Genomic and transcriptomic correlates of Richter transformation in chronic lymphocytic leukemia

The transformation of chronic lymphocytic leukemia (CLL) to high-grade B-cell lymphoma is known as Richter syndrome (RS), a rare event with dismal prognosis. In this study, we conducted whole-genome sequencing (WGS) of paired circulating CLL (PB-CLL) and RS biopsies (tissue-RS) from 17 patients recruited into a clinical trial (CHOP-0). We found that tissue-RS was enriched for mutations in poor-risk CLL drivers and genes in the DNA damage response (DDR) pathway. In addition, we identified genomic aberrations not previously implicated in RS, including the protein tyrosine phosphatase receptor (PTPRD) and tumor necrosis factor receptor-associated factor 3 (TRAF3). In the noncoding genome, we discovered activation-induced cytidine deaminase related and unrelated kataegis in tissue RS affecting regulatory regions of key immune regulatory genes. These include BTG2, CXCR4, NFATC1, PAX5, NOTCH 1, SLC44A5, FCRL3, SELL, TNIP2, and TRIM13. Furthermore, differences between the global mutation signatures of pairs of PB-CLL and tissue-RS samples implicate DDR as the dominant mechanism driving transformation. Pathway-based clonal deconvolution analysis showed that genes in the MAPK and DDR pathways demonstrate high clonal-expansion probability. Direct comparison of nodal-CLL and tissue-RS pairs from an independent cohort confirmed differential expression of the same pathways by RNA expression profiling. Our integrated analysis of WGS and RNA expression data significantly extends previous targeted approaches, which were limited by the lack of germline samples, and it facilitates the identification of novel genomic correlates implicated in RS transformation, which could be targeted therapeutically. Our results inform the future selection of investigative agents for a UK clinical platform study.

Automated summary

The transformation of chronic lymphocytic leukemia into high-grade B-cell lymphoma, known as Richter syndrome, involves specific genetic mutations affecting pathways such as DNA damage response (DDR) and MAPK. Whole-genome sequencing and RNA expression profiling can help identify novel genomic correlates and pathways implicated in this transformation, offering potential therapeutic targets. The study emphasizes the importance of integrated analysis in predicting the genetic changes driving the progression from CLL to RS.