scholarly journals Glycolysis-Related Genes Serve as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Yan Zhang ◽  
Mingying Chen ◽  
Meihong Liu ◽  
Yingkun Xu ◽  
Guangzhen Wu
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Predictive Model ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Drug Sensitivity ◽  
Clear Cell ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma

Metabolic rearrangement is a marker of cancer that has been widely studied in recent years. One of the major metabolic characteristics of tumor cells is the high levels of glycolysis, even under aerobic conditions, a phenomenon that is called the “Warburg effect.” We investigated the expression and copy number variation (CNV) frequency of all glycolysis-related genes in multiple cancer types and found many differentially expressed genes, particularly in clear cell renal cell carcinoma (ccRCC). Single nucleotide variants (SNVs) showed that the overall average mutation frequency for all genes was low. The purpose of this study was to establish a predictive model by studying glycolysis-related genes in ccRCC. We compared the expression of glycolysis-related genes in 539 ccRCC tissues and 72 normal renal tissues from The Cancer Genome Atlas dataset and identified 17 upregulated and 26 downregulated genes. Pathway analysis revealed that PSAT1 and SDHB could activate the cell cycle, RPIA could activate the DNA damage response, and HK3 could activate apoptosis and EMT signaling, while PDK2 could inhibit apoptosis. The results of the drug sensitivity analysis suggested that some of these differentially expressed genes were positively correlated with drug sensitivity. Thirteen genes were selected from the gene coexpression network and the LASSO regression analysis. The Kaplan-Meier overall survival curves showed that the expression of upregulated genes in ccRCC patients was associated with lower overall survival. We established a predictive model consisting of 13 genes (RPIA, G6PD, PSAT1, ENO2, HK3, IDH1, PDK4, PGM2, PGK1, FBP1, OGDH, SUCLA2, and SUCLG2). This predictive model correlated well with the development and progression of ccRCC. Thus, it is of great value in the diagnosis and prognostic evaluation of ccRCC and may aid the identification of potential prognostic biomarkers and drug targets.

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 Genome-Wide Analysis of Differentially Expressed Genes and Splicing Isoforms in Clear Cell Renal Cell Carcinoma

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e78452 ◽  
Author(s):  
Alessio Valletti ◽  
Margherita Gigante ◽  
Orazio Palumbo ◽  
Massimo Carella ◽  
Chiara Divella ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Clear Cell ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Splicing Isoforms

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

2020 ◽  
Vol 10 ◽  
Author(s):  
Bing Zhang ◽  
Wei Chu ◽  
Feifei Wen ◽  
Li Zhang ◽  
Lixia Sun ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Biological Function ◽  
Clear Cell ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Cell Renal Cell Carcinoma ◽  
Non Coding Rnas

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.

scholarly journals Differentially Expressed Genes in Clear Cell Renal Cell Carcinoma as a Potential Marker for Prognostic and Immune Signatures

2021 ◽  
Vol 11 ◽  
Author(s):  
Ying Tong ◽  
Yiwen Yu ◽  
Hui Zheng ◽  
Yanchun Wang ◽  
Suhong Xie ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Clear Cell ◽  
Differentially Expressed ◽  
High Expression ◽  
Molecular Networks ◽  
Cell Renal Cell Carcinoma ◽  
Potential Marker

Clear cell renal cell carcinoma (ccRCC) is characterized by the inactivation of the von Hippel–Lindau (VHL) gene. Of note, no other gene is mutated as frequently as VHL in ccRCC, turning out that patients with inactivated VHL constitute the majority of ccRCC-related character. Thus, differentially expressed genes (DEGs) and their molecular networks caused by VHL mutation were considered as important factors for influencing the prognosis of ccRCC. Here, we first screened out six DEGs (GSTA1, GSTA2, NAT8, FABP7, SLC17A3, and SLC17A4) which downregulated in ccRCC patients with VHL non-mutation than with the mutation. Generally, most DEGs with high expression were associated with a favorable prognosis and low-risk score. Meanwhile, we spotted transcription factors and their kinases as hubs of DEGs. Finally, we clustered ccRCC patients into three subgroups according to the expression of hub proteins, and analyzed these subgroups with clinical profile, outcome, immune infiltration, and potential Immune checkpoint blockade (ICB) response. Herein, DEGs might be a promising biomarker panel for immunotherapy and prognosis in ccRCC. Moreover, the ccRCC subtype associated with high expression of hubs fit better for ICB therapy.

scholarly journals Nuclear and cytosolic pS727-STAT3 levels correlate with overall survival of patients affected by clear cell renal cell carcinoma (ccRCC)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jazmine Arévalo ◽  
David Lorente ◽  
Enrique Trilla ◽  
María Teresa Salcedo ◽  
Juan Morote ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Independent Manner ◽  
Fuhrman Grade ◽  
Transcription 3 ◽  
Aggressive Subtype

AbstractClear cell renal cell carcinoma (ccRCC) is the most frequent and aggressive subtype of renal carcinoma. So far, the basis of its oncogenesis remains unclear resulting in a deficiency of usable and reliable biomarkers for its clinical management. Previously, we showed that nuclear expression of the signal transducer and activator of transcription 3 (STAT3), phosphorylated at its serine 727 (pS727), was inversely proportional to the overall survival of ccRCC patients. Therefore, in the present study, we validated the value of pS727-STAT3 as a clinically relevant biomarker in ccRCC. This work is a retrospective study on 82 ccRCC patients treated with nephrectomy and followed-up for 10 years. Immunohistochemical expression of pS727-STAT3 was analyzed on a tissue microarray and nuclear and cytosolic levels were correlated with clinical outcome of patients. Our results showed that pS727-STAT3 levels, whether in the nucleus (p = 0.002; 95% CI 1.004–1.026) or the cytosol (p = 0.040; 95% CI 1.003–1.042), significantly correlate with patients’ survival in an independent-manner of clinicopathological features (Fuhrman grade, risk group, and tumor size). Moreover, we report that patients with high pS727-STAT3 levels who undergone adjuvant therapy exhibited a significant stabilization of the disease (~ 20 months), indicating that pS727-STAT3 can pinpoint a subset of patients susceptible to respond well to treatment. In summary, we demonstrated that high pS727-STAT3 levels (regardless of their cellular location) correlate with low overall survival of ccRCC patients, and we suggested the use of pS727-STAT3 as a prognostic biomarker to select patients for adjuvant treatment to increase their survival.

Factors Influencing Overall Survival for Patients With Metastatic Clear-Cell Renal-Cell Carcinoma in Daily Practice

2018 ◽  
Vol 16 (2) ◽  
pp. e297-e305 ◽  
Author(s):  
Antoine Thiery-Vuillemin ◽  
Tiphaine Cholley ◽  
Fabien Calcagno ◽  
Marion Hugues ◽  
Tristan Maurina ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Daily Practice ◽  
Cell Renal Cell Carcinoma ◽  
Factors Influencing
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