Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


osu1211958921.pdf (2.04 MB)

ETD Abstract Container

Abstract Header

Comparative Gene Expression Analysis To Identify Common Factors In Multiple Cancers

Rybaczyk, Leszek A.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1211958921

Abstract Details

2008, Doctor of Philosophy, Ohio State University, Integrated Biomedical Sciences.
Most current cancer research is focused on tissue-specific genetic mutations. Familial inheritance (e.g., APC in colon cancer), genetic mutation (e.g., p53), and overexpression of growth receptors (e.g., Her2-neu in breast cancer) can potentially lead to aberrant replication of a cell. Studies of these changes provide tremendous information about tissue-specific effects but are less informative about common changes that occur in multiple tissues. The similarity in the behavior of cancers from different organ systems and species suggests that a pervasive mechanism drives carcinogenesis, regardless of the specific tissue or species. In order to detect this mechanism, I applied three tiers of analysis at different levels: hypothesis testing on individual pathways to identify significant expression changes within each dataset, intersection of results between different datasets to find common themes across experiments, and Pearson correlations between individual genes to identify correlated genes within each dataset. By comparing a variety of cancers from different tissues and species, I was able to separate tissue and species specific effects from cancer specific effects. I found that downregulation of Monoamine Oxidase A is an indicator of this pervasive mechanism and can potentially be used to detect pathways and functions related to the initiation, promotion, and progression of cancer.
Kun Huang, PhD (Advisor)
Jeffery Kuret, PhD (Committee Member)
Daniel Janies, PhD (Committee Member)
Randy Nelson, PhD (Other)
160 p.
Biochemistry; Bioinformatics; Biology; Biomedical Research; Biostatistics; Cellular Biology; Epidemiology; Gender; Genetics; Gerontology; Gynecology; Health; Immunology; Mathematics; Molecular Biology; Oncology; Pharmaceuticals; Pharmacology; Scientific Imaging; Statistics
Monoamine; cancer; indicator of cancer; multiple cancers; microarray; multiple datasets; cross platform; biomarker

Recommended Citations

Citations

  • Rybaczyk, L. A. (2008). Comparative Gene Expression Analysis To Identify Common Factors In Multiple Cancers [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1211958921

    APA Style (7th edition)

  • Rybaczyk, Leszek. Comparative Gene Expression Analysis To Identify Common Factors In Multiple Cancers. 2008. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1211958921.

    MLA Style (8th edition)

  • Rybaczyk, Leszek. "Comparative Gene Expression Analysis To Identify Common Factors In Multiple Cancers." Doctoral dissertation, Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1211958921

    Chicago Manual of Style (17th edition)

osu1211958921
1,583
© 2008, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.