Dataset Information

Expression of BAG1 is associated with prognosis in kidney renal clear cell carcinoma based on bioinformatics.

ABSTRACT:

Background

BCL2 associated Athano-Gene 1 (BAG1) has been described to be involved in the development and progression of cancer. But the role of BAG1 in kidney renal clear cell carcinoma (KIRC) has remained largely unknown.

Methods

We performed bioinformatic analysis of data from TCGA and GEO dataset. The role of BAG1 in KIRC was explored by Logistic and Cox regression model. The molecular mechanisms of BAG1 was revealed by GSEA.

Results

The current study found that the KIRC tumor samples have a low level of BAG1 mRNA expression compared to the matched normal tissues based on TCGA data and GEO databases. Low expression of BAG1 in KIRC was significantly associated with Sex, clinical pathological stage, tumor-node-metastasis (TNM) stage, hemoglobin levels, cancer status and history of neoadjuvant treatment. Kaplan-Meier survival analysis indicated that KIRC patients with BAG1 high expression have a longer survival time than those with BAG1 low expression (p?ConclusionsThese findings suggested that BAG1 expression may act as a potential favorable prognostic marker and challenging therapeutic target.

SUBMITTER: Wu H

PROVIDER: S-EPMC7881605 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Expression of BAG1 is associated with prognosis in kidney renal clear cell carcinoma based on bioinformatics.

Wu Hongrong H Liu Minjing M He Yuejun Y Meng Guozhao G Guo Wanbei W Guo Qiong Q

BMC cancer 20210213 1

<h4>Background</h4>BCL2 associated Athano-Gene 1 (BAG1) has been described to be involved in the development and progression of cancer. But the role of BAG1 in kidney renal clear cell carcinoma (KIRC) has remained largely unknown.<h4>Methods</h4>We performed bioinformatic analysis of data from TCGA and GEO dataset. The role of BAG1 in KIRC was explored by Logistic and Cox regression model. The molecular mechanisms of BAG1 was revealed by GSEA.<h4>Results</h4>The current study found that the KIRC ...[more]

PMID: 33581726

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Project description:BackgroundKidney renal clear cell carcinoma (KIRC) is the most common pathological subtype of renal cell cancer. APOBEC3 activity has been identified in a variety of human cancers. Although its involvement in cancer has been studied widely, its influence on the tumor immune microenvironment remains poorly understood. Therefore, this study aimed to focus on the effect of APOBEC3 on tumor immune microenvironment of KIRC.MethodsIn this study, we comprehensively analyzed the expression and prognostic significance of the APOBEC3 family in pan-cancer using multiple databases. The functions of key APOBEC3 family members were further investigated in KIRC, with APOBEC3G determined to be a candidate biomarker for unfavorable prognosis. We subsequently explored the correlation of APOBEC3G with the tumor immune environment in KIRC by analyzing the Cancer Genome Atlas (TCGA) dataset, then validated the prognostic significance and PD-L1 correlation of APOBEC3G by using tissue microarrays which included 233 primary tumor samples from patients with renal clear cell carcinoma.ResultsThe APOBEC3 family was overexpressed in KIRC and high APOBEC3 expression predicted poor prognosis. In addition, APOBEC3G was positively correlated with the expression of immunoinhibitors such as TIGIT, LAG3, CD96, PD-1, and CTLA4. In addition, APOBEC3G had a positive correlation with immunosuppressive cells, including regulatory T cell and myeloid-derived suppressor cell. Finally, based on 233 clinical samples, we validated that high expression of APOBEC3G contributed to a poor prognosis for KIRC patients and the positive relationship between APOBEC3G and PD-L1 expression. High APOBEC3G expression was also found to be more common in patients with sarcomatoid histology (P = 0.0026).ConclusionsOur study showed that APOBEC3G was a prognostic biomarker correlated with the immune response in KIRC. In addition, APOBE3G had a positive correlation with PD-L1 expression and sarcomatoid histology, perhaps suggesting the potential impact of APOBEC3G on immunotherapy.

Project description:BackgroundClear cell renal cell carcinoma (ccRCC) represents the most invasive and common adult kidney neoplasm. Mounting evidence suggests that microRNAs (miRNAs) are important regulators of gene expression. But their function in tumourigenesis in this tumour type remains elusive. With the development of high throughput technologies such as microarrays and NGS, aberrant miRNA expression has been widely observed in ccRCC. Systematic and integrative analysis of multiple microRNA expression datasets may reveal potential mechanisms by which microRNAs contribute to ccRCC pathogenesis.MethodsWe collected 5 public microRNA expression datasets in ccRCC versus non-matching normal renal tissues from GEO database and published literatures. We analyzed these data sets with an integrated bioinformatics framework to identify expression signatures. The framework incorporates a novel statistic method for abnormal gene expression detection and an in-house developed predictor to assess the regulatory activity of microRNAs. We then mapped target genes of DE-miRNAs to different databases, such as GO, KEGG, GeneGo etc, for functional enrichment analysis.ResultsUsing this framework we identified a consistent panel of eleven deregulated miRNAs shared by five independent datasets that can distinguish normal kidney tissues from ccRCC. After comparison with 3 RNA-seq based microRNA profiling studies, we found that our data correlated well with the results of next generation sequencing. We also discovered 14 novel molecular pathways that are likely to play a role in the tumourigenesis of ccRCC.ConclusionsThe integrative framework described in this paper greatly improves the inter-dataset consistency of microRNA expression signatures. Consensus expression profile should be identified at pathway or network level to address the heterogeneity of cancer. The DE-miRNA signature and novel pathways identified herein could provide potential biomarkers for ccRCC that await further validation.

Project description:Background: Kidney renal clear cell carcinoma (KIRC) originates from proximal tubular cells and is the most common subtype of renal cell carcinoma. KIRC is characterized by changes in lipid metabolism, and obesity is a risk factor for it. C1q And TNF Related 1 (C1QTNF1), a novel adipokine and member of the C1q and TNF-related protein (CTRP) family, has been shown to affect the progression of various cancers. However, the role of C1QTNF1 in KIRC has not been studied. Methods: The Wilcoxon rank sum test was used to analyze the expression of C1QTNF1 in KIRC tissues and normal tissues. The relationship between clinicopathological features and C1QTNF1 levels was also examined by logistic regression and the Wilcoxon rank sum test. In addition, the effect of C1QTNF1 on the prognosis of KIRC patients was analyzed by Kaplan-Meier (KM). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the potential signaling pathways and biological functions of differential genes. A nomogram was constructed to predict the prognosis of KIRC patients. Spearman correlation analysis was performed to determine the association between C1QTNF1 expression and immune cell infiltration and immune checkpoint genes. The upstream miRNAs and lncRNAs of C1QTNF1 were predicted by the ENCORI online tool. Finally, we examined the proliferation, invasion, and migration abilities of KIRC cells after C1QTNF1 knockdown. Results: The expression of C1QTNF1 in KIRC tissues was significantly higher than in normal renal tissues. Patients with higher C1QTNF1 expression had a poor prognosis, a finding supported by Kaplan-Meier survival analysis. C1QTNF1 expression was significantly correlated with TNM and pathologic stages, age, and gender (p < 0.05). The C1QTNF1 expression level was significantly correlated with immune cell infiltration and immune checkpoint genes in KIRC. Additionally, high C1QTNF1 expression was associated with poor prognosis in stage I and II, T1 and T2, T3 and T4, N0, and M0 patients (HR > 1, p < 0.05). The calibration diagram shows that the C1QTNF1 model has effective predictive performance for the survival of KIRC patients. Knockdown of C1QTNF1 inhibited KIRC cell proliferation, cell migration, and cell invasion. In addition, CYTOR and AC040970.1/hsa-miR-27b-3p axis were identified as the most likely upstream ncRNA-related pathways of C1QTNF1 in KIRC. Conclusion: In conclusion, our study suggests that high expression of C1QTNF1 is associated with KIRC progression and immune infiltration. The increased expression of C1QTNF1 suggests a poor prognosis in KIRC patients.

Dataset Information

Expression of BAG1 is associated with prognosis in kidney renal clear cell carcinoma based on bioinformatics.

Background

Methods

Results

Publications

Expression of BAG1 is associated with prognosis in kidney renal clear cell carcinoma based on bioinformatics.

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