scholarly journals Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Wen Li ◽  
Xiaobin Wang ◽  
Xianbin Zhang ◽  
Peng Gong ◽  
Degang Ding ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Multiple Reaction Monitoring ◽  
Leading Edge ◽  
Lipid Classes ◽  
Metabolic Reprogramming ◽  
Cell Renal Cell Carcinoma

Abstract Background The high drug resistance and metabolic reprogramming of clear cell renal cell carcinoma (ccRCC) are considered responsible for poor prognosis. In-depth research at multiple levels is urgently warranted to illustrate the lipid composition, distribution, and metabolic pathways of clinical ccRCC specimens. Methods In this project, a leading-edge targeted quantitative lipidomic study was conducted using 10 pairs of cancerous and adjacent normal tissues obtained from ccRCC patients. Accurate lipid quantification was performed according to a linear equation calculated using internal standards. Qualitative and quantitative analyses of lipids were performed with multiple reaction monitoring analysis based on ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS). Additionally, a multivariate statistical analysis was performed using data obtained on lipids. Results A total of 28 lipid classes were identified. Among them, the most abundant were triacylglycerol (TG), diacylglycerol (DG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE). Cholesteryl ester (CE) was the lipid exhibiting the most considerable difference between normal samples and tumor samples. Lipid content, chain length, and chain unsaturation of acylcarnitine (CAR), CE, and DG were found to be significantly increased. Based on screening for variable importance in projection scores ≥1, as well as fold change limits between 0.5 and 2, 160 differentially expressed lipids were identified. CE was found to be the most significantly upregulated lipid, while TG was observed to be the most significantly downregulated lipid. Conclusion Based on the absolute quantitative analysis of lipids in ccRCC specimens, it was observed that the content and change trends varied in different lipid classes. Upregulation of CAR, CE, and DG was observed, and analysis of changes in the distribution helped clarify the causes of lipid accumulation in ccRCC and possible carcinogenic molecular mechanisms. The results and methods described herein provide a comprehensive analysis of ccRCC lipid metabolism and lay a theoretical foundation for cancer treatment.

scholarly journals Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8096 ◽  
Author(s):  
Haiping Zhang ◽  
Jian Zou ◽  
Ying Yin ◽  
Bo Zhang ◽  
Yaling Hu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Clinical Stage ◽  
Stage I ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

scholarly journals Integrative Bioinformatics Analysis Demonstrates the Prognostic Value of Chromatin Accessibility Biomarkers in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Meng Meng ◽  
Tianjun Lan ◽  
Duanqing Tian ◽  
Zeman Qin ◽  
Yu Li ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Proportional Hazards Model ◽  
Immune Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Chromatin Accessibility ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for 75%–85% of renal cell carcinoma (RCC) and has a poor 5-year survival rate. In recent years, medical advancement has promoted the understanding of the histopathological and molecular characterization of ccRCC; however, the carcinogenesis and molecular mechanisms of ccRCC remain unclear. Chromatin accessibility is an essential determinant of cellular phenotype. This study aimed to explore the potential role of chromatin accessibility in the development and progression of ccRCC. By the combination of open-access genome-wide chromatin accessibility profiles and gene expression profiles in ccRCC, we obtained a total of 13,474 crucial peaks, corresponding to 5,120 crucial genes and 9,185 differentially expressed genes. Moreover, two potential function modules (P2 and G4) that contained 129 upregulated genes were identified via the weighted gene co-expression network analysis (WGCNA). Furthermore, we obtained five independent predictors (FSCN1, SLC17A9, ANKRD13B, ADCY2, and MAPT), and a prognostic model was established based on these genes through the least absolute shrinkage and selection operator-proportional hazards model (LASSO-Cox) analysis. This model can stratify the ccRCC samples into a high-risk and a low-risk group, from which the patients have distinct prognosis. Further analysis demonstrated a completely different immune cell infiltration pattern between these two risk groups. This study also suggested that mast cell resting is associated with the prognosis of ccRCC and could be a target of immunotherapy. Overall, this study indicated that chromatin accessibility plays an essential role in ccRCC. The five prognostic chromatin accessibility biomarkers and the prognostic immune cells can provide a new direction for the treatment of ccRCC.

scholarly journals Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Dengyong Xu ◽  
Yuzi Xu ◽  
Yiming Lv ◽  
Fei Wu ◽  
Yunlong Liu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Early Diagnosis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Clear Cell ◽  
Clinical Stage ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a major histological subtype of renal cell carcinoma and can be clinically divided into four stages according to the TNM criteria. Identifying clinical stage-related genes is beneficial for improving the early diagnosis and prognosis of ccRCC. By using bioinformatics analysis, we aim to identify clinical stage-relevant genes that are significantly associated with the development of ccRCC. First, we analyzed the gene expression microarray data sets: GSE53757 and GSE73731. We divided these data into five groups by staging information—normal tissue and ccRCC stages I, II, III, and IV—and eventually identified 500 differentially expressed genes (DEGs). To obtain precise stage-relevant genes, we subsequently applied weighted gene coexpression network analysis (WGCNA) to the GSE73731 dataset and KIRC data from The Cancer Genome Atlas (TCGA). Two modules from each dataset were identified to be related to the tumor TNM stage. Several genes with high inner connection inside the modules were considered hub genes. The intersection results between hub genes of key modules and 500 DEGs revealed UBE2C, BUB1B, RRM2, and TPX2 as highly associated with the stage of ccRCC. In addition, the candidate genes were validated at both the RNA expression level and the protein level. Survival analysis also showed that 4 genes were significantly correlated with overall survival. In conclusion, our study affords a deeper understanding of the molecular mechanisms associated with the development of ccRCC and provides potential biomarkers for early diagnosis and individualized treatment for patients at different stages of ccRCC.

scholarly journals The ceRNA Network Has Potential Prognostic Value in Clear Cell Renal Cell Carcinoma: A Study Based on TCGA Database

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Haosheng Liu ◽  
Zhaowen Zhu ◽  
Jianxiong Fang ◽  
Tianqi Liu ◽  
Zhenhui Zhang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Kidney Development ◽  
Cox Regression ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Cerna Network

Clear cell renal cell carcinoma (ccRCC) is a very common cancer in urology. Many evidences suggest that complex changed pathways take a nonnegligible part in the occurrence and development of ccRCC. Nevertheless, the underlying mechanism is not clear. In this study, the expression data between ccRCC and normal tissue samples in TCGA database were compared to distinguish differentially expressed genes (DEGs: mRNAs, miRNAs, and lncRNAs). Afterwards, we used GO enrichment and KEGG pathway enrichment analyses to explore the functions of these DEGs. We also found the correlation between three RNAs and created a competing endogenous RNA (ceRNA) network. Moreover, we used univariate Cox regression analysis to select DEGs that are connected with overall survival (OS) of ccRCC patients. We found 1652 mRNAs, 1534 lncRNAs, and 173 miRNAs that were distinguished in ccRCC compared with normal tissues. According to GO analysis, the maladjusted mRNAs are mainly concentrated in immune cell activation and kidney development, while according to KEGG, they are mainly concentrated in pathways related to cancer. A total of 5 mRNAs, 1 miRNA, and 4 lncRNAs were connected with patients’ OS. In this article, a network of lncRNA-miRNA-mRNA was established; it is expected to be able to indicate possible molecular mechanisms for initial of ccRCC and provide a new viewpoint for diagnosis of ccRCC.

scholarly journals CircAGAP1 promotes tumor progression by sponging miR-15-5p in clear cell renal cell carcinoma

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Qi Lv ◽  
Gangmin Wang ◽  
Yinan Zhang ◽  
Aijun Shen ◽  
Junjun Tang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Progression ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Luciferase Reporter ◽  
Clinical Samples ◽  
Cell Renal Cell Carcinoma

Abstract Background Accumulating evidence has revealed that circular RNAs (circRNAs), as novel noncoding RNAs, play critical roles in carcinogenesis and tumor progression. However, the functions and molecular mechanisms of circRNAs in clear cell renal cell carcinoma (ccRCC) are largely unknown. Methods The expression and functions of circAGAP1 were identified in clinical samples, ccRCC cells and in vivo animal models. The molecular mechanism of circAGAP1 was investigated by fluorescence in situ hybridization, RNA immunoprecipitation and luciferase assays. Results circAGAP1 (circ0058792) expression was significantly upregulated in ccRCC tissues compared to adjacent nontumor tissues. Moreover, the expression of circAGAP1 was closely related to the tumor size, nuclear grade and clinical stage of ccRCC in patients. Mechanistic studies demonstrated that cytoplasmic circAGAP1 targeted miR-15-5p in an RNA-induced silencing complex. Additionally, miR-15-5p expression was downregulated in ccRCC. Luciferase reporter assays showed that E2F transcription factor 3 (E2F3) was a target of miR-15-5p, and upregulated E2F3 expression was positively correlated with circAGAP1 in ccRCC. Furthermore, the tumor-promoting functions of circAGAP1 could be alleviated by miR-15-5p mimics in vitro and in vivo. Conclusion Our results clarify that circAGAP1 exerts its oncogenic functions as a competitive endogenous RNA (ceRNA) by sponging miR-15-5p, which promotes E2F3 expression. Targeting circAGAP1 might be a new attractive therapeutic strategy in ccRCC.

scholarly journals SETD2 deficiency impairs β-catenin destruction complex to facilitate renal cell carcinoma formation

2020 ◽  
Author(s):  
Hanyu Rao ◽  
Xiaoxue Li ◽  
Min Liu ◽  
Jing Liu ◽  
Wenxin Feng ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Set Domain ◽  
Cell Renal Cell Carcinoma ◽  
Incurable Disease ◽  
First Time

AbstractClear cell renal cell carcinoma (ccRCC) is a largely incurable disease that is highly relevant to epigenetic regulation including histone modification and DNA methylation. SET domain–containing 2 (SETD2) is a predominant histone methyltransferase catalyzing the trimethylation of histone H3 Lysine 36 (H3K36me3) and its mutations are highly relevant to clear cell renal cell carcinoma (ccRCC). However, its physiology role in ccRCC remains largely unexplored. Here we report that Setd2 deletion impairs the β-catenin destruction complex to facilitate ccRCC formation in a c-MYC-generated polycystic kidney disease (PKD) model, which can be relieved by an inhibitor of β-catenin-responsive transcription. Clinically, SETD2 loss is widely observed in ccRCC samples, and negatively correlated with expression of some members of β-catenin destruction complex, but positively correlated with the activation of Wnt/β-catenin signaling. Our findings thus highlight a previously unrecognized role of SETD2-mediated H3K36me3 modification in regulation of Wnt/β-catenin pathway in ccRCC.SummaryOur findings for the first time reveal a previously unrecognized role of the SETD2-mediated H3K36me3 modification in regulation of the Wnt/β-catenin pathway in ccRCC and shed light on the molecular mechanisms underlying the formation of renal cell carcinoma with epigenetic disorders.

scholarly journals Expression of AOX1 Predicts Prognosis of Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Luyang Xiong ◽  
Yuchen Feng ◽  
Wei Hu ◽  
Jiahong Tan ◽  
Shusheng Li ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Clear Cell ◽  
Metabolic Reprogramming ◽  
Differentially Expressed ◽  
Normal Kidney ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Management

Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer worldwide, and appropriate cancer biomarkers facilitate early diagnosis, treatment, and prognosis prediction in cancer management. However, an accurate biomarker for ccRCC is lacking. This study identified 356 differentially expressed genes in ccRCC tissues compared with normal kidney tissues by integrative analysis of eight ccRCC datasets. Enrichment analysis of the differentially expressed genes unveiled improved adaptation to hypoxia and metabolic reprogramming of the tumor cells. Aldehyde oxidase 1 (AOX1) gene was identified as a biomarker for ccRCC among all the differentially expressed genes. ccRCC tissues expressed significantly lower AOX1 than normal kidney tissues, which was further validated by immunohistochemistry at the protein level and The Cancer Genome Atlas (TCGA) data mining at the mRNA level. Higher AOX1 expression predicted better overall survival in ccRCC patients. Furthermore, AOX1 DNA copy number deletion and hypermethylation were negatively correlated with AOX1 expression, which might be the potential mechanism for its dysregulation in ccRCC. Finally, we illustrated that the effect of AOX1 as a tumor suppressor gene is not restricted to ccRCC but universally exists in many other cancer types. Hence, AOX1 may act as a potential prognostic biomarker and therapeutic target for ccRCC.

scholarly journals Full-Length Enrich c-DNA Libraries-Clear Cell-Renal Cell Carcinoma

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Sai-Wen Tang ◽  
Jung-Yaw Lin
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Expression Profiles ◽  
Full Length ◽  
Cdna Libraries ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC), the most common subtype of RCC, is characterized by high metastasis potential and strong resistance to traditional therapies, resulting in a poor five-year survival rate of patients. Several therapies targeted to VEGF pathway for advanced RCC have been developed, however, it still needs to discover new therapeutic targets for treating RCC. Genome-wide gene expression analyses have been broadly used to identify unknown molecular mechanisms of cancer progression. Recently, we applied the oligo-capping method to construct the full-length cDNA libraries of ccRCC and adjacent normal kidney, and analyzed the gene expression profiles by high-throughput sequencing. This paper presents a review for recent findings on therapeutic potential of MYC pathway and nicotinamide N-methyltransferase for the treatment of RCC.

scholarly journals Circulating microRNAs from the Molecular Mechanisms to Clinical Biomarkers: A Focus on the Clear Cell Renal Cell Carcinoma

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1154
Author(s):  
Claudia Tito ◽  
Elena De Falco ◽  
Paolo Rosa ◽  
Alessia Iaiza ◽  
Francesco Fazi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Mirna Expression ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Transcriptional Level ◽  
Cell Renal Cell Carcinoma ◽  
Post Surgery ◽  
Clinical Biomarkers

microRNAs (miRNAs) are emerging as relevant molecules in cancer development and progression. MiRNAs add a post-transcriptional level of control to the regulation of gene expression. The deregulation of miRNA expression results in changing the molecular circuitry in which miRNAs are involved, leading to alterations of cell fate determination. In this review, we describe the miRNAs that are emerging as innovative molecular biomarkers from liquid biopsies, not only for diagnosis, but also for post-surgery management in cancer. We focus our attention on renal cell carcinoma, in particular highlighting the crucial role of circulating miRNAs in clear cell renal cell carcinoma (ccRCC) management. In addition, the functional deregulation of miRNA expression in ccRCC is also discussed, to underline the contribution of miRNAs to ccRCC development and progression, which may be relevant for the identification and design of innovative clinical strategies against this tumor.

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