No abstract

Venetoclax inhibits the pro-survival protein BCL2 to induce apoptosis and is a standard therapy for chronic lymphocytic leukemia (CLL), delivering high complete remission rates and prolonged progression-free survival in relapsed CLL, but with eventual loss of efficacy. A spectrum of sub-clonal genetic changes associated with venetoclax resistance have now been described. To fully understand clinical resistance to venetoclax, we combined single-cell short- and long‑read RNA‑sequencing to reveal the previously unappreciated scale of genetic and epigenetic changes underpinning acquired venetoclax resistance. These appear to be multi-layered. One layer comprises changes in the BCL2 family of apoptosis regulators, especially the pro-survival family members. This includes previously described mutations in BCL2 and amplification of the MCL1 gene but heterogeneous across and within individual patient's leukemias. Changes in the pro-apoptotic genes are notably uncommon, except for single cases with sub-clonal losses of BAX or NOXA. Much more prominent was universal MCL1 gene upregulation. This was driven by an overlying layer of emergent NF‑kB activation which persisted in circulating cells during venetoclax therapy. We discovered that MCL1 could be a direct transcriptional target of NF‑kB. Both the switch to alternative pro-survival factors and NF‑kB activation largely dissipate following venetoclax discontinuation. Our studies reveal the extent of plasticity of CLL cells in their ability to evade venetoclax-induced apoptosis. Importantly, these findings pinpoint new approaches to circumvent venetoclax resistance and provide a specific biological justification for the strategy of venetoclax discontinuation once maximal response is achieved rather than maintaining long-term selective pressure with the drug.

Mass cytometry (CyTOF) is a technology that has revolutionised single cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches which includes an R-Shiny application with diagnostics plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.