Multi-Omics Analysis Based on Genomic Instability for Prognostic Prediction in Lower-Grade Glioma

作者：Yudong Cao, Hecheng Zhu, Weidong Liu, Lei Wang, Wen Yin, Jun Tan, Quanwei Zhou, Zhaoqi Xin, Hailong Huang, Dongcheng Xie, Ming Zhao, Xingjun Jiang, Jiahui Peng, Caiping Ren · 发表于：Frontiers in Genetics · 年份：2022 · DOI：10.3389/fgene.2021.758596 · 被引用次数：13 · 研究领域：Cancer-related molecular mechanisms research、RNA modifications and cancer、Circular RNAs in diseases

Background: Lower-grade gliomas (LGGs) are a heterogeneous set of gliomas. One of the primary sources of glioma heterogeneity is genomic instability, a novel characteristic of cancer. It has been reported that long noncoding RNAs (lncRNAs) play an essential role in regulating genomic stability. However, the potential relationship between genomic instability and lncRNA in LGGs and its prognostic value is unclear. Methods: In this study, the LGG samples from The Cancer Genome Atlas (TCGA) were divided into two clusters by integrating the lncRNA expression profile and somatic mutation data using hierarchical clustering. Then, with the differentially expressed lncRNAs between these two clusters, we identified genomic instability-related lncRNAs (GInLncRNAs) in the LGG samples and analyzed their potential function and pathway by co-expression network. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were conducted to establish a GInLncRNA prognostic signature (GInLncSig), which was assessed by internal and external verification, correlation analysis with somatic mutation, independent prognostic analysis, clinical stratification analysis, and model comparisons. We also established a nomogram to predict the prognosis more accurately. Finally, we performed multi-omics-based analyses to explore the relationship between risk scores and multi-omics data, including immune characteristics, N 6 -methyladenosine (m 6 A), stemness index, drug sensitivity, a...