Literature DB >> 31853837

Identification and validation of a 21-mRNA prognostic signature in diffuse lower-grade gliomas.

Lai-Rong Song1,2,3,4, Jian-Cong Weng1,2,3,4, Xu-Lei Huo1,2,3,4, Liang Wang1,2,3,4, Huan Li1,3,4, Da Li5,6,7,8, Zhen Wu9,10,11,12, Jun-Ting Zhang13,14,15,16.   

Abstract

PURPOSE: Diffuse low-grade and intermediate-grade gliomas, also known as lower-grade gliomas (LGGs), are a class of central nervous system tumors. Overall survival varies greatly between patients, highlighting the importance of evaluating exact outcomes to facilitate individualized clinical management. We aimed to identify an mRNA-based prognostic signature to predict the survival of patients with LGGs.
METHODS: A total of 874 LGGs from two public datasets were included. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select the most prognostic mRNAs and build a risk score. A nomogram incorporating the risk score and clinical factors was established for individualized survival prediction. The performance of the nomogram was assessed in the training set (329 patients), internal validation set (140 patients), and external validation set (405 patients).
RESULTS: 21 most prognostic mRNAs remained following the LASSO Cox regression. The 21-mRNA signature successfully stratified patients into high- and low-risk groups (P < 0.001 for all datasets in Kaplan-Meier analysis). Subsequent gene set enrichment analysis identified 19 essential biological processes in high-risk LGGs. Furthermore, a nomogram incorporating the risk score, age, grade, and 1p/19q status was developed with favorable calibration and high predictive accuracy in the training set and validation sets (C-index: 0.877, 0.878, and 0.812, respectively).
CONCLUSION: The 21-mRNA signature has reliable prognostic value for LGGs and might facilitate the effective stratification and individualized management of patients.

Entities:  

Keywords:  Biomarkers; LASSO cox regression; Lower-grade gliomas; Prognosis; mRNA signature

Mesh:

Substances:

Year:  2019        PMID: 31853837     DOI: 10.1007/s11060-019-03372-z

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


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