Open AccessPrediction of Survival Outcome in Lower-Grade Glioma Using a Prognostic Signature with 33 Immune-Related Gene Pairs
Author(s) -
Shaohua Chen,
Yongchu Sun,
Xiaodong Zhu,
Zengnan Mo
Publication year - 2021
Publication title -
international journal of general medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.722
H-Index - 36
ISSN - 1178-7074
DOI - 10.2147/ijgm.s338135
Subject(s) - medicine , proportional hazards model , glioma , oncology , immune system , gene signature , lasso (programming language) , univariate , survival analysis , gene , bioinformatics , multivariate statistics , immunology , gene expression , cancer research , biology , genetics , machine learning , world wide web , computer science
Lower-grade glioma (LGG) is one of the prevalent malignancies threatening human health, with considerable intrinsic heterogeneities in their biological behavior. Previous studies have revealed that the immune component is a key factor influencing the formation and development of malignancies. In this study, we aim to use a novel approach to develop a prognostic signature of immune-related gene pairs (IRGPs) to determine the survival outcome of patients with LGG.