FADS1 is a Prognostic Biomarker in Bladder Cancer: A Study Based on TCGA Data

Aim and Objective: Fatty acid desaturase 1 (FADS1) has been reported to be a potential biomarker in various cancers. However, no study has explored the relationship between FADS1 expression and bladder cancer. Our study aimed to investigate the role of FADS1 in bladder cancer prognosis via The Cancer Genome Atlas (TCGA). Materials and Methods: RNA-Seq expression of 414 tumor tissues and 19 paired normal tissues, as well as corresponding clinical data, were downloaded from TCGA database. Two cancer cases were excluded due to a lack of clinical information. The association between FADS1 and the clinicopathological features of bladder cancer was analyzed. This study was conducted in October of 2019 in China. Results: The high expression of FADS1 in bladder cancer was significantly related to histological grade (OR = 0.155 for low vs. high), clinical stage (OR=2.074 for III or IV vs. I or II), T classification (OR=2.326 for T3 or T4 vs. T1 or T2), lymphatic metastasis (OR=1.923 for N1 or N2 or N3 vs. N0) and distant metastasis (OR=4.883 for yes vs. no) (all p-values <0.05). Bladder cancer with high FADS1 levels was related to a worse prognosis than bladder cancer with low FADS1 levels (p= 1.626*10-5 ), according to median expression value 3.622. FADS1 was an independent factor of overall survival in bladder cancer, with a hazard ratio of 1.048 (95%CI: 1.020–1.077, p = 0.001). Conclusions: Increased FADS1 expression in bladder cancer is associated with advanced clinical pathological features and may be a potential biomarker for poor prognosis.

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Hyaluronan-mediated motility receptor expression functions as a prognostic biomarker in uterine carcinosarcoma based on bioinformatics analysis

Journal of International Medical Research ◽

10.1177/03000605211021043 ◽

2021 ◽

Vol 49 (6) ◽

pp. 030006052110210

Author(s):

Hui Sun ◽

Li Ma ◽

Jie Chen

Keyword(s):

Interaction Network ◽

Maximal Clique ◽

Receptor Expression ◽

The Cancer Genome Atlas ◽

Uterine Carcinosarcoma ◽

Sequencing Data ◽

Hub Genes ◽

Protein Protein Interaction ◽

Normal Tissues ◽

Potential Biomarker

Objective Uterine carcinosarcoma (UCS) is a rare, aggressive tumour with a high metastasis rate and poor prognosis. This study aimed to explore potential key genes associated with the prognosis of UCS. Methods Transcriptional expression data were downloaded from the Gene Expression Profiling Interactive Analysis database and differentially expressed genes (DEGs) were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses using Metascape. A protein–protein interaction network was constructed using the STRING website and Cytoscape software, and the top 30 genes obtained through the Maximal Clique Centrality algorithm were selected as hub genes. These hub genes were validated by clinicopathological and sequencing data for 56 patients with UCS from The Cancer Genome Atlas database. Results A total of 1894 DEGs were identified, and the top 30 genes were considered as hub genes. Hyaluronan-mediated motility receptor (HMMR) expression was significantly higher in UCS tissues compared with normal tissues, and elevated expression of HMMR was identified as an independent prognostic factor for shorter survival in patients with UCS. Conclusions These results suggest that HMMR may be a potential biomarker for predicting the prognosis of patients with UCS.

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Prognostic value of CLIC3 mRNA overexpression in bladder cancer

PeerJ ◽

10.7717/peerj.8348 ◽

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.

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

10.21203/rs.3.rs-135089/v1 ◽

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.

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LETM1 is a potential biomarker of prognosis in lung non-small cell carcinoma

BMC Cancer ◽

10.1186/s12885-019-6128-9 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 3

Author(s):

Longzhen Piao ◽

Zhaoting Yang ◽

Ying Feng ◽

Chengye Zhang ◽

Chunai Cui ◽

...

Keyword(s):

Cox Regression ◽

Transmembrane Protein ◽

Small Cell Lung Carcinoma ◽

Clinical Stage ◽

Small Cell ◽

Cancer Prognosis ◽

Normal Lung ◽

Cell Lung Carcinoma ◽

Cox Regression Analysis ◽

Potential Biomarker

Abstract Background Although the leucine zipper-EF-hand-containing transmembrane protein 1 (LETM1) is one of the mitochondrial inner membrane proteins that is involved in cancer prognosis in various tumors, LETM1 as a biomarker for prognostic evaluation of non-small cell lung carcinoma (NSCLC) has not been well studied. Methods To address this issue, we used 75 cases NSCLC, 20 cases adjacent normal lung tissues and NSCLC cell lines. We performed immunohistochemistry staining and western blot analysis as well as immunofluorescence imaging. Results Our studies show that expression of LETM1 is significantly correlated with the lymph node metastasis (p = 0.003) and the clinical stage (p = 0.005) of NSCLC. The Kaplan-Meier survival analysis revealed that NSCLC patients with positive expression of LETM1 exhibits a shorter overall survival (OS) rate (p = 0.005). The univariate and multivariate Cox regression analysis indicated that LETM1 is a independent poor prognostic marker of NSCLC. In addition, the LETM1 expression is correlated with cancer stemness-related gene LGR5 (p < 0.001) and HIF1α expression (p < 0.001), but not with others. Moreover, LETM1 expression was associated with the expression of cyclin D1 (p = 0.003), p27 (p = 0.001), pPI3K(p85) (p = 0.025), and pAkt-Thr308 (p = 0.004). Further, our studies show in LETM1-positive NSCLC tissues the microvessel density was significantly higher than in the negative ones (p = 0.024). Conclusion These results indicate that LETM1 is a potential prognostic biomarker of NSCLC.

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Molecular subtyping of metastatic urothelial bladder cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.6_suppl.326 ◽

2017 ◽

Vol 35 (6_suppl) ◽

pp. 326-326

Author(s):

Charlotte Ackerman ◽

Sanjeev Mariathasan ◽

Dorothee Nickles ◽

Alfonso Gomez De Liano Lista ◽

Akhila Ganeshi Wimalasingham ◽

...

Keyword(s):

Bladder Cancer ◽

Immune Therapy ◽

Clinical Information ◽

Progression Free Survival ◽

The Cancer Genome Atlas ◽

Urothelial Bladder Cancer ◽

First Line ◽

Metastatic Urothelial Cancer ◽

Urothelial Bladder ◽

Line Chemotherapy

326 Background: TCGA molecular sybtyping is established in metastatic urothelial bladder cancer (UBC). It remains unclear if it is of prognostic importance with chemotherapy in metastatic UBC. Data into immune therapy suggests TCGA subtyping is predictive to response. Methods: Archival formalin-fixed paraffin embedded (FFPE) tissue were analysed from 170 patients that had consented into a clinical trial (NCT00949455) after first line chemotherapy for metastatic disease. Gene expression levels were quantified by NanoString technology. Molecular subtypes were assigned according to The Cancer Genome Atlas (TCGA) subtypes. Clinical information was available for all patients and analysis on individual genes were explored. Results: 170 patients were analysed, 75% male. 107 (64%) patients received cisplatin based first-line chemotherapy, with 36% receiving carboplatin based regimen. Median overall survival (OS) was 15.73 months [95% CI: 13.87-17.58], and median progression free survival (PFS) was 10.71 months [95% CI: 8.97-12.45]. Samples were initially clustered into luminal (n=109) and basal (n=61) subtypes. Response to first line chemotherapy occurred in all subtypes but was shown to be significantly higher in the luminal subtype versus the basal subtype [58% vs 20%, p=0.01]. PFS was superior in luminal subtypes [11.8 months vs 8.9 months, p=0.005]. Exploratory analysis showed that luminal II subtype had the best outcome for OS [20.3 months, p=0.03] compared to the other subtypes. Outcomes with other genes including immune markers were explored. TCGA outcomes can be summarised in the table. Conclusions: In metastatic urothelial cancer, TCGA subclassifying influences outcome of patients post chemotherapy. [Table: see text]

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Identification of Key Genes Associated with Progression and Prognosis of Bladder Cancer through Integrated Bioinformatics Analysis

Cancers ◽

10.3390/cancers13235931 ◽

2021 ◽

Vol 13 (23) ◽

pp. 5931

Author(s):

Shiv Verma ◽

Eswar Shankar ◽

Spencer Lin ◽

Vaibhav Singh ◽

E. Ricky Chan ◽

...

Keyword(s):

Bladder Cancer ◽

Cancer Progression ◽

Univariate Analysis ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Kaplan Meier ◽

Human Protein Atlas ◽

Validation Set ◽

Muscle Invasive

Bladder cancer prognosis remains dismal due to lack of appropriate biomarkers that can predict its progression. The study aims to identify novel prognostic biomarkers associated with the progression of bladder cancer by utilizing three Gene Expression Omnibus (GEO) datasets to screen differentially expressed genes (DEGs). A total of 1516 DEGs were identified between non-muscle invasive and muscle invasive bladder cancer specimens. To identify genes of prognostic value, we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A total of seven genes, including CDKN2A, CDC20, CTSV, FOXM1, MAGEA6, KRT23, and S100A9 were confirmed with strong prognostic values in bladder cancer and validated by qRT-PCR conducted in various human bladder cancer cells representing stage-specific disease progression. ULCAN, human protein atlas and The Cancer Genome Atlas datasets were used to confirm the predictive value of these genes in bladder cancer progression. Moreover, Kaplan–Meier analysis and Cox hazard ratio analysis were performed to determine the prognostic role of these genes. Univariate analysis performed on a validation set identified a 3-panel gene set viz. CDKN2A, CTSV and FOXM1 with 95.5% sensitivity and 100% specificity in predicting bladder cancer progression. In summary, our study screened and confirmed a 3-panel biomarker that could accurately predict the progression and prognosis of bladder cancer.

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Upregulation of GNPNAT1 Predicts Poor Prognosis and Correlates With Immune Infiltration in Lung Adenocarcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.605754 ◽

2021 ◽

Vol 8 ◽

Author(s):

Wenting Liu ◽

Kaiting Jiang ◽

Jingya Wang ◽

Ting Mei ◽

Min Zhao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Signaling Pathways ◽

Poor Prognosis ◽

Cox Regression ◽

Clinical Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Cox Regression Analysis ◽

Normal Tissues

BackgroundGlucosamine 6-phosphate N-acetyltransferase (GNPNAT1) is a key enzyme in the hexosamine biosynthetic pathway (HBP), which functions as promoting proliferation in some tumors, yet its potential biological function and mechanism in lung adenocarcinoma (LUAD) have not been explored.MethodsThe mRNA differential expression of GNPNAT1 in LUAD and normal tissues was analyzed using the Cancer Genome Atlas (TCGA) database and validated by real-time PCR. The clinical value of GNPNAT1 in LUAD was investigated based on the data from the TCGA database. Then, immunohistochemistry (IHC) of GNPNAT1 was applied to verify the expression and clinical significance in LUAD from the protein level. The relationship between GNPNAT1 and epigenetics was explored using the cBioPortal database, and the miRNAs regulating GNPNAT1 were found using the miRNA database. The association between GNPNAT1 expression and tumor-infiltrating immune cells in LUAD was observed through the Tumor IMmune Estimation Resource (TIMER). Finally, Gene set enrichment analysis (GSEA) was used to explore the biological signaling pathways involved in GNPNAT1 in LUAD.ResultsGNPNAT1 was upregulated in LUAD compared with normal tissues, which was verified through qRT-PCR in different cell lines (P < 0.05), and associated with patients’ clinical stage, tumor size, and lymphatic metastasis status (all P < 0.01). Kaplan–Meier (KM) analysis suggested that patients with upregulated GNPNAT1 had a relatively poor prognosis (P < 0.0001). Furthermore, multivariate Cox regression analysis indicated that GNPNAT1 was an independent prognostic factor for LUAD (OS, TCGA dataset: HR = 1.028, 95% CI: 1.013–1.044, P < 0.001; OS, validation set: HR = 1.313, 95% CI: 1.130–1.526, P < 0.001). GNPNAT1 overexpression was correlated with DNA copy amplification (P < 0.0001), low DNA methylation (R = −0.52, P < 0.0001), and downregulation of hsa-miR-30d-3p (R = −0.17, P < 0.001). GNPNAT1 expression was linked to B cells (R = −0.304, P < 0.0001), CD4+T cells (R = −0.218, P < 0.0001), and dendritic cells (R = −0.137, P = 0.002). Eventually, GSEA showed that the signaling pathways of the cell cycle, ubiquitin-mediated proteolysis, mismatch repair and p53 were enriched in the GNPNAT1 overexpression group.ConclusionGNPNAT1 may be a potential prognostic biomarker and novel target for intervention in LUAD.

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Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer

Frontiers in Medicine ◽

10.3389/fmed.2021.654635 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yi Shen ◽

Wei Xiong ◽

Qi Gu ◽

Qin Zhang ◽

Jia Yue ◽

...

Keyword(s):

Liver Cancer ◽

Molecular Subtypes ◽

Therapeutic Targets ◽

Clinical Information ◽

Copy Number Variations ◽

The Cancer Genome Atlas ◽

Liver Carcinoma ◽

Normal Tissues ◽

Omics Analysis ◽

Cancer Tissues

Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis.Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical information for liver carcinoma were retrieved from The Cancer Genome Atlas (TCGA). Multi-omics analysis was performed to identify molecular subtypes of liver cancer via integrating CNV, methylation as well as transcriptome data. Immune scores of two molecular subtypes were estimated using tumor immune estimation resource (TIMER) tool. Key mRNAs were screened and prognosis analysis was performed, which were validated using RT-qPCR. Furthermore, mutation spectra were analyzed in the different subtypes.Results: Two molecular subtypes (iC1 and iC2) were conducted for liver cancer. Compared with the iC2 subtype, the iC1 subtype had a worse prognosis and a higher immune score. Two key mRNAs (ANXA2 and CHAF1B) were significantly related to liver cancer patients' prognosis, which were both up-regulated in liver cancer tissues in comparison to normal tissues. Seventeen genes with p < 0.01 differed significantly for SNV loci between iC1 and iC2 subtypes.Conclusion: Our integrated multi-omics analyses provided new insights into the molecular subtypes of liver cancer, helping to identify novel mRNAs as therapeutic targets and uncover the mechanisms of liver cancer.

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A Simple Competing Endogenous RNA Network Identifies Novel mRNA, miRNA, and lncRNA Markers in Human Cholangiocarcinoma

BioMed Research International ◽

10.1155/2019/3526407 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Cheng Zhang ◽

Chunlin Ge

Keyword(s):

Cox Regression ◽

Clinical Information ◽

The Cancer Genome Atlas ◽

Primary Liver Tumor ◽

Normal Tissues ◽

Cerna Network ◽

Tumorigenesis And Progression ◽

Competing Endogenous Rna Network ◽

Cancer Genome Atlas ◽

Novel Biomarkers

Background. Cholangiocarcinoma (CCA) is the second most common malignant primary liver tumor and has shown an alarming increase in incidence over the last two decades. However, the mechanisms behind tumorigenesis and progression remain insufficient. The present study aimed to uncover the underlying regulatory mechanism on CCA and find novel biomarkers for the disease prognosis. Method. The RNA-sequencing (RNA-seq) datasets of lncRNAs, miRNAs, and mRNAs in CCA as well as relevant clinical information were obtained from the Cancer Genome Atlas (TCGA) database. After pretreatment, differentially expressed RNAs (DERNAs) were identified and further interrogated for their correlations with clinical information. Prognostic RNAs were selected using univariate Cox regression. Then, a ceRNA network was constructed based on these RNAs. Results. We identified a total of five prognostic DEmiRNAs, 63 DElncRNAs, and 90 DEmRNAs between CCA and matched normal tissues. Integrating the relationship between the different types of RNAs, an lncRNA-miRNA-mRNA network was established and included 28 molecules and 47 interactions. Screened prognostic RNAs involved in the ceRNA network included 3 miRNAs (hsa-mir-1295b, hsa-mir-33b, and hsa-mir-6715a), 7 lncRNAs (ENSG00000271133, ENSG00000233834, ENSG00000276791, ENSG00000241155, COL18A1-AS1, ENSG00000274737, and ENSG00000235052), and 18 mRNAs (ANO9, FUT4, MLLT3, ABCA3, FSCN2, GRID2IP, NCK2, MACC1, SLC35E4, ST14, SH2D3A, MOB3B, ACTL10, RAB36, ATP1B3, MST1R, SEMA6A, and SEL1L3). Conclusions. Our study identified novel prognostic makers and predicted a previously unknown ceRNA regulatory network in CCA and may provide novel insight into a further understanding of lncRNA-mediated ceRNA regulatory mechanisms in CCA.

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Integrative Analysis of Genomic and Clinical Data Reveals Intrinsic Characteristics of Bladder Urothelial Carcinoma Progression

Genes ◽

10.3390/genes10060464 ◽

2019 ◽

Vol 10 (6) ◽

pp. 464 ◽

Cited By ~ 2

Author(s):

Bin Zhou ◽

Rui Guo

Keyword(s):

Bladder Cancer ◽

Regulatory Networks ◽

Large Scale ◽

Molecular Mechanisms ◽

Clinical Information ◽

Copy Number Variations ◽

The Cancer Genome Atlas ◽

Genomic Alteration ◽

Structural Variations ◽

New Perspective

The progression of bladder cancer is generally a complex and dynamic process, involving a variety of biological factors. Here, we aimed to identify a set of survival-related genes that play an important role in the progression of bladder cancer and uncover their synergistic patterns. Based on the large-scale genomic profiling data and clinical information of 404 bladder cancer patients derived from The Cancer Genome Atlas (TCGA) database, we first discovered 1078 survival-related genes related to their survival states using univariate and multivariate Cox proportional hazardous regression. We then investigated the dynamic changes of the cooperative behaviors of these 1078 genes by analyzing their respective genomic features, including copy number variations, DNA methylations, somatic mutations, and microRNA regulatory networks. Our analyses showed that during the progression of bladder cancer, the biological disorder involving the identified survival-related genes can be reflected by multiple levels of abnormal gene regulation, ranging from genomic alteration to post-transcriptional dysregulation. In particular, the stage-specific co-expression networks of these genes undergo a series of structural variations. Our findings provide useful hints on understanding the underlying complex molecular mechanisms related to the evolution of bladder cancer and offer a new perspective on clinical diagnosis and treatment of bladder cancer.

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