Selective ERBB2 and BCL2 Inhibition Is Synergistic for Mitochondrial-Mediated Apoptosis in MDS and AML Cells

Integrated Machine Learning and Bioinformatic Analyses Constructed a Network Between Mitochondrial Dysfunction and Immune Microenvironment of Periodontitis

Periodontitis is a prevalent and persistent inflammatory condition that impacts the supporting tissues of the teeth, including the gums and bone. Recent research indicates that mitochondrial dysfunction may be involved in the onset and advancement of periodontitis. The current work sought to reveal the interaction between mitochondrial dysfunction and the immune microenvironment in periodontitis. Public data were acquired from MitoCarta 3.0, Mitomap, and GEO databases. Hub markers were screened out by five integrated machine learning algorithms and verified by laboratory experiments. Single-cell sequencing data were utilized to unravel cell-type specific expression levels of hub genes. An artificial neural network model was constructed to discriminate periodontitis from healthy controls. An unsupervised consensus clustering algorithm revealed mitochondrial dysfunction-related periodontitis subtypes. The immune and mitochondrial characteristics were calculated using CIBERSORTx and ssGSEA algorithms. Two hub mitochondria-related markers (CYP24A1 and HINT3) were identified. Single-cell sequencing data revealed that HINT3 was primarily expressed in dendritic cells, while CYP24A1 was mainly expressed in monocytes. The hub genes based artificial neural network model showed robust diagnostic performance. The unsupervised consensus clustering algorithm revealed two distinct mitochondrial phenotypes. The hub genes exhibited a strong correlation with the immune cell infiltration and mitochondrial respiratory chain complexes. The study identified two hub markers that may serve as potential targets for immunotherapy and provided a novel reference for future investigations into the function of mitochondria in periodontitis.

Neratinib inhibits proliferation and promotes apoptosis of acute myeloid leukemia cells by activating autophagy-dependent ferroptosis

Acute myeloid leukemia (AML) is a hematologic malignancy with increased lethality. We focused on elucidating the role of Neratinib, a tyrosine kinase inhibitor, in the progression of AML and identify the potential mechanisms. Upon the treatment of Neratinib, autophagy suppressor 3-methyladenine (3-MA) and ferroptosis stimulator Erastin, the viability and proliferation of HL-60 cells were evaluated by cell counting kit-8 and 5-Ethynyl-20-Deoxyuridine staining assays. A flow cytometer was to observe cell cycle and apoptosis. Production of reactive oxygen species (ROS) was tested via 2,7-dichlorodihydrofluorescein diacetate  assay. Additionally, malondialdehyde (MDA) content and Fe²⁺ activity were examined with commercial kits. LC3-II expression was examined by using immunofluoresence staining. Western blot analysis ascertained the expression of proliferation, apoptosis, ferroptosis and autophagy-associated proteins. It was noted that Neratinib notably mitigated cell viability and proliferation, cut down Ki67 and proliferating cell nuclear antigen expression. Moreover, Neratinib hindered cell cycle at G0/G1 phase whereas exacerbated apoptosis. ROS, MDA and Fe²⁺ activities were elevated by Neratinib, coupled with the reduced glutathione peroxidase 4, ferritin heavy chain 1 expression and enhanced acyl-CoA synthetase long-chain family member 4 expression. Furthermore, Neratinib promoted autophagy of HL-60 cells, evidenced by raised LC3-II, ATG5, Beclin1 expression and lessened p62 expression. Importantly, 3-MA eased the impacts of Neratinib on cell ferroptosis, proliferation and apoptosis, which were offset by further administration of Erastin. To conclude, Neratinib could suppress proliferation and promote apoptosis of HL-60 cells through autophagy-dependent ferroptosis.