Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer
Background: Colorectal cancer is a significant medical burden worldwide and in Newfoundland and Labrador. Examining the relationships of SNP interactions with survival outcomes can help identify new prognostic markers for this disease. Objectives: To examine associations between colorectal cancer su...
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Memorial University of Newfoundland
2023
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ftmemorialuniv:oai:research.library.mun.ca:15965 2023-10-01T03:57:34+02:00 Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer Curtis, Aaron Albert 2023-06 application/pdf https://research.library.mun.ca/15965/ https://research.library.mun.ca/15965/1/converted.pdf en eng Memorial University of Newfoundland https://research.library.mun.ca/15965/1/converted.pdf Curtis, Aaron Albert <https://research.library.mun.ca/view/creator_az/Curtis=3AAaron_Albert=3A=3A.html> (2023) Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer. Masters thesis, Memorial University of Newfoundland. thesis_license Thesis NonPeerReviewed 2023 ftmemorialuniv 2023-09-03T06:50:30Z Background: Colorectal cancer is a significant medical burden worldwide and in Newfoundland and Labrador. Examining the relationships of SNP interactions with survival outcomes can help identify new prognostic markers for this disease. Objectives: To examine associations between colorectal cancer survival outcomes and interactions of SNPs from MMP family and VEGF interactome genes using data-reduction methods. Methods: Two data-reduction software programs, Cox-MDR and GMDR 0.9, were applied to the data of patients from the Newfoundland Familial Colorectal Cancer Registry. Eight datasets were investigated: one for the MMP gene SNPs (201 SNPs), and seven for the VEGF interaction networks (total 1,517 SNPs). Significance of interaction models was assessed using permutation testing. Associations between significant interaction models and clinical outcomes were confirmed using multivariable regression methods. Results: For the MMP dataset two multi-SNP models and one single-SNP model were identified, while fifteen novel multi-SNP models and thirteen single-SNP models were identified for the VEGF interaction network datasets. All but one of these models were able to distinguish patients based on their outcome risk in multivariable regression models (p-value range: 0.03 – 2.2E-9). Conclusion: This research demonstrated that novel genetic interactions associated with outcome risk in colorectal cancer can be found using data-reduction methods. This proves the utility of these methods in prognostic research. Thesis Newfoundland Memorial University of Newfoundland: Research Repository Newfoundland |
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Background: Colorectal cancer is a significant medical burden worldwide and in Newfoundland and Labrador. Examining the relationships of SNP interactions with survival outcomes can help identify new prognostic markers for this disease. Objectives: To examine associations between colorectal cancer survival outcomes and interactions of SNPs from MMP family and VEGF interactome genes using data-reduction methods. Methods: Two data-reduction software programs, Cox-MDR and GMDR 0.9, were applied to the data of patients from the Newfoundland Familial Colorectal Cancer Registry. Eight datasets were investigated: one for the MMP gene SNPs (201 SNPs), and seven for the VEGF interaction networks (total 1,517 SNPs). Significance of interaction models was assessed using permutation testing. Associations between significant interaction models and clinical outcomes were confirmed using multivariable regression methods. Results: For the MMP dataset two multi-SNP models and one single-SNP model were identified, while fifteen novel multi-SNP models and thirteen single-SNP models were identified for the VEGF interaction network datasets. All but one of these models were able to distinguish patients based on their outcome risk in multivariable regression models (p-value range: 0.03 – 2.2E-9). Conclusion: This research demonstrated that novel genetic interactions associated with outcome risk in colorectal cancer can be found using data-reduction methods. This proves the utility of these methods in prognostic research. |
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Thesis |
author |
Curtis, Aaron Albert |
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Curtis, Aaron Albert Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer |
author_facet |
Curtis, Aaron Albert |
author_sort |
Curtis, Aaron Albert |
title |
Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer |
title_short |
Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer |
title_full |
Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer |
title_fullStr |
Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer |
title_full_unstemmed |
Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer |
title_sort |
examining interactions among snps that can explain the prognostic variability in colorectal cancer |
publisher |
Memorial University of Newfoundland |
publishDate |
2023 |
url |
https://research.library.mun.ca/15965/ https://research.library.mun.ca/15965/1/converted.pdf |
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Newfoundland |
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Newfoundland |
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Newfoundland |
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Newfoundland |
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https://research.library.mun.ca/15965/1/converted.pdf Curtis, Aaron Albert <https://research.library.mun.ca/view/creator_az/Curtis=3AAaron_Albert=3A=3A.html> (2023) Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer. Masters thesis, Memorial University of Newfoundland. |
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