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Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways.

Carlson MW, Iyer VR, Marcotte EM - BMC Genomics (2007)

Bottom Line: 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.Applying this method to individual pathways, we identified the appropriateness of particular cell lines for studying specific pathways in cervical cancer.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA. mark.carlson@tufts.edu <mark.carlson@tufts.edu>

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.

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Related in: MedlinePlus

Venn diagram of the overlap of differentially expressed cervical cancer genes in the literature. Eight reports of differentially expressed cervical cancer genes from the literature were compared against each other and to our results. Seven of the studies were combined into one group (203 genes, no overlap between studies). Our results (Carlson, 140 genes) overlapped with Santin (488 genes) by 9 genes and with the rest by 11 genes. Santin had 20 genes in common with the 203 gene combined group. Only 2 genes were found in all three data sets, SLC2A1 and a serine protease inhibitor (clone IDs 25389 and 2562939). Our results show comparable overlap with the literature, and provide additional evidence that the tissue samples analyzed are representative of previous reports on cervical cancer.
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Figure 1: Venn diagram of the overlap of differentially expressed cervical cancer genes in the literature. Eight reports of differentially expressed cervical cancer genes from the literature were compared against each other and to our results. Seven of the studies were combined into one group (203 genes, no overlap between studies). Our results (Carlson, 140 genes) overlapped with Santin (488 genes) by 9 genes and with the rest by 11 genes. Santin had 20 genes in common with the 203 gene combined group. Only 2 genes were found in all three data sets, SLC2A1 and a serine protease inhibitor (clone IDs 25389 and 2562939). Our results show comparable overlap with the literature, and provide additional evidence that the tissue samples analyzed are representative of previous reports on cervical cancer.

Mentions: A second analysis provided further evidence that the expression profiles in these cervical cancer biopsies were consistent with previous observations in the literature and therefore suitable for further detailed analysis. Approximately 650 differentially expressed genes identified in the literature, derived from small scale microarray studies [18-22], differential RNA display [23-27], or single gene studies [28,29], were compared to the 140 genes identified in our study (Figure 1). Nineteen genes were observed in both data sets (*) [see Additional file 1]; 30 genes in the same sequence family (homologs) were also identified (**) [see Additional file 1]. Despite the apparent small overlap in large scale datasets, the overlap is significant (p < 0.001, hypergeometric distribution) and indicates that our tissue biopsies are representative of the literature and can be used for further analysis.


Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways.

Carlson MW, Iyer VR, Marcotte EM - BMC Genomics (2007)

Venn diagram of the overlap of differentially expressed cervical cancer genes in the literature. Eight reports of differentially expressed cervical cancer genes from the literature were compared against each other and to our results. Seven of the studies were combined into one group (203 genes, no overlap between studies). Our results (Carlson, 140 genes) overlapped with Santin (488 genes) by 9 genes and with the rest by 11 genes. Santin had 20 genes in common with the 203 gene combined group. Only 2 genes were found in all three data sets, SLC2A1 and a serine protease inhibitor (clone IDs 25389 and 2562939). Our results show comparable overlap with the literature, and provide additional evidence that the tissue samples analyzed are representative of previous reports on cervical cancer.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1878486&req=5

Figure 1: Venn diagram of the overlap of differentially expressed cervical cancer genes in the literature. Eight reports of differentially expressed cervical cancer genes from the literature were compared against each other and to our results. Seven of the studies were combined into one group (203 genes, no overlap between studies). Our results (Carlson, 140 genes) overlapped with Santin (488 genes) by 9 genes and with the rest by 11 genes. Santin had 20 genes in common with the 203 gene combined group. Only 2 genes were found in all three data sets, SLC2A1 and a serine protease inhibitor (clone IDs 25389 and 2562939). Our results show comparable overlap with the literature, and provide additional evidence that the tissue samples analyzed are representative of previous reports on cervical cancer.
Mentions: A second analysis provided further evidence that the expression profiles in these cervical cancer biopsies were consistent with previous observations in the literature and therefore suitable for further detailed analysis. Approximately 650 differentially expressed genes identified in the literature, derived from small scale microarray studies [18-22], differential RNA display [23-27], or single gene studies [28,29], were compared to the 140 genes identified in our study (Figure 1). Nineteen genes were observed in both data sets (*) [see Additional file 1]; 30 genes in the same sequence family (homologs) were also identified (**) [see Additional file 1]. Despite the apparent small overlap in large scale datasets, the overlap is significant (p < 0.001, hypergeometric distribution) and indicates that our tissue biopsies are representative of the literature and can be used for further analysis.

Bottom Line: 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.Applying this method to individual pathways, we identified the appropriateness of particular cell lines for studying specific pathways in cervical cancer.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA. mark.carlson@tufts.edu <mark.carlson@tufts.edu>

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.

Show MeSH
Related in: MedlinePlus