1. Identifying miRNA signature for predicting and treatment of breast cancer using the transcriptomic data of 7,000 breast tumors
- Author
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Omran Davarinejad, Payam Mohammadi, Davood Ghavi, Farzaneh Golmohammadi, Zahra Foruzandeh, MohammadReza Alivand, and Yazdan Rahmati
- Abstract
The high mortality rate in Breast Cancer (BC) is largely due to the difficulty of early detection and inadequate accuracy of the current diagnostic approaches. In this study, we investigated serum and tumor miRNA profiles of 1800 breast cancer miRNA expression profiles of GEO (Gene Expression Omnibus) and also more than 2500 patients in TCGA (The Cancer Genome Atlas) database. After data analysis by some packages like Limma, and WGCNA, we selected 6 hub miRNAs. Then by collecting serum samples of 100 breast cancer patients, real-time PCR was performed and the diagnosis performance of hub miRNAs was evaluated by ROC curve. Due to more validation, Kaplan-Meier Plot of hub miRNAs was evaluated by 1262 BC samples using METABRIC database. The target genes of 6 hub miRNAs were investigated using Mirbase, Mirtarbase, Targetscan, and TransmiR and after the identification of target genes, their expression was evaluated in 1600 BC samples using GEO database. Finally, six miRNAs including Hsa-miR-151a-5p, Hsa-miR-34a-5p, Hsa-miR-1307-3p, Hsa-miR-450b-5p, Hsa-miR-501-3p, and Hsa-miR-532-5p were introduced as effective biomarkers of BC.
- Published
- 2022
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