Detailed Information

Cited 0 time in webofscience Cited 23 time in scopus
Metadata Downloads

Systematic analysis of genotype-specific drug responses in cancer

Authors
Kim, NayoungHe, NingningKim, ChangsikZhang, FanLu, YilingYu, QinghuaStemke-Hale, KatherineGreshock, JoelWooster, RichardYoon, SukjoonMills, Gordon B.
Issue Date
Nov-2012
Publisher
WILEY
Keywords
drug sensitivity and resistance; cancer cell line modeling; cancer genotype; reverse phase protein assay; network analysis
Citation
INTERNATIONAL JOURNAL OF CANCER, v.131, no.10, pp 2456 - 2464
Pages
9
Journal Title
INTERNATIONAL JOURNAL OF CANCER
Volume
131
Number
10
Start Page
2456
End Page
2464
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/11816
DOI
10.1002/ijc.27529
ISSN
0020-7136
1097-0215
Abstract
A systematic understanding of genotype-specific sensitivity or resistance to anticancer agents is required to provide improved patient therapy. The availability of an expansive panel of annotated cancer cell lines enables comparative surveys of associations between genotypes and compounds of various target classes. Thus, one can better predict the optimal treatment for a specific tumor. Here, we present a statistical framework, cell line enrichment analysis (CLEA), to associate the response of anticancer agents with major cancer genotypes. Multilevel omics data, including transcriptome, proteome and phosphatome data, were integrated with drug data based on the genotypic classification of cancer cell lines. The results reproduced known patterns of compound sensitivity associated with particular genotypes. In addition, this approach reveals multiple unexpected associations between compounds and mutational genotypes. The mutational genotypes led to unique protein activation and gene expression signatures, which provided a mechanistic understanding of their functional effects. Furthermore, CLEA maps revealed interconnections between TP53 mutations and other mutations in the context of drug responses. The TP53 mutational status appears to play a dominant role in determining clustering patterns of gene and protein expression profiles for major cancer genotypes. This study provides a framework for the integrative analysis of mutations, drug responses and omics data in cancers.
Files in This Item
There are no files associated with this item.
Appears in
Collections
이과대학 > 생명시스템학부 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Yoon, Suk Joon photo

Yoon, Suk Joon
이과대학 (생명시스템학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE