Dataset Information

In silico identification of the prognostic biomarkers and therapeutic targets associated with cancer stem cell characteristics of glioma.

ABSTRACT: Glioma is the common histological subtype of malignancy in central nervous system, with a high morbidity and mortality. Cancer stem cells (CSCs) play an important role in regulating the tumorigenesis and progression of glioma; however, the prognostic biomarkers and therapeutic targets associated with CSC characteristics have not been fully acknowledged in glioma. In order to identify the prognostic stemness-related genes (SRGs) of glioma in silico, the RNA sequencing data of patients with glioma were retrieved from The Cancer Genome Atlas (TCGA) databases. The mRNA expression-based stemness index (mRNAsi) was significantly associated with the glioma histologic grade, isocitrate dehydrogenase 1 (IDH1) mutation and overall survival of glioma patients by the nonparametric test and Kaplan-Meier survival analysis. A total of 340 SRGs were identified as the overlapped stemness-related differential expressed genes (DEGs) of different histologic grade screened by the univariate Cox analysis. Based on 11 prognostic SRGs, the predict nomogram was constructed with the AUC of 0.832. Moreover, the risk score of the nomogram was an independent prognostic factor, indicating its significant applicability. Besides other eight reported biomarkers of glioma, we found that F2RL2, CLCNKA and LOXL4 were first identified as prognostic biomarkers for glioma. In conclusion, this bioinformatics study demonstrates the mRNAsi as a reliable index for the IDH1 mutation, histologic grade and OS of glioma patients and provides a well-applied model for predicting the OS for patients with glioma based on prognostic SRGs. Additionally, this in silico study also identifies three novel prognostic biomarkers (F2RL2, CLCNKA and LOXL4) for glioma patients.

SUBMITTER: Lvu W

PROVIDER: S-EPMC7418212 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

In silico identification of the prognostic biomarkers and therapeutic targets associated with cancer stem cell characteristics of glioma.

Lvu Wen W Fei Xu X Chen Cheng C Zhang Bo B

Bioscience reports 20200801 8

Glioma is the common histological subtype of malignancy in central nervous system, with a high morbidity and mortality. Cancer stem cells (CSCs) play an important role in regulating the tumorigenesis and progression of glioma; however, the prognostic biomarkers and therapeutic targets associated with CSC characteristics have not been fully acknowledged in glioma. In order to identify the prognostic stemness-related genes (SRGs) of glioma in silico, the RNA sequencing data of patients with glioma ...[more]

PMID: 32725165

Similar Datasets

Project description:Background: Gastric cancer (GC) is one of the most common and poor prognosis malignancy in the world. The Family with sequence similarity 83 (FAM83) comprises of eight members of A-H. Accumulating evidence confirmed important roles for FAM83 family in tumorigenesis and progression. However, the prognostic values of FAM83 family in GC still have not been clarified. Methods: ONCOMINE, UALCAN, GEPIA, THE HUMAN PROTEIN ATLAS, Kaplan-Meier Plotter, cBioPortal, DAVID, STRING and TIMER databases and R software were adopted in this study. Results: In this study, we demonstrated that the mRNA levels of FAM83 B/C/D/H were significantly up-regulated in stomach adenocarcinoma (STAD), but the protein level of FAM83G/H were remarkable lowly in STAD. Next, FAM83C/D/G/H were significantly associated with tumor stages in STAD patients. Then, the mutation rate of FAM83 family members in STAD patients was 46%, and the highest mutation rate was FAM83H (23%). Furthermore, the functions of FAM83 family and their 259 co-expression genes were primarily related to Shigellosis, RNA degradation and Ribosome biogenesis in eukaryotes pathway. Besides, we have established the prognostic model of FAM83 family in STAD, including the prognostic model of STAD patients (FAM83C/D/G), STAD with lymph node metastasis (FAM83C/D/G/H) and STAD with ERBB2 high expression (FAM83G/H). FAM83C/D high expression with a poor prognosis, while FAM83G/H high expression with a favorable prognosis of STAD. Additionally, we found that the expression of FAM83C/D/G/H were significantly correlated with the infiltration of six types of immune cells [B cells, CD8+T cells, CD4+T cells, macrophages and Myeloid dendritic cells (DC)], whereas CD4+T cells and Macrophage cells have higher risk scores (HR > 1) when FAM83C lowly expression and FAM83D highly expression. The risk score of NK cells was significantly reduced when FAM83G lowly expression and FAM83H highly expression (HR < 1). Conclusion: These findings suggested that FAM83C/D/G/H might play key roles in STAD tumorigenesis and progression, and FAM83C/D might be risk factors but FAM83G/H might be favorable prognostic factors for STAD patients. In addition, CD4+T cells and Macrophage cells may be the promoters of FAM83D in progression of STAD, while NK cells may promote the protective effect of FAM83H on STAD patients.

Dataset Information

In silico identification of the prognostic biomarkers and therapeutic targets associated with cancer stem cell characteristics of glioma.

Publications

In silico identification of the prognostic biomarkers and therapeutic targets associated with cancer stem cell characteristics of glioma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure