Generic placeholder image

Anti-Cancer Agents in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1871-5206
ISSN (Online): 1875-5992

Review Article

Guide for Selection of Relevant Cell Lines During the Evaluation of new Anti-Cancer Compounds

Author(s): Angel J. Ruiz-Moreno, Patricia Torres-Barrera, Mireya Velázquez-Paniagua, Alexander Dömling and Marco A. Velasco-Velázquez*

Volume 18, Issue 8, 2018

Page: [1072 - 1081] Pages: 10

DOI: 10.2174/1871520618666180220120544

Price: $65

Abstract

Background: Human cancer cell lines are valuable models for anti-cancer drug development. Although all cancer cells share common biological features, each cancer cell line has unique genotypic/ phenotypic characteristics that affect drug response. Thus, the information obtained with a specific cancer cell line cannot be easily extrapolated to other cancer cells. Consequently, cell line selection during experimental design is critical for providing proper and clinically relevant structure-activity analysis.

Methods: Herein, we critically review the use of cancer cell lines as tools for activity analysis by comparing two different scenarios: i) the use of multiple cancer cell lines, with the NCI-60 Program as the most representative example; and, ii) the selection of a single cell line with specific biological characteristics that match the rationale of compound design.

Results: Considering that most laboratories evaluate the activity of new compounds using few cell lines, we provide a systematic strategy for selection based on the expression levels and genetic status of the target and the effectiveness of target inhibition or silencing. We exemplify the use of public databases for data retrieval and analysis as well as the critical comparison of such information with published results.

Conclusion: This approach refines cell line selection, avoiding the perpetuation of published poor selection and enhancing the relevance of the results.

Keywords: Anti-cancer drugs, preclinical screening, cancer cell line, NCI-60, EGFR, CD44, cancer genomics.

Graphical Abstract

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy