2026-09-23T23:38:26Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/104825 2023-07-11 col_2142_5131 col_2142_8951 com_2142_5130 com_2142_8950 com_2142_150

Made available in DSpace on 2019-08-23T19:51:52Z (GMT). No. of bitstreams: 2 WANG-THESIS-2019.pdf: 5412791 bytes, checksum: 03dc1b07be536fed2bb50fd688310fa8 (MD5) LICENSE.txt: 4207 bytes, checksum: 7471f5efdab5eba639655da64b717063 (MD5) Previous issue date: 2019-04-17 application/pdf http://hdl.handle.net/2142/104825 en Copyright 2019 Yu Wang Literature-based discovery literature review breast cancer cholesterol mechanisms Literature-based discovery of known and potential new mechanisms for relating the status of cholesterol to the progression of breast cancer Torvik, Vetle I. Nelson, Erik Russell Wang, Yu 2019-08-23T19:51:52Z 2019-08-23T19:51:52Z 2019-04-17 2019-05 Breast cancer has been studied for a long period of time and from a variety of perspectives in order to understand its pathogeny. The pathogeny of breast cancer can be classified into two groups: hereditary and spontaneous. Although cancer in general is considered a genetic disease, spontaneous factors are responsible for most of the pathogeny of breast cancer. In other words, breast cancer is more likely to be caused and deteriorated by the dysfunction of a physical molecule than be caused by germline mutation directly. Interestingly, cholesterol, as one of those molecules, has been discovered to correlate with breast cancer risk. However, the mechanisms of how cholesterol helps breast cancer progression are not thoroughly understood. As a result, this study aims to study known and discover potential new mechanisms regarding to the correlation of cholesterol and breast cancer progression using literature review and literature-based discovery. The known mechanisms are further classified into four groups: cholesterol membrane content, transport of cholesterol, cholesterol metabolites, and other. The potential mechanisms, which are intended to provide potential new treatments, have been identified and checked for feasibility by an expert. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2019-08-22 without embargo terms The student, Yu Wang, accepted the attached license on 2019-04-14 at 23:20. The student, Yu Wang, submitted this Thesis for approval on 2019-04-14 at 23:30. This Thesis was approved for publication on 2019-04-17 at 10:01. DSpace SAF Submission Ingestion Package generated from Vireo submission #13618 on 2019-08-22 at 14:43:26 text text Information Sciences Bioinformatics University of Illinois at Urbana-Champaign Thesis M.S.