Dataset Information

Identification of a NFKBIA polymorphism associated with lower NFKBIA protein levels and poor survival outcomes in patients with glioblastoma multiforme.

ABSTRACT: The aberrant constitutive activation of nuclear factor-?B (NF-?B) has been observed in glioblastomas, while NF-?B inhibitor alpha (NFKBIA) inhibits the NF-?B signaling pathway under several physiological processes. However, the contribution of NFKBIA to glioblastomas is poorly understood. In the present study, using gene sequencing, we identified rs1957106 as a novel single nucleotide polymorphism (SNP) in NFKBIA in glioblastoma and found that it was more frequently present in glioblastoma patients. In addition, we examined the association between different genotypes of the rs1957106 SNP of NFKBIA and the gene copy number, mRNA level and protein expression of NFKBIA. The SNP rs1957106 CT and TT genotypes were found to be associated with lower NFKBIA protein levels and a poor prognosis of pateints with glioblastoma. Hence, by identifying rs1957106 as a novel SNP in NFKBIA in glioblastoma patients, we provide a new platform for further investigating the function of NFKBIA in the pathobiology of glioblastoma.

SUBMITTER: Zhao Z

PROVIDER: S-EPMC4199416 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Identification of a NFKBIA polymorphism associated with lower NFKBIA protein levels and poor survival outcomes in patients with glioblastoma multiforme.

Zhao Zhaohui Z Zhong Xingming X Wu Tinfeng T Yang Tianquan T Chen Guilin G Xie Xueshun X Wei Yongxin Y Ye Ming M Zhou Youxin Y Du Ziwei Z

International journal of molecular medicine 20140912 5

The aberrant constitutive activation of nuclear factor-κB (NF-κB) has been observed in glioblastomas, while NF-κB inhibitor alpha (NFKBIA) inhibits the NF-κB signaling pathway under several physiological processes. However, the contribution of NFKBIA to glioblastomas is poorly understood. In the present study, using gene sequencing, we identified rs1957106 as a novel single nucleotide polymorphism (SNP) in NFKBIA in glioblastoma and found that it was more frequently present in glioblastoma patie ...[more]

PMID: 25215581

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Project description:PurposeHOXD10 is a tumor modulator that can either be a tumor-suppressor or a tumor-promoting gene. However, the role of HOXD10 in glioblastoma multiforme (GBM) remains unclear.MethodsImmunohistochemistry (IHC) was applied to detect protein expression of HOXD10 in GBM and normal brain tissue patients. Clinicopathological characteristics with GBM were recorded, and a Kaplan-Meier curve was plotted. Additionally, the mRNA expression of HOXD10 and its effect on prognosis were analyzed using the online tool GEPIA and the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and the Gene Expression Omnibus (GEO) databases. Based on the mRNA expression of HOXD10, GBM patients from TCGA database were divided into low- and high-HOXD10 expression groups to analyze the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and construct a lncRNA-miRNA-mRNA network and a protein-protein interaction (PPI) network.ResultsThe mRNA expression of HOXD10 was up-regulated in GBM according to GEPIA, while the protein expression of HOXD10 in GBM was down-regulated according to IHC analysis of samples from patients collected from our hospital. Correlation analysis showed that HOXD10 expression was significantly related to IDH1 status. Univariate analysis revealed that low HOXD10 expression, complete surgical resection, postoperative radiotherapy, postoperative temozolomide chemotherapy and IDH1 mutation were all beneficial prognostic factors. Further multivariate analysis revealed that only complete surgical resection and postoperative radiotherapy were independent prognostic factors. GO and KEGG enrichment analyses indicated that HOXD10 expression is mainly involved in cytokine-cytokine receptor interactions. In the ceRNA network, 89 nodes, containing 45 mRNAs, 39 miRNAs and five lncRNAs associated with prognosis were involved. The PPI network revealed a tight interaction between HOXD10 and HOXD8, HOXD9, HOXD11, HOXD13 and HOXB3.ConclusionBased on our experimental data, although HOXD10 expression is low in GBM compared with normal brain tissue, GBM patients with high HOXD10 expression have a worse prognosis. HOXD10 may play different or even opposite roles in different stages of GBM occurrence and development. For patients with GBM, HOXD10 may be a valid predictor of prognosis.

Project description:BACKGROUND:Alternative exon usage (AEU) is an important component of gene regulation. Exon expression platforms allow the detection of associations between AEU and phenotypes such as cancer. Numerous studies have identified associations between gene expression and the brain cancer glioblastoma multiforme (GBM). The few consistent gene expression biomarkers of GBM that have been reported may be due to the limited consideration of AEU and the analytical approaches used. The objectives of this study were to develop a model that accounts for the variations in expression present between the exons within a gene and to identify AEU biomarkers of GBM survival. METHODS:The expression of exons corresponding to 25,403 genes was related to the survival of 250 individuals diagnosed with GBM in a training data set. Genes exhibiting AEU in the training data set were confirmed in an independent validation data set of 78 patients. A hierarchical mixed model that allows the consideration of covariation between exons within a gene and of the effect of the epidemiological characteristics of the patients was developed to identify associations between exon expression and patient survival. This general model describes all three possible scenarios: multi-exon genes with and without AEU, and single-exon genes. RESULTS:AEU associated with GBM survival was identified on 2477 genes (P-value < 5.0E-04 or FDR-adjusted P-value < 0.05). G-protein coupled receptor 98 (Gpr98) and epidermal growth factor (Egf) were among the genes exhibiting AEU with 30 and 9 exons associated with GBM survival, respectively. Pathways enriched among the AEU genes included focal adhesion, ECM-receptor interaction, ABC transporters and pathways in cancer. In addition, 24 multi-exon genes without AEU and 8 single-exon genes were associated with GBM survival (FDR-adjusted P-value < 0.05). CONCLUSIONS:The inferred patterns of AEU were consistent with in silico AS models. The hierarchical model used offered a flexible and simple way to interpret and identify associations between survival that accommodates multi-exon genes with or without AEU and single exon genes. Our results indicate that differential expression of AEU could be used as biomarker for GBM and potentially other cancers.

Project description:BACKGROUND:Glioblastoma multiform (GBM) is a devastating brain tumor with maximum surgical resection, radiotherapy plus concomitant and adjuvant temozolomide (TMZ) as the standard treatment. Diverse clinicopathological and molecular features are major obstacles to accurate predict survival and evaluate the efficacy of chemotherapy or radiotherapy. Reliable prognostic biomarkers are urgently needed for postoperative GBM patients. METHODS:The protein coding genes (PCGs) and long non-coding RNA (lncRNA) gene expression profiles of 233 GBM postoperative patients were obtained from The Cancer Genome Atlas (TCGA), TANRIC and Gene Expression Omnibus (GEO) database. We randomly divided the TCGA set into a training (n = 76) and a test set (n = 77) and used GSE7696 (n = 80) as an independent validation set. Survival analysis and the random survival forest algorithm were performed to screen survival associated signature. RESULTS:Six PCGs (EIF2AK3, EPRS, GALE, GUCY2C, MTHFD2, RNF212) and five lncRNAs (CTD-2140B24.6, LINC02015, AC068888.1, CERNA1, LINC00618) were screened out by a risk score model and formed a PCG-lncRNA signature for its predictive power was strongest (AUC = 0.78 in the training dataset). The PCG-lncRNA signature could divide patients into high- risk or low-risk group with significantly different survival (median 7.47 vs. 18.27 months, log-rank test P < 0.001) in the training dataset. Similar result was observed in the test dataset (median 11.40 vs. 16.80 months, log-rank test P = 0.001) and the independent set (median 8.93 vs. 16.22 months, log-rank test P = 0.007). Multivariable Cox regression analysis verified that it was an independent prognostic factor for the postsurgical patients with GBM. Compared with IDH mutation status, O-(6)-methylguanine DNA methyltransferase promoter methylation status and age, the signature was proved to have a superior predictive power. And stratified analysis found that the signature could further separated postoperative GBM patients who received TMZ-chemoradiation into high- and low-risk groups in TCGA and GEO dataset. CONCLUSIONS:The PCG-lncRNA signature was a novel prognostic marker to predict survival and TMZ-chemoradiation response in GBM patients after surgery.

Dataset Information

Identification of a NFKBIA polymorphism associated with lower NFKBIA protein levels and poor survival outcomes in patients with glioblastoma multiforme.

Publications

Identification of a NFKBIA polymorphism associated with lower NFKBIA protein levels and poor survival outcomes in patients with glioblastoma multiforme.

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