Common genomic and transcriptomic signatures in Richter transformation highlight druggable vulnerabilities and guide drug repurposing strategies

Richter transformation (RT) is a rare and aggressive lymphoma occurring in patients with chronic lymphocytic leukemia (CLL).Despite advancements in understanding the pathogenetic mechanisms driving disease transformation, it remains a challenging malignancy 123.In recent years, multi-center genomic studies have shed light on the heterogeneity of RT, with no single driver alteration identified 4567.This complexity underscores the need for a comprehensive molecular profiling through multi-omic approaches, as one-fits-all therapeutic strategies are unlikely to succeed.Such profiling offers a way to capture actionable vulnerabilities, based on experimental approaches that identify and prioritize "recurrent players" across cohorts.To identify novel therapeutic opportunities through a drug repurposing strategy -aimed at accelerating translation from research to the clinics -we investigated paired genomic and transcriptomic data from a cohort of 20 RT patients.Results were then integrated with data from 3 recently published cohorts 4,5,8 to derive a RT "blueprint", and define a hierarchy of consistent disease hallmarks.The convergent features were exploited to design an ad-hoc drug library, functionally validated through a high-throughput screening in RT models (Fig. 1A).DNA and RNA were co-extracted from 20 formalin-fixed paraffin-embedded (FFPE) lymph-node biopsies from RT patients collected between 2010 and 2020.Targeted DNA sequencing was performed using TruSight Oncology 500, enabling detection of clinically relevant single-nucleotide variants (SNVs)/indels and copy-number variations (CNVs) within cancer-associated genes.Bulk RNA sequencing was feasible in 14/20 samples and allowed us to identify differential gene expression (DGE) compared to the preceding disease phase, exploiting multiple GEO/EGA CLL datasets (n = 250).Although being a valid source of material and information for genetic analyses, FFPE samples may present quality issues due to the conservation technique 9,10.Methodological fidelity was assessed in a matched comparison, using the RT-PDX model RS1316, sequencing both DNA and RNA from fresh material, and from its FFPE counterpart.Variant allele frequencies (VAF) for five known variants in RS1316 11 were preserved between conditions (paired t-test not significant), with a Spearman correlation indicating strong concordance ( = 0.9; Supplementary Fig. S1A).For transcriptomics, linear regression of log 10 TPMs between fresh and FFPE material showed strong correlation (R = 0.74; P < 0.0001; Supplementary