Integrative Analysis of a Novel Eleven-Small Nucleolar RNA Prognostic Signature in Patients With Lower Grade Glioma

Abstract

ObjectiveThe present study used the RNA sequencing (RNA-seq) dataset to identify prognostic snoRNAs and construct a prognostic signature of The Cancer Genome Atla (TCGA) lower grade glioma (LGG) cohort, and comprehensive analysis of this signature.MethodsRNA-seq dataset of 488 patients from TCGA LGG cohort were included in this study. Comprehensive analysis including function enrichment, gene set enrichment analysis (GSEA), immune infiltration, cancer immune microenvironment, and connectivity map (CMap) were used to evaluate the snoRNAs prognostic signature.ResultsWe identified 21 LGG prognostic snoRNAs and constructed a novel eleven-snoRNA prognostic signature for LGG patients. Survival analysis suggests that this signature is an independent prognostic risk factor for LGG, and the prognosis of LGG patients with a high-risk phenotype is poor (adjusted P = 0.003, adjusted hazard ratio = 2.076, 95% confidence interval = 1.290–3.340). GSEA and functional enrichment analysis suggest that this signature may be involved in the following biological processes and signaling pathways: such as cell cycle, Wnt, mitogen-activated protein kinase, janus kinase/signal transducer and activator of tran-ions, T cell receptor, nuclear factor-kappa B signaling pathway. CMap analysis screened out ten targeted therapy drugs for this signature: 15-delta prostaglandin J2, MG-262, vorinostat, 5155877, puromycin, anisomycin, withaferin A, ciclopirox, chloropyrazine and megestrol. We also found that high- and low-risk score phenotypes of LGG patients have significant differences in immune infiltration and cancer immune microenvironment.ConclusionsThe present study identified a novel eleven-snoRNA prognostic signature of LGG and performed a integrative analysis of its molecular mechanisms and relationship with tumor immunity.

Identification of ferroptosis-related genes as potential diagnostic biomarkers for diabetic nephropathy based on bioinformatics

“…Multiple studies have found that ferroptosis plays a crucial role in various diseases ( Li et al, 2020 ; Jiang et al, 2021 ). Recently, bioinformatics analysis has been playing a crucial role in disease studies and facilitates the understanding of cellular and molecular mechanisms behind the progression of disease ( Deng et al, 2021 ; Kazeminasab et al, 2021 ). The present study performed bioinformatics to analyze the diabetes data sets from GEO database to confirm the key diabetes-causing genes and determine their significance in diabetes prognosis.…”

“…frontiersin.org mechanisms behind the progression of disease (Deng et al, 2021;Kazeminasab et al, 2021). The present study performed bioinformatics to analyze the diabetes data sets from GEO database to confirm the key diabetes-causing genes and determine their significance in diabetes prognosis.…”

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

“…Recently, with the considerable progress of cutting-edge highthroughput sequencing technologies and the growing improvement of public databases, two authoritative databases, the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), have collected considerable clinical, pathological, and biological data of cancer patients (6,7). Researchers can use these data and a variety of bioinformatics analysis methods to screen and predict new diagnostic and prognostic markers for various cancers.…”