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Bladder cancer-associated protein, a potential prognostic biomarker in human bladder cancer.

ABSTRACT: It is becoming increasingly clear that no single marker will have the sensitivity and specificity necessary to be used on its own for diagnosis/prognosis of tumors. Interpatient and intratumor heterogeneity provides overwhelming odds against the existence of such an ideal marker. With this in mind, our laboratory has been applying a long term systematic approach to identify multiple biomarkers that can be used for clinical purposes. As a result of these studies, we have identified and reported several candidate biomarker proteins that are deregulated in bladder cancer. Following the conceptual biomarker development phases proposed by the Early Detection Research Network, we have taken some of the most promising candidate proteins into postdiscovery validation studies, and here we report on the characterization of one such biomarker, the bladder cancer-associated protein (BLCAP), formerly termed Bc10. To characterize BLCAP protein expression and cellular localization patterns in benign bladder urothelium and urothelial carcinomas (UCs), we used two independent sets of samples from different patient cohorts: a reference set consisting of 120 bladder specimens (formalin-fixed as well as frozen biopsies) and a validation set consisting of 2,108 retrospectively collected UCs with long term clinical follow-up. We could categorize the UCs examined into four groups based on levels of expression and subcellular localization of BLCAP protein and showed that loss of BLCAP expression is associated with tumor progression. The results indicated that increased expression of this protein confers an adverse patient outcome, suggesting that categorization of staining patterns for this protein may have prognostic value. Finally, we applied a combinatorial two-marker discriminator using BLCAP and adipocyte-type fatty acid-binding protein, another UC biomarker previously reported by us, and found that the combination of the two markers correlated more closely with grade and/or stage of disease than the individual markers. The implications of these results in biomarker discovery are discussed.

SUBMITTER: Moreira JM

PROVIDER: S-EPMC2808262 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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Bladder cancer-associated protein, a potential prognostic biomarker in human bladder cancer.

Moreira José M A JM Ohlsson Gita G Gromov Pavel P Simon Ronald R Sauter Guido G Celis Julio E JE Gromova Irina I

Molecular & cellular proteomics : MCP 20090925 1

It is becoming increasingly clear that no single marker will have the sensitivity and specificity necessary to be used on its own for diagnosis/prognosis of tumors. Interpatient and intratumor heterogeneity provides overwhelming odds against the existence of such an ideal marker. With this in mind, our laboratory has been applying a long term systematic approach to identify multiple biomarkers that can be used for clinical purposes. As a result of these studies, we have identified and reported s ...[more]

PMID: 19783793

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Project description:BackgroundThe tumor microenvironment (TME) plays a crucial role in the initiation and progression of cancer. Bladder cancer (BLCA) is a malignant tumor of the genitourinary system. Its heterogeneity results in significant differences in the prognosis of patients. To date, this is still a huge challenge for clinical treatment. In recent years, more and more evidence showed that dysregulation of transcription factors (TFs) plays an important role in tumor progression, invasion, and metastasis. Unfortunately, the role of TFs on the tumor microenvironment in bladder cancer is unclear.MethodsThe original data of BLCA and corresponding adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. TFs were downloaded from the Animal Transcription Factor DataBase (Animal TFDB). Intersection analysis was used to obtain TFs that were differentially expressed between tumor and adjacent tissues. Gene Set Cancer Analysis (GSCALite) and CIBERSORT software were used to reveal the key differentially expressed TFs (DE-TFs). Subsequently, UALCAN and Human Protein Atlas (HPA) databases were used to disclose the expression of key DE-TFs in BLCA. The K-M curve divulged the relationship between the key DE-TFs and the patient's overall survival (OS), and the univariate and multivariate Cox regression analyses were conducted to explore independent prognostic factors. The cluster profiler package and Gene Set Enrichment Analysis (GSEA) were used for functional enrichment of genes related to the key DE-TFs. Finally, CIBERSORT software analyzed the immune landscape of BLCA.ResultsWe obtained a total of 117 BLCA-related DE-TFs. Among them, ETV7 was identified as the key DE-TFs due to its association with the autophagy activation pathway and various immune cells in cancer. Online databases of UALCAN and HPA indicated that ETV7 was overexpressed in tumors and negatively correlated with tumor severity. The K-M curve showed that the OS of patients with high expression of ETV7 was poor, which indicated that it was an independent prognostic factor. Functional enrichment of 87 DEGs between ETV7-high and -low expression groups indicated that it was closely related to the immune response and the functions of a variety of immune cells. Finally, CIBERSORT results proved that the high and low expression of ETV7 also caused significant differences in the tumor immune microenvironment of patients.ConclusionOverall, we proved that the transcription factor ETV7 was a novel prognostic factor, which may improve the individualized outcome prediction in BLCA by regulating the tumor immune microenvironment.

Project description:Background: Transcriptional factors (TFs) are responsible for regulating the transcription of pro-oncogenes and tumor suppressor genes in the process of tumor development. However, the role of these transcription factors in Bladder cancer (BCa) remains unclear. And the main purpose of this research is to explore the possibility of these TFs serving as biomarkers for BCa. Methods: We analyzed the differential expression of TFs in BCa from The Cancer Genome Atlas (TCGA) online database, identified 408 up-regulated TFs and 751down-regulated TFs. We obtained some hub genes via WGCNA model and detected the RNAs level in BCa cells and tissues. Then, the relationship between the expression and clinicopathological parameters was further investigated. Kaplan-Meier curves and the log-rank test were carried out to analyze the relationship between NFATC1, AKNA and five-TFs combination and overall survival (OS). And RT-PCR assay was conducted to further consolidate and verify these results. Results: There were significant differences in the expression of five TFs (CBX7, AKNA, HDAC4, EBF2 and NFATC1) between bladder cancer and normal bladder tissue. In BCa tissue and cell lines, the five TFs were frequently down-regulated, and closely related to poor prognosis. Moreover, the RT-PCR results of five TFs in bladder cancer and normal bladder tissue were consistent with the database results, and reduced TFs could significantly induce or restrain the transcription of many critical factors. The expression level of AKNA and NFATC1 could serve as independent biomarker to predict the overall survival (P<0.05). And the above five TFs combined detection of bladder cancer has higher sensitivity and specificity. Furthermore, differential neutrophils expression between high-risk and low-risk were found, which consolidated the role and function of the five TFs combination model in the progression of BCa. Conclusions: Our analysis effectively provides a newly TFs-associated prognostic model for bladder cancer. The combination of five identified-TFs is an independent prognostic biomarker, which could serve as a more effective therapeutic target for BCa patients.

Project description:SLMO2 is a lipid transporter that transports phosphatidylserine to the interior of mitochondria, also known as PRELID3B, which plays an important role in lipid metabolism. It has also been reported to be involved in the growth process of breast and lung tumors. However, its functions and underlying mechanisms in cancer progress remain elusive, and the potential as pan-cancer biomarker and therapeutic target remains unexplored. Using the TCGA project and GEO database, we performed pan-cancer analysis of SLMO2, which including the expression pattern, prognostic value, mutation landscape, methylation modification, protein-protein interaction network and the relationship between SLMO2 expression and immune infiltration. KEGG enrichment analysis was also performed to predict function and relevant cellular pathways of SLMO2. In addition, proliferation and migration assays were performed to detect the proliferation and metastasis capacity of breast cancer and lung cancer cells. In our study, we found that SLMO2 was overexpressed in pan-cancer and the elevated expression of SLMO2 was correlated with poorer prognosis. SLMO2 mutations were distributed in a variety of tumors and correlated with prognosis. Promoter methylation analysis showed that SLMO2 methylation levels were lower in most tumors compared with normal tissues, while a few tumors showed increased methylation levels of SLMO2. SLMO2 expression was also positively correlated with immune infiltration of MDSCs. Further pathway enrichment analysis indicated that SLMO2 was involved in regulating of cytoplasmic transport and other oncogenic processes. In vitro experiments have shown that SLMO2 promotes the proliferation and migration of breast cancer and lung cancer cells. In conclusion, our findings suggested that SLMO2 was a potential prognostic and immunological marker in pan-cancer. This study suggested a potential strategy for targeting SLMO2 to treat tumors, including manipulating tumor growth or the tumor microenvironment, especially the infiltration of MDSC.

Project description:BackgroundLong noncoding RNAs (lncRNAs) play important roles in competing endogenous RNA (ceRNA) networks involved in the development and progression of various cancers, including muscle-invasive bladder cancer (MIBC).PurposeThis study aims to construct the lncRNA-associated ceRNA network and identify lncRNA signatures correlated with the clinical features of MIBC tissue samples from The Cancer Genome Atlas (TGCA) database.MethodsThe differential expression profiles of MIBC associated lncRNAs, miRNAs and mRNAs were obtained from TCGA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to determine the principal functions of significantly dysregulated mRNAs. The dysregulated lncRNA-associated ceRNA network of MIBC was constructed based on the bioinformatics data, and the correlations between lncRNA expression and clinical features were analyzed using a weighted gene coexpression network analysis (WGCNA). Six cancer specific lncRNAs from the ceRNA network were randomly selected to detect their expression in 32 paired MIBC tissue samples and 5 bladder cancer cell lines using quantitative real-time polymerase chain reaction (qRT-PCR).ResultsThe ceRNA network was constructed with 30 lncRNAs, 13 miRNAs and 32 mRNAs. Seventeen lncRNAs in the ceRNA network correlated with certain clinical features, and only 1 lncRNA (MIR137HG) correlated with the overall survival (OS) of patients with MIBC (log-rank test P<0.05). GO and KEGG analyses revealed roles for the potential mRNA targets of MIR137HG in epithelial cell differentiation and the peroxisome proliferator-activated receptor (PPAR) and tumor necrosis factor (TNF) signaling pathways. The expression data from TCGA were highly consistent with the verification results of the MIBC tissue samples and bladder cancer cell lines.ConclusionThese findings improve our understanding of the regulatory mechanism of the lncRNA-miRNA-mRNA ceRNA network and reveal potential lncRNAs as prognostic biomarkers of MIBC.

Dataset Information

Bladder cancer-associated protein, a potential prognostic biomarker in human bladder cancer.

Publications

Bladder cancer-associated protein, a potential prognostic biomarker in human bladder cancer.

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