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Osteosarcoma is a kind of primary malignant tumor of bone. In recent years, its therapeutic effect and prognostic survival are dissatisfactory. The tumor immune microenvironment (TIME) reflects immune status of patients, but it is little known in osteosarcoma. Therefore, this study attempts to conduct a comprehensive analysis to explore TIME of osteosarcoma and identify TIME-related subtypes for clinical management and treatment. We successfully established two novel tumor immune infiltration clusters (TIIC) which are characterized by difference of microenvironment and immune-related biological processes. High tumor immune infiltration cluster (H-TIIC) subtypes with higher immune infiltration score shows a better overall survival. Further, the two immune subtypes are shown to differ in immunotherapy and chemotherapy. The results would be helpful for clinical decision in osteosarcoma. [ABSTRACT FROM AUTHOR]

Due to the complex function of the Notch signal pathway in gastric cancer (GC), the association between Notch homolog 1 (Notch1) intracellular domain (NICD) and differentiation of GC remains unknown. The present study aimed to investigate the potential association between NICD and GC differentiation, and demonstrated that poorly differentiated GC expressed increased NICD levels compared with well differentiated GC. A γ-secretase inhibitor inhibited the growth of AGS cells through downregulating NICD level. Additional data suggested that a COX-2 inhibitor caused a marked reduction of NICD level in comparison with a control group treated with dimethyl sulfoxide. Combined administration of γ-secretase and COX-2 inhibitor produced a marked inhibition of growth in AGS cells, which suggests that patients with poorly differentiated GC may benefit from the blockage of NICD, which potentially serves a role in GC differentiation. [ABSTRACT FROM AUTHOR]

• A group of immune-related glycosylation genes were identified for osteosarcoma; • A novel classification was put forward for predicting prognosis and guiding treatment in osteosarcoma; • A novel risk score model and nomogram was constructed for predicting prognosis of osteosarcoma. Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type's preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs' risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma. [ABSTRACT FROM AUTHOR]