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    Characterization of transcriptome diversity of invasive ductal carcinoma tissue from individuals of different ethnicities and ages

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    Master's Dissertation (1.727Mb)
    Manuscript (1.810Mb)
    Date
    2023
    Author
    Ssegawa, Abdulkarim
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    Abstract
    Breast cancer is a heterogeneous disease, and its incidence and prognosis are influenced by various factors including age and ethnicity. Consequently, tumors from individuals of different age groups and ethnicities may exhibit unique molecular fingerprints including transcriptomic profiles. However, while much work has been done to characterize tumors and describe their heterogeneity across epidemiological states, our understanding of their molecular features remains limited. This knowledge is critical and a prerequisite in the quest to fully understand the etiology of the disease and biology of tumors for the prevention, early diagnosis, and improved treatment of cancer. RNA sequencing (RNA-Seq) has emerged as a powerful tool for transcriptome analysis, providing a comprehensive view of gene expression and regulation. Therefore, in this study, we aimed to use RNA-Seq to investigate transcriptome diversity in breast cancer tissue from individuals of different ethnicities and ages. This study aimed to obtain RNA-Sequence sample data of breast cancer tissue from various ethnicities and age groups and perform RNA-Seq to analyze the gene expression profiles. The objectives of this study are to identify differentially expressed genes and pathways associated with breast cancer progression and prognosis and to characterize the transcriptome diversity between breast cancer tissues from individuals of different ethnicities and ages. Additionally, we will explore the potential clinical implications of our findings by investigating the relationship between transcriptome diversity, treatment responses, and survival outcomes. Ultimately, our study aims to provide important insights into the molecular basis of ethnic and age-related differences in breast cancer biology and to identify potential targets for personalized breast cancer management.
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    http://hdl.handle.net/10570/14658
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