated with ascorbate deficiency. Mammals, which are susceptible to Shigella infection (humans, non-human primates and guinea pigs) are among the few species unable to synthesize ascorbate. We optimized a low-ascorbate diet to induce moderate ascorbate deficiency, but not scurvy, in guinea pigs to investigate whether poor vitamin C status increases the progression of shigellosis. Moderate ascorbate deficiency increased shigellosis symptom severity during an extended period of time (up to 48 h) in all strains tested (Shigella sonnei, Shigella flexneri 5a, and 2a). At late time points, an important influx of neutrophils was observed both within the disrupted colonic mucosa and in the luminal compartment, although Shigella was able to disseminate deep into the organ to reach the sub-mucosal layer and the bloodstream. Moreover, we found that ascorbate deficiency also increased Shigella penetration into the colon epithelium layer in a Gulo-/- mouse infection model. The use of these new rodent models of shigellosis opens new doors for the study of both Shigella infection strategies and immune responses to Shigella infection.
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Affiliation(s)
- Jurate Skerniskyte
- Institut de Biologie Moléculaire et Cellulaire, Architecture et Réactivité de l’ARN, Université de Strasbourg, Strasbourg, France
| | - Céline Mulet
- Unité de Pathogénie Microbienne Moléculaire, Institut Pasteur, Université de Paris, Paris, France
| | - Antonin C. André
- Institut de Biologie Moléculaire et Cellulaire, Architecture et Réactivité de l’ARN, Université de Strasbourg, Strasbourg, France
- Unité de Pathogénie Microbienne Moléculaire, Institut Pasteur, Université de Paris, Paris, France
| | - Mark C. Anderson
- Unité de Pathogénie Microbienne Moléculaire, Institut Pasteur, Université de Paris, Paris, France
| | - Louise Injarabian
- Institut de Biologie Moléculaire et Cellulaire, Architecture et Réactivité de l’ARN, Université de Strasbourg, Strasbourg, France
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Verena M. Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Philippe J. Sansonetti
- Unité de Pathogénie Microbienne Moléculaire, Institut Pasteur, Université de Paris, Paris, France
- Collège de France, Paris, France
| | | | - Axel K. Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Michel Lebel
- Centre de recherche du CHU de Québec, Faculty of Medicine, Université Laval, Québec, Canada
| | - Jens Lykkesfeldt
- Section for Experimental Animal Models, Faculty of Health and Medical Sciences, University Copenhagen, Copenhagen, Denmark
| | - Benoit S. Marteyn
- Institut de Biologie Moléculaire et Cellulaire, Architecture et Réactivité de l’ARN, Université de Strasbourg, Strasbourg, France
- Unité de Pathogenèse des Infections Vasculaires, Institut Pasteur, INSERM U1225, Paris, France
- University of Strasbourg Institute for Advanced Study (USIAS), Strasbourg, France
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Wang J, Sun N, Kunzke T, Shen J, Zens P, Prade VM, Feuchtinger A, Berezowska S, Walch A. Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma. NPJ Precis Oncol 2023; 7:114. [PMID: 37919427 PMCID: PMC10622419 DOI: 10.1038/s41698-023-00434-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 08/08/2023] [Indexed: 11/04/2023] Open
Abstract
Molecular subtyping of lung squamous cell carcinoma (LUSC) has been performed at the genomic, transcriptomic, and proteomic level. However, LUSC stratification based on tissue metabolomics is still lacking. Combining high-mass-resolution imaging mass spectrometry with consensus clustering, four tumor- and four stroma-specific subtypes with distinct metabolite patterns were identified in 330 LUSC patients. The first tumor subtype T1 negatively correlated with DNA damage and immunological features including CD3, CD8, and PD-L1. The same features positively correlated with the tumor subtype T2. Tumor subtype T4 was associated with high PD-L1 expression. Compared with the status of subtypes T1 and T4, patients with subtype T3 had improved prognosis, and T3 was an independent prognostic factor with regard to UICC stage. Similarly, stroma subtypes were linked to distinct immunological features and metabolic pathways. Stroma subtype S4 had a better prognosis than S2. Subsequently, analyses based on an independent LUSC cohort treated by neoadjuvant therapy revealed that the S2 stroma subtype was associated with chemotherapy resistance. Clinically relevant patient subtypes as determined by tissue-based spatial metabolomics are a valuable addition to existing molecular classification systems. Metabolic differences among the subtypes and their associations with immunological features may contribute to the improvement of personalized therapy.
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Affiliation(s)
- Jun Wang
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Jian Shen
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Philipp Zens
- Institute of Tissue Medicine and Pathology, University of Bern, Murtenstrasse 31, 3008, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Mittelstrasse 43, Bern, 3012, Switzerland
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Sabina Berezowska
- Institute of Tissue Medicine and Pathology, University of Bern, Murtenstrasse 31, 3008, Bern, Switzerland.
- Department of Laboratory Medicine and Pathology, Institute of Pathology, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland.
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, 85764, Germany.
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Shen J, Sun N, Wang J, Zens P, Kunzke T, Buck A, Prade VM, Wang Q, Feuchtinger A, Hu R, Berezowska S, Walch A. Patterns of Carbon-Bound Exogenous Compounds Impact Disease Pathophysiology in Lung Cancer Subtypes in Different Ways. ACS Nano 2023; 17:16396-16411. [PMID: 37639684 PMCID: PMC10510585 DOI: 10.1021/acsnano.2c11161] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 08/23/2023] [Indexed: 08/31/2023]
Abstract
Carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, aromatic amines, and organohalogens, are known to affect both tumor characteristics and patient outcomes in lung squamous cell carcinoma (LUSC); however, the roles of these compounds in lung adenocarcinoma (LUAD) remain unclear. We analyzed 11 carbon-bound exogenous compounds in LUAD and LUSC samples using in situ high mass-resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging and performed a cluster analysis to compare the patterns of carbon-bound exogenous compounds between these two lung cancer subtypes. Correlation analyses were conducted to investigate associations among exogenous compounds, endogenous metabolites, and clinical data, including patient survival outcomes and smoking behaviors. Additionally, we examined differences in exogenous compound patterns between normal and tumor tissues. Our analyses revealed that PAHs, aromatic amines, and organohalogens were more abundant in LUAD than in LUSC, whereas the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone was more abundant in LUSC. Patients with LUAD and LUSC could be separated according to carbon-bound exogenous compound patterns detected in the tumor compartment. The same compounds had differential impacts on patient outcomes, depending on the cancer subtype. Correlation and network analyses indicated substantial differences between LUAD and LUSC metabolomes, associated with substantial differences in the patterns of the carbon-bound exogenous compounds. These data suggest that the contributions of these carcinogenic compounds to cancer biology may differ according to the cancer subtypes.
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Affiliation(s)
- Jian Shen
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
- Nanxishan
Hospital of Guangxi Zhuang Autonomous Region, Institute of Pathology, Guilin 541002, People’s Republic of China
| | - Na Sun
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Jun Wang
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Philipp Zens
- Institute
of Tissue Medicine and Pathology, University
of Bern, Murtenstrasse 31, Bern 3008, Switzerland
- Graduate
School for Health Sciences, University of
Bern, Mittelstrasse 43, Bern 3012, Switzerland
| | - Thomas Kunzke
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Achim Buck
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Verena M. Prade
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Qian Wang
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Annette Feuchtinger
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Ronggui Hu
- Center
for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200030, People’s
Republic of China
| | - Sabina Berezowska
- Institute
of Tissue Medicine and Pathology, University
of Bern, Murtenstrasse 31, Bern 3008, Switzerland
- Department
of Laboratory Medicine and Pathology, Institute of Pathology, Lausanne University Hospital and University of Lausanne, Lausanne 1011, Switzerland
| | - Axel Walch
- Research
Unit Analytical Pathology, Helmholtz Zentrum
München − German Research Center for Environmental Health, Neuherberg 85764, Germany
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Buck A, Prade VM, Kunzke T, Erben RG, Walch A. Spatial metabolomics reveals upregulation of several pyrophosphate-producing pathways in cortical bone of Hyp mice. JCI Insight 2022; 7:162138. [DOI: 10.1172/jci.insight.162138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/31/2022] [Indexed: 11/17/2022] Open
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Erlmeier F, Sun N, Shen J, Feuchtinger A, Buck A, Prade VM, Kunzke T, Schraml P, Moch H, Autenrieth M, Weichert W, Hartmann A, Walch A. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging: Diagnostic Pathways and Metabolites for Renal Tumor Entities. Oncology 2022; 101:126-133. [PMID: 36198279 DOI: 10.1159/000526436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/20/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic. PATIENTS AND METHODS Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes. RESULTS We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC. CONCLUSION In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection.
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Affiliation(s)
- Franziska Erlmeier
- Institute of Pathology, University Hospital Erlangen-Nuernberg, Erlangen, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Jian Shen
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Peter Schraml
- Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Holger Moch
- Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Autenrieth
- Department of Urology, Rechts der Isar Medical Center, Technical University of Munich, Munich, Germany
| | - Wilko Weichert
- Institute of Pathology, Technical University Munich, Munich, Germany
| | - Arndt Hartmann
- Institute of Pathology, University Hospital Erlangen-Nuernberg, Erlangen, Germany
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
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Shen J, Sun N, Zens P, Kunzke T, Buck A, Prade VM, Wang J, Wang Q, Hu R, Feuchtinger A, Berezowska S, Walch A. Spatial metabolomics for evaluating response to neoadjuvant therapy in non-small cell lung cancer patients. Cancer Commun (Lond) 2022; 42:517-535. [PMID: 35593195 PMCID: PMC9198346 DOI: 10.1002/cac2.12310] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 02/18/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Background The response to neoadjuvant chemotherapy (NAC) differs substantially among individual patients with non‐small cell lung cancer (NSCLC). Major pathological response (MPR) is a histomorphological read‐out used to assess treatment response and prognosis in patients NSCLC after NAC. Although spatial metabolomics is a promising tool for evaluating metabolic phenotypes, it has not yet been utilized to assess therapy responses in patients with NSCLC. We evaluated the potential application of spatial metabolomics in cancer tissues to assess the response to NAC, using a metabolic classifier that utilizes mass spectrometry imaging combined with machine learning. Methods Resected NSCLC tissue specimens obtained after NAC (n = 88) were subjected to high‐resolution mass spectrometry, and these data were used to develop an approach for assessing the response to NAC in patients with NSCLC. The specificities of the generated tumor cell and stroma classifiers were validated by applying this approach to a cohort of biologically matched chemotherapy‐naïve patients with NSCLC (n = 85). Results The developed tumor cell metabolic classifier stratified patients into different prognostic groups with 81.6% accuracy, whereas the stroma metabolic classifier displayed 78.4% accuracy. By contrast, the accuracies of MPR and TNM staging for stratification were 62.5% and 54.1%, respectively. The combination of metabolic and MPR classifiers showed slightly lower accuracy than either individual metabolic classifier. In multivariate analysis, metabolic classifiers were the only independent prognostic factors identified (tumor: P = 0.001, hazards ratio [HR] = 3.823, 95% confidence interval [CI] = 1.716–8.514; stroma: P = 0.049, HR = 2.180, 95% CI = 1.004–4.737), whereas MPR (P = 0.804; HR = 0.913; 95% CI = 0.445–1.874) and TNM staging (P = 0.078; HR = 1.223; 95% CI = 0.977–1.550) were not independent prognostic factors. Using Kaplan‐Meier survival analyses, both tumor and stroma metabolic classifiers were able to further stratify patients as NAC responders (P < 0.001) and non‐responders (P < 0.001). Conclusions Our findings indicate that the metabolic constitutions of both tumor cells and the stroma are valuable additions to the classical histomorphology‐based assessment of tumor response.
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Affiliation(s)
- Jian Shen
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Philipp Zens
- Institute of Pathology, University of Bern, Bern, 3008, Switzerland.,Graduate School for Health Sciences, University of Bern, Mittelstrasse 43, Bern, 3012, Switzerland
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Jun Wang
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Qian Wang
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Ronggui Hu
- Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, 200031, P. R. China
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Sabina Berezowska
- Institute of Pathology, University of Bern, Bern, 3008, Switzerland.,Department of Laboratory Medicine and Pathology, Institute of Pathology, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
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Wang J, Kunzke T, Prade VM, Shen J, Buck A, Feuchtinger A, Haffner I, Luber B, Liu DHW, Langer R, Lordick F, Sun N, Walch A. Spatial metabolomics identifies distinct tumor-specific subtypes in gastric cancer patients. Clin Cancer Res 2022; 28:2865-2877. [PMID: 35395077 DOI: 10.1158/1078-0432.ccr-21-4383] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/01/2022] [Accepted: 04/06/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE Current systems of gastric cancer (GC) molecular classification include genomic, molecular, and morphological features. GC classification based on tissue metabolomics remains lacking. This study aimed to define metabolically distinct GC subtypes and identify their clinicopathological and molecular characteristics. EXPERIMENTAL DESIGN Spatial metabolomics by high mass resolution imaging mass spectrometry was performed in 362 GC patients. K-means clustering was used to define tumor and stroma-related subtypes based on tissue metabolites. The identified subtypes were linked with clinicopathological characteristics, molecular features, and metabolic signatures. Responses to trastuzumab treatment were investigated across the subtypes by introducing an independent patient cohort with HER2-positive GC from a multicenter observational study. RESULTS Three tumor- and three stroma-specific subtypes with distinct tissue metabolite patterns were identified. Tumor-specific subtype T1(HER2+MIB+CD3+) positively correlated with HER2, MIB1, DEFA-1, CD3, CD8, FOXP3, but negatively correlated with MMR. Tumor-specific subtype T2(HER2-MIB-CD3-) negatively correlated with HER2, MIB1, CD3, FOXP3, but positively correlated with MMR. Tumor-specific subtype T3(pEGFR+) positively correlated with pEGFR. Patients with tumor subtype T1(HER2+MIB+CD3+) had elevated nucleotide levels, enhanced DNA metabolism, and a better prognosis than T2(HER2-MIB-CD3-) and T3(pEGFR+). An independent validation cohort confirmed that the T1 subtype benefited from trastuzumab therapy. Stroma-specific subtypes had no association with clinicopathological characteristics, however linked to distinct metabolic pathways and molecular features. CONCLUSIONS Patient subtypes derived by tissue-based spatial metabolomics are a valuable addition to existing GC molecular classification systems. Metabolic differences between the subtypes and their associations with molecular features could provide a valuable tool to aid in selecting specific treatment approaches.
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Affiliation(s)
- Jun Wang
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Jian Shen
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Ivonne Haffner
- University Cancer Center Leipzig (UCCL), Leipzig University Medical Center, Leipzig, Germany
| | - Birgit Luber
- Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie, München, Germany
| | - Drolaiz H W Liu
- Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center, Maastricht, the Netherlands
- Institute of Clinical Pathology and Molecular Pathology, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Rupert Langer
- Institute of Clinical Pathology and Molecular Pathology, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Florian Lordick
- University Cancer Center Leipzig (UCCL), Leipzig University Medical Center, Leipzig, Germany
- Department of Oncology, Gastroenterology, Hepatology, Pulmonology and Infectious Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
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Wang Q, Sun N, Kunzke T, Buck A, Shen J, Prade VM, Stöckl B, Wang J, Feuchtinger A, Walch A. A simple preparation step to remove excess liquid lipids in white adipose tissue enabling improved detection of metabolites via MALDI-FTICR imaging MS. Histochem Cell Biol 2022; 157:595-605. [PMID: 35391562 PMCID: PMC9114030 DOI: 10.1007/s00418-022-02088-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2022] [Indexed: 11/10/2022]
Abstract
Matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) imaging mass spectrometry (MS) is a powerful technology used to analyze metabolites in various tissues. However, it faces significant challenges in studying adipose tissues. Poor matrix distribution and crystallization caused by excess liquid lipids on the surface of tissue sections hamper m/z species detection, an adverse effect that particularly presents in lipid-rich white adipose tissue (WAT). In this study, we integrated a simple and low-cost preparation step into the existing MALDI-FTICR imaging MS pipeline. The new method—referred to as filter paper application—is characterized by an easy sample handling and high reproducibility. The aforementioned filter paper is placed onto the tissue prior to matrix application in order to remove the layer of excess liquid lipids. Consequently, MALDI-FTICR imaging MS detection was significantly improved, resulting in a higher number of detected m/z species and higher ion intensities. After analyzing various durations of filter paper application, 30 s was found to be optimal, resulting in the detection of more than 3700 m/z species. Apart from the most common lipids found in WAT, other molecules involved in various metabolic pathways were detected, including nucleotides, carbohydrates, and amino acids. Our study is the first to propose a solution to a specific limitation of MALDI-FTICR imaging MS in investigating lipid-rich WAT. The filter paper approach can be performed quickly and is particularly effective for achieving uniform matrix distribution on fresh frozen WAT while maintaining tissue integrity. It thus helps to gain insight into the metabolism in WAT.
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Affiliation(s)
- Qian Wang
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Jian Shen
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Barbara Stöckl
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Jun Wang
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
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9
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Erlmeier F, Sun N, Shen J, Feuchtinger A, Buck A, Prade VM, Kunzke T, Schraml P, Moch H, Autenrieth M, Weichert W, Hartmann A, Walch A. MALDI Mass Spectrometry Imaging-Prognostic Pathways and Metabolites for Renal Cell Carcinomas. Cancers (Basel) 2022; 14:cancers14071763. [PMID: 35406537 PMCID: PMC8996951 DOI: 10.3390/cancers14071763] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 03/24/2022] [Accepted: 03/24/2022] [Indexed: 01/27/2023] Open
Abstract
Simple Summary Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Nevertheless, prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by high mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) for prognostic biomarker detection. This is a suitable method for biomarker detection for several tumor entities. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes. Abstract High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan–Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.
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Affiliation(s)
- Franziska Erlmeier
- Institute of Pathology, University Hospital Erlangen-Nuremberg, 91054 Erlangen, Germany;
- Correspondence: (F.E.); (N.S.)
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
- Correspondence: (F.E.); (N.S.)
| | - Jian Shen
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
| | - Verena M. Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
| | - Peter Schraml
- Department of Pathology and Molecular Pathology, University Hospital Zurich, 8091 Zurich, Switzerland; (P.S.); (H.M.)
| | - Holger Moch
- Department of Pathology and Molecular Pathology, University Hospital Zurich, 8091 Zurich, Switzerland; (P.S.); (H.M.)
| | - Michael Autenrieth
- Department of Urology, Rechts der Isar Medical Center, Technical University of Munich, 81675 Munich, Germany;
| | - Wilko Weichert
- Institute of Pathology, Technical University Munich, 81675 Munich, Germany;
| | - Arndt Hartmann
- Institute of Pathology, University Hospital Erlangen-Nuremberg, 91054 Erlangen, Germany;
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München–German Research Center for Environmental Health, 85764 Neuherberg, Germany; (J.S.); (A.F.); (A.B.); (V.M.P.); (T.K.); (A.W.)
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10
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Prade VM, Sun N, Shen J, Feuchtinger A, Kunzke T, Buck A, Schraml P, Moch H, Schwamborn K, Autenrieth M, Gschwend JE, Erlmeier F, Hartmann A, Walch A. The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification. Clin Transl Med 2022; 12:e666. [PMID: 35184396 PMCID: PMC8858620 DOI: 10.1002/ctm2.666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/11/2021] [Accepted: 11/17/2021] [Indexed: 12/14/2022] Open
Affiliation(s)
- Verena M. Prade
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
| | - Na Sun
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
| | - Jian Shen
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
| | - Thomas Kunzke
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
| | - Achim Buck
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
| | - Peter Schraml
- Institute of Pathology and Molecular Pathology University Hospital Zurich Zurich Switzerland
| | - Holger Moch
- Institute of Pathology and Molecular Pathology University Hospital Zurich Zurich Switzerland
| | | | | | | | - Franziska Erlmeier
- Institute of Pathology, University Hospital Erlangen Friedrich‐Alexander‐University Erlangen‐Nürnberg Erlangen Germany
- Comprehensive Cancer Center Erlangen‐EMN (CCC ER‐EMN) Erlangen Germany
| | - Arndt Hartmann
- Institute of Pathology, University Hospital Erlangen Friedrich‐Alexander‐University Erlangen‐Nürnberg Erlangen Germany
- Comprehensive Cancer Center Erlangen‐EMN (CCC ER‐EMN) Erlangen Germany
| | - Axel Walch
- Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany
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11
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Sato S, Dyar KA, Treebak JT, Jepsen SL, Ehrlich AM, Ashcroft SP, Trost K, Kunzke T, Prade VM, Small L, Basse AL, Schönke M, Chen S, Samad M, Baldi P, Barrès R, Walch A, Moritz T, Holst JJ, Lutter D, Zierath JR, Sassone-Corsi P. Atlas of exercise metabolism reveals time-dependent signatures of metabolic homeostasis. Cell Metab 2022; 34:329-345.e8. [PMID: 35030324 DOI: 10.1016/j.cmet.2021.12.016] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 11/22/2021] [Accepted: 12/15/2021] [Indexed: 12/12/2022]
Abstract
Tissue sensitivity and response to exercise vary according to the time of day and alignment of circadian clocks, but the optimal exercise time to elicit a desired metabolic outcome is not fully defined. To understand how tissues independently and collectively respond to timed exercise, we applied a systems biology approach. We mapped and compared global metabolite responses of seven different mouse tissues and serum after an acute exercise bout performed at different times of the day. Comparative analyses of intra- and inter-tissue metabolite dynamics, including temporal profiling and blood sampling across liver and hindlimb muscles, uncovered an unbiased view of local and systemic metabolic responses to exercise unique to time of day. This comprehensive atlas of exercise metabolism provides clarity and physiological context regarding the production and distribution of canonical and novel time-dependent exerkine metabolites, such as 2-hydroxybutyrate (2-HB), and reveals insight into the health-promoting benefits of exercise on metabolism.
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Affiliation(s)
- Shogo Sato
- Center for Epigenetics and Metabolism, INSERM U1233, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Kenneth A Dyar
- Metabolic Physiology, Institute for Diabetes and Cancer, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Jonas T Treebak
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sara L Jepsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Biomedical Sciences, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Amy M Ehrlich
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stephen P Ashcroft
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kajetan Trost
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lewin Small
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Astrid Linde Basse
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Milena Schönke
- Department of Molecular Medicine and Surgery, Integrative Physiology, Karolinska Institutet, Stockholm, Sweden
| | - Siwei Chen
- Institute for Genomics and Bioinformatics, University of California, Irvine, Irvine, CA, USA
| | - Muntaha Samad
- Institute for Genomics and Bioinformatics, University of California, Irvine, Irvine, CA, USA
| | - Pierre Baldi
- Institute for Genomics and Bioinformatics, University of California, Irvine, Irvine, CA, USA
| | - Romain Barrès
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Moritz
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens J Holst
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Biomedical Sciences, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Dominik Lutter
- German Center for Diabetes Research, Neuherberg, Germany; Computational Discovery Research, Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Juleen R Zierath
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Molecular Medicine and Surgery, Integrative Physiology, Karolinska Institutet, Stockholm, Sweden; Department of Physiology and Pharmacology, Integrative Physiology, Karolinska Institutet, Stockholm, Sweden.
| | - Paolo Sassone-Corsi
- Center for Epigenetics and Metabolism, INSERM U1233, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA, USA
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12
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Buck A, Prade VM, Kunzke T, Feuchtinger A, Kröll D, Feith M, Dislich B, Balluff B, Langer R, Walch A. Metabolic tumor constitution is superior to tumor regression grading for evaluating response to neoadjuvant therapy of esophageal adenocarcinoma patients. J Pathol 2021; 256:202-213. [PMID: 34719782 DOI: 10.1002/path.5828] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 10/04/2021] [Accepted: 10/28/2021] [Indexed: 11/11/2022]
Abstract
The response to neoadjuvant therapy can vary widely between individual patients. Histopathological tumor regression grading (TRG) is a strong factor for treatment response and survival prognosis of esophageal adenocarcinoma (EAC) patients following neoadjuvant treatment and surgery. However, TRG systems are usually based on the estimation of residual tumor but do not consider stromal or metabolic changes after treatment. Spatial metabolomics analysis is a powerful tool for molecular tissue phenotyping but has not been used so far in the context of neoadjuvant treatment of esophageal cancer. We used imaging mass spectrometry to assess the potential of spatial metabolomics on tumor and stroma tissue for evaluating therapy response of neoadjuvant-treated EAC patients. With an accuracy of 89.7%, the binary classifier trained on spatial tumor metabolite data proved to be superior for stratifying patients when compared to histopathological response assessment which had an accuracy of 70.5%. Sensitivities and specificities for the poor and favorable survival patient groups ranged from 84.9 to 93.3% using the metabolic classifier and from 62.2 to 78.1% using TRG. The tumor classifier was the only significant prognostic factor (HR 3.38, 95% CI = 1.40-8.12, P = 0.007) when adjusted for clinicopathological parameters such as TRG (HR 1.01, 95% CI = 0.67-1.53, P = 0.968) or stromal classifier (HR 1.856, 95% CI = 0.81-4.25, P = 0.143). The classifier even allowed to further stratify patients within the TRG1-3 categories. The underlying mechanisms of response to treatment has been figured out through network analysis. In summary, metabolic response evaluation outperformed histopathological response evaluation in our study with regard to prognostic stratification. This finding indicates that the metabolic constitution of tumor may have a greater impact on patient survival than the quantity of residual tumor cells or the stroma. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Dino Kröll
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, 3008, Bern, Switzerland.,Department of Surgery, Campus Charité Mitte
- Campus Virchow-Klinikum, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany
| | - Marcus Feith
- Department of Surgery, Klinikum rechts der Isar, TUM School of Medicine, 81675, Munich, Germany
| | - Bastian Dislich
- Institute of Pathology, University of Bern, Bern, Switzerland
| | - Benjamin Balluff
- Maastricht Multimodal Molecular Imaging Institute (M4i), Maastricht University, Maastricht, The Netherlands
| | - Rupert Langer
- Institute of Pathology, University of Bern, Bern, Switzerland.,Institute of Clinical Pathology and Molecular Pathology, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
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13
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Kunzke T, Prade VM, Buck A, Sun N, Feuchtinger A, Matzka M, Fernandez IE, Wuyts W, Ackermann M, Jonigk D, Aichler M, Schmid RA, Eickelberg O, Berezowska S, Walch A. Patterns of carbon-bound exogenous compounds in lung cancer patients and association with disease pathophysiology. Cancer Res 2021; 81:5862-5875. [PMID: 34666994 DOI: 10.1158/0008-5472.can-21-1175] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/30/2021] [Accepted: 10/14/2021] [Indexed: 11/16/2022]
Abstract
Asymptomatic anthracosis is the accumulation of black carbon particles in adult human lungs. It is a common occurrence, but the pathophysiological significance of anthracosis is debatable. Using in situ high mass resolution matrix-assisted laser desorption/ionization (MALDI) fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging analysis, we discovered noxious carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, or aromatic amines, in a series of 330 lung cancer patients in highly variable and unique patterns. The characteristic nature of carbon-bound exogenous compound had a strong association with patient outcome, tumor progression, the tumor immune microenvironment, PD-L1 expression, and DNA damage. Spatial correlation network analyses revealed substantial differences in the metabolome of tumor cells compared to tumor stroma depending on carbon-bound exogenous compounds. Overall, the bioactive pool of exogenous compounds is associated with several changes in lung cancer pathophysiology and correlates with patient outcome. Given the high prevalence of anthracosis in the lungs of adult humans, future work should investigate the role of carbon-bound exogenous compounds in lung carcinogenesis and lung cancer therapy.
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Affiliation(s)
- Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
| | - Marco Matzka
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
| | | | | | | | | | | | | | | | - Sabina Berezowska
- Deparment of Laboratory Medicine and Pathology, Institute of Pathology, Lausanne University Hospital and University of Lausanne
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Center Munich - German Research Center for Environmental Health
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14
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Kunzke T, Hölzl FT, Prade VM, Buck A, Huber K, Feuchtinger A, Ebert K, Zwingenberger G, Geffers R, Hauck SM, Haffner I, Luber B, Lordick F, Walch A. Metabolomic therapy response prediction in pretherapeutic tissue biopsies for trastuzumab in patients with HER2-positive advanced gastric cancer. Clin Transl Med 2021; 11:e547. [PMID: 34586736 PMCID: PMC8473480 DOI: 10.1002/ctm2.547] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 08/06/2021] [Accepted: 08/09/2021] [Indexed: 12/13/2022] Open
Affiliation(s)
- Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Fabian T Hölzl
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Katharina Huber
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Karolin Ebert
- Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie, München, Germany
| | - Gwen Zwingenberger
- Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie, München, Germany
| | - Robert Geffers
- Genome Analytics Group, Helmholtz Center for Infection Research HZI, Braunschweig, Germany
| | - Stefanie M Hauck
- Research Unit Protein Science and Metabolomics and Proteomics Core, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Ivonne Haffner
- University Cancer Center Leipzig (UCCL), Leipzig University Medical Center, Leipzig, Germany
| | - Birgit Luber
- Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie, München, Germany
| | - Florian Lordick
- University Cancer Center Leipzig (UCCL), Leipzig University Medical Center, Leipzig, Germany.,Department of Oncology, Gastroenterology, Hepatology, Pulmonology and Infectious Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
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15
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Kunzke T, Buck A, Prade VM, Feuchtinger A, Prokopchuk O, Martignoni ME, Heisz S, Hauner H, Janssen KP, Walch A, Aichler M. Derangements of amino acids in cachectic skeletal muscle are caused by mitochondrial dysfunction. J Cachexia Sarcopenia Muscle 2020; 11:226-240. [PMID: 31965747 PMCID: PMC7015243 DOI: 10.1002/jcsm.12498] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 07/12/2019] [Accepted: 08/25/2019] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Cachexia is the direct cause of at least 20% of cancer-associated deaths. Muscle wasting in skeletal muscle results in weakness, immobility, and death secondary to impaired respiratory muscle function. Muscle proteins are massively degraded in cachexia; nevertheless, the molecular mechanisms related to this process are poorly understood. Previous studies have reported conflicting results regarding the amino acid abundances in cachectic skeletal muscle tissues. There is a clear need to identify the molecular processes of muscle metabolism in the context of cachexia, especially how different types of molecules are involved in the muscle wasting process. METHODS New in situ -omics techniques were used to produce a more comprehensive picture of amino acid metabolism in cachectic muscles by determining the quantities of amino acids, proteins, and cellular metabolites. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging, we determined the in situ concentrations of amino acids and proteins, as well as energy and other cellular metabolites, in skeletal muscle tissues from genetic mouse cancer models (n = 21) and from patients with cancer (n = 6). Combined results from three individual MALDI mass spectrometry imaging methods were obtained and interpreted. Immunohistochemistry staining for mitochondrial proteins and myosin heavy chain expression, digital image analysis, and transmission electron microscopy complemented the MALDI mass spectrometry imaging results. RESULTS Metabolic derangements in cachectic mouse muscle tissues were detected, with significantly increased quantities of lysine, arginine, proline, and tyrosine (P = 0.0037, P = 0.0048, P = 0.0430, and P = 0.0357, respectively) and significantly reduced quantities of glutamate and aspartate (P = 0.0008 and P = 0.0124). Human skeletal muscle tissues revealed similar tendencies. A majority of altered amino acids were released by the breakdown of proteins involved in oxidative phosphorylation. Decreased energy charge was observed in cachectic muscle tissues (P = 0.0101), which was related to the breakdown of specific proteins. Additionally, expression of the cationic amino acid transporter CAT1 was significantly decreased in the mitochondria of cachectic mouse muscles (P = 0.0133); this decrease may play an important role in the alterations of cationic amino acid metabolism and decreased quantity of glutamate observed in cachexia. CONCLUSIONS Our results suggest that mitochondrial dysfunction has a substantial influence on amino acid metabolism in cachectic skeletal muscles, which appears to be triggered by diminished CAT1 expression, as well as the degradation of mitochondrial proteins. These findings provide new insights into the pathobiochemistry of muscle wasting.
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Affiliation(s)
- Thomas Kunzke
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Achim Buck
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Verena M Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Olga Prokopchuk
- Department of Surgery, Klinikum rechts der Isar, TUM, Munich, Germany
| | - Marc E Martignoni
- Department of Surgery, Klinikum rechts der Isar, TUM, Munich, Germany
| | - Simone Heisz
- Else Kroener-Fresenius-Center for Nutritional Medicine, Klinikum rechts der Isar, TUM, Munich, Germany.,ZIEL-Institute for Food and Health, Nutritional Medicine Unit, TUM, Freising, Germany
| | - Hans Hauner
- Else Kroener-Fresenius-Center for Nutritional Medicine, Klinikum rechts der Isar, TUM, Munich, Germany.,ZIEL-Institute for Food and Health, Nutritional Medicine Unit, TUM, Freising, Germany
| | | | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Michaela Aichler
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Oberschleißheim, Germany
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Prade VM, Gundlach H, Twardziok S, Chapman B, Tan C, Langridge P, Schulman AH, Stein N, Waugh R, Zhang G, Platzer M, Li C, Spannagl M, Mayer KFX. The pseudogenes of barley. Plant J 2018; 93:502-514. [PMID: 29205595 DOI: 10.1111/tpj.13794] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Revised: 11/16/2017] [Accepted: 11/24/2017] [Indexed: 06/07/2023]
Abstract
Pseudogenes have a reputation of being 'evolutionary relics' or 'junk DNA'. While they are well characterized in mammals, studies in more complex plant genomes have so far been hampered by the absence of reference genome sequences. Barley is one of the economically most important cereals and has a genome size of 5.1 Gb. With the first high-quality genome reference assembly available for a Triticeae crop, we conducted a whole-genome assessment of pseudogenes on the barley genome. We identified, characterized and classified 89 440 gene fragments and pseudogenes scattered along the chromosomes, with occasional hotspots and higher densities at the chromosome ends. Full-length pseudogenes (11 015) have preferentially retained their exon-intron structure. Retrotransposition of processed mRNAs only plays a marginal role in their creation. However, the distribution of retroposed pseudogenes reflects the Rabl configuration of barley chromosomes and thus hints at founding mechanisms. While parent genes related to the defense-response were found to be under-represented in cultivated barley, we detected several defense-related pseudogenes in wild barley accessions. The percentage of transcriptionally active pseudogenes is 7.2%, and these may potentially adopt new regulatory roles.The barley genome is rich in pseudogenes and small gene fragments mainly located towards chromosome tips or as tandemly repeated units. Our results indicate non-random duplication and pseudogenization preferences and improve our understanding of the dynamics of gene birth and death in large plant genomes and the mechanisms that lead to evolutionary innovations.
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Affiliation(s)
- Verena M Prade
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Heidrun Gundlach
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Sven Twardziok
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Brett Chapman
- Centre for Comparative Genomics, Murdoch University, 90 South Street, WA6150, Murdoch, Australia
| | - Cong Tan
- School of Veterinary and Life Sciences, Murdoch University, 90 South Street, WA6150, Murdoch, Australia
| | - Peter Langridge
- School of Agriculture, University of Adelaide, Waite Campus, SA5064, Urrbrae, Australia
| | - Alan H Schulman
- Green Technology, Natural Resources Institute (Luke), Viikki Plant Science Centre, Institute of Biotechnology, University of Helsinki, 00014, Helsinki, Finland
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
- School of Plant Biology, University of Western Australia, Crawley, WA6009, Australia
| | - Robbie Waugh
- The James Hutton Institute, Dundee, DD2 5DA, UK
- School of Life Sciences, University of Dundee, Dundee, DD2 5DA, UK
| | - Guoping Zhang
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Matthias Platzer
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), 07745, Jena, Germany
| | - Chengdao Li
- School of Veterinary and Life Sciences, Murdoch University, 90 South Street, WA6150, Murdoch, Australia
- Department of Agriculture and Food, Government of Western Australia, South Perth, WA, 6151, Australia
| | - Manuel Spannagl
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Klaus F X Mayer
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Alte Akademie 8, 85354, Freising, Germany
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