Identification of altered cell signaling pathways using proteomic profiling in stable and progressive chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is characterized by significant biologic and clinical heterogeneity. This study was designed to explore CLL B‐cells’ proteomic profile in order to identify biologic processes affected at an early stage and during disease evolution as stable or progressive. Purified B cells from 11 untreated CLL patients were tested at two time points by liquid chromatography–tandem mass spectrometry. Patients included in the study evolved to either progressive (n = 6) or stable disease (n = 5). First, at an early stage of the disease (Binet stage A), based on the relative abundance levels of 389 differentially expressed proteins (DEPs), samples were separated into stable and progressive clusters with the main differentiating factor being the RNA splicing pathway. Next, in order to test how the DEPs affect RNA splicing, a RNA‐Seq study was conducted showing 4217 differentially spliced genes between the two clusters. Distinct longitudinal evolutions were observed with predominantly proteomic modifications in the stable CLL group and spliced genes in the progressive CLL group. Splicing events were shown to be six times more frequent in the progressive CLL group. The main aberrant biologic processes controlled by DEPs and spliced genes in the progressive group were cytoskeletal organization, Wnt/β‐catenin signaling, and mitochondrial and inositol phosphate metabolism with a downstream impact on CLL B‐cell survival and migration. This study suggests that proteomic profiles at the early stage of CLL can discriminate progressive from stable disease and that RNA splicing dysregulation underlies CLL evolution, which opens new perspectives in terms of biomarkers and therapy. Graphical Proteomic profiles at the early stage of CLL can discriminate progressive from stable disease and RNA splicing and cell cycle dysregulation underlies CLL evolution; opening new perspectives on potential biomarkers and therapy.