Abstract
Enhancer RNAs (eRNAs) are present specifically in tumors, where they affect the expression of eRNA-regulated genes (ERGs). Owing to this characteristic, ERGs were hypothesized to improve prognosis of overall survival in heterogeneous low-grade and intermediate-grade gliomas. This study aimed to construct and validate an ERG prognostic tool to facilitate clinical management, and offer more effective diagnostic and therapeutic biomarkers for glioma. Survival-related eRNAs were identified, and their ERGs were selected based on eRNA and target gene information. The ERG prognostic model was constructed and validated using internal and external validation cohorts. Finally, biological differences related to the ERG signature were analysed to explore the potential mechanisms influencing survival outcomes. Thirteen ERGs were identified and used to build an ERG risk signature, which included five super-enhancer RNA (seRNA)-regulated genes and five LGG-specific eRNA-regulated genes. The prognostic nomogram established based on combining the ERG score, age, and sex was evaluated by calibration curves, clinical utility, Harrell’s concordance index (0.86; 95% CI: 0.83-0.90), and time-dependent receiver operator characteristic curves. We also explored potential immune-related mechanisms that might cause variation in survival. The established prognostic model displayed high validity and robustness. Several immune-related genes regulated by seRNAs or specific eRNAs were identified, indicating that these transcripts or their genes were potential targets for improving immunotherapeutic/therapeutic outcomes. The functions of an important specific eRNA-regulated gene (USP28) were validated in robust vitro experiments. In addition, the ERG risk signature was significantly associated with the immune microenvironment and other immune-related features.
Highlights
Gliomas, derived from glial cells or glial precursor cells, are the most common lethal primary tumors of the central nervous system [1]
Gene expression and clinical data, Enhancer RNAs (eRNAs) expression data, immune infiltration data and copy number variation data of 530 lower-grade gliomas (LGGs) patients were collected from the TCGA, enhancer RNA in cancers (eRic), Tumor Immune Estimation Resource (TIMER) and cBioPortal datasets
An effective prognostic model based on specific biomarkers could accurately forecast survival outcomes, allowing efficient management of patients with LGGs
Summary
Gliomas, derived from glial cells or glial precursor cells, are the most common lethal primary tumors of the central nervous system [1]. The first two types, known as lower-grade gliomas (LGGs), account for approximately 43.2% of all gliomas and are relatively slow-growing but prone to recurrence [1, 2]. They have greater therapeutic and public health value than high-grade gliomas, which lead to worse outcomes and a median overall survival (OS) of < 14.4 months [3]. To improve the effectiveness of treatment and postoperative management, OS predictions should be more accurate; this depends on the availability of precise biomarkers and prognostic tools. To predict outcomes and improve treatment quality, more sensitive and specific biomarkers are required
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