LncRNA HCG18 affects aortic dissection through the miR-103a-3p/HMGA2 axis by modulating proliferation and apoptosis of vascular smoothing muscle cells.

BACKGROUND: Aortic Dissection (AD) is a vascular disease with a high mortality rate and limited treatment strategies. The current research analyzed the function and regulatory mechanism of lncRNA HCG18 in AD. METHODS: HCG18, miR-103a-3p, and HMGA2 levels in the aortic tissue of AD patients were examined by RT-qPCR. After transfection with relevant plasmids, the proliferation of rat aortic Vascular Smoothing Muscle Cells (VSMCs) was detected by CCK-8 and colony formation assay, Bcl-2 and Bax was measured by Western blot, and apoptosis was checked by flow cytometry. Then, the targeting relationship between miR-103a-3p and HCG18 or HMGA2 was verified by bioinformation website analysis and dual luciferase reporter assay. Finally, the effect of HCG18 was verified in an AD rat model induced by ß-aminopropionitrile. RESULTS: HCG18 and HMGA2 were upregulated and miR-103a-3p was downregulated in the aortic tissues of AD patients. Downregulating HCG18 or upregulating miR-103a-3p enhanced the proliferation of VSMCs and limited cell apoptosis. HCG18 promoted HMGA2 expression by competing with miR-103a-3p and restoring HMGA2 could impair the effect of HCG18 downregulation or miR-103a-3p upregulation in mediating the proliferation and apoptosis of VSMCs. In addition, down-regulation of HCG18 could improve the pathological injury of the aorta in AD rats. CONCLUSION: HCG18 reduces proliferation and induces apoptosis of VSMCs through the miR-103a-3p/HMGA2 axis, thus aggravating AD.

Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma.

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1273 newly diagnosed patients with MM, we identified 63 driver genes, some of which are novel, including IDH1, IDH2, HUWE1, KLHL6, and PTPN11 Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more driver gene abnormalities are associated with worse outcomes, as are identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in FGFR3, DIS3, and PRKD2; t(11;14) with mutations in CCND1 and IRF4; t(14;16) with mutations in MAF, BRAF, DIS3, and ATM; and hyperdiploidy with gain 11q, mutations in FAM46C, and MYC rearrangements. These associations indicate that the genomic landscape of myeloma is predetermined by the primary events upon which further dependencies are built, giving rise to a nonrandom accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens.