A TOP2A‑derived cancer panel drives cancer progression in papillary renal cell carcinoma

Ye, Mushi; He, Zhuobin; Dai, Wei; Li, Zhuo; Chen, Xiaojun; Liu, Jianjun

doi:10.3892/ol.2018.9179

Cited by 9 publications

(9 citation statements)

References 39 publications

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“…These results suggest that higher TOP2A levels lead to EC progression and represent a higher degree of malignancy in EC. In other studies, TOP2A was upregulated in cancer tissues when compared with that of adjacent non-cancerous tissues in breast cancer (Wang et al, 2012), renal cell carcinoma (Ye et al, 2018), ovarian cancer (Erriquez et al, 2015), prostate cancer (De Resende et al, 2013), nasopharyngeal carcinoma (Lan et al, 2014), and colon cancer (Zhang et al, 2018). Furthermore, TOP2A overexpression is a positive tumor metastasis marker and a poor biomarker for prognosis.…”

Section: Discussionmentioning

confidence: 86%

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Liu

Lin

2019

Front. Genet.

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Background and Objective: Endometrial cancer (EC) is a common gynecological malignancy worldwide. Despite advances in the development of strategies for treating EC, prognosis of the disease remains unsatisfactory, especially for advanced EC. The aim of this study was to identify novel genes that can be used as potential biomarkers for identifying the prognosis of EC and to construct a novel risk stratification using these genes. Methods and Results: An mRNA sequencing dataset, corresponding survival data and expression profiling of an array of EC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Common differentially expressed genes (DEGs) were identified based on sequencing and expression as given in the profiling dataset. Pathway enrichment analysis of the DEGs was performed using the Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction network was established using the string online database in order to identify hub genes. Univariate and multivariable Cox regression analyses were used to screen prognostic DEGs and to construct a prognostic signature. Survival analysis based on the prognostic signature was performed on TCGA EC dataset. A total of 255 common DEGs were found and 11 hub genes (TOP2A, CDK1, CCNB1, CCNB2, AURKA, PCNA, CCNA2, BIRC5, NDC80, CDC20, and BUB1BA) that may be closely related to the pathogenesis of EC were identified. A panel of 7 DEG signatures consisting of PHLDA2, GGH, ESPL1, FAM184A, KIAA1644, ESPL1, and TRPM4 were constructed. The signature performed well for prognosis prediction (p < 0.001) and time-dependent receiver-operating characteristic (ROC) analysis displayed an area under the curve (AUC) of 0.797, 0.734, 0.729, and 0.647 for 1, 3, 5, and 10-year overall survival (OS) prediction, respectively. Conclusion: This study identified potential genes that may be involved in the pathophysiology of EC and constructed a novel gene expression signature for EC risk stratification and prognosis prediction.

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Section: Discussionmentioning

confidence: 86%

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Liu

Lin

2019

Front. Genet.

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“…TOP2A (Topoisomerase 2-alpha) is a critical enzyme in DNA replication, transcription and regulating the topologic states of DNA. Studies have confirmed that TOP2A is implicated in various types of tumors, such as gastric cancer (Terashima et al, 2017), colon cancer (Hou et al, 2018), pancreatic cancer (Pei, Yin & Liu, 2018) and papillary renal cell carcinoma (Ye et al, 2018). TOP2A is reported to be a novel prognostic marker in renal cell carcinoma (Lu et al, 2017).…”

Section: Discussionmentioning

confidence: 96%

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

Zhang

Zou

Yin

et al. 2019

PeerJ

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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 was downloaded from the Gene Expression Omnibus database. The 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.

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“…30,33,34 It is also important for the progression of prognostic marker for papillary RCC. 50 Aurora-A (AURKA) and Aurora-B (AURKB) are kinases that play key roles in the regulation of cell-cycle progression. [51][52][53] In addition to cell cycle regulation, Aurora-A is involved in contributing to epithelial-mesenchymal transition (EMT) and stem-like properties of cancer cells.…”

Section: Discussionmentioning

confidence: 99%

“…It is upregulated in ccRCC and associated with progression and prognosis, especially survival among patients undergoing surgery, with a more prominent prognostic value among patients with low‐risk disease 30,33,34 . It is also important for the progression of prognostic marker for papillary RCC 50 …”

Section: Discussionmentioning

confidence: 99%

Influence of gene expression on survival of clear cell renal cell carcinoma

et al. 2020

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A TOP2A‑derived cancer panel drives cancer progression in papillary renal cell carcinoma

Cited by 9 publications

References 39 publications

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

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

Influence of gene expression on survival of clear cell renal cell carcinoma

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