Reversal of MYB-dependent suppression of MAFB expression overrides leukaemia phenotype in MLL-rearranged AML.

The transcription factor MYB plays a pivotal role in haematopoietic homoeostasis and its aberrant expression is involved in the genesis and maintenance of acute myeloid leukaemia (AML). We have previously demonstrated that not all AML subtypes display the same dependency on MYB expression and that such variability is dictated by the nature of the driver mutation. However, whether this difference in MYB dependency is a general trend in AML remains to be further elucidated. Here, we investigate the role of MYB in human leukaemia by performing siRNA-mediated knock-down in cell line models of AML with different driver lesions. We show that the characteristic reduction in proliferation and the concomitant induction of myeloid differentiation that is observed in MLL-rearranged and t(8;21) leukaemias upon MYB suppression is not seen in AML cells with a complex karyotype. Transcriptome analyses revealed that MYB ablation produces consensual increase of MAFB expression in MYB-dependent cells and, interestingly, the ectopic expression of MAFB could phenocopy the effect of MYB suppression. Accordingly, in silico stratification analyses of molecular data from AML patients revealed a reciprocal relationship between MYB and MAFB expression, highlighting a novel biological interconnection between these two factors in AML and supporting new rationales of MAFB targeting in MLL-rearranged leukaemias.

Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue.

Background: Gene expression profiling (GEP) studies recognized a prognostic role for tumor microenvironment (TME) in diffuse large B-cell lymphoma (DLBCL), but the routinely adoption of prognostic stromal signatures remains limited. Patients and methods: Here, we applied the computational method CIBERSORT to generate a 1028-gene matrix incorporating signatures of 17 immune and stromal cytotypes. Then, we carried out a deconvolution on publicly available GEP data of 482 untreated DLBCLs to reveal associations between clinical outcomes and proportions of putative tumor-infiltrating cell types. Forty-five genes related to peculiar prognostic cytotypes were selected and their expression digitally quantified by NanoString technology on a validation set of 175 formalin-fixed, paraffin-embedded DLBCLs from two randomized trials. Data from an unsupervised clustering analysis were used to build a model of clustering assignment, whose prognostic value was also assessed on an independent cohort of 40 cases. All tissue samples consisted of pretreatment biopsies of advanced-stage DLBCLs treated by comparable R-CHOP/R-CHOP-like regimens. Results: In silico analysis demonstrated that higher proportion of myofibroblasts (MFs), dendritic cells, and CD4+ T cells correlated with better outcomes and the expression of genes in our panel is associated with a risk of overall and progression-free survival. In a multivariate Cox model, the microenvironment genes retained high prognostic performance independently of the cell-of-origin (COO), and integration of the two prognosticators (COO + TME) improved survival prediction in both validation set and independent cohort. Moreover, the major contribution of MF-related genes to the panel and Gene Set Enrichment Analysis suggested a strong influence of extracellular matrix determinants in DLBCL biology. Conclusions: Our study identified new prognostic categories of DLBCL, providing an easy-to-apply gene panel that powerfully predicts patients' survival. Moreover, owing to its relationship with specific stromal and immune components, the panel may acquire a predictive relevance in clinical trials exploring new drugs with known impact on TME.