Myeloid ecotropic virus insertion site 1 (MEIS1) is essential for normal hematopoiesis and is a critical factor in the pathogenesis of a large subset of acute myeloid leukemia (AML). Despite the clinical relevance of MEIS1, its regulation is largely unknown. To understand the transcriptional regulatory mechanisms contributing to human MEIS1 expression, we created a knock-in green florescent protein (GFP) reporter system at the endogenous MEIS1 locus in a human AML cell line. Using this model, we have delineated and dissected a critical enhancer region of the MEIS1 locus for transcription factor (TF) binding through in silico prediction in combination with oligo pull-down, mass-spectrometry and knockout analysis leading to the identification of FLI1, an E-twenty-six (ETS) transcription factor, as an important regulator of MEIS1 transcription. We further show direct binding of FLI1 to the MEIS1 locus in human AML cell lines as well as enrichment of histone acetylation in MEIS1-high healthy and leukemic cells. We also observe a positive correlation between high FLI1 transcript levels and worse overall survival in AML patients. Our study expands the role of ETS factors in AML and our model constitutes a feasible tool for a more detailed understanding of transcriptional regulatory elements and their interactome.

Background: Expression levels of the cell surface glycoprotein, CD7, and the serine protease, elastase 2 (ELA2), in the leukemic cells of patients with chronic myeloid leukemia (CML) have been associated with clinical outcome. However, little is known about the mechanisms that underlie the variable expression of these genes in the leukemic cells.Results: To address this question, we compared the level of their expression with the DNA methylation and histone acetylation status of 5' sequences of both genes in leukemic cell lines and primitive (lin^-CD34⁺) leukemic cells from chronic phase CML patients. DNA methylation of theELA2gene promoter did not correlate with its expression pattern in lin^-CD34⁺cells from chronic phase CML patient samples even though there was clear differential DNA methylation of this locus inELA2-expressing and non-expressing cell lines. In contrast, we found a strong relation between CD7 expression and transcription-permissive chromatin modifications, both at the level of DNA methylation and histone acetylation with evidence of hypomethylation of theCD7promoter region in the lin^-CD34⁺cells from CML patients with high CD7 expression.Conclusion: These findings indicate a link between epigenetic modifications and CD7 expression in primitive CML cells.

Recent studies have identified mutational genomic signatures introduced by Apolipoprotein B mRNA-Editing Catalytic Polypeptidelike (APOBEC) deaminases as well as inflammatory processes as being pivotal for MM onset and progression [1-4]. Although these recent insights provide a better understanding of MM pathogenesis, they have not yet been translated into clinical applications such as MM risk stratification. The current standards for MM patient risk classification are the International Staging System (ISS), the Revised ISS (R-ISS) and the second revision of the R-ISS (R2-ISS) introduced between 2005 and 2022, respectively [5]. All scores are based on clinical parameters reflecting tumor burden, and the newer R-ISS and R2-ISS further incorporate high-risk cytogenetics [5]. Considering that most risk-defining chromosomal abnormalities reflect early events in MM cells [6], we concluded that tumor burden and/or cytogenetics-based classifiers might not accurately reflect the dynamics of disease progression in MM patients. Therefore, we hypothesized that a predictive score which reflects molecular mechanisms that drive MM progression, can improve the accuracy of current MM risk classifiers. To test this hypothesis, we constructed and validated a proof-of-principle risk classifier called Editor/Inflammation-or EI-score, which combines mRNA levels of survival-associated APOBEC genes, pro/anti-inflammatory genes as well as clinical markers for MM disease burden. Data from 1143 patients with newly diagnosed MM (NDMM) and available survival information was obtained through the CoMMpass database version IA14, which was generated as part of the Multiple Myeloma Research Foundation (MMRF) Personalized Medicine Initiatives (www.themmrf.org). ISS, R-ISS and R2-ISS staging information was available for 1113, 694, and 694 patients, respectively. For 599 patients, information on both blood parameters and RNA-seq was available. As an independent validation cohort, we analyzed clinical, cytogenetic, and RNA-seq