Clinical utility of chromosomal microarray in establishing clonality and high risk features in patients with Richter transformation

Brian Hess, James Kalmuk, Iya Znoyko, Cynthia A. Schandl, Nina Wagner-Johnston, Sandra Mazzoni, Lindsey Hendrickson, Zane Chiad, Irl Brian Greenwell, Daynna J. Wolff

Research output: Contribution to journalArticlepeer-review

Abstract

Richter transformation (RT) refers to the development of an aggressive lymphoma in patients with pre-existing chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). It carries a poor prognosis secondary to poor response to therapy or rapid disease relapse. Currently there are no randomized trials to guide treatment. Therapeutic decisions are often influenced by the presence or absence of a clonal relationship between the underlying CLL/SLL and the new lymphoma given the poor prognosis of patients with clonally related RT. Chromosomal microarray analysis (CMA) can help to establish clonality while also detecting genomic complexity and clinically relevant genetic variants such as loss of CDKN2A and/or TP53. As a result, CMA has potential prognostic and therapeutic implications. For this study, CMA results from patients with Richter transformation were evaluated in paired CLL/SLL and transformed lymphoma samples. CMA revealed that 86% of patients had common aberrations in the two samples indicating evidence of common clonality. CMA was also useful in detecting aberrations associated with a poor prognosis in 71% of patients with RT. This study highlights the potential clinical utility of CMA to investigate the clonal relationship between CLL/SLL and RT, provide prognostic information, and possibly guide therapeutic decision making for patients with Richter transformation.

Original languageEnglish (US)
Pages (from-to)18-22
Number of pages5
JournalCancer Genetics
Volume260-261
DOIs
StatePublished - Jan 2022

Keywords

  • CLL/SLL
  • Chromosomal microarray analysis
  • Richter transformation

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Cancer Research

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