Predicting chemotherapy sensitivity profiles for breast cancer cell lines with and without stem cell-like features

Date
2013
Authors
Isbilen, M.
Senses, K. M.
Gure, A. O.
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Current Signal Transduction Therapy
Print ISSN
1574-3624
Electronic ISSN
Publisher
Bentham Science Publishers B.V.
Volume
8
Issue
3
Pages
268 - 273
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Series
Abstract

Our current understanding of cancer-stem cells (CSCs) is that they are slow growing, generally mesenchymallike cells capable of generating tumors. Convincing evidence for the existence of such cells comes from recent lineage tracing experiments. CSCs have been reported as being resistant to conventional drug treatment and have been considered as being responsible for failure of chemotherapy. Recently, several databases aiming the genetic characterization of a large number of cancer cell lines have been made publicly available. In addition to gene expression data, these databases contain cytotoxicity information for all cell lines for a number of drugs as well. It is possible to classify known cell lines derived from a given tumor, based on how similar they are to CSCs, or in other words, to define their stem-ness, using gene-lists that define such cells. Using two such, independently generated, gene lists we found that breast cancer cell lines could be categorized into two distinct groups which we designate CSC-like and non-CSC-like. We then identified drugs to which the two groups were most sensitive to. We also generated sensitivity profiles for all drugs, within one such database, to identify chemotherapeutics with preferential action on breast cancer. We believe this is a straight-forward approach for swiftly identifying drugs that would selectively target a subpopulation of cells for any given tumor type. © 2013 Bentham Science Publishers.

Course
Other identifiers
Book Title
Keywords
Cancer, Cancer stem cells, Chemotherapy, Cytotoxicity, Database mining, Lapatinib, LBW242, TKI258
Citation
Published Version (Please cite this version)