Predictive Significance of Glycosyltransferase-Related lncRNAs in Endometrial Cancer: A Comprehensive Analysis and Experimental Validation

Glycosylation is
a crucial post-translational modification
that
regulates cellular functions and the surrounding microenvironment.
The abnormal expression of glycosyltransferases, essential enzymes
in this process, has been linked to tumor development. In addition,
long noncoding RNAs (lncRNAs) have been shown to exert a multifaceted
regulatory influence on gene expression. Nevertheless, research on
glycosyltransferase-related lncRNAs (GTRLs) in endometrial cancer
(EC) is still unclear. In this study, we constructed a novel prognostic
model based on GTRLs using univariate Cox regression, Lasso, and multivariate
stepwise Cox regression analysis. Our findings identified four GTRLs
that were significantly associated with the prognosis of EC patients.
The Kaplan–Meier (KM) survival analysis revealed a notable
reduction in overall survival (OS) among high-risk populations. Furthermore,
independent prognostic assessments, receiver operating characteristic
(ROC) curves and nomograms, demonstrated that risk scores derived
from these GTRLs outperformed other clinical variables within the
TCGA-UCEC clinical data set in predicting patient prognosis. And the
low-risk cohort exhibited increased immune infiltration and decreased
tumor purity. Additionally, significant differences in tumor mutation
profiles were observed, with the tumor mutation burden (TMB) being
higher in the low-risk cohort, suggesting a potentially better response
to immunotherapy. Different patient subgroups also displayed varying
sensitivities to several chemotherapeutic agents. Finally, the model’s
validity was confirmed through clinical specimens and in vitro experiments,
which demonstrated that AC090617.5 and AP001107.9 can influence the
proliferation, migratory functions, and cisplatin sensitivity of EC.
Therefore, the prognostic features can effectively predict the prognosis
of EC and guide therapeutic decision-making.