Original Article

Association of hsa-miR‐5571-5p Expression with Clinicopathological Factors besides Identification of its Hub Target Genes and Key Pathway in Breast Cancer

Abstract

Background: miRNAs are small non-coding RNAs; regulate gene expression using RNA degradation or translation repression. Dysregulation of miRNAs is involved in the initiation and progression of many cancers. We aimed to determine the relationship between miR-5571-5p expression and clinical factors and regulatory mechanisms in breast cancer.

Methods: Histopathologic sections approximately with 25 microns thick from FFPE tissues were achievement of Al-Zahra Hospital (Isfahan, Iran) in 2020-2021 years by Pathologist. miR-5571-5p expression, determined using real-time PCR. For miRNA target genes prediction, integrated miRNA target prediction tools, were used. Gene ontology and KEGG pathway analysis were accomplished to identify the biological function. A PPI network was constructed to display key target genes. For hub genes validation, GEPIA databases were used.

Results: miR-5571-5p was upregulated in breast tumor tissues, and its increase was significantly related to a poor prognosis in breast cancer (P<0.0001). At first, 324 target genes were predicted, and then 110 genes with a decrease in expression were selected. GO analysis showed that genes were mainly enriched in the regulation of the ERBB2 and EGFR signaling pathway. KEGG pathway analysis suggested that downregulated genes were enriched in glioma, the ErbB signaling pathway, and breast cancer. Finally, the ten hub genes (EGF, PIK3R1, SOS1, PTEN, SHC1, CBLB, LIFR, LEP, PDE1C, and NT5C2) were detected from the PPI network.

Conclusion: miR-5571-5p up-regulation is associated with breast cancer progression and worse survival. The current study identified ten genes associated with breast cancer, which might help to provide candidate targets for the treatment.

 

1. Azamjah N, Soltan-Zadeh Y, Zayeri F (2019). Global Trend of Breast Cancer Mortality Rate: A 25-Year Study. Asian Pac J Cancer Prev, 20:2015-2020.
2. Perou CM, Sorlie T, Eisen MB, et al (2000). Molecular portraits of human breast tumours. Nature, 406:747-52.
3. Barber MD, Jack W, Dixon JM (2004). Diagnostic delay in breast cancer. Br J Surg, 91:49-53.
4. Chen W, Zheng R, Baade PD, et al (2016). Cancer statistics in China, 2015. CA Cancer J Clin, 66:115-132.
5. Hill M, Tran N (2021). miRNA interplay: mechanisms and consequences in cancer. Dis Model Mech, 14(4):dmm047662.
6. Bartel DP (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 116:281-97.
7. O'Day E, Lal A (2010). MicroRNAs and their target gene networks in breast cancer. Breast Cancer Res, 12(2):201.
8. Peng Y, Croce CM (2016). The role of MicroRNAs in human cancer. Signal Transduct Target Ther, 1:15004.
9. Pu Q, Huang Y, Lu Y, et al (2016). miRNA biomarkers of NSCLC in TNM stage. Thorac Cancer, 7:348-354.
10. Ma F, Zhang J, Zhong L, et al (2014). Upregulated microRNA-301a in breast cancer promotes tumor metastasis by targeting PTEN and activating Wnt/β-catenin signaling. Gene, 535:191-197.
11. Wang H, Chen F, Tong J, et al (2017). Circulating microRNAs as novel biomarkers for dilated cardiomyopathy. Cardiol J, 24:65-73.
12. Li C, Tang Z, Zhang W, Ye Z, Liu F (2021). GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA. Nucleic Acids Res.
13. Kuleshov MV, Jones MR, Rouillard AD, et al (2016). Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res, 44(W1):W90-7.
14. Shannon P, Markiel A, Ozier O, et al (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res, 13:2498-2504.
15. Györffy B, Lanczky A, Eklund AC, et al (2010). An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res Treat, 123:725-731.
16. Lánczky A, Nagy Á, Bottai G, et al (2016). miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients. Breast Cancer Res Treat, 160:439-446.
17. Lango-Chavarria M, Chimal-Ramirez G, Ruiz-Tachiquin M, et al (2017). A 22q11. 2 amplification in the region encoding microRNA-650 correlates with the epithelial to mesenchymal transition in breast cancer primary cultures of Mexican patients. Int J Oncol, 50:432-440.
18. Malvestiti F, Agrati C, Chinetti S, et al (2014). Complex variant of Philadelphia translocation involving chromosomes 9, 12, and 22 in a case with chronic myeloid leukaemia. Case Rep Genet, 2014:691630.
19. Li W, Liu S, Su S, Chen Y, Sun G (2021). Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma. PeerJ, 9:e10470.
20. Liu H, Wu L, Cui J, Wang D (2023). Anticancer Activity of Zn (II) Coordination Polymer Against Cervical Cancer Cells via miR-5571/MDM2. J Clust Sci, 34:1195–1206
21. Yan L-X, Liu Y-H, Xiang J-W, et al (2016). PIK3R1 targeting by miR-21 suppresses tumor cell migration and invasion by reducing PI3K/AKT signaling and reversing EMT, and predicts clinical outcome of breast cancer. Int J Oncol, 48:471-484.
22. Cizkova M, Vacher S, Meseure D, et al (2013). PIK3R1 underexpression is an independent prognostic marker in breast cancer. BMC Cancer, 13:545.
23. Carbognin L, Miglietta F, Paris I, Dieci MV (2019). Prognostic and predictive implications of PTEN in breast cancer: Unfulfilled promises but intriguing perspectives. Cancers (Basel), 11(9):1401.
24. Leslie NR, Downes CP (2004). PTEN function: how normal cells control it and tumour cells lose it. Biochem J, 382(Pt 1):1-11.
25. Fang H, Xie J, Zhang M, et al (2017). miRNA-21 promotes proliferation and invasion of triple-negative breast cancer cells through targeting PTEN. Am J Transl Res, 9(3):953-961.
26. Xu L, Zhang Y, Qu X, et al (2017). E3 ubiquitin ligase Cbl-b prevents tumor metastasis by maintaining the epithelial phenotype in multiple drug-resistant gastric and breast cancer cells. Neoplasia, 19:374-382.
27. Murakami M, Kamimura D, Hirano T (2019). Pleiotropy and specificity: insights from the interleukin 6 family of cytokines. Immunity, 50:812-831.
28. Hergovich A (2012). YAP-Hippo signalling downstream of leukemia inhibitory factor receptor: implications for breast cancer. Breast Cancer Res, 14(6):326.
29. Andò S, Gelsomino L, Panza S, et al (2019). Obesity, leptin and breast cancer: epidemiological evidence and proposed mechanisms. Cancers (Basel), 11:62.
30. Wu M, Zhao H (2020). Analysis of key genes and pathways in breast ductal carcinoma in situ. Oncol Lett, 20:217.
31. Jin TY, Saindane M, Park KS, et al (2021). LEP as a potential biomarker in prognosis of breast cancer: Systemic review and meta analyses (PRISMA). Medicine (Baltimore), 100(33):e26896.
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IssueVol 52 No 5 (2023) QRcode
SectionOriginal Article(s)
DOI https://doi.org/10.18502/ijph.v52i5.12723
Keywords
Breast cancer Bioinformatics miRNA targets

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How to Cite
1.
Samie Ghahfarokhi M, Reiisi S, Zamanzadeh Z, Abkar M. Association of hsa-miR‐5571-5p Expression with Clinicopathological Factors besides Identification of its Hub Target Genes and Key Pathway in Breast Cancer. Iran J Public Health. 2023;52(5):1048-1060.