Abstract
Accumulating evidence suggests that hypoxia microenvironment and long non-coding lncRNAs (lncRNAs) exert critical roles in tumor development. Herein, we aim to develop a hypoxia-related lncRNA (HRL) model to predict the survival outcomes of patient with lower-grade glioma (LGG). The RNA-sequencing data of 505 LGG samples were acquired from The Cancer Genome Atlas (TCGA). Using consensus clustering based on the expression of hypoxia-related mRNAs, these samples were divided into three subsets that exhibit distinct hypoxia content, clinicopathologic features, and survival status. The differentially expressed lncRNAs across the subgroups were documented as candidate HRLs. With LASSO regression analysis, eight informative lncRNAs were selected for constructing the prognostic HRL model. This signature had a good performance in predicting LGG patients’ overall survival in the TCGA cohort, and similar results could be achieved in two validation cohorts from the Chinese Glioma Genome Atlas. The HRL model also showed correlations with important clinicopathologic characteristics such as patients’ age, tumor grade, IDH mutation, 1p/19q codeletion, MGMT methylation, and tumor progression risk. Functional enrichment analysis indicated that the HLR signature was mainly involved in regulation of inflammatory response, complement, hypoxia, Kras signaling, and apical junction. More importantly, the signature was related to immune cell infiltration, estimated immune score, tumor mutation burden, neoantigen load, and expressions of immune checkpoints and immunosuppressive cytokines. Finally, a nomogram was developed by integrating the HRL signature and clinicopathologic features, with a concordance index of 0.852 to estimate the survival probability of LGG patients. In conclusion, our study established an effective HRL model for prognosis assessment of LGG patients, which may provide insights for future research and facilitate the designing of individualized treatment.
Highlights
Lower-grade glioma (LGG), defined as World Health Organization (WHO) grade II/III gliomas, is a prevalent and aggressive type of primary intracranial tumors in adults [1]
Since the hypoxialncRNA interactions have attracted much attention in cancer research [31], we further illustrated whether a hypoxia-related long noncoding RNAs (lncRNAs) (HRL)-based model could effectively predict the prognosis of lowergrade glioma (LGG) patients
LGG is less aggressive than glioblastoma, increasing studies have demonstrated that it has a propensity towards progressing to higher grades, resulting in adverse outcomes [32]
Summary
Lower-grade glioma (LGG), defined as World Health Organization (WHO) grade II/III gliomas, is a prevalent and aggressive type of primary intracranial tumors in adults [1]. Despite the advances in neurosurgical resection and adjunctive therapy, a majority of LGG patients still undergo tumor recurrence and progression to glioblastoma (WHO grade IV), resulting in deteriorations in quality. Hypoxia-Related lncRNAs in LGG of life and survival outcomes [2, 3]. This prognostic heterogeneity highlights the importance of molecular classification in the clinical management of LGG patients. In the era of precision medicine, these widely accepted factors are unlikely to provide sufficient insights for individual risk assessment of patients with LGG. It is necessary to uncover novel biomarkers with excellent performance in predicting the prognosis and optimizing the treatment of LGG patients
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
