Identification of chemoresistance-associated microRNAs and hub genes in breast cancer using bioinformatics analysis

2021 ◽  
Author(s):  
Ming Wu ◽  
Yujie Zhao ◽  
Nanxi Peng ◽  
Zuo Tao ◽  
Bo Chen
Keyword(s):  
Breast Cancer ◽  
Bioinformatics Analysis ◽  
Hub Genes

scholarly journals Integrated bioinformatics analysis to identify 15 hub genes in breast cancer

2019 ◽  
Author(s):  
Haoxuan Jin ◽  
Xiaoyan Huang ◽  
Kang Shao ◽  
Guibo Li ◽  
Jian Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bioinformatics Analysis ◽  
Hub Genes

scholarly journals Identification of hub genes in triple-negative breast cancer by integrated bioinformatics analysis

Gland Surgery ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 799-806
Author(s):  
Li-Min Wei ◽  
Xin-Yang Li ◽  
Zi-Ming Wang ◽  
Yu-Kun Wang ◽  
Ge Yao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Bioinformatics Analysis ◽  
Hub Genes

Identification of hub genes associated with EMT-induced chemoresistance in breast cancer using integrated bioinformatics analysis

Gene ◽  
2021 ◽  
pp. 146016
Author(s):  
Bhavjot Kaur ◽  
Yahya Mukhlis ◽  
Jagadish Natesh ◽  
Dhanamjai Penta ◽  
Syed Musthapa Meeran
Keyword(s):  
Breast Cancer ◽  
Bioinformatics Analysis ◽  
Hub Genes

scholarly journals Bioinformatics analysis on enrichment analysis of potential hub genes in breast cancer

2021 ◽  
Vol 10 (5) ◽  
pp. 2399-2408
Author(s):  
Limin Wei ◽  
Yukun Wang ◽  
Dan Zhou ◽  
Xinyang Li ◽  
Ziming Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Hub Genes

scholarly journals Identification of hub genes and small molecule therapeutic drugs related to breast cancer with comprehensive bioinformatics analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9946
Author(s):  
Mingqian Hao ◽  
Wencong Liu ◽  
Chuanbo Ding ◽  
Xiaojuan Peng ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Small Molecule ◽  
Bioinformatics Analysis ◽  
Genetic Alterations ◽  
Clinicopathological Parameters ◽  
Gallium Nitrate ◽  
High Morbidity ◽  
Hub Genes ◽  
Drug Candidates

Breast cancer is one of the most common malignant tumors among women worldwide and has a high morbidity and mortality. This research aimed to identify hub genes and small molecule drugs for breast cancer by integrated bioinformatics analysis. After downloading multiple gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, 283 overlapping differentially expressed genes (DEGs) significantly enriched in different cancer-related functions and pathways were obtained using LIMMA, VennDiagram and ClusterProfiler packages of R. We then analyzed the topology of protein–protein interaction (PPI) network with overlapping DEGs and further obtained six hub genes (RRM2, CDC20, CCNB2, BUB1B, CDK1, and CCNA2) from the network via STRING and Cytoscape. Subsequently, we conducted genes expression verification, genetic alterations evaluation, immune infiltration prediction, clinicopathological parameters analysis, identification of transcriptional and post-transcriptional regulatory molecules, and survival analysis for these hub genes. Meanwhile, 29 possible drug candidates (e.g., Cladribine, Gallium nitrate, Alvocidib, 1β-hydroxyalantolactone, Berberine hydrochloride, Nitidine chloride) were identified from the DGIdb database and the GSE85871 dataset. In addition, some transcription factors and miRNAs (e.g., E2F1, PTTG1, TP53, ZBTB16, hsa-miR-130a-3p, hsa-miR-204-5p) targeting hub genes were identified as key regulators in the progression of breast cancer. In conclusion, our study identified six hub genes and 29 potential drug candidates for breast cancer. These findings may advance understanding regarding the diagnosis, prognosis and treatment of breast cancer.

Sign in / Sign up

Export Citation Format

Share Document