BMC Genomics Research article Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways Mark W Carlson1,2, Vishwanath R Iyer2 and Edward M Marcotte*2 BioMed Central Open Access Address: 1Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA and 2Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas 78712, USA Email: Mark W Carlson - mark.carlson@tufts.edu; Vishwanath R Iyer - vishy@icmb.utexas.edu; Edward M Marcotte* - marcotte@intron.icmb.utexas.edu * Corresponding author Published: 10 May 2007 BMC Genomics 2007, 8:117 doi:10.1186/1471-2164-8-117 This article is available from: http://www.biomedcentral.com/1471-2164/8/117 Received: 6 November 2006 Accepted: 10 May 2007 © 2007 Carlson et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Cell lines have been used to study cancer for decades, but truly quantitative assessment of their performance as models is often lacking. We used gene expression profiling to quantitatively assess the gene expression of nine cell line models of cervical cancer. Results: We find a wide variation in the extent to which different cell culture models mimic late- stage invasive cervical cancer biopsies. The lowest agreement was from monolayer HeLa cells, a common cervical cancer model; the highest agreement was from primary epithelial cells, C4-I, and C4-II cell lines. In addition, HeLa and SiHa cell lines cultured in an organotypic environment increased their correlation to cervical cancer significantly. We also find wide variation in agreement when we considered how well individual biological pathways model cervical cancer. Cell lines with an anti-correlation to cervical cancer were also identified and should be avoided. Conclusion: Using gene expression profiling and quantitative analysis, we have characterized nine cell lines with respect to how well they serve as models of cervical cancer. Applying this method to individual pathways, we identified the appropriateness of particular cell lines for studying specific pathways in cervical cancer. This study will allow researchers to choose a cell line with the highest correlation to cervical cancer at a pathway level. This method is applicable to other cancers and could be used to identify the appropriate cell line and growth condition to employ when studying other cancers. Background Cancer cell lines have been widely used as models of human cancer to better understand the biology of tumor formation and progression, as well as to help develop new therapeutic agents to treat the disease [1,2]. However, cell lines do not duplicate the in vivo environment, are subject to genetic drift, and cell-cell interactions are lost [3,4]. Therefore, we sought to quantitatively assess which of the commonly used cell lines in cervical cancer research were better models of cervical cancer relative to the cell lines we tested. Current in vitro research of cervical cancer involves the cul- ture of immortal cervical cell lines in monolayer [1,5]. Cell lines typically used include HeLa, SiHa, and Caski, among others. An alternative method to culturing in mon- olayer is organotypic culture, an advanced cell culture technique that transforms the growth environment from Page 1 of 13 (page number not for citation purposes)