Identification of key genes and small molecule drugs in osteoarthritis by integrated bioinformatics analysis.

Background: Osteoarthritis (OA) is a common joint degenerative disease that can affect multiple joints. Genetic events may play an important regulatory role in the early stages of the disease, but the specific mechanisms have not yet been fully elucidated. The main purpose of this study was to screen for disease-causing hub genes and effective small molecule drugs to reveal the pathogenesis of OA and to develop novel drugs for treatment. Methods: Two gene expression profile datasets, GSE55235 and GSE55457, were integrated and further analyzed. The consistently differentially expressed genes (DEGs) were identified, and functional annotation and pathway analysis of these genes were performed with GO and KEGG. A protein-protein interaction network (PPI) of the DEGs was generated using STRING, and potential small molecule drug screening was performed on the connectivity map (CMap). Results: A total of 158 consistently differentially expressed genes were identified from the two profile datasets. The functions of these DEGs are mainly related to the TNF signaling pathway, osteoclast differentiation, MAPK signaling pathway and so on. The PPI network contains 127 nodes and 1802 edges, and the ten hub genes were interleukin 6 (IL6), vascular endothelial growth factor A (VEGFA)and so on. 7 small molecule drugs were identified as potential interactors with these hubs. Conclusions: This study explains the disorder of expression in the pathological process of OA at transcriptome, which will help to understand the pathogenesis of OA.

ECM2, a prognostic biomarker for lower grade glioma, serves as a potential novel target for immunotherapy.

Extracellular matrix protein 2 (ECM2), which regulates cell proliferation and differentiation, has recently been reported as a prognostic indicator for multiple cancers, but its value in lower grade glioma (LGG) remains unknown. In this study, LGG transcriptomic data of 503 cases in The Cancer Genome Atlas (TCGA) database and 403 cases in The Chinese Glioma Genome Atlas (CGGA) database were collected to analyze ECM2 expression patterns and the relationship with clinical characteristics, prognosis, enriched signaling pathways, and immune-related markers. In addition, a total of 12 laboratory samples were used for experimental validation. Wilcoxon or Kruskal-Wallis tests demonstrated highly expressed ECM2 in LGG was positively associated with malignant histological features and molecular features such as recurrent LGG and isocitrate dehydrogenase (IDH) wild-type. Also, Kaplan-Meier (KM) curves proved high ECM2 expression could predict shorter overall survival in LGG patients, as multivariate analysis and meta-analysis claimed ECM2 was a deleterious factor for LGG prognosis. In addition, the enrichment of immune-related pathways for ECM2, for instance JAK-STAT pathway, was obtained by Gene Set Enrichment Analysis (GSEA) analysis. Furthermore, positive relationships between ECM2 expression with immune cells infiltration and cancer-associated fibroblasts (CAFs), iconic markers (CD163), and immune checkpoints (CD274, encoding PD-L1) were proved by Pearson correlation analysis. Finally, laboratory experiments of RT-qPCR and immunohistochemistry showed high expression of ECM2, as well as CD163 and PD-L1 in LGG samples. This study identifies ECM2, for the first time, as a subtype marker and prognostic indicator for LGG. ECM2 could also provide a reliable guarantee for further personalized therapy, synergizing with tumor immunity, to break through the current limitations and thus reinvigorating immunotherapy for LGG. AVAILABILITY OF DATA AND MATERIALS: Raw data from all public databases involved in this study are stored in the online repository (chengMD2022/ECM2 (github.com)).

ZNF480 influences the prognosis, pathogenesis, and immune microenvironment in patients with lower-grade glioma.

ZNF480 has not yet attracted attention in the study of malignant tumors. Therefore, this study attempts to explain the significance of ZNF480 in the pathological process of lower-grade gliomas (LGG) based on large-scale samples from public database sources and in vitro experiments. Reverse transcription quantitative real-time polymerase chain reaction and immunohistochemistry confirmed that ZNF480 was highly expressed at both the mRNA and protein levels in LGG. Prognostic correlation analysis confirmed that the high expression of ZNF480, as an independent pathogenic gene, significantly correlates with poor survival in patients. Furthermore, the expression level of ZNF480 was significantly inhibited in SHG-44 cells treated with ademetionine disulfate tosylate. Gene set enrichment analysis showed that ZNF480 exists in multiple tumor-related signaling pathways, including the Notch signaling pathway. Immunological correlation analysis showed that ZNF480 can promote the LGG microenvironment to a high immune state and significantly enhance the infiltration of various immune cells, such as M2 macrophages. Finally, Spearman analysis showed a positive correlation of ZNF480 with many immune checkpoints, such as PD-L1. Overall, this study reveals for the first time the adverse effects of ZNF480 on the prognosis of tumor patients, which expands our understanding of the molecular mechanisms behind the regulation of ZNF480. We believe that the high expression of ZNF480 in LGG may be valuable for molecular targeted therapy or combined immunotherapy.