Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Abstract

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

High-throughput proteomics identifies THEMIS2 as independent biomarker of treatment-free survival in untreated CLL

“…We con ned the molecular characterization of our cohort to those features commonly determined in clinical practice. As such, we were unable to study the proteomic effects of other recurrent mutations, such as lesions affecting NOTCH1 and SF3B1, although in other screens, their effects on global protein expression were found to be minimal (22,27). In addition, as biobank participation terminated upon treatment initiation, the effects of protein expression on treatment e cacy and OS could not be evaluated in this CLL biobank cohort.…”

“…Two publicly available, independently generated datasets were used for biomarker external validation. The rst dataset, generated by Herbst e.a., comprised bulk RNA sequencing and mass spectrometry data of 68 CLL patients (22). As not all patients in this cohort were treatment-free, TFS was reported as endpoint.…”

Drug‐microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL

“…We hypothesised that modulation of response to the microenvironment may play a role in the mechanism of trisomy 12 pathogenicity, which is so far incompletely understood. Previous work has indicated that trisomy 12 CLLs show higher transcript and protein abundance of microenvironmental pathways including BCR (preprint: Herbst et al , 2022b ) and chemokine signalling genes (Dietrich et al , 2018 ).…”

High-dimensional single-cell definition of CLL T cells identifies Galectin-9 as novel immunotherapy target

“…To estimate the relevance of Galectin-9 in CLL development, we analyzed a previously published proteome data set of CLL cells for Galectin-9 expression (Herbst et al, 2022). Dividing patients into two groups based on the median level of Galectin-9 expression clearly demonstrated a significantly shorter treatment-free survival in cases with low Galectin-9 expression (Figure 5F).…”