Temozolomide (TMZ) has been used as a first-line therapy against low-grade gliomas (LGGs) combined with other chemotherapy drugs. However, there has been no reliable index predicting TMZ response of patients with LGGs. In this study, we aim to investigate the relationship between gene expressions and the prognosis of TMZ therapy in LGGs. We integrated transcriptome and clinical data of 171 LGGs from the Chinese Glioma Genome Atlas (CGGA). Consensus LASSO Cox regression was used to identify 14 key genes related to different clinical outcomes under TMZ chemotherapy. We constructed and evaluated a risk score based on the 14 genes. Patients with LGGs of lower risk scores (low-risk group) generally had better survival than those LGGs of higher risk scores (high-risk group), which is independent of clinicopathological factors. High-risk patients showed activation of innate and humoral-type immunity. The prognostic contribution of the risk score was validated in an independent validation cohort of 65 patients. Besides, combined with three independent predictors (grade, IDH1 mutation status, and chr1p19q co-deletion status), we further developed a nomogram to predict the benefit from TMZ treatment in LGGs. Our results indicate that transcriptome-based index can optimize the treatment strategy for patients with LGGs under TMZ therapy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.