Proteogenomic Subtyping of Chronic Lymphocytic Leukemia Identifies a Novel Poor Outcome Subgroup with a Distinct Drug Response Profile

▪ Background: Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in the western world and shows a very heterogeneous clinical course. While the genetic landscape of CLL has been well characterized during recent years it can only partially explain the underlying biology of this heterogeneity. Proteogenomics could offer a valuable tool to fill this gap and improve the understanding of CLL biology. Methods: Here, we performed a large proteogenomic analysis (n=263) of three clinically annotated CLL cohorts: For the discovery cohort (Germany_1: n=68) we performed in-depth HiRIEF LC-MS based proteomics (more than 9000 proteins quantified) alongside genome-, transcriptome and ex-vivo drug response-profiling with 43 clinically established drugs. The proteome of two additional validation cohorts (Germany_2: n=44, Sweden_1: n=89), were characterized by data-independent acquisition (DIA) mass spectrometry. Results: To connect the CLL genotype with the molecular phenotype, we investigated associations between recurrent genetic alterations of CLL, mRNA expression and protein abundance. We found that trisomy 12, IGHV status and SF3B1 mutations had the greatest impact on protein abundances. CLL specific recurrent chromosomal deletions and gains (trisomy 12, del17p, del13q, del11q, gain8q24) consistently impacted on gene expression and protein abundance through gene dosage effects. We explored functional consequences of these gene dosage effects and found that the additional copy of chromosome 12 increased the abundance of central B-cell receptor (BCR) protein complexes through cis- and trans-effects, which could explain the increased response of trisomy 12 patient samples to BCR inhibition. Somatic mutations of TP53, ATM and XPO1 were associated with less, but specific and biologically-relevant protein abundance changes. p53 for instance, was the most upregulated protein in TP53 mutated samples, owing to the known stabilisation of mutant p53. This effect was not detectable on transcript level. ATM and XPO1 protein abundances were significantly lower in ATM and XPO1 mutated cases, indicating loss-of-function phenotypes of these mutations. To understand global similarities and differences between CLL patients on the proteomic level, we performed unsupervised clustering and identified clinically meaningful subgroups. Unsupervised clustering of the proteomics data identified six subgroups with contrasting clinical behaviour. TP53 mutations, IGHV status, tri