Author
Remco Hoogenboezem
Other affiliations: Erasmus University Medical Center
Bio: Remco Hoogenboezem is an academic researcher from Erasmus University Rotterdam. The author has contributed to research in topics: Haematopoiesis & Myeloid. The author has an hindex of 19, co-authored 47 publications receiving 1722 citations. Previous affiliations of Remco Hoogenboezem include Erasmus University Medical Center.
Topics: Haematopoiesis, Myeloid, Progenitor cell, Leukemia, Bone marrow
Papers
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TL;DR: The data show that structural rearrangements involving the chromosomal repositioning of a single enhancer can cause deregulation of two unrelated distal genes, with cancer as the outcome.
545 citations
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RWTH Aachen University1, Bayer HealthCare Pharmaceuticals2, Martin Luther University of Halle-Wittenberg3, Heidelberg University4, Radboud University Nijmegen5, Boston Children's Hospital6, University of Edinburgh7, University of Hamburg8, Monash University9, Erasmus University Rotterdam10, Molecular Medicine Partnership Unit11
TL;DR: Using single-cell RNA sequencing, the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys are profiled to map the entire human kidney and identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibro Blasts during human kidney fibrosis.
Abstract: Kidney fibrosis is the hallmark of chronic kidney disease progression; however, at present no antifibrotic therapies exist1-3. The origin, functional heterogeneity and regulation of scar-forming cells that occur during human kidney fibrosis remain poorly understood1,2,4. Here, using single-cell RNA sequencing, we profiled the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys to map the entire human kidney. This analysis enabled us to map all matrix-producing cells at high resolution, and to identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibroblasts during human kidney fibrosis. We used genetic fate-tracing, time-course single-cell RNA sequencing and ATAC-seq (assay for transposase-accessible chromatin using sequencing) experiments in mice, and spatial transcriptomics in human kidney fibrosis, to shed light on the cellular origins and differentiation of human kidney myofibroblasts and their precursors at high resolution. Finally, we used this strategy to detect potential therapeutic targets, and identified NKD2 as a myofibroblast-specific target in human kidney fibrosis.
301 citations
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TL;DR: P perturbation of mesenchymal cells in a mouse model of the pre-leukemic disorder Shwachman-Diamond syndrome induces mitochondrial dysfunction, oxidative stress, and activation of DNA damage responses in hematopoietic stem and progenitor cells.
262 citations
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TL;DR: It is shown that LMS tumors are characterized by substantial mutational heterogeneity, near-universal inactivation of TP53 and RB1, widespread DNA copy number alterations including chromothripsis, and frequent whole-genome duplication, and recurrent alterations in telomere maintenance genes.
Abstract: Leiomyosarcoma (LMS) is an aggressive mesenchymal malignancy with few therapeutic options. The mechanisms underlying LMS development, including clinically actionable genetic vulnerabilities, are largely unknown. Here we show, using whole-exome and transcriptome sequencing, that LMS tumors are characterized by substantial mutational heterogeneity, near-universal inactivation of TP53 and RB1, widespread DNA copy number alterations including chromothripsis, and frequent whole-genome duplication. Furthermore, we detect alternative telomere lengthening in 78% of cases and identify recurrent alterations in telomere maintenance genes such as ATRX, RBL2, and SP100, providing insight into the genetic basis of this mechanism. Finally, most tumors display hallmarks of "BRCAness", including alterations in homologous recombination DNA repair genes, multiple structural rearrangements, and enrichment of specific mutational signatures, and cultured LMS cells are sensitive towards olaparib and cisplatin. This comprehensive study of LMS genomics has uncovered key biological features that may inform future experimental research and enable the design of novel therapies.
195 citations
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TL;DR: It is shown that Gli1+ mesenchymal stromal cells are recruited from the endosteal and perivascular niche to become fibrosis-driving myofibroblasts in the bone marrow, and Gli1 expression in BMF significantly correlates with the severity of the disease.
190 citations
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TL;DR: The 2016 edition of the World Health Organization classification of tumors of the hematopoietic and lymphoid tissues represents a revision of the prior classification rather than an entirely new classification and attempts to incorporate new clinical, prognostic, morphologic, immunophenotypic, and genetic data that have emerged since the last edition.
7,147 citations
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University of Ulm1, Fred Hutchinson Cancer Research Center2, King's College London3, University of Rome Tor Vergata4, University of Münster5, Brigham and Women's Hospital6, University of Chicago7, Memorial Sloan Kettering Cancer Center8, Leipzig University9, VU University Amsterdam10, University of Valencia11, National Taiwan University12, Monash University13, Alfred Hospital14, Erasmus University Medical Center15, Ohio State University16
TL;DR: An international panel to provide updated evidence- and expert opinion-based recommendations for diagnosis and management of acute myeloid leukemia in adults includes a revised version of the ELN genetic categories, a proposal for a response category based on MRD status, and criteria for progressive disease.
4,066 citations
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TL;DR: The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification.
Abstract: BackgroundRecent studies have provided a detailed census of genes that are mutated in acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity defines the pathophysiology of AML and informs clinical practice. MethodsWe enrolled a total of 1540 patients in three prospective trials of intensive therapy. Combining driver mutations in 111 cancer genes with cytogenetic and clinical data, we defined AML genomic subgroups and their relevance to clinical outcomes. ResultsWe identified 5234 driver mutations across 76 genes or genomic regions, with 2 or more drivers identified in 86% of the patients. Patterns of co-mutation compartmentalized the cohort into 11 classes, each with distinct diagnostic features and clinical outcomes. In addition to currently defined AML subgroups, three heterogeneous genomic categories emerged: AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients); AML with TP53 mutations, chromosomal aneuploidies, or b...
2,834 citations
01 Jan 2011
TL;DR: The sheer volume and scope of data posed by this flood of data pose a significant challenge to the development of efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.
2,187 citations
01 Mar 2001
TL;DR: Using singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype.
Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.
1,815 citations