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A Network-Based Analysis of Hepatoce...

Bhat, Mamatha.

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A Network-Based Analysis of Hepatocellular Carcinoma.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Network-Based Analysis of Hepatocellular Carcinoma./
作者:	Bhat, Mamatha.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	136 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:	Dissertations Abstracts International80-10B.
標題:	Molecular biology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10975500
ISBN:	9781392014936

A Network-Based Analysis of Hepatocellular Carcinoma.
Bhat, Mamatha.

A Network-Based Analysis of Hepatocellular Carcinoma. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 136 p.

Source: Dissertations Abstracts International, Volume: 80-10, Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2019.

This item must not be sold to any third party vendors.

Hepatocellular carcinoma (HCC) is a high-fatality cancer with complex pathogenesis, often arising in the setting of various chronic liver diseases when it is too late to offer any curative therapy. This PhD thesis is divided into two parts, the first of which was completed at McGill University under the supervision of Dr. Nahum Sonenberg, and evaluated inhibition of translation downstream of mTOR. This work was performed in the context of much interest in inhibiting the mTOR pathway in HCC, given its identification as a dominant pathway in this cancer. In the first part of this thesis, I evaluated how metformin inhibits HCC growth, by decreasing translation of anti-apoptotic proteins such as Mcl-1 downstream of mTOR. In the second part of this thesis, I sought to better understand the role of the mTOR pathway in relation to other commonly dysregulated pathways in HCC. All publicly available, high-throughput gene expression data in HCC was curated at http://ophid.utoronto.ca/CDIPLiver. Clinical variables such as etiology of liver disease and liver function parameters, important to understanding clinical relevance of gene expression data, were only available in around 50% of studies. Betweenness centrality calculation was performed on genes differentially expressed between HCC and corresponding background liver tissue, and revealed Estrogen Receptor 1 (ESR1) to be most central to the HCC Protein-Protein Interaction (PPI) network. HCC cells transfected with ESR1 and exposed to estradiol had significantly decreased proliferation and viability. Gene expression revealed that ESR1 upregulation significantly affected cellular processes such as histone methylation, transcription, and cell cycle. High expression of ESR1 in HCC tumors was found to be protective. Finally, we curated all publicly available whole exome sequencing, DNA methylation, microRNA, and proteomics data in HCC. Pathway analysis was performed on significantly dysregulated genes, and overlapping pathways identified. The following pathways overlapped among the 5 different datasets: Epidermal Growth Factor (EGFR), B1-integrin and axon guidance proteins, suggesting pathway dependencies in HCC. A systems biology approach to HCC allowed us to elucidate the role of sex-specific differences and importance of specific pathways in HCC biology, providing biological rationale for a more targeted therapeutic approach to HCC.

ISBN: 9781392014936Subjects--Topical Terms:

517296
Molecular biology.

A Network-Based Analysis of Hepatocellular Carcinoma.
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