Study of some circulating microRNAs as potential biomarkers of breast cancer / Maha Rafik Ragheb Gabra Elmasry ; Supervised Tarek Mohamed Kamal Motawi , Nermin Abdelhamid Sadik , Olfat Gamil Shaker
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- دراسة بعض انواع الميكرو آر ان ايه كمؤشرات محتملة فى سرطان الثدى [Added title page title]
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.08.01.M.Sc.2019.Ma.S (Browse shelf(Opens below)) | Not for loan | 01010110079735000 | ||
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.08.01.M.Sc.2019.Ma.S (Browse shelf(Opens below)) | 79735.CD | Not for loan | 01020110079735000 |
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Thesis (M.Sc.) - Cairo University - Faculty of Pharmacy - Department of Biochemistry
MicroRNAs (miRNAs) play an important role in cancer prognosis. They are small molecules, approximately 17-25 nucleotides in length, and their high stability in human serum supports their use as novel diagnostic biomarkers of cancer and other pathological conditions. In this study, we analyzed the expression patterns of miR-21 and miR-221 in the serum from a total of 100 Egyptian female subjects with breast cancer, fibroadenoma, and healthy control subjects. Using microarray-based expression profiling followed by real-time polymerase chain reaction validation, we compared the levels of the two circulating miRNAs in the serum of patients with breast cancer (n=50), fibroadenoma (n=25), and healthy controls (n=25). The miRNA SNORD68 was chosen as the housekeeping endogenous control. We found that the serum levels of miR-21 and miR-221 were significantly overexpressed in breast cancer patients compared to normal controls and fibroadenoma patients. Receiver operating characteristic (ROC) curve analysis revealed that miR-21 has greater potential in discriminating between breast cancer patients and the control group, while miR-221 has greater potential in discriminating between breast cancer and fibroadenoma patients. Classification models using k-Nearest Neighbor (kNN), Naïve Bayes (NB), and Random Forests (RF) were developed using expression levels of both miR-21 and miR-221. Best classification performance was achieved by NB Classification models, reaching 91% of correct classification. Furthermore, relative miR-221 expression was associated with histological tumor grades. Therefore, it may be concluded that both miR-21 and miR-221 can be used to differentiate between breast cancer patients and healthy controls, but that the diagnostic accuracy of serum miR-21 is superior to miR-221 for breast cancer prediction. miR-221 has more diagnostic power in discriminating between breast cancer and fibroadenoma patients
Issued also as CD
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