B cell receptor (BCR) signalling has emerged as a therapeutic target in B cell lymphomas, but inhibiting this pathway in diffuse large B cell lymphoma (DLBCL) has benefited only a subset of patients. Gene expression profiling identified two major subtypes of DLBCL, known as germinal centre B cell-like and activated B cell-like (ABC), that show poor outcomes after immunochemotherapy in ABC. Autoantigens drive BCR-dependent activation of NF-κB in ABC DLBCL through a kinase signalling cascade of SYK, BTK and PKCβ to promote the assembly of the CARD11-BCL10-MALT1 adaptor complex, which recruits and activates IκB kinase. Genome sequencing revealed gain-of-function mutations that target the CD79A and CD79B BCR subunits and the Toll-like receptor signalling adaptor MYD88, with MYD88(L265P) being the most prevalent isoform. In a clinical trial, the BTK inhibitor ibrutinib produced responses in 37% of cases of ABC. The most striking response rate (80%) was observed in tumours with both CD79B and MYD88(L265P) mutations, but how these mutations cooperate to promote dependence on BCR signalling remains unclear. Here we used genome-wide CRISPR-Cas9 screening and functional proteomics to determine the molecular basis of exceptional clinical responses to ibrutinib. We discovered a new mode of oncogenic BCR signalling in ibrutinib-responsive cell lines and biopsies, coordinated by a multiprotein supercomplex formed by MYD88, TLR9 and the BCR (hereafter termed the My-T-BCR supercomplex). The My-T-BCR supercomplex co-localizes with mTOR on endolysosomes, where it drives pro-survival NF-κB and mTOR signalling. Inhibitors of BCR and mTOR signalling cooperatively decreased the formation and function of the My-T-BCR supercomplex, providing mechanistic insight into their synergistic toxicity for My-T-BCR DLBCL cells. My-T-BCR supercomplexes characterized ibrutinib-responsive malignancies and distinguished ibrutinib responders from non-responders. Our data provide a framework for the rational design of oncogenic signalling inhibitors in molecularly defined subsets of DLBCL.

Myelodysplastic syndromes (MDS) are a heterogeneous group of hematologic neoplasms with an annual incidence of 4.1 cases per 100,000 Americans. Patients with MDS suffer from chronic cytopenias that may lead to recurrent transfusions, infections, and increased risk for bleeding. They are also at risk for progression to acute myeloid leukemia. Allogeneic hematopoietic cell transplantation is the only potentially curative treatment for MDS, although 3 drugs have been approved by the US Food and Drug Administration for its treatment: lenalidomide, 5-azacitidine, and decitabine. These therapies can be effective in the relief of cytopenias, achievement of cytogenetic remissions, and reduction in bone marrow blasts. 5-azacitidine has also been shown to improve overall survival. However, there remain many unmet needs in the treatment of MDS. Breakthroughs in our understanding of the complex pathogenesis of MDS through epigenetic, genetic, immunologic, and other biological mechanisms have allowed us to develop new therapeutic strategies that can lead to improvements in outcomes in MDS. In this review, we aim to provide an overview of the evolution in classifcation and risk stratifcation in MDS and to illustrate how we can use this to guide us in tailoring therapeutic choices in this disease. Responses and outcomes related to com monly used MDS therapies will be discussed together with novel therapies that have evolved with the improved understanding of MDS pathophysiology.

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The following discrepancies and errors were found in the original publication:-As correctly specified in Table 1, the male PCNSL patients treated with HD-MTX made up 46% of that group (not 54% as specified in the Abstract and the text of the Results section). -As correctly specified in the Results section (Table 2 and text), the average first detected WMC score was 0.8 (± 0.9) (mean, ± SD) in the HD-MTX group; not 1.5 (± 0.6) as specified in the Abstract. Also, the term 'non-zero' in the Abstract and in the text of the Results section should not have been used here. -As correctly specified in Table 2, the p-value for the Overall WMC score is 0.0048; not 0.04 as specified for the average WMC score in the text in the Results section. -In the first column of Table 2, the word 'years' in the bottom entry should read 'months'.-In the Results section, the second sentence in the second paragraph should read as follows: "Median time to detect WMC was shorter in the HD-MTX-R group compared to the HD-MTX group".Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.The original article can be found online at https ://doi.