4.4 Article

The genomic landscape of canine diffuse large B-cell lymphoma identifies distinct subtypes with clinical and therapeutic implications

Journal

LAB ANIMAL
Volume 51, Issue 7, Pages 191-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41684-022-00998-x

Keywords

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Funding

  1. 'Scientific Independence of young Researchers' (SIR) grant from the Ministero dell'Universita (K9LYMPHOMET) [RBSI14EDX9]

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Giannuzzi et al. conducted an integrated analysis of clinical features and exome and RNA sequencing data in dogs with diffuse large B-cell lymphoma (DLBCL) to define the genetic landscape and identify mutations associated with outcome. The study found common signaling pathways and cellular processes with human DLBCL, but different frequencies of recurrently mutated genes. A prognostic model integrating genetic variants and clinical and transcriptomic features was developed to predict outcome in dogs with DLBCL. These findings provide a comprehensive understanding of the genetic drivers of canine DLBCL and potential therapeutic opportunities.
Giannuzzi et al. present an integrated analysis of clinical features and exome and RNA sequencing data in a cohort of dogs with diffuse large B-cell lymphoma to better define the genetic landscape of this tumor and identify multiple mutations associated with the outcome. Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid neoplasm in dogs and in humans. It is characterized by a remarkable degree of clinical heterogeneity that is not completely elucidated by molecular data. This poses a major barrier to understanding the disease and its response to therapy, or when treating dogs with DLBCL within clinical trials. We performed an integrated analysis of exome (n = 77) and RNA sequencing (n = 43) data in a cohort of canine DLBCL to define the genetic landscape of this tumor. A wide range of signaling pathways and cellular processes were found in common with human DLBCL, but the frequencies of the most recurrently mutated genes (TRAF3, SETD2, POT1, TP53, MYC, FBXW7, DDX3X and TBL1XR1) differed. We developed a prognostic model integrating exonic variants and clinical and transcriptomic features to predict the outcome in dogs with DLBCL. These results comprehensively define the genetic drivers of canine DLBCL and can be prospectively utilized to identify new therapeutic opportunities.

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