肾透明细胞癌预后相关miRNAs的生物信息学分析

目的寻找可作为肾透明细胞癌（ccRCC）生物标志物的miRNA,以及ccRCC与正常组织间miRNA差异表达情况。 方法利用TCGA数据库下载ccRCC中miRNA表达数据,分析肿瘤与正常组织间差异表达miRNA。使用Kaplan-Meier曲线对患者进行生存分析,筛选出表达情况与临床预后相关的miRNA。通过生物信息学对miRNA的靶基因进行预测,然后运用FunRich软件和ClueGO对靶基因进行GO和KEGG富集分析。 结果通过TCGA数据库分析发现,ccRCC较正常组织差异表达miRNA共54个,其中上调33个,下调21个。通过生存分析发现hsa-miR-21和hsa-miR-155与患者预后相关,P≤0.05。进一步通过Perl软件在Targetscan、miRDB、miRTarBase、miRPath这四个数据库中预测miRNA靶基因并将结果取交集,共发现129个靶基因。GO和KEGG分析结果表明,这些靶基因主要与转录因子活性、信号转导以及FoxO、TNF等信号通路密切相关。 结论通过生物信息学分析发现了ccRCC与正常组织的差异表达miRNA;其中hsa-miR-21和hsa-miR-155与患者总体生存率相关,并通过调控靶基因参与相关的信号通路进而影响ccRCC的发生发展进程,提示hsa-miR-21和hsa-miR-155可能是ccRCC潜在的生物标志物。     

Systematic analysis of survival-associated alternative splicing signatures in clear cell renal cell carcinoma

Alternative splicing (AS) constitutes a major reason for messenger RNA (mRNA) and protein diversity. Increasing studies have shown a link to splicing dysfunction associated with malignant neoplasia. Systematic analysis of AS events in kidney cancer remains poorly reported. Therefore, we generated AS profiles in 533 kidney renal clear cell carcinoma (KIRC) patients in The Cancer Genome Atlas (TCGA) database using RNA-seq data. Then, prognostic models were developed in a primary cohort (N = 351) and validated in a validation cohort (N = 182). In addition, splicing networks were built by integrating bioinformatics analyses. A total of 11 268 and 8083 AS variants were significantly associated with patient overall survival time in the primary and validation KIRC cohorts, respectively, including STAT1, DAZAP1, IDS, NUDT7, and KLHDC4. The AS events in the primary KIRC cohorts served as candidate AS events to screen the independent risk factors associated with survival in the primary cohort and to develop prognostic models. The area under the curve of the receiver-operator characteristic curve for prognostic prediction in the primary and validation KIRC cohorts was 0.84 and 0.82 at 2500 days of overall survival, respectively. In addition, splicing correlation networks revealed key splicing factors (SFs) in KIRC, such as HNRNPH1, HNRNPU, KHDBS1, KHDBS3, SRSF9, RBMX, SFQ, SRP54, HNRNPA0, and SRSF6. In this study, we analyzed the AS landscape in the TCGA KIRC cohort and detected predictors (prognostic) based on AS variants with high performance for risk stratification of the KIRC cohort and revealed key SFs in splicing networks, which could act as underlying mechanisms.     

VNN3 is a potential novel biomarker for predicting prognosis in clear cell renal cell carcinoma

Although pathological observations provide approximate prognoses, it is difficult to achieve prognosis in patients with existing prognostic factors. Therefore, it is very important to find appropriate biomarkers to achieve accurate cancer prognosis. Renal cell carcinoma (RCC) has several subtypes, the discrimination of which is crucial for proper treatment. Here, we present a novel biomarker, VNN3, which is used to prognose clear cell renal cell carcinoma (ccRCC), the most common and aggressive subtype of kidney cancer. Patient information analyzed in our study was extracted from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts. VNN3 expression was considerably higher in stages III and IV than in stages I and II. Moreover, Kaplan–Meier curves associated high VNN3 expression with poor prognoses (TCGA, p?p?=?.00076), confirming that ccRCC prognosis can be predicted via VNN3 expression patterns. Consistent with all patient results, the prognosis of patients with higher VNN3 expression was worse in both low stage (I and II) and high stage (III and IV) (TCGA, p < 0.0001 in stage I and II; ICGC, p = 0.028 in stage I and II; TCGA, p = 0.005 in stage III and IV). Area under the curve and receiver operating characteristic curves supported our results that highlighted VNN3 expression as a suitable ccRCC biomarker. Multivariate analysis also verified the prognostic performance of VNN3 expression (TCGA, p?p?=?.017). Altogether, we suggest that VNN3 is applicable as a new biomarker to establish prognosis in patients with ccRCC.     

Circular RNA circPPP6R3 upregulates CD44 to promote the progression of clear cell renal cell carcinoma via sponging miR-1238-3p

Circular RNAs (circRNAs) are a type of covalently closed circular-formed RNAs and play crucial roles in the oncogenesis and progression of various human cancers. Here we identified a novel circRNA, circPPP6R3, to be highly expressed both in clear cell renal cell carcinoma (ccRCC) tissues and cell lines based on analyzing high-throughput sequencing data and qRT-PCR analysis. Highly expressed circPPP6R3 was positively correlated with higher histological grade, T stage, and M stage as well as advanced clinical stage of ccRCC patients. Functionally, knockdown of circPPP6R3 attenuated the proliferation, migration, and invasion of ccRCC cells whereas overexpression had the reverse effects. Mechanistically, the biotin-labeled pull-down assay and dual-luciferase reporter assay revealed that circPPP6R3 directly interacted with miR-1238-3p. miR-1238-3p inhibitors had a rescue effect on the proliferative and metastatic capacities by knockdown of circPPP6R3. Moreover, RNA-sequencing analysis and dual-luciferase reporter assay indicated that circPPP6R3 upregulated CD44, a cell-surface glycoprotein contributed to the cell adhesion and metastasis, via sponging to miR-1238-3p. Further investigation revealed that MMP9 and Vimentin were regulated by CD44 in ccRCC. Our study thus provided evidence that the regulatory network involving circPPP6R3/miR-1238-3p/CD44 axis might provide promising biomarkers as well as a therapeutic approach for ccRCC.Subject terms: Tumour biomarkers, Renal cell carcinoma, Epithelial-mesenchymal transition, Non-coding RNAs     

Uptake of HDL-cholesterol contributes to lipid accumulation in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), which accounts for the majority of kidney cancer, is known to accumulate excess cholesterol. However, the mechanism and functional significance of the lipid accumulation for development of the cancer remains obscure. In this study, we analyzed 42 primary ccRCC samples, and determined that cholesterol levels of ~ 70% of the tumors were at least two-fold higher than that of benign kidney tissues. Compared to tumors without cholesterol accumulation, those containing excess cholesterol expressed higher levels of scavenger receptor BI (SR-B1), a receptor for uptake of HDL-associated cholesterol, but not genes involved in cholesterol synthesis and uptake of LDL-associated cholesterol. To further determine the roles of sterol accumulation for cancer development, we implanted ccRCC from patients into mouse kidneys using a mouse ccRCC xenograft model. Feeding mice with probucol, a compound lowing HDL-cholesterol, markedly reduced levels of cholesterol in tumors containing excess cholesterol. This treatment, however, did not affect growth of these tumors. Our study suggests that cholesterol overaccumulation in ccRCC is the consequence of increased uptake of HDL-cholesterol as a result of SR-B1 overexpression, but the lipid accumulation by itself may not play a significant role in progression of the cancer.     

Molecular analysis of the chromosome 11p region in renal cell carcinomas.

Comparative histological data suggest that papillary renal cell tumors in adults and Wilms' tumors in children develop from maturation-arrested cells of similar origin. Wilms' tumor is characterized by genetic changes at the chromosome 11p region. In the present study, we have analyzed 10 papillary and 10 non-papillary renal cell tumors and determined the allelic status of 6 loci on the short arm of chromosome 11. Only one papillary renal cell carcinoma among the 20 tumors showed a loss of constitutional heterozygosity for the chromosome 11p region. These data suggest that separate molecular events occur in the development of Wilms' tumor and papillary renal cell tumors, subsequent to the proliferation of maturation-arrested cells of the kidney.     

肾透明细胞癌Caki-1细胞系差异表达基因的生物信息学分析

目的比较肾透明细胞癌Caki-1细胞系与正常肾上皮细胞系ASE-5063中的差异表达基因（DEGs）,寻找潜在的肾透明细胞癌特异性分子标志物。 方法利用GEO数据库自带的GEO2R在线分析工具分析基因芯片GSE78179,将筛选出的DEGs分别导入Metascape、STRING以及Cytoscape进行综合分析并筛选出核心基因。最后使用FunRich等软件对筛选出的核心基因进行GO和KEGG富集分析。 结果共筛选出562个DEGs,其中上调基因345个,下调基因217个。进一步使用MCODE筛选出36个关键基因,GO功能分析发现这些基因与细胞粘附分子活性、趋化因子活性、细胞通讯和信号转导等密切相关;KEGG通路富集结果则表明差异基因主要集中在趋化因子信号通路、TNF信号通路以及NF-κB信号通路等多种与肿瘤相关的通路上。 结论运用生物信息学方法筛选出肾透明细胞癌Caki-1细胞系中DEGs,其中数个核心基因广泛参与多种肿瘤的病理进程,但尚未在肾透明细胞癌有相关研究报道,提示其可能是治疗肾透明细胞癌的潜在靶点。     

A large-scale transcriptome analysis identified ELANE and PRTN3 as novel methylation prognostic signatures for clear cell renal cell carcinoma

DNA methylation was involved in the progress of many types of cancer including clear cell renal cell carcinomas (ccRCCs). This study aimed to identify the prognostic DNA methylation biomarkers for the ccRCCs by a large-scale RNA-seq analysis. The DNA methylation data and the corresponding clinical information of the patients with ccRCCs were extracted from TCGA database and randomly divided into the training group and the validation group. The differentially expressed CpG sites and the survival-related CpG sites were further identified, which was combined into CpG sites pair and followed by screening the survival-related pairs. The C-index and the forward search algorithms were constructed to identify the prognostic signatures for the patients with ccRCCs. The prognostic signatures were verified by the validation dataset and the protein–protein interactions (PPI) network analysis was performed on the CPG sites of the signature. A total of 9,861 differentially expressed CPG sites were identified and 567 CpG sites were found to relate to the overall survival (OS) of the patients with ccRCCs. Besides, 1,146 CPG sites pairs were found to be related to the OS of the ccRCCs samples and the signature composed of seven CpG sites pairs were obtained to predict the prognosis of patients with ccRCCs and the results were verified in the validation dataset. Besides, the PPI network analysis showed that ELANE and PRTN3 gene may be associated with the invasion and metastasis of ccRCCs and could function as potential prognostic and therapeutic signatures for ccRCCs.     

Risk factor for clear cell renal cell carcinoma in Chinese population: a case-control study

Background: Risk factors for clear cell renal cell carcinoma (ccRCC) differ among populations and remain controversial. We carried out a hospital-based case–control study to examine the effects of health status, lifestyle, and some genetic polymorphisms on ccRCC risk in Chinese subjects. Methods: Between 2007 and 2009, 250 newly diagnosed, histologically confirmed ccRCC cases and 299 sex-, age-matched healthy controls provided complete information including consumption of tea and alcohol, smoking, occupational exposure, body mass index (BMI), hypertension, diabetes, and urolithiasis by face-to-face interview in Shanghai. Genetic polymorphisms of cytochrome P450 mono-oxygenase (CYP1A1: 6235T>C, 4889A>G, and 4887C>A), glutathione S-transferase (GSTP1: 342A>G), and N-acetyltransferase (NAT2: 481C>T, 590G>A, and 857G>A) were identified by PCR-RFLP and DNA sequencing. Adjusted odds ratio (AOR) and 95% confidence interval (CI) were derived through multivariate logistic regression. Results: Green tea intake (≥500 ml/d) was inversely associated with ccRCC risk, with an AOR of 0.34 (95% CI 0.21–0.55). BMI (≥25 kg/m²), hypertension, and urolithiasis were independently associated with an increased risk of ccRCC, with AOR (95% CI) of 2.10 (1.32–3.34), 2.49 (1.57–3.93), and 3.33 (1.12–9.89), respectively. No association was observed between smoking, alcohol consumption, or occupational exposure with ccRCC risk. The polymorphisms and their interactions with the environmental exposures were mostly not associated with ccRCC risk. Conclusion: BMI (≥25 kg/m²), hypertension, and urolithiasis are independently associated with an increased risk, whereas green tea intake (≥500 ml/d) is independently associated with a decreased risk of ccRCC. The polymorphisms of the xenobiotic-metabolizing enzymes are weakly associated with ccRCC risk in Chinese subjects.     

Circular RNA circDVL1 inhibits clear cell renal cell carcinoma progression through the miR-412-3p/PCDH7 axis

Clear cell renal cell carcinoma (ccRCC) is a primary kidney cancer with high aggressive phenotype and extremely poor prognosis. Accumulating evidence suggests that circular RNAs (circRNAs) play pivotal roles in the occurrence and development of various human cancers. However, the expression, clinical significance and regulatory role of circRNAs in ccRCC remain largely unclear. Here we report that circDVL1 to be reduced in the serums and tissues from ccRCC patients, and to negatively correlate with ccRCC malignant features. Overexpression of circDVL1 inhibits proliferation, induces G1/S arrest, triggers apoptosis, and reduces migration and invasion in different ccRCC cells in vitro. Correspondingly, circDVL1 overexpression suppresses ccRCC tumorigenicity in a mouse xenograft model. Mechanistically, circDVL1 serves as a sponge for oncogenic miR-412-3p, thereby preventing miR-412-3p-mediated repression of its target protocadherin 7 (PCDH7) in ccRCC cells. Collectively, our results demonstrate that circDVL1 exerts tumor-suppressive function during ccRCC progression through circDVL1/miR-412-3p/PCDH7 axis, and suggest that circDVL1 could be a novel diagnostic and prognositc marker and therapeutic target for ccRCC.     

Proteomic analysis in clear cell renal cell carcinoma: identification of differentially expressed protein by 2-D DIGE

Renal cell carcinoma (RCC), the most common neoplasm affecting the adult kidney, is characterised by heterogeneity of histological subtypes, drug resistance, and absence of molecular markers. Two-dimensional difference gel electrophoresis (2-D DIGE) technology in combination with mass spectrometry (MS) was applied to detect differentially expressed proteins in 20 pairs of RCC tissues and matched adjacent normal kidney cortex (ANK), in order to search for RCC markers. After gel analysis by DeCyder 6.5 and EDA software, differentially expressed protein spots were excised from Deep Purple stained preparative 2DE gel. A total of 100 proteins were identified by MS out of 2500 spots, 23 and 77 of these were, respectively, over- and down-expressed in RCC. The Principal Component Analysis applied to gels and protein spots exactly separated the two sample classes in two groups: RCC and ANK. Moreover, some spots, including ANXA2, PPIA, FABP7 and LEG1, resulted highly differential. The DIGE data were also confirmed by immunoblotting analysis for these proteins. In conclusion, we suggest that applying 2-D DIGE to RCC may provide the basis for a better molecular characterization and for the discovery of candidate biomarkers.     

Resistance to tyrosine kinase inhibitors in clear cell renal cell carcinoma: From the patient's bed to molecular mechanisms

The introduction of anti-angiogenic drugs especially tyrosine kinase inhibitors (TKIs) was a breakthrough in the treatment of renal cell carcinoma (RCC). Although TKIs have significantly improved outcome in patients with metastatic disease, the majority still develop resistance over time. Because different combinations and sequences of TKIs are tested in clinical trials, resistance patterns and mechanisms underlying this phenomenon should be thoroughly investigated. From a clinical point of view, resistance occurs either as a primary phenomenon (intrinsic) or as a secondary phenomenon related to various escape/evasive mechanisms that the tumor develops in response to vascular endothelial growth factor (VEGF) inhibition. Intrinsic resistance is less common, and related to the primary redundancy of available angiogenic signals from the tumor, causing unresponsiveness to VEGF-targeted therapies. Acquired resistance in tumors is associated with activation of an angiogenic switch which leads to either upregulation of the existing VEGF pathway or recruitment of alternative factors responsible for tumor revascularization. Multiple mechanisms can be involved in different tumor settings that contribute both to evasive and intrinsic resistance, and current endeavor aims to identify these processes and assess their importance in clinical settings and design of pharmacological strategies that lead to enduring anti-angiogenic therapies.     

SR-B1 and CD10 combined immunoprofile for differential diagnosis of metastatic clear cell renal cell carcinoma and clear cell carcinoma of the ovary

Journal of Molecular Histology - Both clear cell renal carcinoma (ccRCC) and clear cell carcinoma of the ovary (CCOC) have a clear cytoplasmic morphological feature, hence it is difficult to...     

Systematic analysis of alternative splicing signature unveils prognostic predictor for kidney renal clear cell carcinoma

There is growing evidence that alternative splicing (AS) plays an important role in cancer development. However, a comprehensive analysis of AS signatures in kidney renal clear cell carcinoma (KIRC) is lacking and urgently needed. It remains unclear whether AS acts as diagnostic biomarkers in predicting the prognosis of KIRC patients. In the work, gene expression and clinical data of KIRC were obtained from The Cancer Genome Atlas (TCGA), and profiles of AS events were downloaded from the SpliceSeq database. The RNA sequence/AS data and clinical information were integrated, and we conducted the Cox regression analysis to screen survival-related AS events and messenger RNAs (mRNAs). Correlation between prognostic AS events and gene expression were analyzed using the Pearson correlation coefficient. Protein-protein interaction analysis was conducted for the prognostic AS-related genes, and a potential regulatory network was built using Cytoscape (version 3.6.1). Meanwhile, functional enrichment analysis was conducted. A prognostic risk score model is then established based on seven hub genes (KRT222, LENG8, APOB, SLC3A1, SCD5, AQP1, and ADRA1A) that have high performance in the risk classification of KIRC patients. A total 46,415 AS events including 10,601 genes in 537 patients with KIRC were identified. In univariate Cox regression analysis, 13,362 survival associated AS events and 8,694 survival-specific mRNAs were detected. Common 3,105 genes were screen by overlapping 13,362 survival associated AS events and 8,694 survival-specific mRNAs. The Pearson correlation analysis suggested that 13 genes were significantly correlated with AS events (Pearson correlation coefficient >0.8 or <−0.8). Then, We conducted multivariate Cox regression analyses to select the potential prognostic AS genes. Seven genes were identified to be significantly related to OS. A prognostic model based on seven genes was constructed. The area under the ROC curve was 0.767. In the current study, a robust prognostic prediction model was constructed for KIRC patients, and the findings revealed that the AS events could act as potential prognostic biomarkers for KIRC.     

Prognostic prediction and diagnostic role of intercellular adhesion molecule-1 (ICAM1) expression in clear cell renal cell carcinoma

The intercellular adhesion molecule-1 (ICAM1) has been reported to function in multiple malignancies, but its effect on clear cell renal cell carcinoma (ccRCC) hasn’t been discussed yet. This study aimed to identify the potential role of ICAM1 in prognostic prediction and early diagnosis of ccRCC. ICAM1 expression was inspected by immunohistochemistry and correlated with clinicopathologic variables. Association between protein expression and cancer-specific survival (CSS) of ccRCC patients was evaluated and the value of area under the receiver operating characteristics (ROC) curve (AUC) was calculated to measure the protein’s diagnostic accuracy. ICAM1 was positively immunostained in 83.2 % of 173 ccRCC tissues, but negatively immunostained in all the para-cancerous normal epitheliums of renal tubules. High ICAM1 expression was significantly related to male sex (P = 0.00241), T3/T4 stage (P = 0.02249), non-N0M0 stage (P = 0.03797) and positive renal pelvis invasion (P = 0.04227). Kaplan–Meier survival analysis illustrated that high ICAM1 expression was significantly correlated to a decreased CSS (P = 0.00006). Multivariate Cox analysis indicated that ICAM1 was an independent predictor for CSS of patients (P = 0.00451). Furthermore, the AUC value of ICAM1 in diagnosing ccRCC was 0.916 (P < 0.00001). In conclusion, high ICAM1 expression on tumor cells indicates a poor outcome of patients and ICAM1 is likely to be an independent predictor for the prognosis of ccRCC. Moreover, ICAM1 has a high AUC value and may be a potential and useful diagnostic marker.