Identification and characterization of the V3 promoter of the ST3GAL4 gene

Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways

BACKGROUND

Metabolic remodeling and changes in tumor immune microenvironment (TIME) in osteosarcoma are important factors affecting prognosis and treatment. However, the relationship between metabolism and TIME needs to be further explored.

METHODS

RNA-Seq data and clinical information of 84 patients with osteosarcoma from the TARGET database and an independent cohort from the GEO database were included in this study. The activity of seven metabolic super-pathways and immune infiltration levels were inferred in osteosarcoma patients. Metabolism-related genes (MRGs) were identified and different metabolic clusters and MRG-related gene clusters were identified using unsupervised clustering. Then the TIME differences between the different clusters were compared. In addition, an MRGs-based risk model was constructed and the role of a key risk gene, ST3GAL4, in osteosarcoma cells was explored using molecular biological experiments.

RESULTS

This study revealed four key metabolic pathways in osteosarcoma, with vitamin and cofactor metabolism being the most relevant to prognosis and to TIME. Two metabolic pathway-related clusters (C1 and C2) were identified, with some differences in immune activating cell infiltration between the two clusters, and C2 was more likely to respond to two chemotherapeutic agents than C1. Three MRG-related gene clusters (GC1-3) were also identified, with significant differences in prognosis among the three clusters. GC2 and GC3 had higher immune cell infiltration than GC1. GC3 is most likely to respond to immune checkpoint blockade and to three commonly used clinical drugs. A metabolism-related risk model was developed and validated. The risk model has strong prognostic predictive power and the low-risk group has a higher level of immune infiltration than the high-risk group. Knockdown of ST3GAL4 significantly inhibited proliferation, migration, invasion and glycolysis of osteosarcoma cells and inhibited the M2 polarization of macrophages.

CONCLUSION

The metabolism of vitamins and cofactors is an important prognostic regulator of TIME in osteosarcoma, MRG-related gene clusters can well reflect changes in osteosarcoma TIME and predict chemotherapy and immunotherapy response. The metabolism-related risk model may serve as a useful prognostic predictor. ST3GAL4 plays a critical role in the progression, glycolysis, and TIME of osteosarcoma cells.

The role of sialyltransferases in gynecological malignant tumors

Sialylation is the addition of sialic acids to the terminus of various glycoconjugates, and it is involved in many essential biological processes, such as cell adhesion, signal transduction, immune regulation, etc. The levels of sialylation in a cell are tightly regulated by two groups of enzymes, sialyltransferases (STs, responsible for sialylation) and sialidases (responsible for desialylation). Many studies have reported that the occurrence, development, and survival rates of tumors are significantly associated with STs' abnormal changes. In recent years, the morbidity and mortality rates of gynecological malignant tumors have been continuously rising, which has caused great harm to women's reproduction and health. Abnormal changes of STs in gynecological malignant tumor cell membranes cause the changes of expression of sialic acids, promoting cell migration and, eventually, leading to tumor metastasis. In this review, we outlined the biological characteristics of STs and summarized the expression profiles of 20 STs in different tumors via transcriptome data from Gene Expression Profiling Interactive Analysis (GEPIA) database. Moreover, STs' functions in four common gynecological tumors (ovarian cancer, cervical cancer, endometrial cancer, and gestational trophoblast tumor) were reviewed.