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Abstract Recently, a novel knowledge bank (KB) approach to predict outcomes of individual patients with acute myeloid leukemia (AML) was developed using unbiased machine learning. To validate its prognostic value, we analyzed 1612 adults with de novo AML treated on Cancer and Leukemia Group B front-line trials who had pretreatment clinical, cytogenetics, and mutation data on 81 leukemia/cancer-associated genes available. We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate the predictive values of the KB algorithm and other risk classifications. The KB algorithm predicted 3-year overall survival (OS) probability in the entire patient cohort (AUCKB = 0.799), and both younger (

Abstract Background Exportin 1 (XPO1/CRM1) is a key mediator of nuclear export with relevance to multiple cancers, including chronic lymphocytic leukemia (CLL). Whole exome sequencing has identified hot-spot somatic XPO1 point mutations which we found to disrupt highly conserved biophysical interactions in the NES-binding groove, conferring novel cargo-binding abilities and forcing cellular mis-localization of critical regulators. However, the pathogenic role played by change-in-function XPO1 mutations in CLL is not fully understood. Methods We performed a large, multi-center retrospective analysis of CLL cases (N = 1286) to correlate nonsynonymous mutations in XPO1 (predominantly E571K or E571G; n = 72) with genetic and epigenetic features contributing to the overall outcomes in these patients. We then established a mouse model with over-expression of wildtype (wt) or mutant (E571K or E571G) XPO1 restricted to the B cell compartment (Eµ-XPO1). Eµ-XPO1 mice were then crossed with the Eµ-TCL1 CLL mouse model. Lastly, we determined crystal structures of XPO1 (wt or E571K) bound to several selective inhibitors of nuclear export (SINE) molecules (KPT-185, KPT-330/Selinexor, and KPT-8602/Eltanexor). Results We report that nonsynonymous mutations in XPO1 associate with high risk genetic and epigenetic features and accelerated CLL progression. Using the newly-generated Eµ-XPO1 mouse model, we found that constitutive B-cell over-expression of wt or mutant XPO1 could affect development of a CLL-like disease in aged mice. Furthermore, concurrent B-cell expression of XPO1 with E571K or E571G mutations and TCL1 accelerated the rate of leukemogenesis relative to that of Eµ-TCL1 mice. Lastly, crystal structures of E571 or E571K-XPO1 bound to SINEs, including Selinexor, are highly similar, suggesting that the activity of this class of compounds will not be affected by XPO1 mutations at E571 in patients with CLL. Conclusions These findings indicate that mutations in XPO1 at E571 can drive leukemogenesis by priming the pre-neoplastic lymphocytes for acquisition of additional genetic and epigenetic abnormalities that collectively result in neoplastic transformation.