Chondroitin sulphate synthase 3 () is an important enzyme that regulates glycosylation, but it has not been reported in tumours. This study explored for the first time the oncological features of in stomach adenocarcinoma (STAD). We analysed expression in STAD through the Cancer Genome Atlas (TCGA) database and verified our findings by immunohistochemical staining and Western blot experiments. The prognostic value of in STAD was analysed through the biological aspects of in STAD, such as communal clinical follow-up survival data, methylation sites, tumour immune microenvironment (TIME) and immune cell surface checkpoints. Finally, the immune-evasion potential of in STAD was assessed on the Tumor Immune Dysfunction and Exclusion (TIDE) website and immunohistochemical staining experiment. overexpression in STAD was associated with a poor prognosis based on immunohistochemical staining and Western blot experiments. Multivariate Cox analysis suggested that could be an independent prognostic risk factor. Pathway enrichment and TIME analysis demonstrated that up-regulated mesenchymal activation and immune activation signals in STAD, while TIDE assessment revealed that the risk of immune evasion was significantly higher in the high expression group than in the low expression group. Risk model scores based on -associated immune cell surface checkpoints also presented poor prognosis, and immune evasion was significantly higher in the high-risk group than in the low-risk group. This study analysed from multiple biological perspectives and revealed that can be a biomarker of poor prognosis and mediates the TIME immune-evasion status in STAD.
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http://dx.doi.org/10.3389/fgene.2022.876588 | DOI Listing |
J Extracell Vesicles
December 2024
Department of Orthopedics, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
The development of strategies for the prevention and treatment of aseptic loosening of prostheses stands as a critical area of global research interest. The pyroptosis of local macrophages triggered by wear particles plays a pivotal role in the onset of periprosthetic osteolysis and subsequent loosening. Extracellular vesicles, carrying the surface components and regulatory molecules of their parent cells, embody the cellular characteristics and biological functions of these progenitors.
View Article and Find Full Text PDFImmunology
December 2024
Department of Hepatobiliary Surgery, Municipal Hospital Affiliated to Taizhou University, Taizhou, Zhejiang, China.
This study attempted to identify the relevant pathways involved in autophagy activation of pancreatic cancer and explore the mechanisms underlying immune evasion. Western blot (WB) was used to detect the expression of ITGB4, BNIP3, autophagy-related proteins and MHC-I. Co-immunoprecipitation (Co-IP) was used to verify the binding mode of ITGB4 and BNIP3.
View Article and Find Full Text PDFCancer Med
December 2024
Department of Urology, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Background: Immunotherapy has shown promise for bladder cancer (BC) treatment but is effective only in a subset of patients. Understanding the tumor microenvironment (TME) and its regulators, such as the expression of N6-methyladenosine (m6A) regulators, may improve therapeutic outcomes. This study focuses on the role of IGF2BP2, an m6A reader, in modulating the BC TME.
View Article and Find Full Text PDFJ Immunother
December 2024
Department of Rehabilitation Medicine, The First People's Hospital of Wenling, Wenling, China.
Lung adenocarcinoma (LUAD) is a widespread and deadly form of cancer. Prostaglandin 15-deoxy-Δ-12,14-prostaglandin J2 (15d-PGJ2) possesses antioxidant, anti-inflammatory, and anticancer properties. However, it is unclear whether this effect on LUAD progression stems from its ability to influence macrophage polarization.
View Article and Find Full Text PDFSignal Transduct Target Ther
December 2024
School of Basic Medical Science, Tsinghua University, 30 Shuangqing Rd., Haidian District, Beijing, 100084, China.
Modeling and predicting mutations are critical for COVID-19 and similar pandemic preparedness. However, existing predictive models have yet to integrate the regularity and randomness of viral mutations with minimal data requirements. Here, we develop a non-demanding language model utilizing both regularity and randomness to predict candidate SARS-CoV-2 variants and mutations that might prevail.
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