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Ellingsen EB, Bounova G, Kerzeli I, Anzar I, Simnica D, Aamdal E, Guren T, Clancy T, Mezheyeuski A, Inderberg EM, Mangsbo SM, Binder M, Hovig E, Gaudernack G. Characterization of the T cell receptor repertoire and melanoma tumor microenvironment upon combined treatment with ipilimumab and hTERT vaccination. Lab Invest 2022; 20:419. [PMID: 36089578 PMCID: PMC9465869 DOI: 10.1186/s12967-022-03624-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/01/2022] [Indexed: 11/10/2022]
Abstract
Background This clinical trial evaluated a novel telomerase-targeting therapeutic cancer vaccine, UV1, in combination with ipilimumab, in patients with metastatic melanoma. Translational research was conducted on patient-derived blood and tissue samples with the goal of elucidating the effects of treatment on the T cell receptor repertoire and tumor microenvironment. Methods The trial was an open-label, single-center phase I/IIa study. Eligible patients had unresectable metastatic melanoma. Patients received up to 9 UV1 vaccinations and four ipilimumab infusions. Clinical responses were assessed according to RECIST 1.1. Patients were followed up for progression-free survival (PFS) and overall survival (OS). Whole-exome and RNA sequencing, and multiplex immunofluorescence were performed on the biopsies. T cell receptor (TCR) sequencing was performed on the peripheral blood and tumor tissues. Results Twelve patients were enrolled in the study. Vaccine-specific immune responses were detected in 91% of evaluable patients. Clinical responses were observed in four patients. The mPFS was 6.7 months, and the mOS was 66.3 months. There was no association between baseline tumor mutational burden, neoantigen load, IFN-γ gene signature, tumor-infiltrating lymphocytes, and response to therapy. Tumor telomerase expression was confirmed in all available biopsies. Vaccine-enriched TCR clones were detected in blood and biopsy, and an increase in the tumor IFN-γ gene signature was detected in clinically responding patients. Conclusion Clinical responses were observed irrespective of established predictive biomarkers for checkpoint inhibitor efficacy, indicating an added benefit of the vaccine-induced T cells. The clinical and immunological read-out warrants further investigation of UV1 in combination with checkpoint inhibitors. Trial registration Clinicaltrials.gov identifier: NCT02275416. Registered October 27, 2014. https://clinicaltrials.gov/ct2/show/NCT02275416?term=uv1&draw=2&rank=6 Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03624-z.
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2
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Broeren MGA, Wang JJ, Balzaretti G, Groenen PJTA, van Schaik BDC, Chataway T, Kaffa C, Bervoets S, Hebeda KM, Bounova G, Pruijn GJM, Gordon TP, De Vries N, Thurlings RM. Proteogenomic analysis of the autoreactive B cell repertoire in blood and tissues of patients with Sjögren's syndrome. Ann Rheum Dis 2022; 81:644-652. [PMID: 35144926 PMCID: PMC8995816 DOI: 10.1136/annrheumdis-2021-221604] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [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: 10/01/2021] [Accepted: 01/06/2022] [Indexed: 11/30/2022]
Abstract
Objective To comparatively analyse the aberrant affinity maturation of the antinuclear and rheumatoid factor (RF) B cell repertoires in blood and tissues of patients with Sjögren’s syndrome (SjS) using an integrated omics workflow. Methods Peptide sequencing of anti-Ro60, anti-Ro52, anti-La and RF was combined with B cell repertoire analysis at the DNA, RNA and single cell level in blood B cell subsets, affected salivary gland and extranodal marginal zone lymphomas of mucosa-associated lymphoid tissue (MALT) of patients with SjS. Results Affected tissues contained anti-Ro60, anti-Ro52, anti-La and RF clones as a small part of a polyclonal infiltrate. Anti-Ro60, anti-La and anti-Ro52 clones outnumbered RF clones. MALT lymphoma tissues contained monoclonal RF expansions. Autoreactive clones were not selected from a restricted repertoire in a circulating B cell subset. The antinuclear antibody (ANA) repertoires displayed similar antigen-dependent and immunoglobulin (Ig) G1-directed affinity maturation. RF clones displayed antigen-dependent, IgM-directed and more B cell receptor integrity-dependent affinity maturation. This coincided with extensive intra-clonal diversification in RF-derived lymphomas. Regeneration of clinical disease manifestations after rituximab coincided with large RF clones, which not necessarily belonged to the lymphoma clone, that displayed continuous affinity maturation and intra-clonal diversification. Conclusion The ANA and RF repertoires in patients with SjS display tissue-restricted, antigen-dependent and divergent affinity maturation. Affinity maturation of RF clones deviates further during RF clone derived lymphomagenesis and during regeneration of the autoreactive repertoire after temporary disruption by rituximab. These data give insight into the molecular mechanisms of autoreactive inflammation in SjS, assist MALT lymphoma diagnosis and allow tracking its response to rituximab.
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Affiliation(s)
- Mathijs G A Broeren
- Department of Rheumatology, Radboudumc, Nijmegen, The Netherlands.,Department of Biomolecular Chemistry, Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - Jing J Wang
- Department of Immunology, Flinders University, Adelaide, South Australia, Australia
| | - Giulia Balzaretti
- Department of Clinical Immunology and Rheumatology, Amsterdam Rheumatology and Immunology Center, Amsterdam, The Netherlands
| | | | - Barbera D C van Schaik
- Bioinformatics Laboratory, Department of Epidemiology and Data Science, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Tim Chataway
- College of Medicine and Public Health, Flinders University of South Australia, Adelaide, South Australia, Australia
| | - Charlotte Kaffa
- Radboud Technology Center for Bioinformatics, Radboudumc, Nijmegen, The Netherlands
| | - Sander Bervoets
- Radboud Technology Center for Bioinformatics, Radboudumc, Nijmegen, The Netherlands
| | - Konnie M Hebeda
- Department of Pathology, Radboudumc, Nijmegen, The Netherlands
| | | | - Ger J M Pruijn
- Department of Biomolecular Chemistry, Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - Thomas P Gordon
- SA Pathology, Department of Immunology, College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
| | - Niek De Vries
- Department of Clinical Immunology and Rheumatology, Amsterdam Rheumatology and Immunology Center, Amsterdam, The Netherlands
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3
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Driehuis E, van Hoeck A, Moore K, Kolders S, Francies HE, Gulersonmez MC, Stigter ECA, Burgering B, Geurts V, Gracanin A, Bounova G, Morsink FH, Vries R, Boj S, van Es J, Offerhaus GJA, Kranenburg O, Garnett MJ, Wessels L, Cuppen E, Brosens LAA, Clevers H. Pancreatic cancer organoids recapitulate disease and allow personalized drug screening. Proc Natl Acad Sci U S A 2019; 116:26580-26590. [PMID: 31818951 PMCID: PMC6936689 DOI: 10.1073/pnas.1911273116] [Citation(s) in RCA: 232] [Impact Index Per Article: 46.4] [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] [Indexed: 12/21/2022] Open
Abstract
We report the derivation of 30 patient-derived organoid lines (PDOs) from tumors arising in the pancreas and distal bile duct. PDOs recapitulate tumor histology and contain genetic alterations typical of pancreatic cancer. In vitro testing of a panel of 76 therapeutic agents revealed sensitivities currently not exploited in the clinic, and underscores the importance of personalized approaches for effective cancer treatment. The PRMT5 inhibitor EZP015556, shown to target MTAP (a gene commonly lost in pancreatic cancer)-negative tumors, was validated as such, but also appeared to constitute an effective therapy for a subset of MTAP-positive tumors. Taken together, the work presented here provides a platform to identify novel therapeutics to target pancreatic tumor cells using PDOs.
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Affiliation(s)
- Else Driehuis
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, 3584 CT Utrecht, The Netherlands
| | - Arne van Hoeck
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Center for Molecular Medicine, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
| | - Kat Moore
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Sigrid Kolders
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, 3584 CT Utrecht, The Netherlands
| | | | - M. Can Gulersonmez
- Department of Molecular Cancer Research, Center Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Edwin C. A. Stigter
- Department of Molecular Cancer Research, Center Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Boudewijn Burgering
- Department of Molecular Cancer Research, Center Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Veerle Geurts
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, 3584 CT Utrecht, The Netherlands
| | - Ana Gracanin
- Hubrecht Organoid Technology, Utrecht 3584 CM, The Netherlands
| | - Gergana Bounova
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Folkert H. Morsink
- Department of Pathology, University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Robert Vries
- Hubrecht Organoid Technology, Utrecht 3584 CM, The Netherlands
| | - Sylvia Boj
- Hubrecht Organoid Technology, Utrecht 3584 CM, The Netherlands
| | - Johan van Es
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, 3584 CT Utrecht, The Netherlands
| | - G. Johan A. Offerhaus
- Department of Pathology, University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Onno Kranenburg
- Utrecht Platform for Organoid Technology, Utrecht Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | | | - Lodewyk Wessels
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Edwin Cuppen
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Center for Molecular Medicine, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
- Hartwig Medical Foundation, 1098 XH Amsterdam, The Netherlands
- Center for Personalized Cancer Treatment,University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Lodewijk A. A. Brosens
- Department of Pathology, University Medical Center Utrecht, Utrecht 3584 CM, The Netherlands
| | - Hans Clevers
- Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, 3584 CT Utrecht, The Netherlands
- Princess Maxima Center, Utrecht 3584 CS, The Netherlands
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4
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Komor MA, Bosch LJ, Bounova G, Bolijn AS, Delis-van Diemen PM, Rausch C, Hoogstrate Y, Stubbs AP, de Jong M, Jenster G, van Grieken NC, Carvalho B, Wessels LF, Jimenez CR, Fijneman RJ, Meijer GA. Consensus molecular subtype classification of colorectal adenomas. J Pathol 2018; 246:266-276. [PMID: 29968252 PMCID: PMC6221003 DOI: 10.1002/path.5129] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 05/08/2018] [Accepted: 06/20/2018] [Indexed: 01/15/2023]
Abstract
Consensus molecular subtyping is an RNA expression‐based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction‐based methodology. DNA copy number was assessed by low‐coverage DNA sequencing (n = 30) or array‐comparative genomic hybridisation (n = 32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n = 556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 ‘metabolic subtype’, which was least common among CRCs, was most prevalent among adenomas (n = 45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the ‘MSI immune’ subtype. Eight adenomas (13%) were classified as the ‘canonical’ CMS2. No adenomas were classified as the ‘mesenchymal’ CMS4, consistent with the fact that adenomas lack invasion‐associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high‐risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Malgorzata A Komor
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands.,Oncoproteomics Laboratory, Department of Medical Oncology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Linda Jw Bosch
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Gergana Bounova
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Anne S Bolijn
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Pien M Delis-van Diemen
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Christian Rausch
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Youri Hoogstrate
- Department of Urology, Erasmus Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Andrew P Stubbs
- Department of Bioinformatics, Erasmus Medical Centre Rotterdam, Rotterdam, The Netherlands
| | | | - Guido Jenster
- Department of Urology, Erasmus Medical Centre Rotterdam, Rotterdam, The Netherlands
| | | | - Beatriz Carvalho
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Lodewyk Fa Wessels
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Connie R Jimenez
- Oncoproteomics Laboratory, Department of Medical Oncology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Remond Ja Fijneman
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Gerrit A Meijer
- Translational Gastrointestinal Oncology, Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
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5
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Komor MA, Bosch LJ, Bounova G, Bolijn AS, Diemen PDV, Rausch C, Hoogstrate Y, Stubbs A, Jong MD, Jenster G, Grieken NCA, Carvalho B, Wessels L, Jimenez CR, Fijneman RJ, Meijer GA, Consortium NGSP. Abstract 3676: CMS classification of colorectal adenomas. Cancer Res 2018. [DOI: 10.1158/1538-7445.am2018-3676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background Consensus molecular subtyping (CMS) is an RNA-expression-based classification of colorectal cancers (CRC). Genomic alterations, resulting in specific RNA-expression patterns, accumulate during CRC pathogenesis, including the premalignant adenoma stage.
Aim This study aimed to investigate whether differentiation of colorectal neoplasia into CMS classes can already be recognized at the adenoma stage, and whether specific CMS classes could be associated with DNA copy number aberrations that mark adenomas at high-risk of progressing to CRC.
Materials and Methods RNA-sequencing was performed on 62 advanced adenomas and 59 CRCs. DNA copy number analysis in adenomas was performed by low-coverage DNA-sequencing (n=30) or array-Comparative Genomic Hybridization (n=32). Microsatellite instability (MSI) status was determined by PCR methods. Adenomas and CRCs were classified into CMS subtypes together with CRCs (n=556) from The Cancer Genome Atlas, using the Random Forest CMS classifier.
Results The majority of the adenomas were classified as CMS3 (n=45; 72%), the 'metabolic subtype', recognized as least common among CRCs. No adenomas were classified as the 'mesenchymal' CMS4 subtype. One adenoma was classified as the 'MSI immune' CMS1 (2%), and 8 adenomas as the 'canonical' CMS2 (13%) type. The remaining 8 (13%) could not be classified. The CMS3 class was enriched with adenomas at low-risk of progression.
Conclusion Most adenomas were successfully classified. The lack of CMS4 adenomas is consistent with the fact that adenomas lack invasion-associated stroma. Adenomas showing cancer-associated chromosomal instability (CIN) or MSI (24%) were mostly classified as CMS2 and CMS1, respectively. The CMS3 subtype appeared to be the predominant adenoma signature.
Citation Format: Malgorzata A. Komor, Linda J. Bosch, Gergana Bounova, Anne S. Bolijn, Pien Delis-van Diemen, Christian Rausch, Youri Hoogstrate, Andrew Stubbs, Mark de Jong, Guido Jenster, Nicole C. an Grieken, Beatriz Carvalho, Lodewyk Wessels, Connie R. Jimenez, Remond J. Fijneman, Gerrit A. Meijer, NGS-ProToCol Consortium. CMS classification of colorectal adenomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3676.
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Affiliation(s)
| | | | | | | | | | | | | | - Andrew Stubbs
- 1Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | - Guido Jenster
- 3Erasmus Medical Centre Rotterdam, Rotterdam, Netherlands
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6
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Sachs N, de Ligt J, Kopper O, Gogola E, Bounova G, Weeber F, Balgobind AV, Wind K, Gracanin A, Begthel H, Korving J, van Boxtel R, Duarte AA, Lelieveld D, van Hoeck A, Ernst RF, Blokzijl F, Nijman IJ, Hoogstraat M, van de Ven M, Egan DA, Zinzalla V, Moll J, Boj SF, Voest EE, Wessels L, van Diest PJ, Rottenberg S, Vries RGJ, Cuppen E, Clevers H. A Living Biobank of Breast Cancer Organoids Captures Disease Heterogeneity. Cell 2017; 172:373-386.e10. [PMID: 29224780 DOI: 10.1016/j.cell.2017.11.010] [Citation(s) in RCA: 987] [Impact Index Per Article: 141.0] [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: 11/20/2016] [Revised: 10/06/2017] [Accepted: 11/03/2017] [Indexed: 12/12/2022]
Abstract
Breast cancer (BC) comprises multiple distinct subtypes that differ genetically, pathologically, and clinically. Here, we describe a robust protocol for long-term culturing of human mammary epithelial organoids. Using this protocol, >100 primary and metastatic BC organoid lines were generated, broadly recapitulating the diversity of the disease. BC organoid morphologies typically matched the histopathology, hormone receptor status, and HER2 status of the original tumor. DNA copy number variations as well as sequence changes were consistent within tumor-organoid pairs and largely retained even after extended passaging. BC organoids furthermore populated all major gene-expression-based classification groups and allowed in vitro drug screens that were consistent with in vivo xeno-transplantations and patient response. This study describes a representative collection of well-characterized BC organoids available for cancer research and drug development, as well as a strategy to assess in vitro drug response in a personalized fashion.
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Affiliation(s)
- Norman Sachs
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands; Foundation Hubrecht Organoid Technology (HUB), Yalelaan 62, 3584 CM Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Joep de Ligt
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Oded Kopper
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Ewa Gogola
- Division of Molecular Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Gergana Bounova
- Division of Molecular Carcinogenesis, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Fleur Weeber
- Division of Molecular Oncology and Immunology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Anjali Vanita Balgobind
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands; Foundation Hubrecht Organoid Technology (HUB), Yalelaan 62, 3584 CM Utrecht, the Netherlands
| | - Karin Wind
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - Ana Gracanin
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - Harry Begthel
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - Jeroen Korving
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - Ruben van Boxtel
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Alexandra Alves Duarte
- Division of Molecular Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Daphne Lelieveld
- Cell Screening Core, Department of Cell Biology, Center for Molecular Medicine, University Medical Center, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Arne van Hoeck
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Robert Frans Ernst
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Francis Blokzijl
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Isaac Johannes Nijman
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Marlous Hoogstraat
- Division of Molecular Carcinogenesis, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Marieke van de Ven
- Mouse Clinic for Cancer and Aging (MCCA), Preclinical Intervention Unit, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - David Anthony Egan
- Cell Screening Core, Department of Cell Biology, Center for Molecular Medicine, University Medical Center, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Vittoria Zinzalla
- Pharmacology and Translational Research, Boehringer Ingelheim RCV GmbH & Co KG, Dr. Boehringer-Gasse 5-11, 1121 Vienna, Austria
| | - Jurgen Moll
- Pharmacology and Translational Research, Boehringer Ingelheim RCV GmbH & Co KG, Dr. Boehringer-Gasse 5-11, 1121 Vienna, Austria
| | - Sylvia Fernandez Boj
- Foundation Hubrecht Organoid Technology (HUB), Yalelaan 62, 3584 CM Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Emile Eugene Voest
- Division of Molecular Oncology and Immunology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Lodewyk Wessels
- Division of Molecular Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands; Faculty of EEMCS, Delft University of Technology, Delft, the Netherlands
| | - Paul Joannes van Diest
- Department of Pathology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Sven Rottenberg
- Division of Molecular Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Institute of Animal Pathology, Vetsuisse Faculty, University of Bern, Länggassstrasse 122, 3012 Bern, Switzerland
| | - Robert Gerhardus Jacob Vries
- Foundation Hubrecht Organoid Technology (HUB), Yalelaan 62, 3584 CM Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Edwin Cuppen
- Center for Molecular Medicine, Department of Genetics, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands
| | - Hans Clevers
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands; Cancer Genomics Netherlands, Oncode Institute, 3584 CG Utrecht, the Netherlands.
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7
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Koppens MAJ, Bounova G, Cornelissen-Steijger P, de Vries N, Sansom OJ, Wessels LFA, van Lohuizen M. Large variety in a panel of human colon cancer organoids in response to EZH2 inhibition. Oncotarget 2016; 7:69816-69828. [PMID: 27634879 PMCID: PMC5342517 DOI: 10.18632/oncotarget.12002] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [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] [Received: 06/06/2016] [Accepted: 09/04/2016] [Indexed: 01/28/2023] Open
Abstract
EZH2 inhibitors have gained great interest for their use as anti-cancer therapeutics. However, most research has focused on EZH2 mutant cancers and recently adverse effects of EZH2 inactivation have come to light. To determine whether colorectal cancer cells respond to EZH2 inhibition and to explore which factors influence the degree of response, we treated a panel of 20 organoid lines derived from human colon tumors with different concentrations of the EZH2 inhibitor GSK126. The resulting responses were associated with mutation status, gene expression and responses to other drugs. We found that the response to GSK126 treatment greatly varied between organoid lines. Response associated with the mutation status of ATRX and PAX2, and correlated with BIK expression. It also correlated well with response to Nutlin-3a which inhibits MDM2-p53 interaction thereby activating p53 signaling. Sensitivity to EZH2 ablation depended on the presence of wild type p53, as tumor organoids became resistant when p53 was mutated or knocked down. Our exploratory study provides insight into which genetic factors predict sensitivity to EZH2 inhibition. In addition, we show that the response to EZH2 inhibition requires wild type p53. We conclude that a subset of colorectal cancer patients may benefit from EZH2-targeting therapies.
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Affiliation(s)
- Martijn AJ Koppens
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Gergana Bounova
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Nienke de Vries
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Owen J Sansom
- Cancer Research UK Beatson Institute, Glasgow, United Kingdom
| | - Lodewyk FA Wessels
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of EEMCS, Delft University of Technology, Delft, The Netherlands
- Cancer Genomics Centre Netherlands (CGC.nl), The Netherlands
| | - Maarten van Lohuizen
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Cancer Genomics Centre Netherlands (CGC.nl), The Netherlands
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Koppens MAJ, Bounova G, Gargiulo G, Tanger E, Janssen H, Cornelissen-Steijger P, Blom M, Song JY, Wessels LFA, van Lohuizen M. Deletion of Polycomb Repressive Complex 2 From Mouse Intestine Causes Loss of Stem Cells. Gastroenterology 2016; 151:684-697.e12. [PMID: 27342214 DOI: 10.1053/j.gastro.2016.06.020] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [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: 07/16/2015] [Revised: 06/03/2016] [Accepted: 06/13/2016] [Indexed: 12/30/2022]
Abstract
BACKGROUND & AIMS The polycomb repressive complex 2 (PRC2) regulates differentiation by contributing to repression of gene expression and thereby stabilizing the fate of stem cells and their progeny. PRC2 helps to maintain adult stem cell populations, but little is known about its functions in intestinal stem cells. We studied phenotypes of mice with intestine-specific deletion of the PRC2 proteins embryonic ectoderm development (EED) (a subunit required for PRC2 function) and enhancer of zeste homolog 2 (EZH2) (a histone methyltransferase). METHODS We performed studies of AhCre;EedLoxP/LoxP (EED knockout) mice and AhCre;Ezh2LoxP/LoxP (EZH2 knockout) mice, which have intestine-specific disruption in EED and EZH2, respectively. Small intestinal crypts were isolated and subsequently cultured to grow organoids. Intestines and organoids were analyzed by immunohistochemical, in situ hybridization, RNA sequence, and chromatin immunoprecipitation methods. RESULTS Intestines of EED knockout mice had massive crypt degeneration and lower numbers of proliferating cells compared with wild-type control mice. Cdkn2a became derepressed and we detected increased levels of P21. We did not observe any differences between EZH2 knockout and control mice. Intestinal crypts from EED knockout mice had signs of aberrant differentiation of uncommitted crypt cells-these differentiated toward the secretory cell lineage. Furthermore, crypts from EED-knockout mice had impaired Wnt signaling and concomitant loss of intestinal stem cells, this phenotype was not reversed upon ectopic stimulation of Wnt and Notch signaling in organoids. Analysis of gene expression patterns from intestinal tissues of EED knockout mice showed dysregulation of several genes involved in Wnt signaling. Wnt signaling was regulated directly by PRC2. CONCLUSIONS In intestinal tissues of mice, PRC2 maintains small intestinal stem cells by promoting proliferation and preventing differentiation in the intestinal stem cell compartment. PRC2 controls gene expression in multiple signaling pathways that regulate intestinal homeostasis. Sequencing data are available in the genomics data repository GEO under reference series GSE81578; RNA sequencing data are available under subseries GSE81576; and ChIP sequencing data are available under subseries GSE81577.
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Affiliation(s)
- Martijn A J Koppens
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Gergana Bounova
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Gaetano Gargiulo
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Ellen Tanger
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Hans Janssen
- Division of Cell Biology II, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Marleen Blom
- Transgenic Core Facility, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Ji-Ying Song
- Department of Experimental Animal Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Lodewyk F A Wessels
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands; Department of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands; Cancer Genomics Centre Netherlands, Utrecht, The Netherlands
| | - Maarten van Lohuizen
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, The Netherlands; Cancer Genomics Centre Netherlands, Utrecht, The Netherlands.
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Bonhoure N, Bounova G, Bernasconi D, Praz V, Lammers F, Canella D, Willis IM, Herr W, Hernandez N, Delorenzi M. Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization. Genome Res 2014; 24:1157-68. [PMID: 24709819 PMCID: PMC4079971 DOI: 10.1101/gr.168260.113] [Citation(s) in RCA: 101] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.
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Affiliation(s)
- Nicolas Bonhoure
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland
| | - Gergana Bounova
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - David Bernasconi
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Viviane Praz
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Fabienne Lammers
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland
| | - Donatella Canella
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland
| | - Ian M Willis
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Winship Herr
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland
| | - Nouria Hernandez
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland
| | - Mauro Delorenzi
- Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Department of Oncology and the Ludwig Center for Cancer Research, Faculty of Biology and Medicine, University of Lausanne, 1011 Lausanne, Switzerland
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Bounova G, de Weck O. Overview of metrics and their correlation patterns for multiple-metric topology analysis on heterogeneous graph ensembles. Phys Rev E Stat Nonlin Soft Matter Phys 2012; 85:016117. [PMID: 22400635 DOI: 10.1103/physreve.85.016117] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2010] [Revised: 10/26/2011] [Indexed: 05/31/2023]
Abstract
This study is an overview of network topology metrics and a computational approach to analyzing graph topology via multiple-metric analysis on graph ensembles. The paper cautions against studying single metrics or combining disparate graph ensembles from different domains to extract global patterns. This is because there often exists considerable diversity among graphs that share any given topology metric, patterns vary depending on the underlying graph construction model, and many real data sets are not actual statistical ensembles. As real data examples, we present five airline ensembles, comprising temporal snapshots of networks of similar topology. Wikipedia language networks are shown as an example of a nontemporal ensemble. General patterns in metric correlations, as well as exceptions, are discussed by representing the data sets via hierarchically clustered correlation heat maps. Most topology metrics are not independent and their correlation patterns vary across ensembles. In general, density-related metrics and graph distance-based metrics cluster and the two groups are orthogonal to each other. Metrics based on degree-degree correlations have the highest variance across ensembles and cluster the different data sets on par with principal component analysis. Namely, the degree correlation, the s metric, their elasticities, and the rich club moments appear to be most useful in distinguishing topologies.
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Affiliation(s)
- Gergana Bounova
- Engineering Systems Division, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.
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