clonal-analysis-neonatal-mouse-heart-using-nearest-neighbor

Clonal Analysis of the Neonatal Mouse Heart using Nearest Neighbor Modeling

By replacing lost or dysfunctional myocardium, tissue regeneration is a promising approach to treat heart failure. However, the challenge of detecting ...

Duke University

Burkitt lymphoma (BL) is an aggressive, MYC-driven lymphoma comprising 3 distinct clinical subtypes: sporadic BLs that occur worldwide, endemic BLs that occur predominantly in sub-Saharan Africa, and immunodeficiency-associated BLs that occur primarily in the setting of HIV. In this study, we comprehensively delineated the genomic basis of BL through whole-genome sequencing (WGS) of 101 tumors representing all 3 subtypes of BL to identify 72 driver genes. These data were additionally informed by CRISPR screens in BL cell lines to functionally annotate the role of oncogenic drivers. Nearly every driver gene was found to have both coding and non-coding mutations, highlighting the importance of WGS for identifying driver events. Our data implicate coding and non-coding mutations in IGLL5, BACH2, SIN3A, and DNMT1. Epstein-Barr virus (EBV) infection was associated with higher mutation load, with type 1 EBV showing a higher mutational burden than type 2 EBV. Although sporadic and immunodeficiency-associated BLs had similar genetic profiles, endemic BLs manifested more frequent mutations in BCL7A and BCL6 and fewer genetic alterations in DNMT1, SNTB2, and CTCF. Silencing mutations in ID3 were a common feature of all 3 subtypes of BL. In vitro, mass spectrometry-based proteomics demonstrated that the ID3 protein binds primarily to TCF3 and TCF4. In vivo knockout of ID3 potentiated the effects of MYC, leading to rapid tumorigenesis and tumor phenotypes consistent with those observed in the human disease.

The whole-genome landscape of Burkitt lymphoma subtypes.

Non-Hodgkin lymphomas (NHLs) are a diverse group of entities, both clinically and molecularly. Here, we review the evolution of classification schemes in B-cell lymphoma, noting the now standard WHO classification system that is based on immune cell-of-origin and molecular phenotypes. We review how lymphomas arise throughout the B-cell development process as well as the molecular and clinical features of prominent B-cell lymphomas. We provide an overview of the major progress that has occurred over the past decade in terms of our molecular understanding of these diseases. We discuss treatment options available and focus on a number of the diverse research tools that have been employed to improve our understanding of these diseases. We discuss the problem of heterogeneity in lymphomas and anticipate that the near future will bring significant advances that provide a measurable impact on NHL outcomes.

Devang Thakkar

Center for Genomic and Computational Biology

Duke University

Clonal Analysis of the Neonatal Mouse Heart using Nearest Neighbor Modeling

Devang Thakkar

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Duke University

Clonal Analysis of the Neonatal Mouse Heart using Nearest Neighbor Modeling

Center for Genomic and Computational Biology