Dataset Information

Microenvironment-related gene TNFSF13B predicts poor prognosis in kidney renal clear cell carcinoma.

ABSTRACT: Background:Kidney renal clear cell carcinoma (KIRC) affects the genitourinary system. Although treatment of KIRC in early stages can be highly successful, this type of cancer is difficult to detect until later stages of disease that are less easily treatable. Previous studies have focused on tumor cells, but have ignored the contributions of the tumor microenvironment. Methods:We analyzed KIRC gene expression data from The Cancer Genome Atlas with the ESTIMATE algorithm to identify differentially expressed genes. Through protein-protein interaction network analysis, we identified clusters and picked genes from the clusters for further analysis. Differential expression, Kaplan-Meier, and univariate Cox analyses were used to select prognostic biomarkers. Gene Set Enrichment Analysis (GSEA) and Tumor Immune Estimation Resource (TIMER) analysis were used to explore the immune characteristics of these genes as biomarkers. Results:Through the ESTIMATE algorithm and other system biology tools, TNFSF13B was identified as a prognostic biomarker. TNFSF13B is highly expressed in tumors, and high expression of TNFSF13B leads to poor prognosis. Further GSEA and TIMER analysis revealed that the expression of TNFSF13B was related to the immune signaling pathway and lymphocyte infiltration. Our findings strongly suggest that TNFSF13B may be a potential biomarker or target related to the tumor microenvironment for KIRC.

SUBMITTER: Jiang M

PROVIDER: S-EPMC7333652 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Microenvironment-related gene TNFSF13B predicts poor prognosis in kidney renal clear cell carcinoma.

Jiang Mingzhe M Lin Jiaxing J Xing Haotian H An Jun J Yang Jieping J Wang Biao B Yu Meng M Zhu Yuyan Y

PeerJ 20200630

<h4>Background</h4>Kidney renal clear cell carcinoma (KIRC) affects the genitourinary system. Although treatment of KIRC in early stages can be highly successful, this type of cancer is difficult to detect until later stages of disease that are less easily treatable. Previous studies have focused on tumor cells, but have ignored the contributions of the tumor microenvironment.<h4>Methods</h4>We analyzed KIRC gene expression data from The Cancer Genome Atlas with the ESTIMATE algorithm to identif ...[more]

PMID: 32655996

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Project description:Background: M7G modification is extremely vital for the development of many cancers, especially tumor immunity. M7G modification is a novel functional regulator of miRNA, and the researches on m7G-related miRNAs in kidney renal clear cell carcinoma (KIRC) are still insufficient. This research aims to establish a risk signature on the foundation of m7G-associated miRNAs, which can precisely forecast the prognosis of KIRC patients. Methods: Transcriptome data and clinical data used in this study come from The Cancer Genome Atlas database. Our team utilized univariable Cox, Lasso and multivariable Cox analyses to construct a m7G-associated miRNAs risk signature that can forecast the prognosis of KIRC patients. Kaplan-Meier method, time-dependent receiver operating characteristic (ROC) curve, and the independent analysis of risk signatures were employed to verify the predictability and accuracy of the risk signature. Subsequently, based on CIBERSORT, ESTIMATE and ssGSEA algorithms, we speculated the potential impact of the proposed risk signature on tumor immune microenvironment. Ultimately, by virtue of the risk signature and tumor immunity, the hub genes affecting the prognosis of KIRC patients were screened out. Results: Our team established and verified a prognostic signature comprising 7 m7G-associated miRNAs (miR-342-3p, miR-221-3p, miR-222-3p, miR-1277-3p, miR-6718-5p, miR-1251-5p, and miR-486-5p). The results of the Kaplan-Meier survival analysis revealed that the prognosis of KIRC sufferers in the high-risk group was often unsatisfactory. The accuracy of the prediction ability of the risk signature was verified by calculating the area under the ROC curve. Univariate-multivariate Cox analyses further showed that this risk signature could be utilized as an independent prognosis-related biomarker for KIRC sufferers. The results of the immune analysis revealed that remarkable diversities existed in immune status and tumor microenvironment between high-risk and low-risk groups. On the foundation of the proposed risk signature and other clinical factors, a nomogram was established to quantitatively forecast the survival of KIRC sufferers at 1, 3 and 5 years. Conclusion: Based on m7G-related miRNAs, a risk signature was successfully constructed, which could precisely forecast the prognosis of sufferers and guide personalized immunotherapy for KIRC patients.

Project description:BackgroundRunt-related transcription factor 1 (RUNX1) was previously reported to play a dual role in promoting or suppressing tumorigenesis in various malignancies. A public dataset from The Cancer Genome Atlas (TCGA) was used to evaluate the role of RUNX1 in clear cell renal cell carcinoma (ccRCC).MethodsThe Wilcoxon signed-rank test was used to compare the expression of RUNX1 in ccRCC tissues and normal tissues. The Wilcoxon signed-rank test and logistic regression were utilized to investigate the relationship between clinicopathological factors and RUNX1 expression. Additionally, we analysed the differences in prognosis between patients with high and low expression of RUNX1 via the Kaplan-Meier method and Cox regression. Gene set enrichment analysis (GSEA) was performed to explore the mechanisms of RUNX1 in ccRCC.ResultsThe expression of RUNX1 in ccRCC tissues was significantly higher than that in normal tissues. High expression of RUNX1 was significantly associated with gender (p = 0.003), clinical stage (p < 0.001), tissue infiltration (p < 0.001), lymph node metastasis (p = 0.037) and histological grade (p < 0.001). Logistic regression analysis showed that high RUNX1 expression was significantly correlated with gender (OR = 1.71 for male vs. female, p = 0.004), histological grade (OR = 11.61 for grade IV vs. I, p < 0.001), clinical stage (OR = 1.55 for stage III/IV vs. I/II, p = 0.014) and tissue infiltration (OR = 1.54 for positive vs. negative, p = 0.018). Kaplan-Meier survival curves revealed that the prognosis of patients with ccRCC with high RUNX1 expression was worse than that of patients with ccRCC with low RUNX1 expression (p < 0.001). Univariate Cox regression analysis showed that high RUNX1 expression was strongly correlated with poor prognosis (HR = 1.60, 95% CI [1.31-1.97], p < 0.001). In addition, high expression of RUNX1 was an independent prognostic factor for poor overall survival (OS), with an HR of 1.50 (95% CI [1.20-1.87], p < 0.001) in multivariate Cox analysis. GSEA showed that the apoptosis, B cell receptor signalling pathway, calcium signalling pathway, chemokine signalling pathway, JAK/STAT signalling pathway, MAPK signalling pathway, p53 signalling pathway, pathways in cancer, T cell receptor signalling pathway, Toll-like receptor signalling pathway, VEGF signalling pathway, and Wnt signalling pathway were significantly enriched in the RUNX1 high-expression phenotype. In conclusion, RUNX1 can be used as a novel prognostic factor and therapeutic target in ccRCC.

Project description:BackgroundPrevious reports have shown that short/branched chain acyl-CoA dehydrogenase (ACADSB) plays an important role in glioma, but its role in clear cell renal carcinoma (ccRCC) has not been reported.MethodsThe TIMER and UALCAN databases were used for pan-cancer analysis. RNA sequencing and microarray data of patients with ccRCC were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus database. The differential expression of ACADSB in ccRCC and normal kidney tissues was tested. Correlations between ACADSB expression and clinicopathological parameters were assessed using the Wilcoxon test. The influences of ACADSB expression and clinicopathological parameters on overall survival were assessed using Cox proportional hazards models. Gene set enrichment analysis (GSEA) was performed to explore the associated gene sets enriched in different ACADSB expression phenotypes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on genes with similar expression patterns to ACADSB. Correlations between ACADSB and ferroptosis-related genes were assessed using Spearman's correlation analysis.ResultsPan-cancer analysis revealed that ACADSB is down-regulated in multiple cancers, and decreased expression of ACADSB correlates with poor prognosis in certain types of cancer. Differential expression analyses revealed that ACADSB was down-regulated in ccRCC, indicating that ACADSB expression could be a single significant parameter to discriminate between normal and tumor tissues. Clinical association analysis indicated that decreased ACADSB expression was associated with high tumor stage and grade. The Cox regression model indicated that low ACADSB expression was an independent risk factor for the overall survival of patients with ccRCC. GSEA showed that 10 gene sets, including fatty acid (FA) metabolism, were differentially enriched in the ACADSB high expression phenotype. GO and KEGG pathway enrichment analysis revealed that ACADSB-related genes were significantly enriched in categories related to FA metabolism, branched-chain amino acid (BCAA) metabolism, and iron regulation. Spearman's correlation analysis suggested that the expression of ACADSB was positively correlated with the expression of ferroptosis driver genes.ConclusionsACADSB showed good diagnostic and prognostic abilities for ccRCC. The downregulation of ACADSB might promote tumorigenesis and tumor progression by inhibiting FA catabolism, BCAA catabolism, and ferroptosis in ccRCC.

Project description:Paired-like homeodomain transcription factor 1 (PITX1) is involved in numerous biological processes, including cell growth, progression, and invasion in various malignant tumors. Nevertheless, the relationship between PITX1 and kidney renal clear cell carcinoma (KIRC) remains unclear. The clinical role and functions of PITX1 were analyzed by integrating multiple open-access online datasets. Further experimental verification was performed via quantitative real-time PCR (qRT-PCR) to detect the expression of PITX1 in 10 pairs of KIRC tissues. Our results revealed that PITX1 mRNA was overexpressed in tumor tissues compared with normal tissues in the TCGA-KIRC database (p < 0.001) and numerous independent cohorts (p < 0.05). Further, high expression of PITX1 mRNA was detected in KIRC tissues compared with adjacent normal tissues in our center by qRT-PCR (N = 10, p < 0.05). Logistic regression analysis demonstrated that the PITX1 level was positively associated with KIRC patients, T and M stages, histologic grade, and pathologic stage (all p < 0.05). Survival analysis showed that upregulation of PITX1 mRNA was associated with poor overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS) (all p < 0.05). Univariate/multivariate Cox hazard regression analysis revealed that PITX1 was an independent risk factor for OS in patients with KIRC (HR = 1.998, p = 0.003). Accordingly, the time-independent receiver operating characteristic (ROC) curve confirmed that PITX1 had good predictive efficacy for OS and DSS. Meanwhile, a prediction model constructed by nomogram was used to predict the OS of KIRC patients, and the calibration plot indicated this model shows high accuracy. We also revealed some downstream target genes of PITX1-related signaling pathways. Our finding suggested that high PITX1 mRNA expression may act as an independent predictive factor of poor prognosis in patients with KIRC. The prognostic model based on the nomogram would be instrumental in evaluating the survival rate in KIRC patients.

Dataset Information

Microenvironment-related gene TNFSF13B predicts poor prognosis in kidney renal clear cell carcinoma.

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Microenvironment-related gene TNFSF13B predicts poor prognosis in kidney renal clear cell carcinoma.

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