| Tao Fan,Chaoqi Wang,Kun Zhang,Hong Yang,Juan Zhang,Wanyan Wu,Yingjie Song. Differentially expressed genes analysis and target genes prediction of miR-22 in breast cancer. Oncol Transl Med, 2021, 7: 59-64. |
| Differentially expressed genes analysis and target genes prediction of miR-22 in breast cancer |
| Received:October 05, 2020 Revised:March 04, 2021 |
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| KeyWord:bioinformatics; breast cancer; MCF7 cells; MiR-22 |
| Author Name | Affiliation | E-mail | | Tao Fan | Department of Oncology, The People''s Hospital of China Three Gorges University, The First People''s Hospital of Yichang | zhoujuying2017@163.com | | Chaoqi Wang | Department of Urinary Surgery, Affiliated Hospital of Inner Mongolia University for the Nationalities | | | Kun Zhang | Department of Orthopedics, The People''s Hospital of China Three Gorges University, The First People''s Hospital of Yichang | | | Hong Yang | Department of Oncology, The People''s Hospital of China Three Gorges University, The First People''s Hospital of Yichang | | | Juan Zhang | Department of Oncology, The People''s Hospital of China Three Gorges University, The First People''s Hospital of Yichang | | | Wanyan Wu | Department of Oncology, The People''s Hospital of China Three Gorges University, The First People''s Hospital of Yichang | | | Yingjie Song | Department of General Surgery, The People''s Hospital of China Three Gorges University, The First People''s Hospital of Yichang | 1601340054@qq.com |
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| Abstract: |
| Objective miR-22 is highly active in breast cancer, especially in the luminal B and HER2 subtypes.
However, the detailed potential of the use of target genes for miR-22 in breast cancer are still unclear. In
this study, we aimed to discover potential genes and the miRNA-DEGs network of miR-22 in breast cancer
using bioinformatics approaches.
Methods Analysis of microarray data GSE17508 (including 3 miR-22 knockout samples and 3 controls)
obtained from the Gene Expression Omnibus (GEO) database was performed. Differentially expressed
genes (DEGs) between the miR-22 knockout samples and the three control samples were detected using
GEO2R. The gene ontology (GO) functional enrichment analysis and protein-protein interaction (PPI)
network of DEGs were performed using the online tool Metascape and STRING database, separately. The
miR-22 and DEG networks were obtained from the miRNet database. Cytoscape software was used to
construct and analyze a merged miRNA-DEG network. The online tools database, mirDIP 4.1, was used to
predict miR-22 target genes.
Results Certain DEGs and miRNAs may be potential targets for predicting and treating miR-22 expressed
breast cancer.
Conclusion We constructed a prognostic model of rectal adenocarcinomas based on four immunerelated
lncRNAs by analyzing the data based on TCGA database, with high prediction accuracy. We also
identified two biomarkers with poor prognosis (PXN-AS1 and AL158152.2) and one biomarker with good
prognosis (LINC01871) |
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