Constructing a Model Using Clock-Related lncRNAs for Predicting the Tumor Microenvironment of Gliomas.

Abstract

Purpose: Circadian locomotor output cycles kaput (CLOCK) and its related genes play important roles in cellular functions. This study aims to construct a predictive model for CLOCK-related genes and identify lncRNAs that may influence Tumor Microenvironment of Glioma.

Method: We included bulk RNA-sequencing data and clinical information for glioma samples from the TCGA and CGGA databases. Univariate Cox and LASSO-Cox analyses were used to screen CLOCK-related genes. Consensus clustering was applied to classify glioma samples, followed by differential gene expression analysis. CLOCK-related lncRNAs were identified through correlation analyses, hub lncRNAs were selected using LASSO-Cox, and their expression was validated by qPCR in cultured glioma cell lines.

Finding: We identified nine CLOCK-related genes, and unsupervised clustering based on these genes divided glioma samples into three clusters. Enrichment analysis revealed that genes differentially expressed between the high CLOCK-related cluster and other clusters were enriched in immune-related molecular functions. Co-expression analysis detected 102 potentially correlated lncRNAs. We constructed a CLOCK-related lncRNA risk score based on 31 of these lncRNAs. Subsequent multivariable Cox analysis identified 9 hub lncRNAs, and accuracy testing demonstrated the model's good performance. Immune infiltration analysis showed higher stromal, immune, and ESTIMATE scores in the high CLOCK-related lncRNA score group.

Conclusion: CLOCK-related RNAs and lncRNAs play distinct roles within the glioma microenvironment. These findings offer new insights into the challenges that need to be addressed when using immunotherapeutic approaches to treat gliomas.