RCDB: Renal Cancer Gene Database

A novel immune-related lncRNA signature predicts the prognosis and immune landscape in ccRCC

BACKGROUND

As one of the most common tumors, the pathogenesis and progression of clear cell renal cell carcinoma (ccRCC) in the immune microenvironment are still unknown.

METHODS

The differentially expressed immune-related lncRNA (DEirlncRNA) was screened through co-expression analysis and the limma package of R, which based on the ccRCC project of the TCGA database. Then, we designed the risk model by irlncRNA pairs. In RCC patients, we have compared the area under the curve, calculated the Akaike Information Criterion (AIC) value of the 5-year receiver operating characteristic curve, determined the cut-off point, and established the optimal model for distinguishing the high-risk group from the low-risk group. We used the model for immune system assessment, immune point detection and drug sensitivity analysis after verifying the feasibility of the above model through clinical features.

RESULTS

In our study, 1541 irlncRNAs were included. 739 irlncRNAs were identified as DEirlncRNAs to construct irlncRNA pairs. Then, 38 candidate DEirlncRNA pairs were included in the best risk assessment model through improved LASSO regression analysis. As a result, we found that in addition to age and gender, T stage, M stage, N stage, grade and clinical stage are significantly related to risk. Moreover, univariate and multivariate Cox regression analysis results reveals that in addition to gender, age, grade, clinical stage and risk score are independent prognostic factors. The results show that patients in the high-risk group are positively correlated with tumor infiltrating immune cells when the above model is applied to the immune system. But they are negatively correlated with endothelial cells, macrophages M2, mast cell activation, and neutrophils. In addition, the risk model was positively correlated with overexpressed genes (CTLA, LAG3 and SETD2, P<0.05). Finally, risk models can also play as an important role in predicting the sensitivity of targeted drugs.

CONCLUSIONS

The new risk model may be a new method to predict the prognosis and immune status of ccRCC.

Coiled-coil domain containing 25 (CCDC25) regulates cell proliferation, migration, and invasion in clear cell renal cell carcinoma by targeting the ILK-NF-κB signaling pathway

Increasing evidence has demonstrated that the expression of coil domains containing 25 (CCDC25) in various malignancies is abnormally high. However, the potential regulatory role and mechanism of CCDC25 in the development of clear cell renal cell carcinoma (ccRCC) are still unclear. In this experiment, we combined in vitro experiments such as wound healing, CCK8, and transwell assay with in vivo experiments on tumor formation in nude mice to evaluate the effect of CCDC25 on the proliferation, migration, and invasion of renal cancer cells. In addition, we also used Western blotting and qPCR to evaluate the role of CCDC25 in activating the integrin-linked kinase (ILK)-NF-κB signaling pathway. Here, we demonstrate that compared to normal tissues and cell lines, CCDC25 is overexpressed in both human ccRCC tissues and cell lines. After CCDC25 knockdown, it has obvious inhibitory effect on the proliferation, migration, and invasion of cancer cells in vitro and in vivo. In contrast, CCDC25 overexpression promotes these effects. Additionally, we also discovered that CCDC25 interacts with ILK and coordinates the activation of the NF-κB signaling pathway downstream. Generally, our study suggests that CCDC25 plays a vital role in the development of ccRCC, which also means that it may be a potential therapeutic target for ccRCC.

Investigation of pathogenic germline variants in gastric cancer and development of "GasCanBase" database

BACKGROUND

Gastric cancer, which is also known as stomach cancer, can be influenced by both germline and somatic mutations. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) in germline have long been reported to play a pivotal role in cancer progression.

AIM

The aim of this study is to examine the nsSNP in GC-associated genes. The study also aims to develop a database with extensive information regarding the nsSNPs in the GC-associated genes and their impacts.

METHODS AND RESULTS

A total of 34,588 nsSNPs from 1,493,460 SNPs of the 40 genes were extracted from the available SNP database. Drug binding and energy minimization were examined by molecular docking and YASARA. To validate the existence of the germline CDH1 gene mutation (rs34466743) in the isolated blood DNA of gastric cancer (GC) patients, polymerase chain reaction (PCR) and DNA sequencing were performed. According to the results of the gene network analysis, 17 genes may interact with other types of cancer. A total of 11,363 nsSNPs were detected within the 40 GC genes. Among these, 474 nsSNPs were predicted to be damaging and 40 to be the most damaging. The SNPs in domain regions were thought to be strong candidates that alter protein functions. Our findings proposed that most of the selected nsSNPs were within the domains or motif regions. Free Energy Deviation calculation of protein structure pointed toward noteworthy changes in the structure of each protein that can demolish its natural function. Subsequently, drug binding confirmed the structural variation and the ineffectiveness of the drug against the mutant model in individuals with these germline variants. Furthermore, in vitro analysis of the rs34466743 germline variant from the CDH1 gene confirmed the strength and robustness of the pipeline that could expand the somatic alteration for causing cancer. In addition, a comprehensive gastric cancer polymorphism database named "GasCanBase" was developed to make data available to researchers.

CONCLUSION

The findings of this study and the "GasCanBase" database may greatly contribute to our understanding of molecular epidemiology and the development of precise therapeutics for gastric cancer. GasCanBase is available at: https://www.gascanbase.com/.

A critical review of datasets and computational suites for improving cancer theranostics and biomarker discovery

Cancer has been constantly evolving and so is the research pertaining to cancer diagnosis and therapeutic regimens. Early detection and specific therapeutics are the key features of modern cancer therapy. These requirements can only be fulfilled with the integration of diverse high-throughput technologies. Integration of advanced omics methodology involving genomics, epigenomics, proteomics, and transcriptomics provide a clear understanding of multi-faceted cancer. In the past few years, tremendous high-throughput data have been generated from cancer genomics and epigenomic analyses, which on further methodological analyses can yield better biological insights. The major epigenetic alterations reported in cancer are DNA methylation levels, histone post-translational modifications, and epi-miRNA regulating the oncogenes and tumor suppressor genes. While the genomic analyses like gene expression profiling, cancer gene prediction, and genome annotation divulge the genetic alterations in oncogenes or tumor suppressor genes. Also, systems biology approach using biological networks is being extensively used to identify novel cancer biomarkers. Therefore, integration of these multi-dimensional approaches will help to identify potential diagnostic and therapeutic biomarkers. Here, we reviewed the critical databases and tools dedicated to various epigenomic and genomic alterations in cancer. The review further focuses on the multi-omics resources available for further validating the identified cancer biomarkers. We also highlighted the tools for cancer biomarker discovery using a systems biology approach utilizing genomic and epigenomic data. Biomarkers predicted using such integrative approaches are shown to be more clinically relevant.

A regulatory circuit of lncRNA NLGN1-AS1 and Wnt signalling controls clear cell renal cell carcinoma phenotypes through FZD4-modulated pathways

BACKGROUND

Recent evidence has indicated that long non-coding RNAs (lncRNAs) were emerged as key molecules in clear cell renal cell carcinoma (ccRCC). TCGA database showed that the expression level of lncRNA NLGN1-AS1 was up-regulated in ccRCC; However, whether NLGN1-AS1 implicated in the malignant progression of ccRCC remained unclear.

METHODS

Based on TCGA database, candidate lncRNAs were selected and quantitative real-time PCR (qRT-PCR) was utilized to verify the expression levels of candidate lncRNAs in human ccRCC tissues. Loss-of-function experiments were performed to examine the biological functions of NLGN1-AS1 both in vitro and in vivo. According to bioinformatics analysis, fluorescence reporter assays and rescue experiments, the underlying mechanisms of NLGN1-AS1 in ccRCC cell lines were so clearly understood.

RESULTS

As a novel lncRNA, NLGN1-AS1 was up-regulated in ccRCC cell lines and associated with poor prognosis of and ccRCC patients, which was correlated with the progression of ccRCC. Functionally, the down-regulation of NLGN1-AS1 significantly decreased the proliferation of ccRCC cells both in vitro and in vivo. Bioinformatics analysis and luciferase report assays identified that miR-136-5p was a direct target of NLGN1-AS1. We also determined that FZD4 were inhibitory targets of miR-136-5p, and that Wnt/β-catenin signaling was inhibited by both NLGN1-AS1 knockdown and miR-136-5p over-expression. In addition, we found that the suppression of proliferation and the inhibition of Wnt/β-catenin pathway induced by NLGN1-AS1 knockdown would require the over-expression of FZD4.

CONCLUSIONS

Our findings suggested that lncRNA NLGN1-AS1 could promote the progression of ccRCC by targeting miR-136-5p/FZD4 and Wnt/β-catenin pathway, and might serve as a novel potential therapeutic target to inhibit the progression of ccRCC.

Identification of Immune-Related Subtypes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma

Background: Tumor microenvironment (TME) plays indisputable role in the progression of cancers. Immune cell infiltration (ICI) in TME was related to the prognosis of tumor patients. In this paper, we identified the pattern of immune-related ICI subtypes based on the TME immune infiltration pattern.

Methods: The data from kidney renal clear cell carcinoma data (KIRC) was downloaded from the TCGA database. The distinct ICI subtypes were identified using CIBERSORT and ESTIMATE algorithms. The gene subgroups were identified based on DEGs in ICI subtypes. The single sample gene set enrichment analysis (ssGSEA) was used to ascertain the ICI score. Kaplan-Meier curve with log-rank test was conducted to analyze the survival probability of patients with KIRC in different subtypes.

Results: The patients with high ICI scores exhibited a longer survival time and lower expression of checkpoint-related and immune activity-related genes. The high ICI score clusters were positively related to TMB. The patients in the low TMB subgroups have a favorable prognosis. The prediction ICI score did not affect the TMB status, and the low TMB subgroups + low/high ICI score subgroups exhibited better survival.

Conclusion: In all, the tumor immune microenvironment, ICI score, and TMB were important determinants of KIRC patients’ survival outcomes. The TMB + ICI score may be a potential biomarker for predicting the prognosis of patients and for targeted immunotherapies to treating KIRC.

Propofol Disrupts Clear Cell Renal Cell Carcinoma Tumorigenesis by Regulating circFBXW7/miR-942 Axis

<b><i>Background:</i></b> Propofol is a commonly used intravenous anesthetic and has been found to perform anticancer effects in many cancers. However, the effects and mechanisms of propofol in clear cell renal cell carcinoma (ccRCC) remain largely undefined. <b><i>Methods:</i></b> The expression of circular RNA FBXW7 (circFBXW7) and miR-942 was detected by qRT-PCR. Cell proliferation, apoptosis, migration, and invasion capacities were analyzed using cell counting kit-8, colony formation, flow cytometry, and transwell assays, respectively. Western blot was used to detect the expression levels of PCNA, Cleaved-caspase 3 and MMP protein. The bindings between miR-942 and circFBXW7 were verified using RNA pull-down, dual-luciferase reporter, and RIP assays. Xenograft tumor analysis was employed to detect tumorigenesis in vivo. <b><i>Results:</i></b> Propofol alleviated cell proliferation, migration, invasion, and induced apoptosis in vitro and impeded tumor growth in vivo in ccRCC. Propofol elevated the level of circFBXW7, which knockdown reversed the anticancer effects of propofol on ccRCC cell tumorigenesis. CircFBXW7 directly bound to miR-942, and suppressed ccRCC cell malignant biological behaviors via targeting miR-942. Besides that, propofol decreased miR-942 expression, and miR-942 overexpression attenuated the effects of propofol on ccRCC cells. Moreover, propofol could regulate miR-942 expression through circFBXW7. <b><i>Conclusion:</i></b> Propofol suppressed the growth, migration, and invasion of ccRCC cells by regulating circFBXW7/miR-942 axis, suggesting a potential therapeutic strategy for the intervention of human ccRCC development.

Long non-coding RNA MEG8 induced by PLAG1 promotes clear cell renal cell carcinoma through the miR-495-3p/G3BP1 axis

Clear cell renal cell carcinoma (ccRCC) is recognized as one of the most lethal malignancies among the urological system, with constantly increasing mortality. While the molecular mechanisms underlying ccRCC progression are still poorly understood, the molecular and functional role of lncRNA in multiple diseases has been well demonstrated. In this study, we hypothesized that lncRNA MEG8 might participate in ccRCC development. At first, we found that MEG8 expression was increased in ccRCC tumor tissues and cells. Next, we demonstrated that MEG8 knockdown suppressed cell viability, migration, and invasion in vitro and inhibited tumor growth in vivo. Subsequently, we utilized bioinformatics analysis, ChIP, and luciferase assays, and we found that PLAG1 could transcriptionally regulate MEG8 in ccRCC cells. Furthermore, MEG8 promoted G3BP1 expression to aggravate ccRCC tumorigenic properties through sponging miR-495-3p. Our study identified a novel PLAG1/MEG8/miR-495-3p/G3BP1 network in ccRCC development, which might be a promising direction for developing new diagnoses or therapeutic agents for ccRCC.

A comprehensive review of online resources for microRNA-diseases associations: the state of the art

MicroRNAs (miRNAs) as small 19- to 24-nucleotide noncoding RNAs regulate several mRNA targets and signaling pathways. Therefore, miRNAs are considered key regulators in cellular pathways as well as various pathologies. There is substantial interest in the relationship between disease and miRNAs, which made that one of the important research topics. Interestingly, miRNAs emerged as an attractive approach for clinical application, not only as biomarkers for diagnosis and prognosis or in the prediction of therapy response but also as therapeutic tools. For these purposes, the identification of crucial miRNAs in disease is very important. Databases provided valuable experimental and computational miRNAs-disease information in an accessible and comprehensive manner, such as miRNA target genes, miRNA related in signaling pathways and miRNA involvement in various diseases. In this review, we summarized miRNAs-disease databases in two main categories based on the general or specific diseases. In these databases, researchers could search diseases to identify critical miRNAs and developed that for clinical applications. In another way, by searching particular miRNAs, they could recognize in which disease these miRNAs would be dysregulated. Despite the significant development that has been done in these databases, there are still some limitations, such as not being updated and not providing uniform and detailed information that should be resolved in future databases. This survey can be helpful as a comprehensive reference for choosing a suitable database by researchers and as a guideline for comparing the features and limitations of the database by developer or designer. Short abstract We summarized miRNAs-disease databases that researchers could search disease to identify critical miRNAs and developed that for clinical applications. This survey can help choose a suitable database for researchers.

CHDGKB: a knowledgebase for systematic understanding of genetic variations associated with non-syndromic congenital heart disease

Congenital heart disease (CHD) is one of the most common birth defects, with complex genetic and environmental etiologies. The reports of genetic variation associated with CHD have increased dramatically in recent years due to the revolutionary development of molecular technology. However, CHD is a heterogeneous disease, and its genetic origins remain inconclusive in most patients. Here we present a database of genetic variations for non-syndromic CHD (NS-CHD). By manually literature extraction and analyses, 5345 NS-CHD-associated genetic variations were collected, curated and stored in the public online database. The objective of our database is to provide the most comprehensive updates on NS-CHD genetic research and to aid systematic analyses of pathogenesis of NS-CHD in molecular level and the correlation between NS-CHD genotypes and phenotypes. Database URL: http://www.sysbio.org.cn/CHDGKB/.

Dysregulation of Long Non-coding RNAs and mRNAs in Plasma of Clear Cell Renal Cell Carcinoma Patients Using Microarray and Bioinformatic Analysis

Objective: The roles of long non-coding RNAs (lncRNAs) in the diagnosis of clear cell renal cell carcinoma (ccRCC) are still not well-defined. We aimed to identify differentially expressed lncRNAs and mRNAs in plasma of ccRCC patients and health controls systematically.

Methods: Expression profile of plasma lncRNAs and mRNAs in ccRCC patients and healthy controls was analyzed based on microarray assay. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-based approaches were used to investigate biological function and signaling pathways mediated by the differentially expressed mRNAs. SOCS2-AS1 was selected for validation using Real-Time PCR. The differentially expressed lncRNAs and mRNAs were further compared with E-MTAB-1830 datasets using Venn and the NetworkAnalyst website. The GEPIA and ULCAN websites were utilized for the evaluation of the expression level of differentially expressed mRNA and their association with overall survival (OS).

Results: A total of 3,664 differentially expressed lncRNAs were identified in the plasma of ccRCC patients, including 1,511 up-regulated and 2,153 down-regulated lncRNAs (fold change ≥2 and P < 0.05), respectively. There were 2,268 differentially expressed mRNAs, including 932 up-regulated mRNAs and 1,336 down-regulated mRNAs, respectively (fold change ≥2 and P < 0.05). Pathway analysis based on deregulated mRNAs was mainly involved in melanogenesis and Hippo signaling pathway (P < 0.05). In line with the lncRNA microarray findings, the SOCS2-AS1 was down-regulated in ccRCC plasma and tissues, as well as in cell lines. Compared with the E-MTAB-1830 gene expression profiles, we identified 18 lncRNAs and 87 mRNAs differently expressed in both plasma and neoplastic tissues of ccRCC. The expression of 10 mRNAs (EPB41L4B, CCND1, GGT1, CGNL1, CYSLTR1, PLAUR, UGT3A1, PROM2, MUC12, and PCK1) was correlated with the overall survival (OS) rate in ccRCC patients based on the GEPIA and ULCAN websites.

Conclusions: We firstly reported differentially expressed lncRNAs in ccRCC patients and healthy controls systemically. Several differentially expressed lncRNAs and mRNAs were identified, which might serve as diagnostic or prognostic markers. The biological function of these lncRNAs and mRNAs should be further validated. Our study may contribute to the future treatment of ccRCC and provide novel insights into cancer biology.

The oncogenic role of MUC12 in RCC progression depends on c-Jun/TGF-β signalling

Renal cell carcinoma (RCC) is a common kidney cancer worldwide. Even though current treatments show promising therapeutic effectiveness, metastatic RCC still has limited therapeutic options so that novel treatments were urgently needed. Here, we identified that MUC12 was overexpressed in RCC patients and served as poor prognostic factor for RCC progression. Overexpression of MUC12 increased RCC cell growth and cell invasion while deficiency of MUC12 exerted opposite effects on RCC cells. Mechanistic dissection demonstrated that MUC12-mediated RCC cell growth and cell invasion were dependent of TGF-β1 signalling because they could be blocked in the presence of TGF-β1 inhibitor. Moreover, the regulation of TGF-β1 by MUC12 relied on the transactivation of c-Jun. MUC12 promoted the recruitment of c-Jun on the promoter of TGF-β1, leading to its transcription. Importantly, knockdown of c-Jun also attenuated MUC12-mediated TGF-β1 induction and RCC cell invasion. In summary, our study defines the role of MUC12 in RCC progression and provides rational to develop novel targeted therapy to battle against RCC.

Integrated Analysis of Three Publicly Available Gene Expression Profiles Identified Genes and Pathways Associated with Clear Cell Renal Cell Carcinoma

BACKGROUND Although advances have been achieved in the therapy of clear cell renal cell carcinoma (ccRCC), the pathogenesis of ccRCC is not yet fully understood. This study aimed to explore the critical genes and pathways associated with ccRCC by meta-analysis. MATERIAL AND METHODS We performed an integrated analysis of 3 publicly available microarray datasets developed from ccRCC tumor samples and normal tissues. A list of overlapped differentially expressed genes (DEGs) with the consistent expression trend in ccRCC tumor samples were identified, for which the protein-protein interaction (PPI) network was constructed, followed by topology structure and module analysis. The microRNA (miRNA) regulatory network and ccRCC associated pathway network were reconstructed. RESULTS A total of 504 genes were found to be consistently and differentially regulated based on 3 microarray datasets. The overrepresented pathways for DEGs included citric acid cycle (TCA cycle) and peroxisome proliferator-activated receptor (PPAR) signaling pathway and cell cycle. The PPI network was clustered into 6 modules that were closely related with the M phase, desmosome assembly, and response to hormone stimulus. The hsa04110: cell cycle and hsa04510: focal adhesion were the significant pathways associated with ccRCC overlapped with enrichment analysis. KDR and ITGB4 were focal-adhesion-associated genes, which were regulated by has-miR-424 and has-miR-204, respectively. CCND2 and CCNA2 were cell-cycle-associated genes, which were regulated by hsa-miR-324-3p, hsa-miR-146a and hsa-miR-145. CONCLUSIONS Cell cycle and focal adhesion were dysregulated in ccRCC, which were associated with the expression of CCND2, ITGB4, KDR, and CCNA2 genes. The deregulation of pathways and associated genes may provide insights to ccRCC research and therapy.

Discovery and validation of the prognostic value of the lncRNAs encoding snoRNAs in patients with clear cell renal cell carcinoma

Some lncRNAs can encode small nucleolar RNAs (snoRNAs), called small nucleolar RNA host genes (SNHGs), which have exerted certain predictive values for the prognosis of some cancer patients. In this study, using RNA-seq and survival data in TCGA-KIRC, we examined the expression profile of 20 SNHGs and explored their prognostic values in ccRCC. Results showed that SNHG1, GAS5, SNHG3-8, SNHG11, SNHG12, SNHG15-17, SNHG20, SNHG22 and SNHG25 were significantly upregulated in ccRCC tissues compared with adjacent normal tissues. After adjustment for confounding factors, the multivariate analysis confirmed that increased SNHG3 expression was independently associated with shorter OS, while increased SNHG15 expression was an independent predictor of shorter RFS. Using the methylation data, the methylation status of 2 CpG sites (cg07807470 and cg15161854) and 2 CpG sites (cg00953154 and cg16459265) were negatively correlated with SNHG3 and SNHG15 expression, respectively. Moreover, low methylation levels of the 4 CpG sites were significantly associated with shorter OS. Furthermore, we validated the expression patterns, methylation status and prognostic value of SNHG3 and SNHG15 using clinical ccRCC samples. Taken together, SNHG3 and SNHG15 might be valuable prognostic markers in ccRCC, and DNA hypomethylation might play an important role in elevated SNHG3 and SNHG15 transcription in ccRCC.

FOXM1-Activated LINC01094 Promotes Clear Cell Renal Cell Carcinoma Development via MicroRNA 224-5p/CHSY1

Clear cell renal cell carcinoma (ccRCC) is regarded as the most aggressive subtype of RCC, with high rates of metastasis and recurrence. An extensive body of studies had proved long noncoding RNAs (lncRNAs) play pivotal parts in the development and evolution of diverse malignant tumors. However, the potential of LINC01094 in ccRCC tumorigenesis is still unexplored. In the present research, with the aid of the TCGA database, we found that LINC01094 was highly expressed in ccRCC tissues. Upregulation of LINC01094 was also confirmed in ccRCC cell lines, and functional experiments delineated that LINC01094 knockdown led to inhibition on ccRCC cell growth and metastasis. Moreover, LINC01094 was activated by FOXM1 at the transcriptional level. Further assay demonstrated that LINC01094 worked as a sponge of microRNA 224-5p (miR-224-5p) and CHSY1 was a miR-224-5p-targeted mRNA. Further, we verified that LINC01094 acted as a competing endogenous RNA in ccRCC to regulate CHSY1 expression via competitively bind to miR-224-5p. Lastly, our results expounded that LINC01094 exerted its tumor-promoting performance in ccRCC development through miR-224-5p/CHSY1 regulatory axis, which shed light on the molecular mechanism underlying LINC01094 in ccRCC and opened a new prospective for the treatment of ccRCC.

DiPhiSeq: robust comparison of expression levels on RNA-Seq data with large sample sizes

MOTIVATION

In the analysis of RNA-Seq data, detecting differentially expressed (DE) genes has been a hot research area in recent years and many methods have been proposed. DE genes show different average expression levels in different sample groups, and thus can be important biological markers. While generally very successful, these methods need to be further tailored and improved for cancerous data, which often features quite diverse expression in the samples from the cancer group, and this diversity is much larger than that in the control group.

RESULTS

We propose a statistical method that can detect not only genes that show different average expressions, but also genes that show different diversities of expressions in different groups. These 'differentially dispersed' genes can be important clinical markers. Our method uses a redescending penalty on the quasi-likelihood function, and thus has superior robustness against outliers and other noise. Simulations and real data analysis demonstrate that DiPhiSeq outperforms existing methods in the presence of outliers, and identifies unique sets of genes.

AVAILABILITY AND IMPLEMENTATION

DiPhiSeq is publicly available as an R package on CRAN: https://cran.r-project.org/package=DiPhiSeq.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A positive feed-forward loop between LncRNA-URRCC and EGFL7/P-AKT/FOXO3 signaling promotes proliferation and metastasis of clear cell renal cell carcinoma

Background

The aberrant expression of long noncoding RNAs (lncRNAs) has recently emerged as key molecules in human cancers; however, whether lncRNAs are implicated in the progression of clear cell renal cell carcinoma (ccRCC) remains unclear.

Methods

Candidate lncRNAs were selected using microarray analysis and quantitative real-time PCR (qRT-PCR) was performed to detect lncRNAs expression in human ccRCC tissues. Overexpression and knocking down experiments in vivo and in vitro were performed to uncover the biological roles of lncRNA-URRCC on ccRCC cell proliferation and invasion. Microarray, chromatin immunoprecipitation, Luciferase reporter assay and western blot were constructed to investigate the molecular mechanisms underlying the functions of lncRNA-URRCC.

Results

The microarray analysis and qRT-PCR identified a new lncRNA, URRCC, whose expression is upregulated in RCC samples and associated with poor prognosis, leading to promote ccRCC cell proliferation and invasion. Mechanistically, URRCC enhances the expression of EGFL7 via mediating histone H3 acetylation of EGFL7 promoter, activation of P-AKT signaling, and suppressing P-AKT downstream gene, FOXO3. In return, FOXO3 could inhibit the transcription of URRCC via binding to the special region on the promoter of URRCC.

Conclusions

Our data suggests that targeting this newly identified feed-back loop between LncRNA-URRCC and EGFL7/P-AKT/FOXO3 signaling may enhance the efficacy of existing therapy and potentially imparts a new avenue to develop more potent therapeutic approaches to suppress RCC progression.

Electronic supplementary material

The online version of this article (10.1186/s12943-019-0998-y) contains supplementary material, which is available to authorized users.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

ESCC ATLAS: A population wide compendium of biomarkers for Esophageal Squamous Cell Carcinoma

Esophageal cancer (EC) is the eighth most aggressive malignancy and its treatment remains a challenge due to the lack of biomarkers that can facilitate early detection. EC is identified in two major histological forms namely - Adenocarcinoma (EAC) and Squamous cell carcinoma (ESCC), each showing differences in the incidence among populations that are geographically separated. Hence the detection of potential drug target and biomarkers demands a population-centric understanding of the molecular and cellular mechanisms of EC. To provide an adequate impetus to the biomarker discovery for ESCC, which is the most prevalent esophageal cancer worldwide, here we have developed ESCC ATLAS, a manually curated database that integrates genetic, epigenetic, transcriptomic, and proteomic ESCC-related genes from the published literature. It consists of 3475 genes associated to molecular signatures such as, altered transcription (2600), altered translation (560), contain copy number variation/structural variations (233), SNPs (102), altered DNA methylation (82), Histone modifications (16) and miRNA based regulation (261). We provide a user-friendly web interface ( http://www.esccatlas.org , freely accessible for academic, non-profit users) that facilitates the exploration and the analysis of genes among different populations. We anticipate it to be a valuable resource for the population specific investigation and biomarker discovery for ESCC.

ESCC ATLAS: A population wide compendium of biomarkers for Esophageal Squamous Cell Carcinoma

Esophageal cancer (EC) is the eighth most aggressive malignancy and its treatment remains a challenge due to the lack of biomarkers that can facilitate early detection. EC is identified in two major histological forms namely - Adenocarcinoma (EAC) and Squamous cell carcinoma (ESCC), each showing differences in the incidence among populations that are geographically separated. Hence the detection of potential drug target and biomarkers demands a population-centric understanding of the molecular and cellular mechanisms of EC. To provide an adequate impetus to the biomarker discovery for ESCC, which is the most prevalent esophageal cancer worldwide, here we have developed ESCC ATLAS, a manually curated database that integrates genetic, epigenetic, transcriptomic, and proteomic ESCC-related genes from the published literature. It consists of 3475 genes associated to molecular signatures such as, altered transcription (2600), altered translation (560), contain copy number variation/structural variations (233), SNPs (102), altered DNA methylation (82), Histone modifications (16) and miRNA based regulation (261). We provide a user-friendly web interface ( http://www.esccatlas.org , freely accessible for academic, non-profit users) that facilitates the exploration and the analysis of genes among different populations. We anticipate it to be a valuable resource for the population specific investigation and biomarker discovery for ESCC.

HMGB1/RAGE axis mediates the apoptosis, invasion, autophagy, and angiogenesis of the renal cell carcinoma

Background

High mobility group box 1 protein (HMGB1) is a sort of non-histone protein in chromatin, which plays an important role in tumor proliferation, invasion, and immune escape. HMGB1-RAGE (receptor for advanced glycation end products) interactions have been reported to be important in a number of cancers.

Methods

CCK8, flow cytometry and qRT-PCR were used to detected cell viability, apoptosis and gene expression, respectively.

Results

In the present study, we demonstrated that HMGB1/RAGE axis regulated the cell proliferation, apoptosis, and invasion of the renal cell carcinoma (RCC). Further, we discovered that HMGB1/RAGE axis increased the expression of autophagic proteins LC3 and Beclin-1 in RCC. Finally, we used a coculture model of human umbilical vein endothelial cells with RCC cell lines to find out that HMGB1 also increased the expression of VEGF and VEGFR2 in human umbilical vein endothelial cells. An in vivo study further confirmed that HMGB1 knockdown inhibited RCC tumor growth.

Conclusion

Our results illustrated that HMGB1/RAGE axis mediated RCC cell viability, apoptosis, invasion, autophagy, and angiogenesis, which provides a novel theoretical basis for using HMGB1 as the target in RCC.

Infiltrating macrophages increase RCC epithelial mesenchymal transition (EMT) and stem cell-like populations via AKT and mTOR signaling

Infiltrating macrophages are a key component of inflammation during tumorigenesis and progression. However, the role of macrophages in renal cell carcinoma (RCC), especially in the stage of RCC malignant progression, is still unclear. Here, we found the macrophages could be recruited more easily into RCC tissues than the surrounding non-tumor tissues. In vitro co-culture system also confirmed RCC cells had a better capacity to recruit macrophages via CXCL8 signaling than normal renal epithelial cells. The consequences of recruiting more macrophages may then increase RCC cells invasion abilities. Mechanism dissection revealed that infiltrating macrophages could function through induction of epithelial-mesenchymal transition and increased cancer stem cell-like populations via activation of AKT/mTOR signal, and then led to increasing RCC cells invasion. The orthotopically xenografted mouse model with RCC cells and macrophages also confirmed that infiltrating macrophages could increase RCC cells progression via AKT/mTOR signal. Together, our results reveal a new mechanism that macrophages in the RCC tumor microenvironment could increase RCC metastasis via activation of the AKT/mTOR signals. Targeting this newly identified signaling may help us to better inhibit RCC metastasis.

Long non-coding RNA H19 regulates E2F1 expression by competitively sponging endogenous miR-29a-3p in clear cell renal cell carcinoma

Background

Numerous recent studies indicate that the long non-coding RNAs (lncRNAs) are frequently abnormal expressed and take critical roles in many cancers. Renal cell carcinoma is the secondary malignant tumors in the urinary system and has high mortality and morbidity. Around 80% of RCCs is clear cell renal cell carcinoma (ccRCC) and is characterized by high metastasis and relapse rate. However, the clinical significances of lncRNAs in ccRCC are still unknown.

Methods

The human cancer lncRNA PCR array (Yingbio) was performed to detect the differentially expressed lncRNAs in human ccRCC samples. Real-time PCR (RT-PCR), dual-luciferase assay, RNA binding protein immunoprecipitation (RIP) assay, transwell assay, CCK-8 assay, and western blot were performed to explore the molecular mechanism of lncRNAs in ccRCC cell migration and invasion.

Results

In this study, lncRNA-H19 was high expressed and negatively correlated with miR-29a-3p in ccRCC. By bioinformatics software, dual-luciferase reporter and RIP assays, we verified that miR-29a-3p was identified as a direct target of lncRNA-H19. RT-PCR and western blot demonstrated that down-regulated lncRNA-H19 could affect the expression of miR-29a-3p targeting E2F1 with competitively binding miR-29a-3p. Furthermore, transwell assays indicated that lncRNA-H19 knockdown inhibited cells migration and invasion, but this effect was attenuated by co-transfection of lncRNA-H19 siRNA and miR-29a-3p inhibitor. Over expression of E2F1 could rescue lncRNA-H19 siRNA induced suppression on cell migration and invasion in ccRCC cells.

Conclusions

These results show a possible competing endogenous RNAs regulatory network involving lncRNA-H19 regulates E2F1 expression by competitively sponging endogenous miR-29a-3p in ccRCC. This mechanism may contribute to a better understanding of ccRCC pathogenesis, and lncRNA-H19 may be further considered as a potential therapeutic target for ccRCC intervention.

Everolimus suppresses invasion and migration of renal cell carcinoma by inhibiting FAK activity and reversing epithelial to mesenchymal transition in vitro and in vivo

Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults and the major cause of mortality in urological cancer. Most patients with RCC are asymptomatic until the disease is advanced and unresectable. In this situation, systemic therapy with immunotherapy or molecularly targeted therapy agents play an important role in therapeutic strategy. Everolimus (EVE), an m-TOR inhibitor, has the potential to inhibit tumor progression at multiple levels and is indicated for the treatment of advanced RCC in patients whose disease has metastasis. In this study, we provide molecular evidence associated with the antimetastatic effect of everolimus by demonstrating the suppression of lung metastasis of 786-O cells in mouse model. This effect was associated with reduced protein expressions of p-FAK (Tyr 925), p-Src (Tyr416), Vimentin, and RhoA and also with increased the E-cadherin protein expression. In summary, these findings provide new insights into the molecular mechanisms involved in the antimetastatic effect of everolimus and are thus valuable in the treatment of metastatic RCC.

LncRNA-SARCC suppresses renal cell carcinoma (RCC) progression via altering the androgen receptor(AR)/miRNA-143-3p signals

While the androgen receptor (AR) might promote renal cell carcinoma (RCC) initiation and progression, the molecular mechanisms involved remain largely unclear. Here, we discovered the novel LncRNA-SARCC, which was suppressed and associated with better prognosis in RCC. Preclinical studies using multiple RCC cells and in vivo mouse model indicated that LncRNA-SARCC could attenuate RCC cell invasion, migration and proliferation in vitro and in vivo. Mechanistically, LncRNA-SARCC bound and destabilized AR protein with an inhibition of AR function, which led to transcriptionally de-repress miR-143-3p expression, thus inhibition of its downstream signals including AKT, MMP-13, K-RAS and P-ERK. In addition, bisulfite sequencing analysis substantiated that LncRNA-SARCC promoter was highly methylated in renal cancer tissues compared with paired non-cancerous renal tissues. Notably, treating with Sunitinib, the multi-targeted receptor tyrosine kinase inhibitor, increased the expression of LncRNA-SARCC, which decreased RCC cells resistance to Sunitinib. Thus, our study presented a road map for targeting this newly identified LncRNA-SARCC and its pathway, which expands potential therapeutic strategies for RCC treatment.

Androgen receptor (AR) suppresses miRNA-145 to promote renal cell carcinoma (RCC) progression independent of VHL status

Mutational inactivation of the VHL tumor suppressor plays key roles in the development of renal cell carcinoma (RCC), and mutated VHL-mediated VEGF induction has become the main target for the current RCC therapy. Here we identified a signal pathway of VEGF induction by androgen receptor (AR)/miRNA-145 as a new target to suppress RCC progression. Mechanism dissection revealed that AR might function through binding to the androgen receptor element (ARE) located on the promoter region of miRNA-145 to suppress p53's ability to induce expression of miRNA-145 that normally suppresses expression of HIF2α/VEGF/MMP9/CCND1. Suppressing AR with AR-shRNA or introducing exogenous miRNA-145 mimic can attenuate RCC progression independent of VHL status. MiR-145 mimic in preclinical RCC orthotopic xenograft mouse model revealed its efficacy in suppression of RCC progression. These results together identified signals by AR-suppressed miRNA-145 as a key player in the RCC progression via regulating HIF2α/VEGF/MMP9/CCND1 expression levels. Blockade of the newly identified signal by AR inhibition or miRNA-145 mimics has promising therapeutic benefit to suppress RCC progression.

India's Computational Biology Growth and Challenges

India's computational science is growing swiftly due to the outburst of internet and information technology services. The bioinformatics sector of India has been transforming rapidly by creating a competitive position in global bioinformatics market. Bioinformatics is widely used across India to address a wide range of biological issues. Recently, computational researchers and biologists are collaborating in projects such as database development, sequence analysis, genomic prospects and algorithm generations. In this paper, we have presented the Indian computational biology scenario highlighting bioinformatics-related educational activities, manpower development, internet boom, service industry, research activities, conferences and trainings undertaken by the corporate and government sectors. Nonetheless, this new field of science faces lots of challenges.

CoReCG: a comprehensive database of genes associated with colon-rectal cancer

Cancer of large intestine is commonly referred as colorectal cancer, which is also the third most frequently prevailing neoplasm across the globe. Though, much of work is being carried out to understand the mechanism of carcinogenesis and advancement of this disease but, fewer studies has been performed to collate the scattered information of alterations in tumorigenic cells like genes, mutations, expression changes, epigenetic alteration or post translation modification, genetic heterogeneity. Earlier findings were mostly focused on understanding etiology of colorectal carcinogenesis but less emphasis were given for the comprehensive review of the existing findings of individual studies which can provide better diagnostics based on the suggested markers in discrete studies.

Colon Rectal Cancer Gene Database (CoReCG), contains 2056 colon-rectal cancer genes information involved in distinct colorectal cancer stages sourced from published literature with an effective knowledge based information retrieval system. Additionally, interactive web interface enriched with various browsing sections, augmented with advance search facility for querying the database is provided for user friendly browsing, online tools for sequence similarity searches and knowledge based schema ensures a researcher friendly information retrieval mechanism.

Colorectal cancer gene database (CoReCG) is expected to be a single point source for identification of colorectal cancer-related genes, thereby helping with the improvement of classification, diagnosis and treatment of human cancers.

Database URL: lms.snu.edu.in/corecg

Web-based tools for microRNAs involved in human cancer

MicroRNAs (miRNAs/miRs) are a family of small, endogenous and evolutionarily-conserved non-coding RNAs that are involved in the regulation of several cellular and functional processes. miRNAs can act as oncogenes or tumor suppressors in all types of cancer, and could be used as prognostic and diagnostic biomarkers. Databases and computational algorithms are behind the majority of the research performed on miRNAs. These tools assemble and curate the relevant information on miRNAs and present it in a user-friendly manner. The current review presents 14 online databases that address every aspect of miRNA cancer research. Certain databases focus on miRNAs and a particular type of cancer, while others analyze the behavior of miRNAs in different malignancies at the same time. Additional databases allow researchers to search for mutations in miRNAs or their targets, and to review the naming history of a particular miRNA. All these databases are open-access, and are a valuable tool for those researchers working with these molecules, particularly those who lack access to an advanced computational infrastructure.

MiR-204 inhibits the proliferation and invasion of renal cell carcinoma by inhibiting RAB22A expression

While miR-204 expression may be linked to renal cell carcinoma (RCC) progression, the detailed mechanisms remain unclear. In the present study, we demonstrated that miR-204 was differentially expressed in RCC tissues when compared with surrounding normal kidney tissues. Ectopic overexpression of miR-204 in human RCC cells suppressed cell proliferation and invasion in vitro and in vivo. Mechanism dissection revealed that miR-204 may function through RAB22A signals to inhibit RCC proliferation and invasion. Overexpression of RAB22A by oe-RAB22A was able to partially reverse the miR-204-mediated suppression of RCC tumor progression. Together, these results revealed that miR-204 suppressed RCC proliferation and invasion by directly targeting the RAB22A gene. Targeting newly identified RAB22A with miR-204 may aid in the suppression of RCC proliferation and invasion.

MGDB: a comprehensive database of genes involved in melanoma

The Melanoma Gene Database (MGDB) is a manually curated catalog of molecular genetic data relating to genes involved in melanoma. The main purpose of this database is to establish a network of melanoma related genes and to facilitate the mechanistic study of melanoma tumorigenesis. The entries describing the relationships between melanoma and genes in the current release were manually extracted from PubMed abstracts, which contains cumulative to date 527 human melanoma genes (422 protein-coding and 105 non-coding genes). Each melanoma gene was annotated in seven different aspects (General Information, Expression, Methylation, Mutation, Interaction, Pathway and Drug). In addition, manually curated literature references have also been provided to support the inclusion of the gene in MGDB and establish its association with melanoma. MGDB has a user-friendly web interface with multiple browse and search functions. We hoped MGDB will enrich our knowledge about melanoma genetics and serve as a useful complement to the existing public resources.

Database URL:http://bioinfo.ahu.edu.cn:8080/Melanoma/index.jsp

Prediction of MicroRNA Precursors Using Parsimonious Feature Sets

MicroRNAs (miRNAs) are a class of short noncoding RNAs that regulate gene expression through base pairing with messenger RNAs. Due to the interest in studying miRNA dysregulation in disease and limits of validated miRNA references, identification of novel miRNAs is a critical task. The performance of different models to predict novel miRNAs varies with the features chosen as predictors. However, no study has systematically compared published feature sets. We constructed a comprehensive feature set using the minimum free energy of the secondary structure of precursor miRNAs, a set of nucleotide-structure triplets, and additional extracted sequence and structure characteristics. We then compared the predictive value of our comprehensive feature set to those from three previously published studies, using logistic regression and random forest classifiers. We found that classifiers containing as few as seven highly predictive features are able to predict novel precursor miRNAs as well as classifiers that use larger feature sets. In a real data set, our method correctly identified the holdout miRNAs relevant to renal cancer.

Human cancer databases (review)

Cancer is one of the four major non‑communicable diseases (NCD), responsible for ~14.6% of all human deaths. Currently, there are >100 different known types of cancer and >500 genes involved in cancer. Ongoing research efforts have been focused on cancer etiology and therapy. As a result, there is an exponential growth of cancer‑associated data from diverse resources, such as scientific publications, genome‑wide association studies, gene expression experiments, gene‑gene or protein‑protein interaction data, enzymatic assays, epigenomics, immunomics and cytogenetics, stored in relevant repositories. These data are complex and heterogeneous, ranging from unprocessed, unstructured data in the form of raw sequences and polymorphisms to well‑annotated, structured data. Consequently, the storage, mining, retrieval and analysis of these data in an efficient and meaningful manner pose a major challenge to biomedical investigators. In the current review, we present the central, publicly accessible databases that contain data pertinent to cancer, the resources available for delivering and analyzing information from these databases, as well as databases dedicated to specific types of cancer. Examples for this wealth of cancer‑related information and bioinformatic tools have also been provided.

Urinary signatures of Renal Cell Carcinoma investigated by peptidomic approaches

Renal Cell Carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's lifespan only for early stage tumours. Moreover, solid renal masses cannot be confidently differentiated from RCC. Therefore, markers to distinguish malignant kidney tumours and for their detection are needed. Two different peptide signatures were obtained by a MALDI-TOF profiling approach based on urine pre-purification by C8 magnetic beads. One cluster of 12 signals could differentiate malignant tumours (n = 137) from benign renal masses and controls (n = 153) with sensitivity of 76% and specificity of 87% in the validation set. A second cluster of 12 signals distinguished clear cell RCC (n = 118) from controls (n = 137) with sensitivity and specificity values of 84% and 91%, respectively. Most of the peptide signals used in the two models were observed at higher abundance in patient urines and could be identified as fragments of proteins involved in tumour pathogenesis and progression. Among them: the Meprin 1α with a pro-angiogenic activity, the Probable G-protein coupled receptor 162, belonging to the GPCRs family and known to be associated with several key functions in cancer, the Osteopontin that strongly correlates to tumour stages and invasiveness, the Phosphorylase b kinase regulatory subunit alpha and the SeCreted and TransMembrane protein 1.

Let-7d suppresses growth, metastasis, and tumor macrophage infiltration in renal cell carcinoma by targeting COL3A1 and CCL7

Background

MicroRNAs are endogenous small noncoding RNAs that are functionally involved in numerous critical cellular processes including tumorigenesis. Data mining using a microRNA array database suggested that let-7d microRNA may be associated with renal cell carcinoma (RCC) malignant progression. Here, we performed further analyses to determine whether let-7d is functionally linked to RCC malignancy.

Methods

Quantitative real-time PCR was used to determine the level of mature let-7d in RCC clinical specimens and its correlation with clinicopathological data. Immunohistochemical staining was conducted to characterize the stroma of RCC. Let-7d overexpressing RCC cell lines combined with mouse models bearing cell-derived xenografts and patient-derived xenografts were used to assess the functional role of let-7d in vitro and in vivo.

Results

Downregulation of let-7d in clinical RCC samples was associated with advanced tumor grade and T stage and increased vascular invasion. An inverse relationship between let-7d expression and macrophage infiltration was found in clinical RCC samples. Functional studies indicated that ectopic expression of let-7d significantly inhibited RCC cell proliferation, migration, and peripheral blood monocyte (PBMC) recruitment in vitro, as well as tumor growth, metastasis, and tumor macrophage infiltration in vivo. In silico analysis and subsequent experimental validation confirmed collagen, type III, alpha 1 (COL3A1) and C-C subfamily chemokine member CCL7 as direct let-7d target genes. The addition of COL3A1 and CCL7 counteracted the inhibitory effects of let-7d on RCC cell proliferation, migration, and PBMC recruitment. The inhibition of let-7d increased cell proliferation, migration, and PBMC recruitment by the enhanced expression of COL3A1 and CCL7 genes in vitro. The mRNA levels of COL3A1 and CCL7 were inversely correlated with let-7d level in RCC clinical specimens.

Conclusions

These results suggest that let-7d may suppress RCC growth, metastasis, and tumor macrophage infiltration at least partially through targeting COL3A1 and CCL7.

Electronic supplementary material

The online version of this article (doi:10.1186/1476-4598-13-206) contains supplementary material, which is available to authorized users.

Downregulated miR-646 in clear cell renal carcinoma correlated with tumour metastasis by targeting the nin one binding protein (NOB1)

Background:

Nin one binding protein (NOB1) was identified as a potential oncogene in human glioma and miR-646 plays an important role in human growth and development. However, the underlying molecular mechanisms of NOB1 in tumorigenicity and its correlation with miR-646 in renal cell carcinoma (RCC) have not been investigated.

Methods:

We performed bioinformatic analysis to explore miRNA targeting NOB1. The expression of NOB1 and miR-646 from 100 cases of clear cell RCC (ccRCC) and 30 cases of adjacent non-tumour tissues were detected by quantitative real-time PCR. The expression of miR-646 was correlated with NOB1 expression, tumour features and patient metastasis-free survival. The effect of overexpression of mir-646 on renal cancer cell proliferation was detected by colony formation in soft agar. Using a xenograft tumour model, we observed the in vivo tumorigenesis effect of miR-646 and NOB1.

Results:

miR-646 negatively regulated NOB1 and inhibited the proliferation and migration of renal cancer cells. There was a significant upregulation of NOB1 in ccRCC and it was further increased in metastatic cases, while miR-646 was downregulated in tumour tissues and further decreased in metastatic ccRCC. Additionally, expression of miR-646 was inversely correlated with the expression of NOB1. The downregulation of miR-646 also indicated a higher probability of developing metastasis. Most importantly, miR-646 expression was an independent predictor of ccRCC metastasis by the univariate analysis and binary logistic regression model (both P<0.05). Colony formation in soft agar and xenograft tumour model suggested that miR-646 and NOB1 are required for tumorigenesis in vitro and in vivo. Furthermore, suppression of NOB1 increased the phosphorylation of several proteins in MAPK pathway.

Conclusions:

Downregulated miR-646 in ccRCC was associated with tumour metastasis through MAPK pathway by targeting NOB1. miR-646 and NOB1 may play an important role in the development of ccRCC.

Nucleic acid-based biomarkers in body fluids of patients with urologic malignancies

This review focuses on the promising potential of nucleic acids in body fluids such as blood and urine as diagnostic, prognostic, predictive and monitoring biomarkers in urologic malignancies. The tremendous progress in the basic knowledge of molecular processes in cancer, as shown in the companion review on nucleic acid-based biomarkers in tissue of urologic tumors, provides a strong rationale for using these molecular changes as non-invasive markers in body fluids. The changes observed in body fluids are an integrative result, reflecting both tissue changes and processes occurring in the body fluids. The availability of sensitive methods has only recently made possible detailed studies of DNA- and RNA-based markers in body fluids. In addition to these biological aspects, methodological aspects of the determination of nucleic acids in body fluids, i.e. pre-analytical, analytical and post-analytical issues, are particularly emphasized. The characteristic changes of RNA (differential mRNA and miRNA expression) and DNA (concentrations, integrity index, mutations, microsatellite and methylation alterations) in serum/plasma and urine samples of patients suffering from the essential urologic cancers of the prostate, bladder, kidney and testis are summarized and critically discussed below. To translate the promising results into clinical practice, laboratory scientists and clinicians have to collaborate to resolve the challenges of harmonized and feasible pre-analytical and analytical conditions for the selected markers and to validate these markers in well-designed and sufficiently powered multi-center studies.

Microarray profiling of human renal cell carcinoma: identification for potential biomarkers and critical pathways

AIMS

The aim of this study was to screen several novel genes associated with renal cell carcinoma (RCC), and analyze the gene functions and signal pathways which were critical to RCCs with DNA microarray.

METHODS

The gene expression profile of GSE781 was downloaded from Gene Expression Omnibus database, including 9 RCC samples and 9 healthy controls. Compared with the control samples, differentially expressed genes (DEGs) of RCC was identified the by packages in R. The selected DEGs were further analyzed using bioinformatics methods. Gene ontology (GO) enrichment analysis was performed using Gene Set Analysis Toolkit and protein-protein interaction (PPI) network was constructed with prePPI. Then, pathway enrichment analysis to PPI network was performed using WebGestalt software.

RESULTS

A total of 429 DEGs were down-regulated and 418 DEGs were up-regulated in RCC samples compared to healthy controls. A total of 11 remarkable enhanced functions and 13 suppressed functions were identified. PPI nodes of high degrees, such as JAK2, IL8, BMPR2, FN1 and NCR1, were obtained. The DEGs were classified and significantly enriched in cytokine and cytokine receptor pathway.

CONCLUSION

The hub genes we find from RCC samples are not only bio-markers, but also may provide the groundwork for a combination therapy approach for RCCs.

Potential biofluid markers and treatment targets for renal cell carcinoma

Renal cell carcinoma (RCC) is the 13th most common cancer in the world and one of the few cancers for which incidence is increasing. This disease is generally asymptomatic at an early stage and is highly metastatic. Frequently discovered by physicians in the process of working up other diseases such as acute kidney injury, RCC is often discovered in an advanced form and many patients have metastases at the time of diagnosis. Given that life expectancy with currently approved therapies for metastatic RCC is approximately 1-2 years, biomarkers for RCC that will enable early detection are urgently needed. Although it is unlikely that highly sensitive and specific biomarkers will be identified in the near future that are useful for screening the general population, a noninvasive marker or set of markers could soon be used in general medicine, nephrology, and urology clinics to screen patients at increased risk of RCC. In addition to the ongoing need for RCC biomarkers, the frequent resistance reported with currently available targeted therapies makes the identification of new therapeutic targets similarly important. Many promising leads for new targeted therapies have come to light; some of these therapies are in clinical trials and others are still being evaluated in the laboratory.