Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways
Open Access
- 10 May 2007
- journal article
- research article
- Published by Springer Nature in BMC Genomics
- Vol. 8 (1) , 117
- https://doi.org/10.1186/1471-2164-8-117
Abstract
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.Keywords
This publication has 40 references indexed in Scilit:
- Analysis of gene expression induced by microtubule-disrupting agents in HeLa cells using microarrayCancer Letters, 2006
- The clinicopathologic significance of laminin-5 gamma2 chain expression in cervical squamous carcinoma and adenocarcinomaInternational Journal of Gynecologic Cancer, 2005
- New approaches to pathogenic gene function discovery with human squamous cell cervical carcinoma by gene ontologyGynecologic Oncology, 2005
- Panel of Genes Transcriptionally Up-regulated in Squamous Cell Carcinoma of the Cervix Identified by Representational Difference Analysis, Confirmed by Macroarray, and Validated by Real-Time Quantitative Reverse Transcription-PCRClinical Chemistry, 2005
- Comparison of gene expression in squamous cell carcinoma and adenocarcinoma of the uterine cervixGynecologic Oncology, 2004
- Smad4 deficiency in cervical carcinoma cellsOncogene, 2004
- siRNA targeting of the viral E6 oncogene efficiently kills human papillomavirus-positive cancer cellsOncogene, 2003
- A Major Constituent of Green Tea, EGCG, Inhibits the Growth of a Human Cervical Cancer Cell Line, CaSki Cells, through Apoptosis, G1 Arrest, and Regulation of Gene ExpressionDNA and Cell Biology, 2003
- The anti-apoptotic role of interleukin-6 in human cervical cancer is mediated by up-regulation of Mcl-1 through a PI 3-K/Akt pathwayOncogene, 2001
- Systematic variation in gene expression patterns in human cancer cell linesNature Genetics, 2000