Selection of a novel drug-response predictor in esophageal cancer: A novel screening method using microarray and identification of IFITM1 as a potent marker gene of CDDP response

Abstract

Abstract. Prior laboratory prediction of individual drug response is of key importance in esophageal squamous cell carcinoma (ESCC), because of the extremely narrow therapeutic index of chemotherapy. However, very few critical markers have been validated to date for ESCC. We previously demonstrated that simultaneous performance of two different types of comprehensive gene expression analysis might provide a way to identify potent marker genes for drug sensitivity from the expression-sensitivity correlation analysis alone, but the screening method appeared not to be always effective. Therefore, we attempted to identify novel potent marker genes using a new statistical analysis of oligonucleotide microarray expression data, based on a two-dimensional mixed normal model, and selected 3 and 7 novel candidates for 5-fluorouracil (5-FU) and cis-platinum (CDDP), respectively. Interferon induced transmembrane protein 1 (IFITM1) gene alone, being suggested as a key gene of Wnt pathway, was commonly selected in both screening methods. The transfection analyses and siRNA-mediated knock-down experiments revealed that expression of IFITM1 closely related to cellular sensitivity to CDDP. Considering the fact that drug sensitivity is determined by multiple genes, we established the best linear model using quantified expression data of a set of all the selected marker genes including IFITM1, which converted the quantified expression data of ESCC cell lines into an IC 50 value of each drug. In the same way, using the representative genes selected in vitro, we developed highly predictive formulae for disease-free survival (DFS) of the CDDP/5-FU combination after curative operation in esophageal cancer patients (R=0.917). A two-dimensional mixed normal model can be a powerful tool to identify novel drug-response determinants, and the IFITM1 gene selected by the statistical method a novel critical biomarker of CDDP response in ESCC.

Transcriptome Network Analysis Reveals Potential Candidate Genes for Esophageal Squamous Cell Carcinoma

“…Interferon induced transmembrane protein 1 (IFITM1) gene alone, being suggested as a key gene of Wnt pathway, was commonly selected in 5-fluorouracil (5-FU) and cis-platinum (CDDP) screening methods using a new statistical analysis of oligonucleotide microarray expression data, based on a two-dimensional mixed normal model. The results suggested the IFITM1 gene was a novel critical biomarker of CDDP response in ESCC (Fumoto et al, 2008). IFITM1 was up-regulated in esophageal tumor tissue from patients (Chattopadhyay et al, 2009).…”

Application of Embryonic Stem Cells as a Novel Tool in Drug Screening

“…This prevented the endothelial injury usually caused by 5-FU, but the rate of recovery for damaged endothelial cells did not completely return to normal (Kita et al, 1987;Kaneko et al, 1996). In order to understand the biological mechanism of target cell specific toxicants, DNA microarrays have been used to analyse gene profiling, to show the alteration of gene expression (Gunji et al, 2004;Mori et al, 2007;Fumoto et al, 2008). However, studies of gene profiling and the mechanisms within ESCs exposed to special toxicants, including 5-FU, are still rare.…”

Quantitative prediction of tumor response to neoadjuvant chemotherapy in breast cancer: novel marker genes and prediction model using the expression levels

“…Although DNA chip technology enables us to overview a huge number of gene expressions simultaneously, gene expression profiles of drug sensitivity vary considerably even for the same drug. Prediction of a responder for chemotherapy by using ''the snapshot expression profile'' of microarrays is thus increasingly being recognized as being more challenging than anticipated [17][18][19][20][21][22].…”

“…The main obstacle to predicting therapeutic efficacy is the intricate mechanisms of drug sensitivity [16][17][18][19][20]: multifactorial mechanisms limit the prediction of individual drug response using any single marker. Although DNA chip technology enables us to overview a huge number of gene expressions simultaneously, gene expression profiles of drug sensitivity vary considerably even for the same drug.…”

“…We therefore attempted to select a set of key marker genes genome-wide using DNA microarrays in vitro, and we developed a prediction system for clinical chemotherapeutic response based on multiple regression analysis using expression data of the selected genes [16][17][18][19]. For prediction of response to combination chemotherapy, we used all of the biomarkers selected for each component drug.…”