Targeting lysine demethylase 6B ameliorates ASXL1 truncation-mediated myeloid malignancies in preclinical models.

ASXL1 mutation frequently occurs in all forms of myeloid malignancies and is associated with aggressive disease and poor prognosis. ASXL1 recruits Polycomb repressive complex 2 (PRC2) to specific gene loci to repress transcription through trimethylation of histone H3 on lysine 27 (H3K27me3). ASXL1 alterations reduce H3K27me3 levels, which results in leukemogenic gene expression and the development of myeloid malignancies. Standard therapies for myeloid malignancies have limited efficacy when mutated ASXL1 is present. We discovered upregulation of lysine demethylase 6B (KDM6B), a demethylase for H3K27me3, in ASXL1-mutant leukemic cells, which further reduces H3K27me3 levels and facilitates myeloid transformation. Here, we demonstrated that heterozygous deletion of Kdm6b restored H3K27me3 levels and normalized dysregulated gene expression in Asxl1Y588XTg hematopoietic stem/progenitor cells (HSPCs). Furthermore, heterozygous deletion of Kdm6b decreased the HSPC pool, restored their self-renewal capacity, prevented biased myeloid differentiation, and abrogated progression to myeloid malignancies in Asxl1Y588XTg mice. Importantly, administration of GSK-J4, a KDM6B inhibitor, not only restored H3K27me3 levels but also reduced the disease burden in NSG mice xenografted with human ASXL1-mutant leukemic cells in vivo. This preclinical finding provides compelling evidence that targeting KDM6B may be a therapeutic strategy for myeloid malignancies with ASXL1 mutations.

Peroxynitrite nitration of Tyr 56 in Hsp90 induces PC12 cell death through P2X7R-dependent PTEN activation.

The diffusion-limited reaction of nitric oxide (NO) and superoxide (O2-) produces peroxynitrite (ONOO-), a biological oxidant that has been implicated in a number of pathological conditions, including neurodegenerative disorders. We previously reported that incubation of PC12 cells with peroxynitrite triggers apoptosis by simultaneously inhibiting the PI3K/Akt survival pathway, and activating the p38 and JNK MAP kinase pathways. We also reported that peroxynitrite-treated Heat Shock Protein 90 (Hsp90) stimulates PC12 cell death. Here, we show that nitrated Hsp90 mediates peroxynitrite-induced apoptosis by regulating specific signaling pathways triggered by activation of the purine receptor P2X7 (P2X7R) and downstream activation of PTEN. Intracellular delivery of peroxynitrite-treated Hsp90 was sufficient to stimulate PC12 cell death. In contrast, intracellular delivery of peroxynitrite-treated Hsp90 in which the five tyrosine (Tyr) residues susceptible to nitration were replaced by nitration-resistant phenylalanine had no effect on PC12 cell survival. Further, only nitration of Hsp90 at Tyr 56 was necessary and sufficient to stimulate PC12 cell apoptosis, and incubation of PC12 cells with peroxynitrite resulted in Hsp90 nitration at Tyr 56. Inhibition of P2X7R or downstream inhibition of PTEN prevented PC12 cell death stimulated by both incubation with peroxynitrite and nitrated Hsp90 (Hsp90NY). Peroxynitrite, Hsp90NY, and P2X7R activation all increased p38 and JNK MAP kinases activity, while inhibiting the Akt survival pathway. These results suggest that, in undifferentiated PC12 cells, peroxynitrite triggers apoptosis via nitration of Hsp90 at Tyr 56, which in turn activates P2X7R and PTEN. These results contrast with observations in motor neurons where the nitration of either Tyr 33 or Tyr 56 in Hsp90 stimulates apoptosis, suggesting that the targets of peroxynitrite may be different in different cell types. However, uncovering the pathways through which peroxynitrite triggers cell death in neurodegenerative conditions will provide new potential targets for therapeutic treatment.

Influential Usage of Big Data and Artificial Intelligence in Healthcare.

Artificial intelligence (AI) is making computer systems capable of executing human brain tasks in many fields in all aspects of daily life. The enhancement in information and communications technology (ICT) has indisputably improved the quality of people's lives around the globe. Especially, ICT has led to a very needy and tremendous improvement in the health sector which is commonly known as electronic health (eHealth) and medical health (mHealth). Deep machine learning and AI approaches are commonly presented in many applications using big data, which consists of all relevant data about the medical health and diseases which a model can access at the time of execution or diagnosis of diseases. For example, cardiovascular imaging has now accurate imaging combined with big data from the eHealth record and pathology to better characterize the disease and personalized therapy. In clinical work and imaging, cancer care is getting improved by knowing the tumor biology and helping in the implementation of precision medicine. The Markov model is used to extract new approaches for leveraging cancer. In this paper, we have reviewed existing research relevant to eHealth and mHealth where various models are discussed which uses big data for the diagnosis and healthcare system. This paper summarizes the recent promising applications of AI and big data in medical health and electronic health, which have potentially added value to diagnosis and patient care.