Philosophiae Doctor - PhD / Breast cancer is the second most common cancer amongst South African women. Despite
ongoing efforts to combat breast cancer, current prognostic and/or therapeutic monitoring
methods are limited since very little improvement, in the rate of long term recurrence of breast
cancer, has been observed. Considering this, developing novel strategies to detect breast cancer
recurrence – at an early onset – is crucial for monitoring the disease and potentially preventing
disease progression. Methods currently used for the detection of BC are costly and can also be
very uncomfortable for the patient. These methods are also too costly to use as a routine test,
following surgery or treatment to assess disease progression. Thus, developing a cost-effective
detection method appears to be an appealing alternative. Serum/blood-based biomarkers are
ideal targets for the development of low cost detection assays. Two candidate biomarkers,
unique ligand binding protein 2 (ULBP2) and glial cell line-derived neurotrophic factor family
receptor alpha 1 (GFR1) were identified using bioinformatics and proteomics, respectively.
These biomarkers have demonstrated to be useful prognostic biomarkers for breast cancer. The
selection of aptamers against these biomarkers can facilitate the development of cost-effective
detection methods. Aptamers are short DNA or RNA oligonucleotides that have very high
affinity and specificity for its targets and can potentially replace antibodies as tools for
molecular recognition in detection systems, such as the enzyme-linked immunosorbent assay
(ELISA), lateral flow assays and electrochemical biosensors.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uwc/oai:etd.uwc.ac.za:11394/6971 |
Date | January 2019 |
Creators | Swartz, Lauren Taryn |
Contributors | Meyer, Mervin |
Publisher | University of the Western Cape |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Rights | University of the Western Cape |
Page generated in 0.0022 seconds