Middle East Journal of Cancer

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Editorial Board

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

News

Forms

Journal Metrics

Identification of Breast Cancer Biomarkers by Constructing Protein-Protein Interaction and miRNAs-mRNAs Networks

Articles in Press

Document Type : Original Article(s)

Authors

1 Department of Biology, Faculty of Basic Sciences, Nourdanesh Institute of Higher Education, Meymeh, Isfahan, Iran

2 Department of Animal Science, Kashmar Branch, Islamic Azad University, Kashmar, Iran

10.30476/mejc.2024.100604.1994

Abstract

Background: In cancer-related diseases, early detection and control of disease progression are very important for successful treatment. Breast cancer is a significant problem due to its high mortality rate in the female population worldwide. By the early diagnosis of breast cancer, the 5-year survival rate reaches 93 to 98%. In this study, to identify breast cancer biomarkers, we construct new protein-protein interaction (PPI) and miRNAs-mRNAs networks by analyzing upregulated and downregulated genes in breast cancer patients.
Method: In this in silico study, two gene expression profile datasets, with the accession numbers GSE42568 and GSE154255, were downloaded from the GEO database. GEO2R was used to obtain differentially expressed mRNA (DEMs) and miRNAs (DEMIs) based on |logFC|>2 and adjusted P-value <0.05. Gene Ontology and KEGG Pathway Enrichment Analysis were performed by EnrichR. STRING v9. 1 and cytoHubba plugin in Cytoscape (v3.9.1) were used to investigate PPI network construction and identification of hub genes. Finally, key microRNAs (miRNAs) were predicted.
Results: After protein-protein interaction analysis, a total of 10 upregulated DEMs (DLGAP5, CCNB1, TTK, NUSAP1, RRM2, BUB1B, CDK1, CENPF, TOP2A, and ASPM) and 10 downregulated DEMs (PPARG, LIPE, CD36, FABP4, SCD, LPL, DGAT2, PNPLA2, ACSL1, and LEP) were screened as hub genes. Based on miRNAs-mRNAs networks, 4 key miRNAs including hsa-miR-182-5p, hsa-miR-96-5p, hsa-miR-335-3p, and hsa-miR-32-5p play a critical role in network regulation.
Conclusion: Our study presents PPI and miRNAs-mRNAs networks for identifying molecular biomarkers in breast cancer. The introduced biomarkers open a new approach to diagnostic and therapeutic indicators for clinical applications.

Highlights

Azizeh Asadzadeh (Google Scholar)

Keywords

Main Subjects

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination, and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.30476/mejc.2024.100604.1994

References
  1. Barzaman K, Karami J, Zarei Z, Hosseinzadeh A, Kazemi MH, Moradi-Kalbolandi S, et al. Breast cancer: Biology, biomarkers, and treatments. Int Immunopharmacol. 2020;84:106535. doi: 10.1016/j.intimp.2020.106535.
  2. Smolarz B, Nowak AZ, Romanowicz H. Breast cancer-epidemiology, classification, pathogenesis and treatment (review of literature). Cancers (Basel). 2022;14(10):2569. doi: 10.3390/cancers14102569.
  3. Sun YS, Zhao Z, Yang ZN, Xu F, Lu HJ, Zhu ZY, et al. Risk factors and preventions of breast cancer. Int J Biol Sci. 2017;13(11):1387-97. doi: 10.7150/ijbs.21635.
  4. Reiner AS, Sisti J, John EM, Lynch CF, Brooks JD, Mellemkjær L, et al. Breast cancer family history and contralateral breast cancer risk in young women: an update from the women's environmental cancer and radiation epidemiology study. J Clin Oncol. 2018;36(15):1513-20. doi: 10.1200/JCO.2017.77.3424.
  5. Asadzadeh A, Ghorbani N, Dastan K. Identification of druggable hub genes and key pathways associated with cervical cancer by protein-protein interaction analysis: An in silico study. Int J Reprod Biomed. 2023;21(10):809-18. doi: 10.18502/ijrm.v21i10.14536.
  6. Gebert LFR, MacRae IJ. Regulation of microRNA function in animals. Nat Rev Mol Cell Biol. 2019;20(1):21-37. doi: 10.1038/s41580-018-0045-7.
  7. Ergin K, Çetinkaya R. Regulation of MicroRNAs. Methods Mol Biol. 2022;2257:1-32. doi: 10.1007/978-1-0716-1170-8_1.
  8. Khan S, Jha A, Panda AC, Dixit A. Cancer-associated circRNA-miRNA-mRNA regulatory networks: A meta-analysis. Front Mol Biosci. 2021;8:671309. doi: 10.3389/fmolb.2021.671309.
  9. Tang N, Dou X, You X, Shi Q, Ke M, Liu G. Pan-cancer analysis of the oncogenic role of discs large homolog associated protein 5 (DLGAP5) in human tumors. Cancer Cell Int. 2021;28;21(1):457. doi: 10.1186/s12935-021-02155-9.
  10. Li L, Xue Q, Zhang M, Yang Z, Wang D, Yan G, et al. Upregulation of the key biomarker kinesin family member 20A (KIF20A) is associated with pulmonary artery hypertension. Genomics. 2023;115(5):110705. doi: 10.1016/j.ygeno.2023.110705.
  11. Xu T, Dong M, Li H, Zhang R, Li X. Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer. Oncol Lett. 2020;19(6):4053-4065. doi: 10.3892/ol.2020.11533.
  12. Wang Y, Kang J, Wang R, Ramezani K, Bonakdar M, Moghimi N, et al. Bisphenol A interacts with DLGAP5 and regulates IL-6/JAK2/STAT3 signaling pathway to promote tumorigenesis and progression of osteosarcoma. Chemosphere. 2023;312(Pt 1):136545. doi: 10.1016/j.
  13. Fu H, Li K, Wang S, Li Y. High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer. Aging (Albany NY). 2022;14(16):6780-95. doi: 10.18632/aging.204253.
  14. Aljohani AI, Toss MS, Green AR, Rakha EA. The clinical significance of cyclin B1 (CCNB1) in invasive breast cancer with emphasis on its contribution to lymphovascular invasion development. Breast Cancer Res Treat. 2023;198(3):423-35. doi: 10.1007/s10549-022-06801-2.
  15. Xu Q, Xu Y, Pan B, Wu L, Ren X, Zhou Y, et al. TTK is a favorable prognostic biomarker for triple-negative breast cancer survival. Oncotarget. 2016;7(49):81815-29. doi: 10.18632/oncotarget.13245.
  16. Shaath H, Vishnubalaji R, Elango R, Velayutham D, Jithesh PV, Alajez NM. Therapeutic targeting of the TPX2/TTK network in colorectal cancer. Cell Commun Signal. 2023;21(1):265. doi: 10.1186/s12964-023-01290-2.
  17. Yan S, Yue S. Identification of early diagnostic biomarkers for breast cancer through bioinformatics analysis. Medicine (Baltimore). 2023;102(37):e35273. doi: 10.1097/MD.0000000000035273.
  18. Qiu J, Xu L, Zeng X, Wu Z, Wang Y, Wang Y, et al. NUSAP1 promotes the metastasis of breast cancer cells via the AMPK/PPARγ signaling pathway. Ann Transl Med. 2021;9(22):1689. doi: 10.21037/atm-21-5517.
  19. Koyuncu D, Sharma U, Goka ET, Lippman ME. Spindle assembly checkpoint gene BUB1B is essential in breast cancer cell survival. Breast Cancer Res Treat. 2021;185(2):331-41. doi: 10.1007/s10549-020-05962-2.
  20. Otálora-Otálora BA, López-Kleine L, Rojas A. Lung cancer gene regulatory network of transcription factors related to the hallmarks of cancer. Curr Issues Mol Biol. 2023;45(1):434-64. doi: 10.3390/cimb45010029.
  21. Alwadi D, Felty Q, Yoo C, Roy D, Deoraj A. Endocrine Disrupting chemicals influence hub genes associated with aggressive prostate cancer. Int J Mol Sci. 2023;24(4):3191. doi: 10.3390/ijms24043191.
  22. Liu M, Yu X, Qu C, Xu S. Predictive value of gene databases in discovering new biomarkers and new therapeutic targets in lung cancer. Medicina (Kaunas). 2023;59(3):547. doi: 10.3390/medicina59030547.
  23. Sun J, Huang J, Lan J, Zhou K, Gao Y, Song Z, et al. Overexpression of CENPF correlates with poor prognosis and tumor bone metastasis in breast cancer. Cancer Cell Int. 2019;19:264. doi: 10.1186/s12935-019-0986-8.
  24. Zou PA, Yang ZX, Wang X, Tao ZW. Upregulation of CENPF is linked to aggressive features of osteosarcoma. Oncol Lett. 2021;22(3):648. doi: 10.3892/ol.2021.12909.
  25. Li DH, Liu XK, Tian XT, Liu F, Yao XJ, Dong JF. PPARG: a promising therapeutic target in breast cancer and regulation by natural drugs. PPAR Res. 2023;2023:4481354. doi: 10.1155/2023/4481354.
  26. Wu M, Zhao H. Analysis of key genes and pathways in breast ductal carcinoma in situ. Oncol Lett. 2020;20(5):217. doi: 10.3892/ol.2020.12080.
  27. Condrat CE, Thompson DC, Barbu MG, Bugnar OL, Boboc A, Cretoiu D, et al. miRNAs as biomarkers in disease: latest findings regarding their role in diagnosis and prognosis. Cells. 23;9(2):276. doi: 10.3390/cells9020276.
  28. Rana S, Valbuena GN, Curry E, Bevan CL, Keun HC. MicroRNAs as biomarkers for prostate cancer prognosis: a systematic review and a systematic reanalysis of public data. Br J Cancer. 2022;126(3):502-13. doi: 10.1038/s41416-021-01677-3.
  29. Krishnan K, Steptoe AL, Martin HC, Wani S, Nones K, Waddell N, et al. MicroRNA-182-5p targets a network of genes involved in DNA repair. RNA. 2013;19(2):230-42. doi: 10.1261/rna.034926.112.
  30. Darbeheshti F, Kadkhoda S, Keshavarz-Fathi M, Razi S, Bahramy A, Mansoori Y, et al. Investigation of BRCAness associated miRNA-gene axes in breast cancer: cell-free miR-182-5p as a potential expression signature of BRCAness. BMC Cancer. 2022;22(1):668. doi: 10.1186/s12885-022-09761-4.
  31. Lu C, Zhao Y, Wang J, Shi W, Dong F, Xin Y, et al. Breast cancer cell-derived extracellular vesicles transfer miR-182-5p and promote breast carcinogenesis via the CMTM7/EGFR/AKT axis. Mol Med. 2021;27(1):78. doi: 10.1186/s10020-021-00338-8.
  32. Liu B, Zhang J, Yang D. miR-96-5p promotes the proliferation and migration of ovarian cancer cells by suppressing Caveolae1. J Ovarian Res. 2019;12(1):57. doi: 10.1186/s13048-019-0533-1.
  33. Qin WY, Feng SC, Sun YQ, Jiang GQ. MiR-96-5p promotes breast cancer migration by activating MEK/ERK signaling. J Gene Med. 2020;22(8):e3188. doi: 10.1002/jgm.3188.
  34. Yin Z, Wang W, Qu G, Wang L, Wang X, Pan Q. MiRNA-96-5p impacts the progression of breast cancer through targeting FOXO3. Thorac Cancer. 2020;11(4):956-63. doi: 10.1111/1759-7714.13348.
  35. Mulrane L, McGee SF, Gallagher WM, O'Connor DP. miRNA dysregulation in breast cancer. Cancer Res. 2013;73(22):6554-62. doi: 10.1158/0008-5472.CAN-13-1841.
  36. Abolghasemi M, Tehrani SS, Yousefi T, Karimian A, Mahmoodpoor A, Ghamari A, et al. MicroRNAs in breast cancer: Roles, functions, and mechanism of actions. J Cell Physiol. 2020;235(6):5008-29. doi: 10.1002/jcp.29396.
  37. Bahmanpour Z, Sheervalilou R, Choupani J, Shekari Khaniani M, Montazeri V, Mansoori Derakhshan S. A new insight on serum microRNA expression as novel biomarkers in breast cancer patients. J Cell Physiol. 2019;234(11):19199-211. doi: 10.1002/jcp.28656.
  38. Zhang J, Xiao C, Feng Z, Gong Y, Sun B, Li Z, et al. SOX4 promotes the growth and metastasis of breast cancer. Cancer Cell Int. 2020;20:468. doi: 10.1186/s12935-020-01568-2.
  39. Liang J, Deng Y, Zhang Y, Wu B, Zhou J. PRLR and CACNA2D1 impact the prognosis of breast cancer by regulating tumor immunity. J Pers Med. 2022;12(12):2086. doi: 10.3390/jpm12122086.
  40. Xie C, Xiong W, Li J, Wang X, Xu C, Yang L. Intersectin 1 (ITSN1) identified by comprehensive bioinformatic analysis and experimental validation as a key candidate biological target in breast cancer. Onco Targets Ther. 2019;12:7079-93. doi: 10.2147/OTT.S216286.
Middle East Journal of Cancer

Articles in Press, Accepted Manuscript
Available Online from 06 May 2024
Files
Share
How to cite
Statistics