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  • Gene Expression Analysis in Human Breast Cancer

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    Gabrovska_2012_01Abstract.pdf (134.6Kb)
    Gabrovska_2012_02Thesis.pdf (2.803Mb)
    Author(s)
    Gabrovska, Pam
    Primary Supervisor
    Griffiths, Lyn
    Other Supervisors
    Smith, Robert
    Year published
    2012
    Metadata
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    Abstract
    Breast Cancer is the most commonly diagnosed cancer in women, with more than 1.2 million women diagnosed annually worldwide. It is also a frequently fatal disease and remains difficult to treat, despite advances in all facets of cancer management. While a number of genetic mutations have been identified in human breast cancers, he specific combinations of the mutations required in concert for formation of a breast carcinoma remains unknown, making precise detection or prognostic predictions impossible. Although estrogen receptor (ER) status is predictive of response to hormonal treatments, there are currently no clinically ...
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    Breast Cancer is the most commonly diagnosed cancer in women, with more than 1.2 million women diagnosed annually worldwide. It is also a frequently fatal disease and remains difficult to treat, despite advances in all facets of cancer management. While a number of genetic mutations have been identified in human breast cancers, he specific combinations of the mutations required in concert for formation of a breast carcinoma remains unknown, making precise detection or prognostic predictions impossible. Although estrogen receptor (ER) status is predictive of response to hormonal treatments, there are currently no clinically useful predictive markers of a patient’s response to chemotherapy. This results in all patients who are eligible for chemotherapy receiving the same treatment even though de novo drug resistance will result in the treatment failing in about 80% of cases. Developing improved diagnostic tools to cluster different breast cancers into groups based on genetic parameters has the potential to revolutionise individualised treatment options and subsequent efficacy. This in turn will improve quality of life for patients undergoing therapy who will no longer suffer the consequences of unnecessary treatments and more importantly, a subsequent improved survival rate.
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    Thesis Type
    Thesis (PhD Doctorate)
    Degree Program
    Doctor of Philosophy (PhD)
    School
    School of Medical Science
    DOI
    https://doi.org/10.25904/1912/3437
    Copyright Statement
    The author owns the copyright in this thesis, unless stated otherwise.
    Item Access Status
    Public
    Subject
    Breast cancer
    Gene expression
    Estrogen receptor (ER) status
    Chemotherapy
    Publication URI
    http://hdl.handle.net/10072/367577
    Collection
    • Theses - Higher Degree by Research

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