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Data from Antitumor activity of histone deacetylase inhibitors in non-small cell lung cancer cells: development of a molecular predictive model
- Publication Year :
- 2023
- Publisher :
- American Association for Cancer Research (AACR), 2023.
-
Abstract
- To ascertain the potential for histone deacetylase (HDAC) inhibitor-based treatment in non-small cell lung cancer (NSCLC), we analyzed the antitumor effects of trichostatin A (TSA) and suberoylanilide hydroxamic acid (vorinostat) in a panel of 16 NSCLC cell lines via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. TSA and vorinostat both displayed strong antitumor activities in 50% of NSCLC cell lines, suggesting the need for the use of predictive markers to select patients receiving this treatment. There was a strong correlation between the responsiveness to TSA and vorinostat (P < 0.0001). To identify a molecular model of sensitivity to HDAC inhibitor treatment in NSCLC, we conducted a gene expression profiling study using cDNA arrays on the same set of cell lines and related the cytotoxic activity of TSA to corresponding gene expression pattern using a modified National Cancer Institute program. In addition, pathway analysis was done with Pathway Architect software. We used nine genes, which were identified by gene-drug sensitivity correlation and pathway analysis, to build a support vector machine algorithm model by which sensitive cell lines were distinguished from resistant cell lines. The prediction performance of the support vector machine model was validated by an additional nine cell lines, resulting in a prediction value of 100% with respect to determining response to TSA and vorinostat. Our results suggested that (a) HDAC inhibitors may be promising anticancer drugs to NSCLC and (b) the nine-gene classifier is useful in predicting drug sensitivity to HDAC inhibitors and may contribute to achieving individualized therapy for NSCLC patients. [Mol Cancer Ther 2008;7(7):1923–30]
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....3065d74147baf8da05e4c624430e40ff
- Full Text :
- https://doi.org/10.1158/1535-7163.c.6531042.v1