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A Connectivity Mapping Approach to Identifying Senolytic Compounds.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Connectivity Mapping Approach to Identifying Senolytic Compounds./
Author:	White, Jessica B.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	62 p.
Notes:	Source: Masters Abstracts International, Volume: 83-03.
Contained By:	Masters Abstracts International83-03.
Subject:	Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28548918
ISBN:	9798538108084

A Connectivity Mapping Approach to Identifying Senolytic Compounds.
White, Jessica B.

A Connectivity Mapping Approach to Identifying Senolytic Compounds. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 62 p.

Source: Masters Abstracts International, Volume: 83-03.

Thesis (M.S.)--Weill Medical College of Cornell University, 2021.

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

Drug repurposing and in silico identification of promising compounds and mechanisms are two promising methods for reducing the cost and time associated with drug development. Utilizing a robust, open-source database of drug intervention transcriptional profiles, we have developed a workflow to identify compounds potentially capable of reversing the expression signatures of disease and biological states of interest. By modifying an existing protocol, this workflow improves the speed, statistical power, and memory requirements of the standard algorithm associated with this database. We initially validated the revised algorithm using transcriptional profiles of constructs where genes of druggable targets were overexpressed. Having confirmed that the relevant drugs and mechanisms were recovered, we further applied the tool to identify chemical compounds capable of reversing cellular senescence. First, we utilized cell line specific profiles where senescence was induced with various methods. This led us to identify disparate compounds in different cell lines, specifically GSK3i CHIR-99021 and PLKi BI-2536 in endothelial cells and Bcr-Abl/Src inhibitor dasatinib in fibroblast cells. One drug, RAFi SB590885, emerged as a top hit across cell types. We then applied the workflow in more heterogeneous tumor samples exhibiting transcriptional markers of senescence. We found similar compounds were able to reverse these signatures as in the senescent cell line profiles. Dasatinib, in particular, emerged as a top hit both based on the frequency of its occurrence and the strength of its ability to reverse the transcriptional signature.

ISBN: 9798538108084Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Connectivity mapping

A Connectivity Mapping Approach to Identifying Senolytic Compounds.
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300 $a 62 p.
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500 $a Advisor: Elemento, Olivier.
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506 $a This item must not be sold to any third party vendors.
520 $a Drug repurposing and in silico identification of promising compounds and mechanisms are two promising methods for reducing the cost and time associated with drug development. Utilizing a robust, open-source database of drug intervention transcriptional profiles, we have developed a workflow to identify compounds potentially capable of reversing the expression signatures of disease and biological states of interest. By modifying an existing protocol, this workflow improves the speed, statistical power, and memory requirements of the standard algorithm associated with this database. We initially validated the revised algorithm using transcriptional profiles of constructs where genes of druggable targets were overexpressed. Having confirmed that the relevant drugs and mechanisms were recovered, we further applied the tool to identify chemical compounds capable of reversing cellular senescence. First, we utilized cell line specific profiles where senescence was induced with various methods. This led us to identify disparate compounds in different cell lines, specifically GSK3i CHIR-99021 and PLKi BI-2536 in endothelial cells and Bcr-Abl/Src inhibitor dasatinib in fibroblast cells. One drug, RAFi SB590885, emerged as a top hit across cell types. We then applied the workflow in more heterogeneous tumor samples exhibiting transcriptional markers of senescence. We found similar compounds were able to reverse these signatures as in the senescent cell line profiles. Dasatinib, in particular, emerged as a top hit both based on the frequency of its occurrence and the strength of its ability to reverse the transcriptional signature.
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