scholarly journals Multi-omics analysis reveals epithelial-mesenchymal transition-related gene FOXM1 as a novel prognostic biomarker in clear cell renal carcinoma

Aging ◽  
2019 ◽  
Vol 11 (22) ◽  
pp. 10316-10337 ◽  
Author(s):  
Jing Song ◽  
Fangzhou Song ◽  
Kun Liu ◽  
Wanfeng Zhang ◽  
Ruihan Luo ◽  
...  
Oncotarget ◽  
2014 ◽  
Vol 6 (4) ◽  
pp. 2193-2205 ◽  
Author(s):  
Nathaniel Weygant ◽  
Dongfeng Qu ◽  
Randal May ◽  
Ryan M. Tierney ◽  
William L. Berry ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xinghua Du ◽  
Haomin Li ◽  
Xuexia Xie ◽  
Liping Shi ◽  
Fan Wu ◽  
...  

PIWI-interacting RNAs (piRNAs) are small noncoding RNAs that play important roles in germline development and carcinogenesis. In this study, we used the deep sequencing of small RNA Transcriptome to explore the piRNA expression in six clear cell renal carcinoma (ccRCC) tissues and matched adjacent normal tissues and found that six piRNAs were upregulated and sixteen were downregulated in ccRCC tissues. Among them, piRNA-31115 (NCBI accession number: DQ571003) was the most upregulated piRNA in ccRCC tissues compared with matched adjacent normal tissues. Quantitative real-time PCR (qRT-PCR) was used to confirm piR-31115 expression in other ccRCC tissues ( n = 40 ) and ccRCC cell lines. Besides, function analysis demonstrated that silencing of piR-31115 inhibited ccRCC cell proliferation, motility, and invasiveness. Mechanistic investigations showed that piRNA-31115 may activate epithelial-mesenchymal transition (EMT) via the PI3K/AKT signaling pathway. Hence, piR-31115 may represent an oncogene in the development of ccRCC.


2021 ◽  
Author(s):  
Baishun Ma ◽  
Pu Wang

Abstract Background: PANK1 is expressed in some cancer types, but its role in clear cell renal carcinoma (ccRCC) is unclear. We aimed to demonstrate the relationship between PANK1 and ccRCC based on a cancer genomic atlas (TCGA) database.Methods: The Kruskal-Wallis test, Wilcoxon signed rank test and logistic regression were used to analyze the relationship between the clinical pathological characteristics of ccRCC and the expression of PANK1. The ROC curve was used to describe the prognostic value of PANK1 using area under curve (AUC) scores. Kaplan-Meier method and Cox regression analysis were used to evaluate the factors affecting the prognosis of ccRCC. Gene set enrichment analysis (GSEA) and immuno-infiltration analysis were performed to identify a significantly related function of PANK1.Results: PANK1 expression in renal clear cell carcinoma was different from that in stage N (P=1.3E-03),sex (P=5.1E-07),stage M(P=8.3E-04),residual tumor(P<0.001),T stage(T1 vsT4(P=6.5E-03),T1vsT3(P=6.9E-06)), histological grade (G1vsG4(P=3.6E-0.5),G2vsG4(P=2.1E-10),G3vsG4(P=1.7E-05)),pathologic stage(STAGE 1vs.STAGE4(P=1.4E-05),STAGE1vs.STAGE3(P=7.1E-05)). The ROC curve suggest that PANK1 has significant diagnostic and prognostic capabilities (AUC =0.898). Low expression of PANK1 predicted poor overall survival (OS) (P<0.001), while that of PANK1 (HR:0.398; 95% CI:0.248-0.639; P<0.001) is OS-independent predictor in patients with ccRCC. GSEA and immune infiltration analysis showed that the expression of PANK1 is related to extracellular matrix receptor pathway, signaling pathway related to hypertrophic cardiomyopathy, cytokine-cytokine receptor interaction pathway, as well as complement and coagulation cascade pathway.Conclusion: PANK1 expression is significantly associated with poor survival and immune infiltration of ccRCC, which may be a promising prognostic biomarker for ccRCC.


2004 ◽  
Vol 171 (4S) ◽  
pp. 436-436 ◽  
Author(s):  
Hyung L. Kim ◽  
David B. Seligson ◽  
Nicolette Janzen ◽  
Matthew H. Bui ◽  
Robert A. Figlin ◽  
...  

Oncogene ◽  
2007 ◽  
Vol 26 (45) ◽  
pp. 6499-6508 ◽  
Author(s):  
J S P Yuen ◽  
M E Cockman ◽  
M Sullivan ◽  
A Protheroe ◽  
G D H Turner ◽  
...  

2021 ◽  
Vol 22 (3) ◽  
pp. 1342
Author(s):  
Aleksandra Cios ◽  
Martyna Ciepielak ◽  
Wanda Stankiewicz ◽  
Łukasz Szymański

The development of new technologies and industry is conducive to the increase in the number and variety of electromagnetic field (EMF) sources in our environment. The main sources of EMF are high-voltage lines, household appliances, audio/video devices, mobile phones, radio stations, and radar devices. In the growing use of electronic devices, scientists are increasingly interested in the effects of EMF on human health. Even though many studies on the effects of EMF have already been carried out, none of them has shown a significant effect on mammals, including humans. Moreover, it is not entirely clear how EMF influences cell behavior. The International Agency for Research on Cancer on 31 May 2011, classified PEM as a possible carcinogenic factor. This study aimed to investigate the effect of the electromagnetic field on morphological and functional changes in clear cell renal carcinoma. The research was carried out on in vitro cultures of four cell lines: HEK293, 786-O 769-P, and Caki1. The results of the research showed that the EMF of low frequency had a slight effect on the viability of cells. EMF, which induced cell arrest in the G1 phase, increased the number of early apoptotic cells and decreased the number of viable cells in the 786-O line. EMF did not affect the proliferation and viability of HEK293 cells. Extreme low-frequency EMF (ELF-EMF) also showed an inhibitory effect on the migration and metastatic properties of clear cell kidney cancer cells. Moreover, shortly after the end of ELF-EMF exposure, significant increases in ROS levels were observed in all tested cell lines. As part of the work, it was shown that low-frequency EMF shows an inhibitory effect on the proliferation of primary cancer cells, diminishing their migratory, invasive, and metastatic abilities. It also increases the apoptosis of cancer cells and the amount of reactive oxygen species. Based on the results of our research, we want to point up that the effect of ELF-EMF depends on a specific metabolic state or at a specific stage in the cell cycle of the cells under study.


Author(s):  
Ying Ming ◽  
Xinyi Chen ◽  
Jingxu Xu ◽  
Haiyu Zhan ◽  
Jie Zhang ◽  
...  

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