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 [1][2][3].In recent years, multi-center genomic studies have shed light on the heterogeneity of RT, with no single driver alteration identified [4][5][6][7].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