MicroRNA mir-9 is speculated to be involved in insulin secretion because of its ability to regulate exocytosis. Sirt1 is an NAD-dependent protein deacetylase and a critical factor in the modulation of cellular responses to altered metabolic flux. It has also been shown recently to control insulin secretion from pancreatic β-islets. However, little is known about the regulation of Sirt1 and mir-9 levels in pancreatic β-cells, particularly during glucose-dependent insulin secretion. In this article, we report that mir-9 and Sirt1 protein levels are actively regulated in vivo in β-islets during glucose-dependent insulin secretion. Our data also demonstrates that mir-9 targets and regulates Sirt1 expression in insulin-secreting cells. This targeting is relevant in pancreatic β-islets, where we show a reduction in Sirt1 protein levels when mir-9 expression is high during glucose-dependent insulin secretion. This functional interplay between insulin secretion, mir-9 and Sirt1 expression could be relevant in diabetes. It also highlights the crosstalk between an NAD-dependent protein deacetylase and microRNA in pancreatic β-cells.

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Purpose: PARP inhibitors (PARPi) are standard-of-care therapy for high-grade serous ovarian cancer (HGSOC). We investigated combining cediranib (antiangiogenic) with olaparib (PARPi) at emergence of PARPi resistance.Patients and Methods: The proof-of-concept EVOLVE study (NCT-02681237) assessed cediranib-olaparib combination therapy after progression on a PARPi. Women with HGSOC and radiographic evidence of disease progression were enrolled into one of three cohorts: platinum sensitive after PARPi; platinum resistant after PARPi; or progression on standard chemotherapy after progression on PARPi (exploratory cohort). Patients received olaparib tablets 300 mg twice daily with cediranib 20 mg once daily until progression or unacceptable toxicity. The coprimary endpoints were objective response rate (RECIST v1.1) and progression-free survival (PFS) at 16 weeks. Archival tissue (PARPi-na€ ve) and baseline biopsy (post-PARPi) samples were mandatory. Genomic mechanisms of resistance were assessed by whole-exome and RNA sequencing.Results: Among 34 heavily pretreated patients, objective responses were observed in 0 of 11 (0%) platinum-sensitive patients, 2 of 10 (20%) platinum-resistant patients, and 1 of 13 (8%) in the exploratory cohort. Sixteen-week PFS rates were 55%, 50%, and 39%, respectively. The most common grade 3 toxicities were diarrhea (12%) and anemia (9%). Acquired genomic alterations at PARPi progression were reversion mutations in BRCA1, BRCA2, or RAD51B (19%); CCNE1 amplification (16%); ABCB1 upregulation (15%); and SLFN11 downregulation (7%). Patients with reversion mutations in homologous recombination genes and/or ABCB1 upregulation had poor outcomes.Conclusions: This is currently the largest post-PARPi study identifying genomic mechanisms of resistance to PARPis. In this setting, the activity of cediranib-olaparib varied according to the PARPi resistance mechanism.

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FLT3, DNMT3A, and NPM1 are the most frequently mutated genes in cytogenetically normal acute myeloid leukemia (AML), but little is known about how these mutations synergize upon cooccurrence. Here we show that triple-mutated AML is characterized by high leukemia stem cell (LSC) frequency, an aberrant leukemia-specific GPR56highCD34low immunophenotype, and synergistic upregulation of Hepatic Leukemia Factor (HLF). Cell sorting based on the LSC marker GPR56 allowed isolation of triple-mutated from DNMT3A/NPM1 double-mutated subclones. Moreover, in DNMT3A R882-mutated patients, CpG hypomethylation at the HLF transcription start site correlated with high HLF mRNA expression, which was itself associated with poor survival. Loss of HLF via CRISPR/Cas9 significantly reduced the CD34+GPR56+ LSC compartment of primary human triple-mutated AML cells in serial xenotransplantation assays. HLF knockout cells were more actively cycling when freshly harvested from mice, but rapidly exhausted when reintroduced in culture. RNA sequencing of primary human triple-mutated AML cells after shRNA-mediated HLF knockdown revealed the NOTCH target Hairy and Enhancer of Split 1 (HES1) and the cyclin-dependent kinase inhibitor CDKN1C/p57 as novel targets of HLF, potentially mediating these effects. Overall, our data establish HLF as a novel LSC regulator in this genetically defined high-risk AML subgroup.

PurposeThis paper reviews 105 Scopus-indexed articles to identify the degree, scope and purposes of machine learning (ML) adoption in the core functions of human resource management (HRM).Design/methodology/approachA semi-systematic approach has been used in this review. It allows for a more detailed analysis of the literature which emerges from multiple disciplines and uses different methods and theoretical frameworks. Since ML research comes from multiple disciplines and consists of several methods, a semi-systematic approach to literature review was considered appropriate.FindingsThe review suggests that HRM has embraced ML, albeit it is at a nascent stage and is receiving attention largely from technology-oriented researchers. ML applications are strongest in the areas of recruitment and performance management and the use of decision trees and text-mining algorithms for classification dominate all functions of HRM. For complex processes, ML applications are still at an early stage; requiring HR experts and ML specialists to work together.Originality/valueGiven the current focus of organizations on digitalization, this review contributes significantly to the understanding of the current state of ML integration in HRM. Along with increasing efficiency and effectiveness of HRM functions, ML applications improve employees' experience and facilitate performance in the organizations.

Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood characterized by mutations activating RAS signaling. Established clinical and genetic markers fail to fully recapitulate the clinical and biological heterogeneity of this disease. Here we report DNA methylome analysis and mutation profiling of 167 JMML samples. We identify three JMML subgroups with unique molecular and clinical characteristics. The high methylation group (HM) is characterized by somatic PTPN11 mutations and poor clinical outcome. The low methylation group is enriched for somatic NRAS and CBL mutations, as well as for Noonan patients, and has a good prognosis. The intermediate methylation group (IM) shows enrichment for monosomy 7 and somatic KRAS mutations. Hypermethylation is associated with repressed chromatin, genes regulated by RAS signaling, frequent co-occurrence of RAS pathway mutations and upregulation of DNMT1 and DNMT3B, suggesting a link between activation of the DNA methylation machinery and mutational patterns in JMML.