Historically, CLL prognostication relied on disease burden, reflected in clinical stage. Later, chromosome abnormalities and genomics suggested several CLL subtypes which were aligned with response to therapy. Gene expression profiling data identified pathways associated with CLL progression. We hypothesized that transcriptome and proteome may identify functional omics associated with CLL nosology. As a test cohort, we utilized publicly available treatment-naïve CLL transcriptomics data (n = 130) and did consensus clustering that identified BTK-expression-based clusters. The BTK-High and BTK-Low clusters were validated in public and our in-house databases (n = >550 CLL patients). To associate with functional relevance, we took samples from 151 previously treated patient with CLL and analyzed them using RNA sequencing and reverse-phase protein array. Transcript levels were strongly correlated with BTK protein levels. BTK-High subtype showed increased CCL3/CCL4 levels and disease burden such as high WBC. BTK-Low subtype showed down-regulated mRNA/proteins of DNA-repair pathway and increased DNA-damage-response, which may have contributed to enrichment of inflammatory pathway. BTK-Low subtype was rich in proapoptotic gene and protein expression and relied less on BCR pathway. High-BTK subgroup was enriched in replication/repair pathway and transcription machinery. In conclusion, profiling of 5 datasets of ~700 patients revealed unique BTK-associated expression clusters in CLL.
© 2024. The Author(s).