Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma

Abstract

Glioma is well known as the most aggressive and prevalent primary malignant tumor in the central nervous system. Molecular subtypes and prognosis biomarkers remain a promising research area of gliomas. Notably, the aberrant expression of mesenchymal (MES) subtype related long non-coding RNAs (lncRNAs) is significantly associated with the prognosis of glioma patients. In this study, MES-related genes were obtained from The Cancer Genome Atlas (TCGA) and the Ivy Glioblastoma Atlas Project (Ivy GAP) data sets of glioma, and MES-related lncRNAs were acquired by performing co-expression analysis of these genes. Next, Cox regression analysis was used to establish a prognostic model, that integrated ten MES-related lncRNAs. Glioma patients in TCGA were divided into high-risk and low-risk groups based on the median risk score; compared with the low-risk groups, patients in the high-risk group had shorter survival times. Additionally, we measured the specificity and sensitivity of our model with the ROC curve. Univariate and multivariate Cox analyses showed that the prognostic model was an independent prognostic factor for glioma. To verify the predictive power of these candidate lncRNAs, the corresponding RNA-seq data were downloaded from the Chinese Glioma Genome Atlas (CGGA), and similar results were obtained. Next, we performed the immune cell infiltration profile of patients between two risk groups, and gene set enrichment analysis (GSEA) was performed to detect functional annotation. Finally, the protective factors DGCR10 and HAR1B, and risk factor SNHG18 were selected for functional verification. Knockdown of DGCR10 and HAR1B promoted, whereas knockdown of SNHG18 inhibited the migration and invasion of gliomas. Collectively, we successfully constructed a prognostic model based on a ten MES-related lncRNAs signature, which provides a novel target for predicting the prognosis for glioma patients.

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma

“…In pathologic analysis, we found that HGGs had higher KDELR1 expression than LGGs. In addition, previous studies (35)(36)(37) have demonstrated that mesenchymal-subtype gliomas are associated with poor prognosis, which are confirmed by our finding that mesenchymal -subtype gliomas had a higher expression level of KDELR1 than proneural subtype gliomas. Subsequently, we further explored whether the expression of KDELR1 is related to recurrence.…”

Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

“…Through high-throughput bioinformatics analysis, many studies have shown that AL031985.3 is associated with the prognosis of HCC and can be used to build a predictive model for the prognosis of HCC [42][43][44]. Previous studies have found that SNHG18 is abnormally expressed in glioma tissue specimens, and high expression of SNHG18 in gliomas enhances their radiation resistance [45][46][47].…”

Modification Patterns of DNA Methylation-Related lncRNAs Regulating Genomic Instability for Improving the Clinical Outcomes and Tumour Microenvironment Characterisation of Lower-Grade Gliomas

“…The lncRNA SNHG18 has been identified as a novel prognostic biomarker for tumours in previous studies, and high SNHG18 expression is correlated with a poor prognosis. For example, SNHG18 knockdown suppressed metastasis and invasion of gliomas ( Huang et al, 2021 ). Furthermore, mkl1-induced SNHG18 regulates the metastasis and growth of non-small cell lung cancer by modulating the miR-211-5p/BRD4 pathway ( Fan et al, 2021 ).…”