1
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Melliou S, Sangster KT, Kao J, Zarrei M, Lam KHB, Howe J, Papaioannou MD, Tsang QPL, Borhani OA, Sajid RS, Bonnet C, Leheup B, Shannon P, Scherer SW, Stavropoulos DJ, Djuric U, Diamandis P. Regionally defined proteomic profiles of human cerebral tissue and organoids reveal conserved molecular modules of neurodevelopment. Cell Rep 2022; 39:110846. [PMID: 35613588 DOI: 10.1016/j.celrep.2022.110846] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 02/01/2022] [Accepted: 04/28/2022] [Indexed: 12/14/2022] Open
Abstract
Cerebral organoids have emerged as robust models for neurodevelopmental and pathological processes, as well as a powerful discovery platform for less-characterized neurobiological programs. Toward this prospect, we leverage mass-spectrometry-based proteomics to molecularly profile precursor and neuronal compartments of both human-derived organoids and mid-gestation fetal brain tissue to define overlapping programs. Our analysis includes recovery of precursor-enriched transcriptional regulatory proteins not found to be differentially expressed in previous transcriptomic datasets. To highlight the discovery potential of this resource, we show that RUVBL2 is preferentially expressed in the SOX2-positive compartment of organoids and that chemical inactivation leads to precursor cell displacement and apoptosis. To explore clinicopathological correlates of this cytoarchitectural disruption, we interrogate clinical datasets and identify rare de novo genetic variants involving RUVBL2 in patients with neurodevelopmental impairments. Together, our findings demonstrate how cell-type-specific profiling of organoids can help nominate previously unappreciated genes in neurodevelopment and disease.
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Affiliation(s)
- Sofia Melliou
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Kevin T Sangster
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Jennifer Kao
- Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Mehdi Zarrei
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - K H Brian Lam
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Jennifer Howe
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | | | - Queenie P L Tsang
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Okty Abbasi Borhani
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Rifat Shahriar Sajid
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Céline Bonnet
- Department of Clinical Genetics, Nancy University Hospital, Nancy, France
| | - Bruno Leheup
- Department of Clinical Genetics, Nancy University Hospital, Nancy, France
| | - Patrick Shannon
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada; Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Stephen W Scherer
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Molecular Genetics and McLaughlin Centre, University of Toronto, Toronto, ON M5G 1X5, Canada; The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Dimitri James Stavropoulos
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada; Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada; Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON M5S 1A8, Canada.
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2
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Lam KHB, Leon AJ, Hui W, Lee SCE, Batruch I, Faust K, Klekner A, Hutóczki G, Koritzinsky M, Richer M, Djuric U, Diamandis P. Topographic mapping of the glioblastoma proteome reveals a triple-axis model of intra-tumoral heterogeneity. Nat Commun 2022; 13:116. [PMID: 35013227 PMCID: PMC8748638 DOI: 10.1038/s41467-021-27667-w] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [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: 03/19/2021] [Accepted: 12/03/2021] [Indexed: 12/12/2022] Open
Abstract
Glioblastoma is an aggressive form of brain cancer with well-established patterns of intra-tumoral heterogeneity implicated in treatment resistance and progression. While regional and single cell transcriptomic variations of glioblastoma have been recently resolved, downstream phenotype-level proteomic programs have yet to be assigned across glioblastoma's hallmark histomorphologic niches. Here, we leverage mass spectrometry to spatially align abundance levels of 4,794 proteins to distinct histologic patterns across 20 patients and propose diverse molecular programs operational within these regional tumor compartments. Using machine learning, we overlay concordant transcriptional information, and define two distinct proteogenomic programs, MYC- and KRAS-axis hereon, that cooperate with hypoxia to produce a tri-dimensional model of intra-tumoral heterogeneity. Moreover, we highlight differential drug sensitivities and relative chemoresistance in glioblastoma cell lines with enhanced KRAS programs. Importantly, these pharmacological differences are less pronounced in transcriptional glioblastoma subgroups suggesting that this model may provide insights for targeting heterogeneity and overcoming therapy resistance.
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Affiliation(s)
- K H Brian Lam
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
| | - Alberto J Leon
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada
| | - Weili Hui
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada
| | - Sandy Che-Eun Lee
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, #2374-1 King's College Circle, M5S 1A8, Canada
| | - Ihor Batruch
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, M5G 1×5, Canada
| | - Kevin Faust
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada
- Department of Computer Science, University of Toronto, 40 St.George Street, Toronto, Ontario, M5S 2E4, Canada
| | - Almos Klekner
- Department of Neurosurgery, Faculty of Medicine, University of Debrecen, 4032, Debrecen, Hungary
| | - Gábor Hutóczki
- Department of Neurosurgery, Faculty of Medicine, University of Debrecen, 4032, Debrecen, Hungary
| | - Marianne Koritzinsky
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, #2374-1 King's College Circle, M5S 1A8, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, Ontario, #504-149 College Street, M5T1P5, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
| | - Maxime Richer
- Department of Pathology, Centre Hospitalier Universitaire de Sherbrooke, 3001, 12e avenue Nord, Sherbrooke, QC, J1H 5N4, Canada
- Axe neurosciences du Centre de recherche du Centre hospitalier universitaire (CHU) de Québec-Université Laval et Département de biologie moléculaire, biochimie et pathologie de l'Université Laval, Québec, QC, G1V 4G2, Canada
| | - Ugljesa Djuric
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada
- Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, Toronto, Ontario, M5G 2C4, Canada
| | - Phedias Diamandis
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada.
- Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, 610 University Avenue, M5G 2C1, Canada.
- Institute of Medical Science, University of Toronto, Toronto, Ontario, #2374-1 King's College Circle, M5S 1A8, Canada.
- Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, Toronto, Ontario, M5G 2C4, Canada.
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Faust K, Lee MK, Dent A, Fiala C, Portante A, Rabindranath M, Alsafwani N, Gao A, Djuric U, Diamandis P. Integrating morphologic and molecular histopathological features through whole slide image registration and deep learning. Neurooncol Adv 2022; 4:vdac001. [PMID: 35156037 PMCID: PMC8826810 DOI: 10.1093/noajnl/vdac001] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Modern molecular pathology workflows in neuro-oncology heavily rely on the integration of morphologic and immunohistochemical patterns for analysis, classification, and prognostication. However, despite the recent emergence of digital pathology platforms and artificial intelligence-driven computational image analysis tools, automating the integration of histomorphologic information found across these multiple studies is challenged by large files sizes of whole slide images (WSIs) and shifts/rotations in tissue sections introduced during slide preparation.
Methods
To address this, we develop a workflow that couples different computer vision tools including scale-invariant feature transform (SIFT) and deep learning to efficiently align and integrate histopathological information found across multiple independent studies. We highlight the utility and automation potential of this workflow in the molecular subclassification and discovery of previously unappreciated spatial patterns in diffuse gliomas.
Results
First, we show how a SIFT-driven computer vision workflow was effective at automated WSI alignment in a cohort of 107 randomly selected surgical neuropathology cases (97/107 (91%) showing appropriate matches, AUC = 0.96). This alignment allows our AI-driven diagnostic workflow to not only differentiate different brain tumor types, but also integrate and carry out molecular subclassification of diffuse gliomas using relevant immunohistochemical biomarkers (IDH1-R132H, ATRX). To highlight the discovery potential of this workflow, we also examined spatial distributions of tumors showing heterogenous expression of the proliferation marker MIB1 and Olig2. This analysis helped uncovered an interesting and unappreciated association of Olig2 positive and proliferative areas in some gliomas (r = 0.62).
Conclusion
This efficient neuropathologist-inspired workflow provides a generalizable approach to help automate a variety of advanced immunohistochemically compatible diagnostic and discovery exercises in surgical neuropathology and neuro-oncology.
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Affiliation(s)
- Kevin Faust
- Department of Computer Science, University of Toronto, 40 St. George Street, Toronto, ON M5S 2E4, Canada
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
| | - Michael K Lee
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Anglin Dent
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Clare Fiala
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
| | - Alessia Portante
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Madhu Rabindranath
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Noor Alsafwani
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
- Department of Pathology, College of Medicine, Imam Abdulrahman Bin Faisal University, P.O. Box.2208, Dammam, 31441, Saudi Arabia
| | - Andrew Gao
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Phedias Diamandis
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON M5G 1L7, Canada
- Department of Medical Biophysics, University of Toronto, 101 College St, Toronto, ON M5G 1L7, Canada
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Melliou S, Sangster KT, Djuric U, Diamandis P. The promise of organoids for unraveling the proteomic landscape of the developing human brain. Mol Psychiatry 2022; 27:73-80. [PMID: 34703024 DOI: 10.1038/s41380-021-01354-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 10/04/2021] [Accepted: 10/05/2021] [Indexed: 12/13/2022]
Abstract
Cerebral organoids offer an opportunity to bioengineer experimental avatars of the developing human brain and have already begun garnering relevant insights into complex neurobiological processes and disease. Thus far, investigations into their heterogeneous cellular composition and developmental trajectories have been largely limited to transcriptional readouts. Recent advances in global proteomic technologies have enabled a new range of techniques to explore dynamic and non-overlapping spatiotemporal protein-level programs operational in these humanoid neural structures. Here we discuss these early protein-based studies and their potentially essential role for unraveling critical secreted paracrine signals, processes with poor proteogenomic correlations, or neurodevelopmental proteins requiring post-translational modification for biological activity. Integrating emerging proteomic tools with these faithful human-derived neurodevelopmental models could transform our understanding of complex neural cell phenotypes and neurobiological processes, not exclusively driven by transcriptional regulation. These insights, less accessible by exclusive RNA-based approaches, could reveal new knowledge into human brain development and guide improvements in neural regenerative medicine efforts.
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Affiliation(s)
- Sofia Melliou
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Kevin T Sangster
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada. .,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada. .,Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada. .,Department of Medical Biophysics, University of Toronto, Toronto, ON, M5S 1A8, Canada.
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5
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Faust K, Roohi A, Leon AJ, Leroux E, Dent A, Evans AJ, Pugh TJ, Kalimuthu SN, Djuric U, Diamandis P. Unsupervised Resolution of Histomorphologic Heterogeneity in Renal Cell Carcinoma Using a Brain Tumor-Educated Neural Network. JCO Clin Cancer Inform 2021; 4:811-821. [PMID: 32946287 DOI: 10.1200/cci.20.00035] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
PURPOSE Applications of deep learning to histopathology have proven capable of expert-level performance, but approaches have largely focused on supervised classification tasks requiring context-specific training and deployment. More generalizable workflows that can be easily shared across subspecialties could help accelerate and broaden adoption. Here, we hypothesized that histology-optimized feature representations, generated by a convolutional neural network (CNN) during supervised learning, are transferable and can resolve meaningful differences in large-scale, discovery-type unsupervised analyses. METHODS We used a CNN, previously trained to recognize brain tumor histomorphologies, to extract 512 feature representations from > 550 digital whole-slide images (WSIs) of renal cell carcinomas (RCCs) from The Cancer Genome Atlas and other previously unencountered tumors. We use these extracted feature vectors to conduct unsupervised image-set clustering and analyze the clinical and biologic relevance of the intra- and interpatient subgroups generated. RESULTS Within individual WSIs, feature-based clustering could reliably segment tumor regions and other relevant histopathologic subpatterns (eg, adenosquamous and poorly differentiated regions). Across the larger RCC cohorts, clustering extracted features generated subgroups enriched for clinically relevant subtypes (eg, papillary RCC) and outcomes (eg, survival). Importantly, individual feature activation mapping highlighted salient subtype-specific patterns and features of malignancies (eg, nuclear grade, sarcomatous change) contributing to subgroupings. Moreover, some proposed clusters were enriched for recurring, human-based RCC-subtype misclassifications. CONCLUSION Our data support that CNNs, pretrained on large histologic datasets, can extend learned representations to novel scenarios and resolve clinically relevant intra- and interpatient tissue-pattern differences without explicit instruction or additional optimization. Repositioning of existing histology-educated networks could provide scalable approaches for image classification, quality assurance, and discovery of unappreciated patterns and subgroups of disease.
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Affiliation(s)
- Kevin Faust
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Department of Computer Science, University of Toronto, Toronto, Ontario Canada
| | - Adil Roohi
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Harvard Extension School, Cambridge, MA
| | - Alberto J Leon
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Emeline Leroux
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Toronto, Canada
| | - Anglin Dent
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Toronto, Canada
| | - Andrew J Evans
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Toronto, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Trevor J Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Ontario Institute for Cancer Research, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Sangeetha N Kalimuthu
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Toronto, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Phedias Diamandis
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Toronto, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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6
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Lam KB, Djuric U, Batruch I, Richer M, Diamandis P. Abstract 2694: An anatomic proteomic atlas of human glioblastoma. Cancer Res 2021. [DOI: 10.1158/1538-7445.am2021-2694] [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
Glioblastoma (GBM) is an aggressive brain tumor with an expected survival of under 15 months despite spirited multimodal therapy. This grim outlook has remained virtually unchanged over the last 40 years and thus necessitates alternative research and therapeutic development strategies. Historically, traditional models of cancer biology have largely considered GBM tissue to be a homogenous mass. Emerging studies however now suggests that the interaction of tumor cells with various normal components of the brain and immune system play an important role in helping cancer grow and develop resistance to therapies. Better understanding of these hallmark features of GBM, collectively known as the “tumor microenvironment” (TME), could lead to the development of new and more effective therapies. In light of this, there is a renewed interest in revisiting our theories of cancer and preserving the microscopic anatomy of GBM in our molecular profiling efforts. Here we leverage laser capture microdissection (LCM) and mass spectrometry-based proteomics, in order to generate a detailed map of the distribution of proteins within tissues across a large number of patients. Specifically, we will isolate, and profile well-understood microscopic components of GBM: cellular tumor (CT), microvascular proliferation (MVP), infiltrating tumor (IT), palisading cells around necrosis (PAN) and normal brain tissue (LE). All of this data will be provided in an online-based GBM atlas as a publicly available resource. This atlas and the associated database for clinical and genomic data will serve as a useful platform for developing therapeutics and testing novel hypotheses related to GBM biology.
Citation Format: K.H. Brian Lam, Ugljesa Djuric, Ihor Batruch, Maxime Richer, Phedias Diamandis. An anatomic proteomic atlas of human glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2694.
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Affiliation(s)
| | | | | | - Maxime Richer
- 3Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
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7
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Alsafwani N, Alrjoub M, Djuric U, Gao A, Diamandis P. Tumor-Infiltrating Lymphocytes Are Enriched in Nonhypoxic Glioblastoma Niches. J Neuropathol Exp Neurol 2021; 80:202-204. [PMID: 33212506 DOI: 10.1093/jnen/nlaa108] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Affiliation(s)
- Noor Alsafwani
- From the Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada.,Department of Pathology, Collage of Medicine, Imam Abdulrahman Bin Faisal University (IAU), Dammam, Saudi Arabia
| | - Mo'ath Alrjoub
- From the Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Andrew Gao
- From the Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Phedias Diamandis
- From the Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada.,Princess Margaret Cancer Centre, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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8
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Papaioannou MD, Djuric U, Kao J, Karimi S, Zadeh G, Aldape K, Diamandis P. Proteomic analysis of meningiomas reveals clinically distinct molecular patterns. Neuro Oncol 2021; 21:1028-1038. [PMID: 31077268 DOI: 10.1093/neuonc/noz084] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Meningiomas represent one of the most common brain tumors and exhibit a clinically heterogeneous behavior, sometimes difficult to predict with classic histopathologic features. While emerging molecular profiling efforts have linked specific genomic drivers to distinct clinical patterns, the proteomic landscape of meningiomas remains largely unexplored. METHODS We utilize liquid chromatography tandem mass spectrometry with an Orbitrap mass analyzer to quantify global protein abundances of a clinically well-annotated formalin-fixed paraffin embedded (FFPE) cohort (n = 61) of meningiomas spanning all World Health Organization (WHO) grades and various degrees of clinical aggressiveness. RESULTS In total, we quantify 3042 unique proteins comparing patterns across different clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic (n = 106 proteins, Welch's t-test, P < 0.01) and pathway-level (eg, Notch and PI3K/AKT/mTOR) differences between convexity and skull base meningiomas. Supervised comparative analyses of different pathological grades revealed distinct patterns between benign (grade I) and atypical/malignant (grades II‒III) meningiomas with specific oncogenes enriched in higher grade lesions. Independent of WHO grade, clinically aggressive meningiomas that rapidly recurred (<3 y) had distinctive protein patterns converging on mRNA processing and impaired activation of the matrisome complex. Larger sized meningiomas (>3 cm maximum tumor diameter) and those with previous radiation exposure revealed perturbed pro-proliferative (eg, epidermal growth factor receptor) and metabolic as well as inflammatory response pathways (mitochondrial activity, interferon), respectively. CONCLUSIONS Our proteomic study demonstrates that meningiomas of different grades and clinical parameters present distinct proteomic profiles. These proteomic variations offer potential future utility in helping better predict patient outcome and in nominating novel therapeutic targets for personalized care.
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Affiliation(s)
- Michail-Dimitrios Papaioannou
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Jennifer Kao
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Shirin Karimi
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada
| | - Gelareh Zadeh
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada
| | - Kenneth Aldape
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
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9
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Rodrigues DC, Mufteev M, Weatheritt RJ, Djuric U, Ha KCH, Ross PJ, Wei W, Piekna A, Sartori MA, Byres L, Mok RSF, Zaslavsky K, Pasceri P, Diamandis P, Morris Q, Blencowe BJ, Ellis J. Shifts in Ribosome Engagement Impact Key Gene Sets in Neurodevelopment and Ubiquitination in Rett Syndrome. Cell Rep 2021; 30:4179-4196.e11. [PMID: 32209477 DOI: 10.1016/j.celrep.2020.02.107] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 12/30/2019] [Accepted: 02/27/2020] [Indexed: 12/21/2022] Open
Abstract
Regulation of translation during human development is poorly understood, and its dysregulation is associated with Rett syndrome (RTT). To discover shifts in mRNA ribosomal engagement (RE) during human neurodevelopment, we use parallel translating ribosome affinity purification sequencing (TRAP-seq) and RNA sequencing (RNA-seq) on control and RTT human induced pluripotent stem cells, neural progenitor cells, and cortical neurons. We find that 30% of transcribed genes are translationally regulated, including key gene sets (neurodevelopment, transcription and translation factors, and glycolysis). Approximately 35% of abundant intergenic long noncoding RNAs (lncRNAs) are ribosome engaged. Neurons translate mRNAs more efficiently and have longer 3' UTRs, and RE correlates with elements for RNA-binding proteins. RTT neurons have reduced global translation and compromised mTOR signaling, and >2,100 genes are translationally dysregulated. NEDD4L E3-ubiquitin ligase is translationally impaired, ubiquitinated protein levels are reduced, and protein targets accumulate in RTT neurons. Overall, the dynamic translatome in neurodevelopment is disturbed in RTT and provides insight into altered ubiquitination that may have therapeutic implications.
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Affiliation(s)
- Deivid C Rodrigues
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Marat Mufteev
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Robert J Weatheritt
- Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Ugljesa Djuric
- Laboratory Medicine and Pathology Program, University Health Network, Toronto, ON M5G 2C4, Canada
| | - Kevin C H Ha
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Vector Institute, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - P Joel Ross
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Wei Wei
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Alina Piekna
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Maria A Sartori
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Loryn Byres
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Rebecca S F Mok
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Kirill Zaslavsky
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Peter Pasceri
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Phedias Diamandis
- Laboratory Medicine and Pathology Program, University Health Network, Toronto, ON M5G 2C4, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada; Department of Pathology, University Health Network, Toronto, ON M5G 2C4, Canada
| | - Quaid Morris
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Vector Institute, 661 University Avenue, Toronto, ON M5G 1M1, Canada
| | - Benjamin J Blencowe
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - James Ellis
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada.
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10
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Samuel N, So E, Djuric U, Diamandis P. Consumer-grade electroencephalography devices as potential tools for early detection of brain tumors. BMC Med 2021; 19:16. [PMID: 33478449 PMCID: PMC7821483 DOI: 10.1186/s12916-020-01889-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 12/14/2020] [Indexed: 12/27/2022] Open
Affiliation(s)
- Nardin Samuel
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Emily So
- Princess Margaret Cancer Centre, University Health Network, 12-308, 101 College Street, Toronto, ON, M5G 1L7, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, University Health Network, 12-308, 101 College Street, Toronto, ON, M5G 1L7, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, University Health Network, 12-308, 101 College Street, Toronto, ON, M5G 1L7, Canada. .,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada. .,Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada. .,Department of Medical Biophysics, University of Toronto, Toronto, Canada.
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11
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Papaioannou MD, Sangster K, Sajid RS, Djuric U, Diamandis P. Cerebral organoids: emerging ex vivo humanoid models of glioblastoma. Acta Neuropathol Commun 2020; 8:209. [PMID: 33261657 PMCID: PMC7706050 DOI: 10.1186/s40478-020-01077-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 11/11/2020] [Indexed: 02/07/2023] Open
Abstract
Glioblastoma is an aggressive form of brain cancer that has seen only marginal improvements in its bleak survival outlook of 12-15 months over the last forty years. There is therefore an urgent need for the development of advanced drug screening platforms and systems that can better recapitulate glioblastoma's infiltrative biology, a process largely responsible for its relentless propensity for recurrence and progression. Recent advances in stem cell biology have allowed the generation of artificial tridimensional brain-like tissue termed cerebral organoids. In addition to their potential to model brain development, these reagents are providing much needed synthetic humanoid scaffolds to model glioblastoma's infiltrative capacity in a faithful and scalable manner. Here, we highlight and review the early breakthroughs in this growing field and discuss its potential future role for glioblastoma research.
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Affiliation(s)
- Michail-Dimitrios Papaioannou
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada
| | - Kevin Sangster
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Rifat Shahriar Sajid
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada.
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada.
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.
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12
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Malcolm J, Fiala C, Djuric U, Diamandis P. Can gliomas provide insights into promoting synaptogenesis? Mol Psychiatry 2020; 25:1920-1925. [PMID: 32457425 DOI: 10.1038/s41380-020-0795-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 05/11/2020] [Accepted: 05/18/2020] [Indexed: 11/10/2022]
Affiliation(s)
- Jessica Malcolm
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
| | - Clare Fiala
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, 101 College Street, Toronto, ON, M5G 1L7, Canada. .,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada. .,Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, Toronto, ON, M5G 2C4, Canada. .,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
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13
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Affiliation(s)
- K H Brian Lam
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Kristina Valkanas
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Ugljesa Djuric
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Phedias Diamandis
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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14
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15
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Djuric U, Lam KHB, Kao J, Batruch I, Jevtic S, Papaioannou MD, Diamandis P. Defining Protein Pattern Differences Among Molecular Subtypes of Diffuse Gliomas Using Mass Spectrometry. Mol Cell Proteomics 2019; 18:2029-2043. [PMID: 31353322 PMCID: PMC6773564 DOI: 10.1074/mcp.ra119.001521] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 07/09/2019] [Indexed: 12/18/2022] Open
Abstract
Molecular characterization of diffuse gliomas has thus far largely focused on genomic and transcriptomic interrogations. Here, we utilized mass spectrometry and overlay protein-level information onto genomically defined cohorts of diffuse gliomas to improve our downstream molecular understanding of these lethal malignancies. Bulk and macrodissected tissues were utilized to quantitate 5,496 unique proteins over three glioma cohorts subclassified largely based on their IDH and 1p19q codeletion status (IDH wild type (IDHwt), n = 7; IDH mutated (IDHmt), 1p19q non-codeleted, n = 7; IDH mutated, 1p19q-codeleted, n = 10). Clustering analysis highlighted proteome and systems-level pathway differences in gliomas according to IDH and 1p19q-codeletion status, including 287 differentially abundant proteins in macrodissection-enriched tumor specimens. IDHwt tumors were enriched for proteins involved in invasiveness and epithelial to mesenchymal transition (EMT), while IDHmt gliomas had increased abundances of proteins involved in mRNA splicing. Finally, these abundance changes were compared with IDH-matched GBM stem-like cells (GSCs) to better pinpoint protein patterns enriched in putative cellular drivers of gliomas. Using this integrative approach, we outline specific proteins involved in chloride transport (e.g. chloride intracellular channel 1, CLIC1) and EMT (e.g. procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3, PLOD3, and serpin peptidase inhibitor clade H member 1, SERPINH1) that showed concordant IDH-status-dependent abundance differences in both primary tissue and purified GSC cultures. Given the downstream position proteins occupy in driving biology and phenotype, understanding the proteomic patterns operational in distinct glioma subtypes could help propose more specific, personalized, and effective targets for the management of patients with these aggressive malignancies.
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Affiliation(s)
- Ugljesa Djuric
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, College Street 101, Toronto, Ontario, M5G 1L7, Canada; Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, Toronto, Ontario, M5G 2C4, Canada
| | - K H Brian Lam
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, College Street 101, Toronto, Ontario, M5G 1L7, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
| | - Jennifer Kao
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, College Street 101, Toronto, Ontario, M5G 1L7, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
| | - Ihor Batruch
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, M5G 1X5, Canada
| | - Stefan Jevtic
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, College Street 101, Toronto, Ontario, M5G 1L7, Canada
| | - Michail-Dimitrios Papaioannou
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, College Street 101, Toronto, Ontario, M5G 1L7, Canada; Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, Toronto, Ontario, M5G 2C4, Canada
| | - Phedias Diamandis
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, College Street 101, Toronto, Ontario, M5G 1L7, Canada; Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, Toronto, Ontario, M5G 2C4, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, M5G 1L7, Canada.
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16
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Xie Q, Faust K, Van Ommeren R, Sheikh A, Djuric U, Diamandis P. Deep learning for image analysis: Personalizing medicine closer to the point of care. Crit Rev Clin Lab Sci 2019; 56:61-73. [PMID: 30628494 DOI: 10.1080/10408363.2018.1536111] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The precision-based revolution in medicine continues to demand stratification of patients into smaller and more personalized subgroups. While genomic technologies have largely led this movement, diagnostic results can take days to weeks to generate. Management at, or closer to, the point of care still heavily relies on the subjective qualitative interpretation of clinical and diagnostic imaging findings. New and emerging technological advances in artificial intelligence (AI) now appear poised to help bring objectivity and precision to these traditionally qualitative analytic tools. In particular, one specific form of AI, known as deep learning, is achieving expert-level disease classifications in many areas of diagnostic medicine dependent on visual and image-based findings. Here, we briefly review concepts of deep learning, and more specifically recent developments in convolutional neural networks (CNNs), to highlight their transformative potential in personalized medicine and, in particular, diagnostic histopathology. Understanding the opportunities and challenges of these quantitative machine-based decision support tools is critical to their widespread introduction into routine diagnostics.
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Affiliation(s)
- Quin Xie
- a Department of Laboratory Medicine and Pathobiology , University of Toronto , Toronto , Canada.,b MacFeeters-Hamilton Brain Tumour Centre , Princess Margaret Cancer Centre , Toronto , Canada
| | - Kevin Faust
- b MacFeeters-Hamilton Brain Tumour Centre , Princess Margaret Cancer Centre , Toronto , Canada.,c Department of Computer Science , University of Toronto , Toronto , Canada
| | - Randy Van Ommeren
- a Department of Laboratory Medicine and Pathobiology , University of Toronto , Toronto , Canada.,b MacFeeters-Hamilton Brain Tumour Centre , Princess Margaret Cancer Centre , Toronto , Canada
| | - Adeel Sheikh
- b MacFeeters-Hamilton Brain Tumour Centre , Princess Margaret Cancer Centre , Toronto , Canada
| | - Ugljesa Djuric
- b MacFeeters-Hamilton Brain Tumour Centre , Princess Margaret Cancer Centre , Toronto , Canada
| | - Phedias Diamandis
- a Department of Laboratory Medicine and Pathobiology , University of Toronto , Toronto , Canada.,b MacFeeters-Hamilton Brain Tumour Centre , Princess Margaret Cancer Centre , Toronto , Canada.,d Laboratory Medicine Program , University Health Network , Toronto , Canada
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Faust K, Xie Q, Han D, Goyle K, Volynskaya Z, Djuric U, Diamandis P. Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction. BMC Bioinformatics 2018; 19:173. [PMID: 29769044 PMCID: PMC5956828 DOI: 10.1186/s12859-018-2184-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [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: 12/19/2017] [Accepted: 05/02/2018] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce. RESULTS Here, we leverage t-distributed Stochastic Neighbor Embedding (t-SNE) to reduce dimensionality and depict how CNNs organize histomorphologic information. Unique to our workflow, we develop a quantitative and transparent approach to visualizing classification decisions prior to softmax compression. By discretizing the relationships between classes on the t-SNE plot, we show we can super-impose randomly sampled regions of test images and use their distribution to render statistically-driven classifications. Therefore, in addition to providing intuitive outputs for human review, this visual approach can carry out automated and objective multi-class classifications similar to more traditional and less-transparent categorical probability distribution scores. Importantly, this novel classification approach is driven by a priori statistically defined cutoffs. It therefore serves as a generalizable classification and anomaly detection tool less reliant on post-hoc tuning. CONCLUSION Routine incorporation of this convenient approach for quantitative visualization and error reduction in histopathology aims to accelerate early adoption of CNNs into generalized real-world applications where unanticipated and previously untrained classes are often encountered.
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Affiliation(s)
- Kevin Faust
- Department of Computer Science, University of Toronto, 40 St. George Street, Toronto, ON M5S 2E4 Canada
| | - Quin Xie
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8 Canada
| | - Dominick Han
- Department of Computer Science, University of Toronto, 40 St. George Street, Toronto, ON M5S 2E4 Canada
| | - Kartikay Goyle
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto, Toronto, ON Canada
| | - Zoya Volynskaya
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8 Canada
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4 Canada
| | - Ugljesa Djuric
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4 Canada
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, 101 College Street, Toronto, ON M5G 1L7 Canada
| | - Phedias Diamandis
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8 Canada
- Laboratory Medicine Program, Department of Pathology, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4 Canada
- Princess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, 101 College Street, Toronto, ON M5G 1L7 Canada
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18
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Xie Q, Han D, Faust K, Aldape K, Zadeh G, Volynskaya Z, Djuric U, Diamandis P. PATH-46. AUTOMATED HISTOPATHOLOGIC CLASSIFICATION OF BRAIN TUMORS USING ARTIFICIAL INTELLIGENCE. Neuro Oncol 2017. [DOI: 10.1093/neuonc/nox168.736] [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] [Indexed: 11/14/2022] Open
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19
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Djuric U, Rodrigues DC, Batruch I, Ellis J, Shannon P, Diamandis P. Spatiotemporal Proteomic Profiling of Human Cerebral Development. Mol Cell Proteomics 2017; 16:1548-1562. [PMID: 28687556 DOI: 10.1074/mcp.m116.066274] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Revised: 05/30/2017] [Indexed: 12/21/2022] Open
Abstract
Mass spectrometry (MS) analysis of human post-mortem central nervous system (CNS) tissue and induced pluripotent stem cell (iPSC)-based directed differentiations offer complementary avenues to define protein signatures of neurodevelopment. Methodological improvements of formalin-fixed, paraffin-embedded (FFPE) protein isolation now enable widespread proteomic analysis of well-annotated archival tissue samples in the context of development and disease. Here, we utilize a shotgun label-free quantification (LFQ) MS method to profile magnetically enriched human cortical neurons and neural progenitor cells (NPCs) derived from iPSCs. We use these signatures to help define spatiotemporal protein dynamics of developing human FFPE cerebral regions. We show that the use of high resolution Q Exactive mass spectrometers now allow simultaneous quantification of >2700 proteins in a single LFQ experiment and provide sufficient coverage to define novel biomarkers and signatures of NPC maintenance and differentiation. Importantly, we show that this abbreviated strategy allows efficient recovery of novel cytoplasmic, membrane-specific and synaptic proteins that are shared between both in vivo and in vitro neuronal differentiation. This study highlights the discovery potential of non-comprehensive high-throughput proteomic profiling of unfractionated clinically well-annotated FFPE human tissue from a diverse array of development and diseased states.
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Affiliation(s)
- Ugljesa Djuric
- From the ‡Laboratory Medicine and Pathology Program, University Health Network, Toronto, Ontario, M5G 2C4, Canada
| | - Deivid C Rodrigues
- §Department of Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, Ontario, M5G 1L7, Canada
| | - Ihor Batruch
- ¶Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, M5G 1X5, Canada
| | - James Ellis
- §Department of Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, Ontario, M5G 1L7, Canada.,‖Department of Molecular Genetics, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
| | - Patrick Shannon
- ¶Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, M5G 1X5, Canada.,**Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A1, Canada; and
| | - Phedias Diamandis
- From the ‡Laboratory Medicine and Pathology Program, University Health Network, Toronto, Ontario, M5G 2C4, Canada; .,**Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A1, Canada; and
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20
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Novo CL, Tang C, Ahmed K, Djuric U, Fussner E, Mullin NP, Morgan NP, Hayre J, Sienerth AR, Elderkin S, Nishinakamura R, Chambers I, Ellis J, Bazett-Jones DP, Rugg-Gunn PJ. The pluripotency factor Nanog regulates pericentromeric heterochromatin organization in mouse embryonic stem cells. Genes Dev 2016; 30:1101-15. [PMID: 27125671 PMCID: PMC4863740 DOI: 10.1101/gad.275685.115] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [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: 11/29/2015] [Accepted: 03/23/2016] [Indexed: 12/31/2022]
Abstract
Here, Novo et al. identify a new critical role for the transcription factor Nanog in maintaining an open heterochromatin state in pluripotent mouse embryonic stem cells and demonstrate that forced expression of Nanog is sufficient to remodel and decondense chromatin in more developmentally advanced mammalian cell types. This study delineates a direct connection between the pluripotency network and chromatin organization and shows that maintainence of an open heterochromatin architecture is highly regulated in embryonic stem cells. An open and decondensed chromatin organization is a defining property of pluripotency. Several epigenetic regulators have been implicated in maintaining an open chromatin organization, but how these processes are connected to the pluripotency network is unknown. Here, we identified a new role for the transcription factor NANOG as a key regulator connecting the pluripotency network with constitutive heterochromatin organization in mouse embryonic stem cells. Deletion of Nanog leads to chromatin compaction and the remodeling of heterochromatin domains. Forced expression of NANOG in epiblast stem cells is sufficient to decompact chromatin. NANOG associates with satellite repeats within heterochromatin domains, contributing to an architecture characterized by highly dispersed chromatin fibers, low levels of H3K9me3, and high major satellite transcription, and the strong transactivation domain of NANOG is required for this organization. The heterochromatin-associated protein SALL1 is a direct cofactor for NANOG, and loss of Sall1 recapitulates the Nanog-null phenotype, but the loss of Sall1 can be circumvented through direct recruitment of the NANOG transactivation domain to major satellites. These results establish a direct connection between the pluripotency network and chromatin organization and emphasize that maintaining an open heterochromatin architecture is a highly regulated process in embryonic stem cells.
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Affiliation(s)
- Clara Lopes Novo
- Epigenetics Programme, The Babraham Institute, Cambridge CB22 3AT, United Kingdom
| | - Calvin Tang
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, Ontario MSG 1L7, Canada; Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Kashif Ahmed
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, Ontario MSG 1L7, Canada
| | - Ugljesa Djuric
- Program in Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, Ontario M5G 1L7, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Eden Fussner
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, Ontario MSG 1L7, Canada; Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Nicholas P Mullin
- MRC Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, Edinburgh EH16 4UU, United Kingdom
| | - Natasha P Morgan
- Epigenetics Programme, The Babraham Institute, Cambridge CB22 3AT, United Kingdom
| | - Jasvinder Hayre
- Epigenetics Programme, The Babraham Institute, Cambridge CB22 3AT, United Kingdom
| | - Arnold R Sienerth
- Epigenetics Programme, The Babraham Institute, Cambridge CB22 3AT, United Kingdom
| | - Sarah Elderkin
- Nuclear Dynamics Programme, The Babraham Institute, Cambridge, CB22 3AT, United Kingdom
| | - Ryuichi Nishinakamura
- Department of Kidney Development, Institute of Molecular Embryology and Genetics, Kumamoto University, Kumamoto 860-0811, Japan
| | - Ian Chambers
- MRC Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, Edinburgh EH16 4UU, United Kingdom
| | - James Ellis
- Program in Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, Ontario M5G 1L7, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - David P Bazett-Jones
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, Ontario MSG 1L7, Canada; Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Peter J Rugg-Gunn
- Epigenetics Programme, The Babraham Institute, Cambridge CB22 3AT, United Kingdom; Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 3EG, United Kingdom; Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge CB2 1QR, United Kingdom
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21
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Djuric U, Cheung AYL, Zhang W, Mok RS, Lai W, Piekna A, Hendry JA, Ross PJ, Pasceri P, Kim DS, Salter MW, Ellis J. MECP2e1 isoform mutation affects the form and function of neurons derived from Rett syndrome patient iPS cells. Neurobiol Dis 2015; 76:37-45. [PMID: 25644311 PMCID: PMC4380613 DOI: 10.1016/j.nbd.2015.01.001] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [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: 10/02/2014] [Revised: 12/19/2014] [Accepted: 01/11/2015] [Indexed: 01/01/2023] Open
Abstract
MECP2 mutations cause the X-linked neurodevelopmental disorder Rett Syndrome (RTT) by consistently altering the protein encoded by the MECP2e1 alternative transcript. While mutations that simultaneously affect both MECP2e1 and MECP2e2 isoforms have been widely studied, the consequence of MECP2e1 deficiency on human neurons remains unknown. Here we report the first isoform-specific patient induced pluripotent stem cell (iPSC) model of RTT. RTTe1 patient iPS cell-derived neurons retain an inactive X-chromosome and express only the mutant allele. Single-cell mRNA analysis demonstrated they have a molecular signature of cortical neurons. Mutant neurons exhibited a decrease in soma size, reduced dendritic complexity and decreased cell capacitance, consistent with impaired neuronal maturation. The soma size phenotype was rescued cell-autonomously by MECP2e1 transduction in a level-dependent manner but not by MECP2e2 gene transfer. Importantly, MECP2e1 mutant neurons showed a dysfunction in action potential generation, voltage-gated Na(+) currents, and miniature excitatory synaptic current frequency and amplitude. We conclude that MECP2e1 mutation affects soma size, information encoding properties and synaptic connectivity in human neurons that are defective in RTT.
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Affiliation(s)
- Ugljesa Djuric
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Aaron Y L Cheung
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Wenbo Zhang
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada; University of Toronto Centre for the Study of Pain, University of Toronto, Toronto, ON M5T 1P8, Canada
| | - Rebecca S Mok
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Wesley Lai
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Alina Piekna
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jason A Hendry
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - P Joel Ross
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Peter Pasceri
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Dae-Sung Kim
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Michael W Salter
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada; University of Toronto Centre for the Study of Pain, University of Toronto, Toronto, ON M5T 1P8, Canada
| | - James Ellis
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada.
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22
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Messaed C, Akoury E, Djuric U, Zeng J, Saleh M, Gilbert L, Seoud M, Qureshi S, Slim R. NLRP7, a nucleotide oligomerization domain-like receptor protein, is required for normal cytokine secretion and co-localizes with Golgi and the microtubule-organizing center. J Biol Chem 2011; 286:43313-23. [PMID: 22025618 DOI: 10.1074/jbc.m111.306191] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
A hydatidiform mole (HM) is a human pregnancy with hyperproliferative placenta and abnormal embryonic development. Mutations in NLRP7, a member of the nucleotide oligomerization domain-like receptor family of proteins with roles in inflammation and apoptosis, are responsible for recurrent HMs. However, little is known about the functional role of NLRP7. Here, we demonstrate that peripheral blood mononuclear cells from patients with NLRP7 mutations and rare variants secrete low levels of IL-1β and TNF in response to LPS. We show that the cells from patients, carrying mutations or rare variants, have variable levels of increased intracellular pro-IL-1β indicating that normal NLRP7 down-regulates pro-IL-1β synthesis in response to LPS. Using transient transfections, we confirm the role of normal NLRP7 in inhibiting pro-IL-1β and demonstrate that this inhibitory function is abolished by protein-truncating mutations after the Pyrin domain. Within peripheral blood mononuclear cells, NLRP7 co-localizes with the Golgi and the microtubule-organizing center and is associated with microtubules. This suggests that NLRP7 mutations may affect cytokine secretion by interfering, directly or indirectly, with their trafficking. We propose that the impaired cytokine trafficking and secretion caused by NLRP7 defects makes the patients tolerant to the growth of these earlier arrested conceptions with no fetal vessels and that the retention of these conceptions until the end of the first trimester contribute to the molar phenotype. Our data will impact our understanding of postmolar choriocarcinomas, the only allograft non-self tumors that are able to invade maternal tissues.
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Affiliation(s)
- Christiane Messaed
- Department of Human Genetics, McGill University Health Center, Montreal H3G 1A4, Canada
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23
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Djuric U, El-Maarri O, Lamb B, Kuick R, Seoud M, Coullin P, Oldenburg J, Hanash S, Slim R. Familial molar tissues due to mutations in the inflammatory gene, NALP7, have normal postzygotic DNA methylation. Hum Genet 2006; 120:390-5. [PMID: 16874523 DOI: 10.1007/s00439-006-0192-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [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: 03/10/2006] [Accepted: 04/19/2006] [Indexed: 01/19/2023]
Abstract
An imprinting disorder has been believed to underlie the etiology of familial biparental hydatidiform moles (HMs) based on the abnormal methylation or expression of imprinted genes in molar tissues. However, the extent of the epigenetic defect in these tissues and the developmental stage at which the disorder begins have been poorly defined. In this study, we assessed the extent of abnormal DNA methylation in two HMs caused by mutations in the recently identified 19q13.4 gene, NALP7. We demonstrate normal postzygotic DNA methylation patterns at major repetitive and long interspersed nuclear elements (LINEs), genes on the inactive X-chromosome, three-cancer related genes, and CpG rich regions surrounding the PEG3 differentially methylated region (DMR). Our data provide a comprehensive assessment of DNA methylation in familial molar tissues and indicate that abnormal DNA methylation in these tissues is restricted to imprinted DMRs. The known role of NALP7 in apoptosis and inflammation pinpoints previously unrecognized pathways that could directly or indirectly underlie the abnormal methylation of imprinted genes in molar tissues.
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Affiliation(s)
- Ugljesa Djuric
- Departments of Human Genetics and Obstetrics and Gynecology, McGill University Health Center, Montreal, Canada, H3G 1A4
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Murdoch S, Djuric U, Mazhar B, Seoud M, Khan R, Kuick R, Bagga R, Kircheisen R, Ao A, Ratti B, Hanash S, Rouleau GA, Slim R. Mutations in NALP7 cause recurrent hydatidiform moles and reproductive wastage in humans. Nat Genet 2006; 38:300-2. [PMID: 16462743 DOI: 10.1038/ng1740] [Citation(s) in RCA: 342] [Impact Index Per Article: 19.0] [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: 10/03/2005] [Accepted: 11/29/2005] [Indexed: 01/06/2023]
Abstract
Hydatidiform mole (HM) is an abnormal human pregnancy with no embryo and cystic degeneration of placental villi. We report five mutations in the maternal gene NALP7 in individuals with familial and recurrent HMs. NALP7 is a member of the CATERPILLER protein family involved in inflammation and apoptosis. NALP7 is the first maternal effect gene identified in humans and is also responsible for recurrent spontaneous abortions, stillbirths and intrauterine growth retardation.
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Affiliation(s)
- Sharlene Murdoch
- Department of Human Genetics, McGill University Health Center, Montreal H3G 1A4, Canada
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