scholarly journals Prognostic value of CLIC3 mRNA overexpression in bladder cancer

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8348
Author(s):  
Mei Chen ◽  
Shufang Zhang ◽  
Xiaohong Wen ◽  
Hui Cao ◽  
Yuanhui Gao
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Mrna Expression ◽  
Prognostic Value ◽  
Multivariate Analyses ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Normal Tissues

Background Human intracellular chloride channel 3 (CLIC3) is involved in the development of various cancers, but the expression and prognostic value of CLIC3 mRNA in bladder cancer (BC) remain unclear. Methods The gene expression data and clinical information of CLIC3 were obtained from the Gene Expression Omnibus (GEO) database and verified in the Oncomine and The Cancer Genome Atlas (TCGA) database. The expression of CLIC3 mRNA in BC tissues and adjacent normal tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). The Kaplan-Meier method was used to analyze the relationship between the expression of CLIC3 mRNA and the prognosis of BC. Cox univariate and multivariate analyses were performed on the overall survival and tumor-specific survival of BC patients. The genes coexpressed with CLIC3 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). CLIC3-related signal transduction pathways in BC were explored with gene set enrichment analysis (GSEA). Results The expression of CLIC3 mRNA in BC tissues was higher than that in normal tissues (P < 0.01). High CLIC3 mRNA expression was associated with age (P = 0.021) and grade (P = 0.045) in BC patients. High CLIC3 mRNA expression predicted a poor prognosis in BC patients (P < 0.05). Cox univariate and multivariate analyses showed that high CLIC3 mRNA expression was associated with tumor-specific survival in BC patients (P < 0.05). Functional enrichment analyses indicated that CLIC3 may be significantly associated with the cell cycle, focal adhesion, the extracellular matrix (ECM) receptor interaction and the P53 signaling pathway. Conclusions CLIC3 mRNA is highly expressed in BC, and its high expression is related to the adverse clinicopathological factors and prognosis of BC patients. CLIC3 can be used as a biomarker for the prognosis of BC patients.

scholarly journals Controversial T1G3 bladder cancer is the key to revealing the changes in the biological functions of bladder cancer cells

2020 ◽  
Author(s):  
Shen Pan ◽  
Yunhong Zhan ◽  
Xiaonan Chen ◽  
Bin Wu ◽  
Bitian Liu
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Cancer Cells ◽  
Interaction Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Specific Gene ◽  
Gene Sets ◽  
Bladder Cancer Cells

Abstract Background T1G3 shows a higher chance of recurrence and progression among early bladder cancer types and the available treatment option is controversial. High recurrence and progression are the problems that need to be explored and solved. Changes in the internal signals of bladder cancer cells and differential genes may be the root cause of these problems. Methods GSE120736, GSE19915, GSE19423, GSE32548 and GSE37815 datasets were obtained from Gene Expression Omnibus (GEO ) to identify differentially expressed genes (DEGs). Bladder cancer transcript data from The Cancer Genome Atlas (TCGA) were clustered into different cell-specific gene sets according to weighted gene co-expression network analysis (WGCNA). Multiple sets of databases were used for gene expression comparison, functional enrichment, and protein interaction analysis, including The Human Protein Atlas, Cancer Dependency Map, Metascape, Gene set enrichment analysis, and DisNor. Results DEGs were obtained through GEO data comparison and intersection. After WGCNA was proven to recognise cell-specific gene sets, candidate DEGs were selected and shown to be specifically expressed in cancer cells. Candidate DEGs were related to mitosis and cell cycle. Further, 12 functional candidate markers were identified from the sequencing data of 30 bladder cancer cell lines. These genes were all up-regulated and previously shown to be closely related to bladder cancer progression. Conclusions Twelve functional genes with specific differential expression in bladder cancer cells were identified. WGCNA can identify the relatively specific expression sets of different cells in bladder cancer with greater tumour heterogeneity, which provides new perspectives for future cancer research.

scholarly journals Screening and Identification of an Immune-Associated lncRNA Prognostic Signature in Ovarian Carcinoma: Evidence from Bioinformatic Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yan Li ◽  
Fan-fan Huo ◽  
Ying-ying Wen ◽  
Miao Jiang
Keyword(s):  
Ovarian Carcinoma ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Value ◽  
Antigen Processing ◽  
Multivariate Analyses ◽  
Wnt Signaling Pathway ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction

Backgrounds. The dysregulated long noncoding RNAs (lncRNAs) have been described to be crucial regulators in the progression of ovarian carcinoma. The infiltration status of immune cells is also related to the clinical outcomes in ovarian carcinoma. The present research is aimed at constructing an immune-associated lncRNA signature with potential prognostic value for ovarian carcinoma patients. Methods. We obtained 379 ovarian carcinoma cases with available clinical data and transcriptome data from The Cancer Genome Atlas database to evaluate the infiltration status of immune cells, thereby generating high and low immune cell infiltration groups. According to the expression of the immune-associated lncRNA signature, the risk score of each case was calculated. The high- and low-risk groups were classified using the median risk score as threshold. Results. A total of 169 immune-associated lncRNAs that differentially expressed in ovarian carcinoma were included. According to the Lasso regression analysis and Cox univariate and multivariate analyses, 5 immune-associated lncRNAs, including AC134312.1, AL133467.1, CHRM3-AS2, LINC01722, and LINC02207, were identified as a predictive signature with significant prognostic value in ovarian carcinoma. The following Kaplan-Meier analysis, ROC analysis, and Cox univariate and multivariate analyses further suggested that the predicted signature may be an independent prognosticator for patients with ovarian carcinoma. The following gene set enrichment analysis showed that this 5 immune-associated lncRNAs signature was significantly related to the hedgehog pathway, basal cell carcinoma, Wnt signaling pathway, cytokine receptor interaction, antigen processing and presentation, and T cell receptor pathway. Conclusion: This study suggested a predictive model with 5 immune-associated lncRNAs that has an independent prognostic value for ovarian carcinoma patients.

scholarly journals Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7821 ◽  
Author(s):  
Xiaoming Zhang ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
Zhengguo He ◽  
Cun Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Value ◽  
Early Stage ◽  
Expression Profiles ◽  
Diagnostic Value ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

The Clinical Significance and Prognostic Value of HER2 Expression in Bladder Cancer: a Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Kai Gan ◽  
Yue Gao ◽  
KuangZheng Liu ◽  
Bin Xu ◽  
Ming Chen
Keyword(s):  
Bladder Cancer ◽  
Clinical Significance ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Growth Factor Receptor ◽  
Tumor Stage ◽  
The Cancer Genome Atlas ◽  
Her2 Expression ◽  
Large Tumor ◽  
Normal Tissues

Abstract Objective: Human Epidermal Growth Factor Receptor 2 (HER2) is highly expressed in a variety of tumors and associated with patients’ prognosis, but its role in bladder cancer remains unclear. We conducted this meta-analysis to explore the clinical significance and prognostic value of HER2 in bladder cancer and its potentiality as an immunotherapy target.Methods: PubMed was searched for studies published between January 1, 2000 and January 1, 2020. The odds ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (95%CIs) were used to investigate the relationship between HER2 and bladder cancer. UALCAN website was used to obtain TCGA (The cancer genome atlas) database.Results: Our study includes 14 articles, 1398 patients. HER2 expression was significantly higher in bladder cancer than in normal tissues. Our meta-analysis results did not reveal any effect of gender on the expression of HER2 levels in bladder cancer patients. However, HER2 expression in male patients was significantly higher than that in women according to TCGA databases. HER2 expression was also associated with carcinoma in situ, multifocal tumors, large tumor size, high tumor stage and grade, lymph node metastases, risk of recurrence and progression, low recurrence-free survival (RFS) rate. HER2 expression status had no effect on overall survival.Conclusions: Our meta-analysis showed that HER2 expression was related to pathological malignancy and poor prognosis in bladder cancer which indicated that it could be used as an effective biomarker and therapeutic target.

scholarly journals Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4.Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

scholarly journals High Expression of NREP Correlated With Worse Survival and M2 Macrophage Infiltrates in Gastric Cancer

2021 ◽  
Author(s):  
Tailiang Lu ◽  
Chenlong Li ◽  
Wei Peng ◽  
Cailing Xiang ◽  
Yongqiang Gong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
T Cell ◽  
Mrna Expression ◽  
Inflammatory Responses ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
M2 Macrophage ◽  
M2 Macrophages

Abstract Background: Neuronal Regeneration Related Protein (NREP) is a highly conserved protein and is a newly discovered protein that may be closely related to tumor cell migration. We aim at investigating the prognostic role of NREP in gastric cancer (GC). Methods: Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to analysis NREP mRNA expression in GC. Correlations between NREP mRNA expression and clinicopathological characteristic were analyzed. TCGA and GEO data were analyzed by The Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier plotter databases respectively to assess prognostic value of NREP in GC. Gene set enrichment analysis (GSEA) was performed to identify the keg pathways related to NREP expression. TIMER and CIBERSORT analysis were used to found tumor-infiltrating immune cells associated with NREP mRNA expression. Results: NREP was over expressed in GC and significantly associated with T stage (P<0.001), Histologic grade (P = 0.022) and OS events (P = 0.007) of GC patients. High mRNA expression of NREP correlated with worse survival. The significantly kegg pathways enriched in samples with NREP high expression involved in cell adhesion, tumorigenesis, and immune and inflammatory responses. NREP mRNA expression was positively associated with CD4+T cell(r = 0.294, P = 1.04e−08), CD8+T cell(r = 0.125, P = 0.0167), Neutrophil(r = 0.169, P = 0.00116), Dendritic(r = 0.314, P = 1.03e−09), and was strongly associated with Macrophage (r = 0.547, P = 5.44e−30). The CIBERSORT database revealed that NREP mRNA expression was correlated with the activated memory CD4+ T cells(p<0.01), Monocytes(p<0.001) and M2 Macrophages(p<0.001). NREP is strongly correlated with the markers genes of M2 macrophages and tumor-associated macrophages (TAMs). Conclusion: NREP might be served as a novel prognostic biomarker of GC and associated with M2 macrophage infiltrates.

scholarly journals Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

scholarly journals A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yingchun Liang ◽  
Fangdie Ye ◽  
Chenyang Xu ◽  
Lujia Zou ◽  
Yun Hu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognosis Prediction

Abstract Background The effective treatment and prognosis prediction of bladder cancer (BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis is closely related to tumour occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified an FRG signature with potential prognostic value for patients with BLCA. Methods The corresponding clinical data and mRNA expression profiles of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, and a Cox regression model was used to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation. Results Clinical traits were combined with FRGs, and 15 prognosis-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD was related to poor survival in BLCA patients. Multivariate Cox regression was used to construct a prognostic model with 7 FRGs that divided patients into two risk groups. Compared with that in the low-risk group, the overall survival (OS) of patients in the high-risk group was significantly lower (P < 0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR = 1.772, P < 0.01). Receiver operating characteristic (ROC) curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in ssGSEA and different distributed patterns in PCA. Conclusion Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.

scholarly journals A Novel Survival Model Based on Ferroptosis-related Gene Signature for Overall Survival Prediction in Bladder Cancer

2021 ◽  
Author(s):  
Yingchun Liang ◽  
Fangdie Ye ◽  
Chenyang Xu ◽  
Lujia Zou ◽  
Yun Hu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Prognosis Prediction

Abstract Background: The effective treatment and prognosis prediction of bladder cancer(BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis are closely related to tumor occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified a FRGs signature with potential prognostic value for patients with BLCA. Methods: The corresponding clinical data and the mRNA expression profile of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, Cox regression model was applied to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation. Results: Clinical traits were combined with FRGs, so that 15 prognostic-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD are related to poor survival rates of BLCA patients. Multivariate Cox regression constructed a prognostic model with 7 FRGs and divided patients into two risk groups. Compared with the low-risk group, the overall survival(OS) of patients in the high-risk group was significantly lower (P <0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR> 1, P <0.01). ROC curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in the ssGSEA and different distributed patterns in PCA. Conclusion: Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.

scholarly journals Identification of a FLG-wide-type bladder cancer subtype with poor prognosis and prediction use in immune checkpoint

2021 ◽  
Author(s):  
Liang Chen ◽  
Liulin Xiong ◽  
Weinan Chen ◽  
Lizhe An ◽  
Huanrui Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Immune Checkpoint ◽  
Poor Prognosis ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Biomarkers

Abstract Background Bladder cancer (BLCA) is one of most common urinary tract malignant tumor and immunotherapy have generated a great deal of interest in BLCA. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. Multiple studies have suggested that specific genetic mutations may serve as immune biomarkers for ICB therapy. Objective In this study, we aimed to investigate the role of mutations genes and subtypes in prognosis and immune checkpoint prediction in BLCA. Method Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the mutation genes of BLCA. Functional enrichment analysis Gene Ontology (GO) and Gene set enrichment analysis (GSEA) was conducted. The infiltrating immune cells and the prediction of ICB between different subtypes group were explored using immuCellAI algorithm. Results The mutation genes Filaggrin (FLG) gene were identified. Following the study on its subtypes and functional enrichment analysis, Sub2 of FLG-wide type was found to have relationships with poor prognosis and immune infiltration BLCA. What’s more, Sub2 of FLG-wide type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. Conclusion This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

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