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pmid:32922202

Potential mechanism of RRM2 for promoting Cervical Cancer based on weighted gene co-expression network analysis.

Jingtao Wang · Yuexiong Yi · Yurou Chen · Yao Xiong · Wei Zhang

International journal of medical sciences · 2020 doi:10.7150/ijms.47356

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complete

Experiment

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Data

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Analysis

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title
Potential mechanism of RRM2 for promoting Cervical Cancer based on weighted gene co-expression network analysis.
doi
10.7150/ijms.47356
pmid
32922202
authors array · 5 items
[0]
Jingtao Wang
[1]
Yuexiong Yi
[2]
Yurou Chen
[3]
Yao Xiong
[4]
Wei Zhang
journal
International journal of medical sciences
year
2020
abstract
Cervical cancer is the most common gynecologic malignant tumor, with a high incidence in 50-55-year-olds. This study aims to investigate the potential molecular mechanism of RRM2 for promoting the development of cervical cancer based on The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). RRM2 was found to be significant upregulated in cervical tissue (P<0.05) by extracting the expression of RRM2 from TCGA, GSE63514, GSE7410, GSE7803 and GSE9750. Survival analysis indicated that the overall survival was significantly worse in the patients with high-expression of RRM2 (P<0.05). The top 1000 positively/negatively correlated genes with RRM2 by Pearson Correlation test were extracted. The gene co-expression network by Weighted Gene Co-Expression Network Analysis (WGCNA) with these genes and the clinical characteristics (lymphocyte infiltration, monocyte infiltration, necrosis, neutrophil infiltration, the number of normal/stromal/tumor cells and the number of tumor nuclei) was constructed. By screening the hub nodes from the co-expression network, results suggested that RRM2 may co-express with relevant genes to regulate the number of stromal/tumor cells and the process of lymphocyte infiltration to promote the progression of cervical cancer. RRM2 is likely to become a novel potential diagnostic and prognostic biomarker of cervical cancer and provide evidence to support the study of mechanisms for cervical cancer.
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The comparison for each clinical characteristic between each classification in RRM2 expression was performed by student-t test.
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sections[4] "Expression distribution of RRM2 in cervical cancer tissues and patients' characteristics" paragraph 2
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The comparison for each clinical characteristic between each classification in RRM2 expression was performed by student-t test.
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The datasets used and/or analyzed during the current study are available in TCGA and GEO.
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Gene expression analysis of cervical cancer progression
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Top 10 positively correlated genes with RRM2
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Co-expression analysis with RRM2
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Top 10 positively correlated genes with RRM2
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Table 3
caption
Top 10 negatively correlated genes with RRM2
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1.69e-11
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[2]
7.19e-11
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304
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1.32e-10
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304
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[2]
1.55e-10
[3]
304
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TMEM150A
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-0.345
[2]
6.20e-10
[3]
304
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ZNF248
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-0.343
[2]
7.99e-10
[3]
304
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LOC144571
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[2]
1.31e-09
[3]
304
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FAM171A1
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[2]
1.57e-09
[3]
304
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ZNF626
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[2]
2.05e-09
[3]
304
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RNF170
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-0.334
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2.39e-09
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304
locator
section[13]/table-wrap[2]#T3
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The comparison for each clinical characteristic between each classification in RRM2 expression was performed by student-t test.
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The P value obtained from a log-ran
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Automated Assays Laravel application and simulated adapters
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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GSE7410
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GSE7803 and GSE9750
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GSE63514
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GSE7410
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The datasets used and/or analyzed during the current study are available in TCGA and GEO.
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The paper names GSE63514, GSE7410 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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PMID 32922202 full text
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GEO GSE63514
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The comparison for each clinical characteristic between each classification in RRM2 expression was performed by student-t test.
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This study aims to investigate the potential molecular mechanism of RRM2 for promoting the development of cervical cancer based on The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). RRM2 was found to be significant upregulated in cervical tissue (P<0.05) by extracting the expression of RRM2 from TCGA, GSE63514, GSE7410, GSE7803 and GSE9750. Survival analysis indicated that the overall survival was significantly worse in the patients with high-expression of RRM2 (P<0.05). The top 1000 positively/negatively correlated genes with RRM2 by Pearson Correlation test were extracted. The gene co-expression network by Weighted Gene Co-Expression Network Analysis (WGCNA) with these genes and the clinical characteristics (lymphocyte infiltration, monocyte infiltration, necrosis, neutrophil infiltration, the number of normal/stromal/tumor cells and the number of tumor nuclei) was constructed. By screening the hub nodes from the co-expression network, results suggested that RRM2 may co-express with relevant genes to regulate the number of stromal/tumor cells and the process of lymphocyte infiltration to promote the progression of cervical cancer. 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