Affiliation:
1. Harvard Medical School, United States
2. Dana Farber Cancer Institute, Boston, Massachusetts, United States
Abstract
While the genetic landscape of chronic lymphocytic leukemia (CLL) has been broadly profiled by large-scale sequencing studies performed over the past decade, the molecular basis of the transformation of CLL to aggressive lymphoma, or Richter syndrome (RS), has remained incompletely characterized. Recent advances in computational methods of clonal deconvolution, as well as extensive sample collection efforts in this rapidly progressive malignancy, have now enabled comprehensive analysis of paired CLL and RS samples and have led to multiple new studies investigating the genetic, transcriptomic and epigenetic origins of RS. In parallel, new genetically-engineered and xenograft mouse models have provided the opportunity for gleaning fresh biologic and mechanistic insights into RS development and stepwise evolution from antecedent CLL. Altogether, these studies have defined RS driver lesions, CLL risk lesions and identified pathways dysregulated in transformation. Moreover, unique molecular subtypes of RS have been revealed, including disease marked by profound genomic instability with chromothripsis/chromoplexy and whole genome duplication. Novel profiling approaches, including single-cell DNA and transcriptome sequencing of RS biopsy specimens and cell-free DNA profiling of patient plasma, demonstrate promise for the timely identification of RS clones and may translate to non-invasive identification and early diagnosis of RS. This review summarizes the recent scientific advances in RS and supports the integrated study of human genomics with mouse modeling to provide advanced understanding of the biologic underpinnings of transformation. These recent studies have major implications for much needed novel therapeutic strategies for this still largely incurable malignancy.
Publisher
American Society of Hematology
Subject
Cell Biology,Hematology,Immunology,Biochemistry
Cited by
14 articles.
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