Kidney Renal Clear Cell Carcinoma Tissues Research Articles

Development and validation of a prognostic model for kidney renal clear cell carcinoma based on RNA binding protein expression.

Dysregulated expression of RNA-binding proteins (RBPs) is strongly associated with the development and progression of multiple tumors. However, little is known about the role of RBPs in kidney renal clear cell carcinoma (KIRC). In this study, we examined RBP expression profiles using The Cancer Genome Atlas database and identified 133 RBPs that were differentially expressed in KIRC and non-tumor tissues. We then systematically analyzed the potential biological functions of these RBPs and established PPIs. Based on Lasso regression and Cox survival analyses, we constructed a risk model that could independently and accurately predict prognosis based on seven RBPs (NOL12, PABPC1L, RNASE2, RPL22L1, RBM47, OASL, and YBX3). Survival times were shorter in patients with high risk scores for cohorts stratified by different characteristics. Gene set enrichment analysis was also performed to further understand functional differences between high- and low-risk groups. Finally, we developed a clinical nomogram with a concordance index of 0.792 for estimating 3- and 5-year survival probabilities. Our results demonstrate that this risk model could potentially improve individualized diagnostic and therapeutic strategies.

DNA methylation of Hugl-2 is a prognostic biomarker in kidney renal clear cell carcinoma.

It has been reported that loss of Hugl‐2 contributes to tumour formation and progression in vitro and in vivo. However, whether Hugl‐2 levels decrease during kidney renal clear cell carcinoma (KIRC) and the mechanism involved remain unknown. This study aimed to investigate whether DNA methylation of Hugl‐2 reduces its expression, leading to the progression and poor prognosis of KIRC. Hugl‐2 methylation and mRNA expression and KIRC clinicopathological data were extracted from The Cancer Genome Atlas (TCGA), and relationships among these factors were analyzed using UALCAN, MethHC, Wanderer and LinkedOmics web tools. We found that Hugl‐2 mRNA and protein levels were reduced in KIRC tissues. Moreover, Hugl‐2 mRNA levels were related to tumour grade and overall survival, and Hugl‐2 methylation was increased in KIRC. According to the results of methylation‐specific PCR, KIRC cells had higher Hugl‐2 DNA methylation levels than HKC cells. Moreover, Hugl‐2 DNA methylation correlated negatively with Hugl‐2 mRNA and was also related to the pathology and T stage of KIRC patients. KIRC patients with high Hugl‐2 DNA methylation also had shorter overall survival. Additionally, methylation of cg08827674, a Hugl‐2 probe, was related to pathologic stage, T stage, neoplasm histologic grade, serum calcium level without laterality, M stage, N stage, and ethnicity. Furthermore, treatment with the DNA methylation inhibitor decitabine resulted in upregulation of Hugl‐2 mRNA and protein levels in KIRC cell lines. These results indicate that Hugl‐2 DNA methylation may be both a prognostic marker and a therapeutic target in KIRC.

Abnormal expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma based on data mining

BackgroundEPB41L1 gene (erythrocyte membrane protein band 4.1 like 1) encodes the protein 4.1N, a member of 4.1 family, playing a vital role in cell adhesion and migration, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma (KIRC) remain to be investigated.MethodsIn this study, we collected the mRNA expression of EPB41L1 in KIRC through the Oncomine platform, and used the HPA database to perform the pathological tissue immunohistochemistry in patients. Then, the sub-groups and prognosis of KIRC were performed by UALCAN and GEPIA web-tool, respectively. Further, the mutation of EPB41L1 in KIRC was analyzed by c-Bioportal. The co-expression genes of EPB41L1 in KIRC were displayed from the LinkedOmics database, and function enrichment analysis was used by LinkFinder module in LinkedOmics. The function of EPB41L1 in cell adhesion and migration was confirmed by wound healing assay using 786-O cells in vitro. Co-expression gene network was constructed through the STRING database, and the MCODE plug-in of which was used to build the gene modules, both of them was visualized by Cytoscape software. Finally, the top modular genes in the same patient cohort were constructed through data mining in TCGA by using the UCSC Xena browser.ResultsThe results indicated that EPB41L1 was down-expressed in KIRC, leading to a poor prognosis. Moreover, there is a mutation in the FERM domain of EPB41L1, but it has no significant effect on the prognosis of KIRC. The co-expressed genes of EPB41L1 were associated with cell adhesion and confirmed in vitro. Further analysis suggested that EPB41L1 and amyloid beta precursor protein (APP) were coordinated to regulated cancer cell adhesion, thereby increasing the incidence of cancer cell metastasis and tumor invasion.ConclusionsIn summary, EPB41L1 is constantly down-expressed in KIRC tissues, resulting a poor prognosis. Therefore, we suggest that it can be an effective biomarker for the diagnosis of KIRC.

JAK3 is a potential biomarker and associated with immune infiltration in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most common cancers globally, with an overall poor prognosis. The Janus kinase (JAK) family plays an essential role in cellular mechanisms such as proliferation, metastasis, invasion, and immunity. In our study, various web-portals were used to explore the expression and clinical significance of JAK3 in KIRC. JAK3 expression was significantly up-regulated in KIRC tissues. Patients with KIRC having high JAK3 levels displayed a substantially decreased disease-free survival rate and overall survival rate. Significant correlations were obtained between JAK3 expression and the abundance of immune cells and immune biomarker sets. Enrichment function analysis revealed that gene function significantly correlated with JAK3, which was primarily associated with the immune response, JAK-STAT signaling pathway, Ras signaling pathway via several cancer-related kinases, miRNAs, and transcription factors. Moreover, we also identified several kinase, miRNA or transcription factor targets of JAK3 in KIRC. The hub genes (JAK3, FCHO1, INSl3, DEF6, and GPR132) were associated with the activation or inhibition of several famous cancer related pathways. Our results demonstrated that JAK3 is a potential biomarker and associated with immune infiltration in KIRC.

Comprehensive analysis of the HOXA gene family identifies HOXA13 as a novel oncogenic gene in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is one of the most common lethal cancers in the human urogenital system. As members of the Homeobox (HOX) family, Homeobox-A (HOXA) cluster genes have been reported to be involved in the development of many cancer types. However, the expression and clinical significance of HOXA genes in KIRC remain largely unknown. In this study, we comprehensively analyzed the mRNA expression and prognostic values of HOXA genes in KIRC using The Cancer Genome Atlas (TCGA) analysis databases online. Colony formation assay, flow cytometry and Western blot were used to detect cell proliferation, apoptosis, cell cycle, and protein level of the indicated gene. We found that the HOXA genes were differentially expressed in KIRC tissues when compared with normal tissues. The expression of HOXA4 and HOXA13 were significantly up-regulated, while HOXA7 and HOXA11 were down-regulated in KIRC. High mRNA levels of HOXA2, HOXA3 and HOXA13, and low level of HOXA7 predicted poor overall survival (OS) of KIRC patients. High mRNA level of HOXA13 further indicated a poor disease-free survival (DFS) of KIRC patients. Functionally, knockdown of HOXA13 significantly suppressed cell proliferation of KIRC in vitro, increased the protein level of p53 and decreased the protein level of cyclin D1 in KIRC cells. Over-expression of HOXA13 had the opposite effects on KIRC cells. Collectively, our findings suggest that HOXA13 functions as a novel oncogene in KIRC and may be a potential biomarker for this malignancy.

Identification of METTL14 in Kidney Renal Clear Cell Carcinoma Using Bioinformatics Analysis.

The kidney renal clear cell carcinoma (KIRC) with poor prognosis is the main histological subtype of the renal cell carcinoma, accounting for 80–90% of patients. Currently, the N6-methyladenosine (m6A) epitranscriptional modification draws much attention. The m6A RNA modification, the most plentiful internal modification of mRNAs and noncoding RNAs in the majority of eukaryotes, regulates mRNAs at different levels and is involved in disease occurrence and progression. The GTExPortal and TCGAportal were applied to investigate the METTL14 mRNA expression in different tissues and KIRC stages. The Human Protein Atlas was used to verify the location of METTL14 in KIRC tissues. The main microRNAs (miRNAs) related to KIRC were analyzed using OncoLnc and starBase, while corresponding circular RNAs (circRNAs) interacting with miRNAs were predicted via circBank; then, the METTL14-miRNA-circRNA interaction network was established. The level of methyltransferase-like 14 (METTL14) mRNA was significantly lower in KIRC tissues compared with normal kidney tissues, which was relative to clinical and pathological stages. circRNAs may regulate METTL14 mRNA as miRNAs sponge to affect the KIRC progression. METTL14 mRNA is likely to regulate PTEN mRNA expression via changing its m6A RNA modification level. METTL14 mRNA expression negatively correlated with the KIRC stages and positively correlated with KIRC patients' overall survival, which has great potential to serve as a clinical biomarker in KIRC.

The miR-183/182/96 cluster functions as a potential carcinogenic factor and prognostic factor in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is the most common type of renal cell carcinoma. While a number of treatments have been developed over the past few decades, the prognosis of patients with KIRC remains poor due to tumor metastasis and recurrence. Therefore, the molecular mechanisms of KIRC require to be elucidated in order to identify novel biomarkers. MicroRNAs (miRNAs/miRs) have been studied as important regulators of gene expression in a variety of cancer types. In the present study, a bioinformatics analysis of differentially expressed miRNAs in KIRC vs. normal tissues was performed based on raw miRNA expression data and patient information downloaded from the The Cancer Genome Atlas database. Furthermore, the clinical significance of differentially expressed miRNAs was evaluated, and their target genes and biological effects were further predicted. After applying the cut-off criteria of an absolute fold change of ≥2 and P<0.05, 127 differentially expressed miRNAs between KIRC and normal tissues were identified. The product of the miR-183/182/96 gene cluster, namely miR-183, miR-96 and miR-182, was revealed to be associated with multiple clinicopathological features of KIRC and to have a significant predictive and prognostic value. Subsequent functional enrichment analysis indicated that the target genes of the three miRNAs are associated with various Panther pathways, including the α-adrenergic receptor signaling pathway, metabotropic glutamate receptor group I pathway, histamine H1 receptor-mediated signaling pathway and thyrotropin-releasing hormone receptor signaling pathway. In addition, major enriched gene ontology terms in the category biological process included the intracellular signaling cascade, cellular macromolecule catabolic process and response to DNA damage stimulus. Taken together, the present study suggested that miR-183, miR-96 and miR-182 may function as potential carcinogenic factors in KIRC and may be utilized as prognostic predictors.

MiRNA-21 and miRNA-223 expression signature as a predictor for lymph node metastasis, distant metastasis and survival in kidney renal clear cell carcinoma.

Purpose: The aim of this study was to generate a novel miRNA expression signature to effectively assess nodal metastasis, distant metastasis and predict prognosis for patients with kidney renal clear cell carcinoma (KIRC) and explore its potential mechanism of affecting the prognosis.Method: Using expression profiles downloaded from the Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between KIRC and paired normal tissues. The diagnostic values of the differentially expressed miRNAs for nodal metastasis and distant metastasis were evaluated by Receiver Operating Characteristic (ROC) curve analysis. Then, we evaluated the impact of miRNAs on overall survival (OS) by univariate and multivariate COX regression analyzes. This analysis was ultimately used to construct a miRNA signature that effectively assessed nodal metastasis, distant metastasis and predicted prognosis. The functional enrichment analysis of the miRNAs included in the signatures was used to explore its potential molecular mechanism in KIRC.Results: Based on our cutoff criteria (P < 0.05 and |log2FC| > 1.0), we identified 104 differentially expressed microRNAs (miRNAs), including 43 that were up-regulated in KIRC tissues and 61 that were down-regulated. We found 12 miRNAs were potentially diagnostic biomarkers of nodal metastasis and distant metastasis by ROC curve analysis. Two miRNAs (miRNA-21 and miRNA-223) were significant miRNAs independently associated with OS based on Cox univariate and multivariate analysis. We generated a signature index based on expression of these two miRNAs, and the two-miRNA signature is promising as a biomarker for diagnosing nodal metastasis, distant metastasis and predicting 5-year survival rate of KIRC with areas under the curve (AUC)=0.738, 0.659 and 0.731, respectively. Patients were stratified into high-risk and low-risk groups, according to median of the signature prognosis indexes. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group (P = 0.000). The functional enrichment analysis suggested that the target genes of two miRNAs may be involved in various pathways related to cancer, p53 signaling pathway, apoptosis, and MAPK signaling pathway.Conclusion: The two-miRNA signature could assess nodal metastasis, distant metastasis and predict survival of KIRC. As a promising prediction tool, the mechanism of the two miRNAs in KIRC deserves further study.

Identification and Validation of Two Novel Prognostic lncRNAs in Kidney Renal Clear Cell Carcinoma

Background/Aims: Kidney renal clear cell carcinoma (KIRC) is one of the most fatal malignancies due to late diagnosis and poor treatment. To improve its prognosis, a screening for molecular biomarkers of KIRC is urgently needed. Long non-coding RNAs (lncRNAs) play important roles in tumorigenesis and prognosis of cancers. However, it is not clear whether lncRNAs can be used as molecular biomarkers in predicting the survival of KIRC patients. Methods: In this study, our aim was to identify lncRNAs/mRNAs signatures and their prognostic values in KIRC. The aberrant expression profile of mRNAs and lncRNAs in 529 KIRC tissues and 72 adjacent non-tumor pancreatic tissues were obtained from the Cancer Genome Atlas (TCGA). A weighted gene co-expression network analysis (WGCNA) of two key lncRNAs was constructed. We constructed an aberrant lncRNA-mRNA-miRNA ceRNA network in CESC. In addition, Gene Ontology (GO) and KEGG pathway analysis were performed. Results: Using lncRNA/mRNA expression profiling data, the overall analysis revealed that two novel lncRNA signatures (DNM1P35 and MIR155HG) and several mRNAs were found to be significantly correlated with KIRC patient’s overall analysis. Based on the target gene of the two lncRNA in co-expression network, the GO and KEGG analysis were also performed. A dysregulated lncRNA-related ceRNA network was also observed. Conclusion: These results suggested that the two novel lncRNAs signatures may act as independent prognostic biomarkers for predicting the survival of KIRC patient.

Identifying prognostic biomarkers based on aberrant DNA methylation in kidney renal clear cell carcinoma.

The outcome of kidney renal clear cell carcinoma (KIRC) differs even among individuals with similar clinical characteristics. DNA methylation is regarded as a regulator of gene expression in cancers, which may be a molecular marker of prognosis. In this study, we aimed to mine novel methylation markers of the prognosis of KIRC. We revealed a total of 2793 genes differentially methylated in their promoter regions (DMGs) and 2979 differentially expressed genes (DEGs) in KIRC tissues compared with normal tissues using The Cancer Genome Atlas datasets. Then, we detected 57 and 34 subpathways enriched among the DMGs and DEGs, respectively, using the R package iSubpathwayMiner. We retained 56 subpathways related to both aberrant methylation and expression based on a hypergeometric test for further analysis. An integrated gene regulatory network was constructed using the regulatory relationships between genes in the subpathways. Using the top 15% of the nodes from the network ranked by degree, survival analysis was performed. We validated four DNA methylation signatures (RAC2, PLCB2, VAV1, and PARVG) as being highly correlated with prognosis in KIRC. These findings suggest that DNA methylation might become a prognostic predictor in KIRC and could supplement histological prognostic prediction.