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Background: Angiogenesis plays a pivotal role in colorectal cancer (CRC), yet its underlying mechanisms demand further exploration. This study aimed to elucidate the significance of angiogenesis-related genes (ARGs) in CRC through comprehensive multi-omics analysis. Methods: CRC patients were categorized according to ARGs expression to form angiogenesis-related clusters (ARCs). We investigated the correlation between ARCs and patient survival, clinical features, consensus molecular subtypes (CMS), cancer stem cell (CSC) index, tumor microenvironment (TME), gene mutations, and response to immunotherapy. Utilizing three machine learning algorithms (LASSO, Xgboost, and Decision Tree), we screen key ARGs associated with ARCs, further validated in independent cohorts. A prognostic signature based on key ARGs was developed and analyzed at the scRNA-seq level. Validation of gene expression in external cohorts, clinical tissues, and blood samples was conducted via RT-PCR assay. Results: Two distinct ARC subtypes were identified and were significantly associated with patient survival, clinical features, CMS, CSC index, and TME, but not with gene mutations. Four genes (S100A4, COL3A1, TIMP1, and APP) were identified as key ARCs, capable of distinguishing ARC subtypes. The prognostic signature based on these genes effectively stratified patients into high- or low-risk categories. scRNA-seq analysis showed that these genes were predominantly expressed in immune cells rather than in cancer cells. Validation in two external cohorts and through clinical samples confirmed significant expression differences between CRC and controls. Conclusion: This study identified two ARG subtypes in CRC and highlighted four key genes associated with these subtypes, offering new insights into personalized CRC treatment strategies.
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N-glycosylation is a highly conserved glycan modification that plays crucial roles in various physiological processes, including protein folding, trafficking, and signal transduction. Porcine deltacoronavirus (PDCoV) poses a newly emerging threat to the global porcine industry. The spike protein of PDCoV exhibits a high level of N-glycosylation; however, its role in viral infection remains poorly understood. In this study, we applied a lentivirus-based entry reporter system to investigate the role of N-glycosylation on the viral spike protein during PDCoV entry stage. Our findings demonstrate that N-glycosylation at positions 652 and 661 of the viral spike protein significantly reduces the infectivity of PDCoV pseudotyped virus. Overall, our results unveil a novel function of N-glycosylation in PDCoV infection, highlighting its potential for facilitating the development of antiviral strategies.
RESUMO
In China, porcine reproductive and respiratory syndrome virus (PRRSV) vaccines are widely used. These vaccines, which contain inactivated and live attenuated vaccines (LAVs), are produced by MARC-145 cells derived from the monkey kidney cell line. However, some PRRSV strains in MARC-145 cells have a low yield. Here, we used two type 2 PRRSV strains (CH-1R and HuN4) to identify the genes responsible for virus yield in MARC-145 cells. Our findings indicate that the two viruses have different spread patterns, which ultimately determine their yield. By replacing the viral envelope genes with a reverse genetics system, we discovered that the minor envelope proteins, from GP2a to GP4, play a crucial role in determining the spread pattern and yield of type 2 PRRSV in MARC-145 cells. The cell-free transmission pattern of type 2 PRRSV appears to be more efficient than the cell-to-cell transmission pattern. Overall, these findings suggest that GP2a to GP4 contributes to the spread pattern and yield of type 2 PRRSV.