The SF3B1 inhibitor spliceostatin A (SSA) elicits apoptosis in chronic lymphocytic leukemia cells through downregulation of Mcl-1

The pro-survival Bcl-2 family member Mcl-1 is expressed in chronic lymphocytic leukemia (CLL), with high expression correlated with progressive disease. The spliceosome inhibitor spliceostatin A (SSA), is known to regulate Mcl-1 and so here we assessed the ability of SSA to elicit apoptosis in CLL. SSA induced apoptosis of CLL cells at low nanomolar concentrations in a dose- and time-dependent manner, but independently of SF3B1 mutational status, IGHV status and CD38 or ZAP70 expression. However, normal B and T cells were less sensitive than CLL cells (P=0.006 and P<0.001, respectively). SSA altered the splicing of anti-apoptotic MCL-1L to MCL-1s in CLL cells coincident with induction of apoptosis. Overexpression studies in Ramos cells suggested Mcl-1 was important for SSA-induced killing since its expression inversely correlated with apoptosis (P=0.001). IL4 and CD40L, present in patient lymph nodes, are known to protect tumor cells from apoptosis and significantly inhibited SSA, ABT-263 and ABT-199 induced killing following administration to CLL cells (P=0.008). However, by combining SSA with the Bcl-2/Bcl-xL antagonists ABT-263 or ABT-199, we were able to overcome this pro-survival effect. We conclude that SSA combined with Bcl-2/Bcl-xL antagonists may have therapeutic utility for CL

Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features

The value of genome-wide over targeted driver analyses for predicting clinical outcomes of cancer patients is debated. Here, we report the whole-genome sequencing of 485 chronic lymphocytic leukemia patients enrolled in clinical trials as part of the United Kingdom’s 100,000 Genomes Project. We identify an extended catalog of recurrent coding and noncoding genetic mutations that represents a source for future studies and provide the most complete high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and genomic complexity. We demonstrate the relationship of these features with clinical outcome and show that integration of 186 distinct recurrent genomic alterations defines five genomic subgroups that associate with response to therapy, refining conventional outcome prediction. While requiring independent validation, our findings highlight the potential of whole-genome sequencing to inform future risk stratification in chronic lymphocytic leukemia

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease