Identification of membrane biomakers for colorectal cancer using an in-solico and molecular approach
- Authors: Van Vuuren, Larry Peter
- Date: 2014
- Subjects: Cancer -- Research , Colon (Anatomy) -- Cancer , Rectum -- Cancer
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/47970 , vital:40457
- Description: The aim of this study was to identify membrane biomarkers for colorectal cancer using an insilico and molecular approach. Colorectal cancer (CRC) globally accounts for more than half a million deaths. In South Africa alone, approximately one in 97 men is at risk of getting CRC; and for women, it is one in 162. Novel and non-invasive diagnostic tools, such as biomarkers, are needed for early CRC detection. In order to reduce the fatality rate in this disease, Biomarkers are used as indicators of a biological state; and they are measurable in biological media. They can be used to distinguish between a diseased state and a normal state, thus aiding diagnostics, response to specific therapies, and screening for an early diagnosis. A gene list of potential CRC biomarkers was generated by mining two gene databases, namely: Oncomine and Gene Expression Atlas. A total of 44 candidate genes were identified, based on their location on the cell surface, using the Database for Annotation, Visualisation and Integrated Discovery. These 44 genes were then subjected to an in-depth literature mining. The literature search parameters in PubMed, PubMed Central, Google Scholar and Science direct revealed publications showing that 23 genes were validated, while 21 genes were not validated. Nineteen genes were selected for gene validation in human colorectal cancer and healthy tissue of twelve patients. Total RNA was extracted from 12 colorectal cancer and 12 healthy tissue samples. The RNA was then quantified and reverse-transcribed into cDNA for gene expression analysis. The qPCR running conditions were optimized, by running a melting curve, in order to determine the optimum annealing temperatures. Primarily melt curves were run for nineteen of these twenty-one genes. Melt-curve analysis showed that nine genes were poor candidates for further validation studies; and therefore, only ten genes, namely: AGTRAP, ANKRD46, BACE2, CFB, CIAO1, NOMO3, PTDSS1, SLC5A6, TNFRSF12A and ZDHHC9 were validated by qPCR in human resected colorectal carcinoma and the normal tissues of twelve patients. The qPCR results showed that ZDHHC9 and the SLC5A6 genes were the only two statistically significant ones; and they were found to be down-regulated in human colorectal cancer vs healthy tissue samples.
- Full Text:
- Date Issued: 2014
Identification of membrane biomakers for colorectal cancer using an in-solico and molecular approach
- Authors: Van Vuuren, Larry Peter
- Date: 2014
- Subjects: Cancer -- Research , Colon (Anatomy) -- Cancer , Rectum -- Cancer
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/47970 , vital:40457
- Description: The aim of this study was to identify membrane biomarkers for colorectal cancer using an insilico and molecular approach. Colorectal cancer (CRC) globally accounts for more than half a million deaths. In South Africa alone, approximately one in 97 men is at risk of getting CRC; and for women, it is one in 162. Novel and non-invasive diagnostic tools, such as biomarkers, are needed for early CRC detection. In order to reduce the fatality rate in this disease, Biomarkers are used as indicators of a biological state; and they are measurable in biological media. They can be used to distinguish between a diseased state and a normal state, thus aiding diagnostics, response to specific therapies, and screening for an early diagnosis. A gene list of potential CRC biomarkers was generated by mining two gene databases, namely: Oncomine and Gene Expression Atlas. A total of 44 candidate genes were identified, based on their location on the cell surface, using the Database for Annotation, Visualisation and Integrated Discovery. These 44 genes were then subjected to an in-depth literature mining. The literature search parameters in PubMed, PubMed Central, Google Scholar and Science direct revealed publications showing that 23 genes were validated, while 21 genes were not validated. Nineteen genes were selected for gene validation in human colorectal cancer and healthy tissue of twelve patients. Total RNA was extracted from 12 colorectal cancer and 12 healthy tissue samples. The RNA was then quantified and reverse-transcribed into cDNA for gene expression analysis. The qPCR running conditions were optimized, by running a melting curve, in order to determine the optimum annealing temperatures. Primarily melt curves were run for nineteen of these twenty-one genes. Melt-curve analysis showed that nine genes were poor candidates for further validation studies; and therefore, only ten genes, namely: AGTRAP, ANKRD46, BACE2, CFB, CIAO1, NOMO3, PTDSS1, SLC5A6, TNFRSF12A and ZDHHC9 were validated by qPCR in human resected colorectal carcinoma and the normal tissues of twelve patients. The qPCR results showed that ZDHHC9 and the SLC5A6 genes were the only two statistically significant ones; and they were found to be down-regulated in human colorectal cancer vs healthy tissue samples.
- Full Text:
- Date Issued: 2014
The impact of budget deficits on economic growth in South Africa
- Authors: Mrwebo, Luzuko T
- Date: 2013
- Language: English
- Type: Thesis , Masters , M Com
- Identifier: vital:11481 , http://hdl.handle.net/10353/d1015284
- Description: The study examines the impact of budget deficits on economic growth in South Africa. The review of the results from theoretical and empirical studies has shown that budget deficits in the most have a negative impact on GDP growth. The Johansen cointegration test has shown evidence that there is cointegration between the GDP growth and its determinants. The tests indicated the presence of cointegration which led to the estimation of VECM. The measure for the long run relationship was between GDP growth and its determinants such as, budget deficits, domestic activities, government debt, and trade openness. The co-integration and vector error correction modelling techniques were applied to South African data between 1990 to 2012 period. This study at hand indicated that government budget deficits have a long run negative effect on economic growth, but the impact shown from the results of this study is very low.
- Full Text:
- Date Issued: 2013
- Authors: Mrwebo, Luzuko T
- Date: 2013
- Language: English
- Type: Thesis , Masters , M Com
- Identifier: vital:11481 , http://hdl.handle.net/10353/d1015284
- Description: The study examines the impact of budget deficits on economic growth in South Africa. The review of the results from theoretical and empirical studies has shown that budget deficits in the most have a negative impact on GDP growth. The Johansen cointegration test has shown evidence that there is cointegration between the GDP growth and its determinants. The tests indicated the presence of cointegration which led to the estimation of VECM. The measure for the long run relationship was between GDP growth and its determinants such as, budget deficits, domestic activities, government debt, and trade openness. The co-integration and vector error correction modelling techniques were applied to South African data between 1990 to 2012 period. This study at hand indicated that government budget deficits have a long run negative effect on economic growth, but the impact shown from the results of this study is very low.
- Full Text:
- Date Issued: 2013
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