Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome - presented by Dr. Erin M. Parry MD, PhD

Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome

Dr. Erin M. Parry MD, PhD

Dr. Erin M. Parry MD, PhD
Slide at 17:01
I: Assembling RS cohort through collaboration
Discovery Cohort N=53 (WES)
Ulm, Germany
Dana-Farber Cancer Institute
Mayo Clinic
FILO UCSD
MDACC
Validation Cohort N=45 (WES/RNA)
FILO
CLL Sample
Observation
Targeted therapy
RS sample
CLL therapy
Died
Living
RS course
Validation Cohort N=14 (WGS)
Lines of treatment
Klintman et al, Blood 2021
5 20 15 12
Years
Months
Parry, Leshchiner, Guieze et al, Nature Medicine, 2023
1
2
References
  • 1.
    E. M. Parry et al. (2023) Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome. Nature Medicine
  • 2.
    J. Klintman et al. (2020) Genomic and transcriptomic correlates of Richter transformation in chronic lymphocytic leukemia. Blood
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Summary (AI generated)

To overcome limitations in sample collection, a collaborative effort was formed across multiple institutions in the US and internationally. A discovery cohort of 53 patients with serial CLL samples (black dots) and Richter samples (yellow squares) was assembled. Exome sequencing was performed on paired malignant and normal samples for each individual. The swimmer plot shows the long natural history of CLL marked in years at the bottom, compared to the shorter history of Richter's.

After analyzing the discovery cohort for transformation changes, findings were validated using two independent cohorts: one with paired exome and transcriptome sequencing of 45 patients, and another with 14 whole genomes from a UK series. Paired exome sequencing was performed on normal CLL and Richter samples, with additional steps in computational analysis pipelines. The tools din, ABSOLUTE, and phylogic NDT were used to account for tumor in normal contamination, determine cancer cell fraction, and clonal composition.

On a per patient level, CLL clones were separated from Richter's clones to reconstruct the evolution using a probabilistic model and phylogic NDT. The cartoon illustrates CLL clones (green) evolving into Richter's (purple), with some CLL clones diverging or following different evolutionary patterns.