Date of Award

2015

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Biology

First Advisor

Dr. Checo Rorie

Abstract

Purpose: The Triple-Negative Breast Cancer (TNBC) subtype accounts for 15 percent of all breast cancers. It is characterized by cancer cells that lack estrogen, progesterone, and HER2/Neu receptors. TNBC is highly aggressive and deadly, and primarily affects younger African-American women. Identification of microRNAs that can be used as biomarkers for diagnosis, prognosis, and provide drug-able targets is the long-term goal of this study. The objective of this study is to compare and contrast microRNA expression level profiles from microarray (Partek Genomic Suite) and qPCR analysis performed on triple-negative breast cancer versus normal breast tissue cell line in order to find potential biomarkers that could be used for diagnosis, prognosis, and treatment of TNBC. Experimental Design: MicroRNA was extracted from African-American derived normal (AG11132) and TNBC (HCC1806, HCC70, and MB157) cell lines and subjected to microarray analysis using Partek Genomic Suite. MicroRNAs 21, 34a, 103, 141, and let-7a were shown to be differentially expressed; up or downregulated in TNBC cells vs. the normal breast tissue cell lines and were chosen for further analysis. Prior to validation using qPCR, using pelleted cells from each cell line, microRNA was extracted, converted to cDNA, and ran on the NanoDrop to determine purity and concentration levels of the samples. Results: Partek Genomic Suite analysis revealed that microRNAs 21, 34a, 103, 141, and let-7a were differentially expressed in the TNBC cells when compared to the "normal" breast cell line AG11132. Literature was consulted to choose microRNAs that have been reported as playing a role in TNBC for further analysis using qPCR which validated the microarray data. Conclusion: We show that TNBC cells have a differential microRNA expression profile when compared to normal cells. Microarray analysis revealed that microRNA expression profiles cluster the TNBC cells separately from the normal cells. We were also able to validate the findings of five microRNAs that were revealed in the microarray analysis to be up or downregulated in the TNBC cells. The findings suggest that microRNAs could be used as potential biomarkers to diagnose TNBC and could potentially be used as drug-targeted therapies in the future.

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