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Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Published on: February 21, 2014
Circulating ESR1, long non-coding RNA HOTAIR and microRNA-130a gene expression as biomarkers for breast cancer stage
Noura R Abdel-Hamid1, Eman A Mohammed1, Eman A Toraih1,2
1Genetics Unit, Department of Histology and Cell Biology, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.
Abstract:
Breast cancer, the most prevalent cancer among women, has posed a significant challenge in identifying biomarkers for early diagnosis and prognosis. This study aimed to elucidate the gene expression profile of Estrogen Receptor-1 (ESR-1), long non-coding RNA HOTAIR, and microRNA-130a in the serum of Egyptian breast cancer patients, evaluating the potential of HOTAIR and miR-130a as biomarkers for predicting pathological parameters in BC. The study involved 45 patients with primary BC, with serum samples collected preoperatively and postoperatively twice. The expression levels of ESR-1, HOTAIR, and miR-130a were quantified using real-time PCR and analyzed for correlations with each other and with the clinical and pathological parameters of the patients. Serum HOTAIR levels exhibited a strong positive association with metastasis and demonstrated a significant increase after 6 months in all patients with locally advanced and stage IV BC. Conversely, tumors with advanced stages and metastatic lesions showed significantly lower expression levels of miR-130a. Notably, a significant positive correlation was observed between preoperative ESR-1 expression and both HOTAIR and miR-130a levels. Serum HOTAIR and miR-130a levels have emerged as promising non-invasive biomarkers with the potential to predict the pathological features of BC patients. HOTAIR, an oncogenic long non-coding RNA (lncRNA), and miR-130a, a tumor suppressor miRNA, play crucial roles in tumor progression. Further investigations are warranted to elucidate the intricate interplay between HOTAIR and miR-130a and to fully comprehend the contribution of HOTAIR to BC recurrence and its potential utility in early relapse prediction.
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