Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways
<p>Abstract</p> <p>Background</p> <p>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 lin...
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| Format: | Article |
| Language: | English |
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BMC
2007-05-01
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| Series: | BMC Genomics |
| Online Access: | http://www.biomedcentral.com/1471-2164/8/117 |
| _version_ | 1818111604072382464 |
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| author | Iyer Vishwanath R Carlson Mark W Marcotte Edward M |
| author_facet | Iyer Vishwanath R Carlson Mark W Marcotte Edward M |
| author_sort | Iyer Vishwanath R |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> |
| first_indexed | 2024-12-11T03:05:41Z |
| format | Article |
| id | doaj.art-cf8a730046f34b5ab25e59bf08b390e5 |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-12-11T03:05:41Z |
| publishDate | 2007-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genomics |
| spelling | doaj.art-cf8a730046f34b5ab25e59bf08b390e52022-12-22T01:22:58ZengBMCBMC Genomics1471-21642007-05-018111710.1186/1471-2164-8-117Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathwaysIyer Vishwanath RCarlson Mark WMarcotte Edward M<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p>http://www.biomedcentral.com/1471-2164/8/117 |
| spellingShingle | Iyer Vishwanath R Carlson Mark W Marcotte Edward M Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways BMC Genomics |
| title | Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways |
| title_full | Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways |
| title_fullStr | Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways |
| title_full_unstemmed | Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways |
| title_short | Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways |
| title_sort | quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways |
| url | http://www.biomedcentral.com/1471-2164/8/117 |
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