Rabbit Anti-Human ADPGK Polyclonal Antibody

OBJECTIVE: The functions of lncRNAs have been verified to be important biomarkers and regulators for diagnosis and treatment of human diseases. In osteosarcoma (OS), emerging evidence determined that lncRNA was associated with cell progression. However, due to the high incidence and recurrence rate of osteosarcoma, it is important to find an effective treatment for osteosarcoma. PATIENTS AND METHODS: QRT-PCR was used to detect the expression of ADPGK-AS1 and miR-542-3p in tissues and cells. Western blot was applied to measure the protein expression of CDK4, Cyclin D1, Bcl-2, Bax, Cleaved caspase-3, MMP-2, and MMP-9. MTT assay and flow cytometry were used to measure cell proliferation and apoptosis. Cell invasion and migration were determined using the transwell assay. Moreover, luciferase reporter assay was used to ensure the relation between ADPGK-AS1 and miR-542-3p. RESULTS: LncRNA ADPGK-AS1 expression was induced while miR-542-3p expression was reduced in OS tissues and cells. Functional experiments showed that inhibition of ADPGK-AS1 could decrease cell proliferation, migration, and invasion, as well as promoted cell apoptosis in OS cells. Also, miR-542-3p has been verified to be a target miRNA of ADPGK-AS1 and miR-542-3p could reverse the effects of ADPGK-AS1 on cell proliferation, apoptosis, migration, and invasion in OS cells. CONCLUSIONS: ADPGK-AS1 affected cell proliferation. invasion, migration, and apoptosis via targeting miR-542-3p in OS, providing a theoretical basis and a new therapeutic target for the diagnosis and treatment of OS.

Immune-related adverse events (irAEs), caused by anti-PD-1/PD-L1 antibodies, can lead to fulminant and even fatal consequences and thus require early detection and aggressive management. However, a comprehensive approach to identify biomarkers of irAE is lacking. Here, we utilize a strategy that combines pharmacovigilance data and omics data, and evaluate associations between multi-omics factors and irAE reporting odds ratio across different cancer types. We identify a bivariate regression model of LCP1 and ADPGK that can accurately predict irAE. We further validate LCP1 and ADPGK as biomarkers in an independent patient-level cohort. Our approach provides a method for identifying potential biomarkers of irAE in cancer immunotherapy using both pharmacovigilance data and multi-omics data. Immunotherapy, the reactivation of the immune system to recognize cancer cells, can be accompanied by severe adverse effects. Here, the authors use pharmacovigilance and genomic data to be able to predict which patients might be susceptible to such severe events.