Abstract
Abstract
Background
Breast cancer is a common cause of cancer death among women with a complex and heterogeneous picture in histological, molecular and clinical features. The aim of this study was to identify hub gene and their target microRNAs in related pathways for breast cancer.
Methods
We selected screening methods for differentially expressed mRNAs and miRNAs using expression profile data of breast cancer from the cancer genome atlas. Using some databases for annotation, the functional and pathway enrichment for differential expression genes was performed. We selected genes and miRNAs with differential expression pattern. Then we determined target genes for differential expression miRNAs (DEMIs) and intersection between them was selected as differentially expressed miRNA–target genes for breast cancer. In the next step, we constructed miRNA–mRNA regulatory network and protein–protein interaction (PPI) network for more information.
Results
Top 10 DEMIs were identified from miRNA profile. Then, we selected 354 genes as target gene for 10 DEMIs. The miRNA–mRNA and PPI network were constructed, and 10 hub genes and 5 miRNAs identified that some of them are new for breast cancer. Also, miRNA–target genes with differential expressions in this study were all mainly involved in signaling pathways and developmental process.
Conclusion
This study identified some candidate biomarkers for breast cancer that they have a potential role in pathways related to breast. These findings can be used for research, early diagnosis and therapeutic goals.
Publisher
Springer Science and Business Media LLC
Reference41 articles.
1. Adorno G, Lopez E, Burg MA, Loerzel V, Killian M, Dailey AB et al (2018) Positive aspects of having had cancer: a mixed-methods analysis of responses from the American Cancer Society Study of Cancer Survivors-II (SCS-II). Psychooncology 27(5):1412–1425
2. Loibl S, Poortmans P, Morrow M, Denkert C, Curigliano G (2021) Epidemiology and risk factors
3. Ferlay JS, Foucher EL (2013) Cancerinci denceandmortalitypatternsinEurope: estimatesfor40countriesin 2012. EurJCancer 49(6):1374
4. Sun Y-S, Zhao Z, Yang Z-N, Xu F, Lu H-J, Zhu Z-Y et al (2017) Risk factors and preventions of breast cancer. Int J Biol Sci 13(11):1387
5. Xia L, Su X, Shen J, Meng Q, Yan J, Zhang C et al (2018) ANLN functions as a key candidate gene in cervical cancer as determined by integrated bioinformatic analysis. Cancer Manag Res 10:663