Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the Western world. The most active drug against this malignancy is 5 Fluorouracil (5FU), which produces response rates of only 20 to 25% in advanced CRC. Efforts to improve efficacy have led to combination of 5FU with newer agents such as Irinotecan and Oxaliplatin, which have significantly improved response rates to 40 to 50%. Despite these improvements, less than half of patients who undergo chemotherapy will receive any benefit from treatment. A major factor limiting the effectiveness of chemotherapy against CRC is inherent or acquired drug resistance. We have previously generated a panel of HCT116 CRC cell lines resistant to 5FU and Oxaliplatin by repeated exposure to stepwise increasing concentrations of drug over a period of months. We have used these model cell lines in conjunction with DNA microarray technology to identify novel determinants of response to 5FU and Oxaliplatin. Using data analysis software (Genespring and SAM), we have identified panels of genes whose expression is constitutively altered in drug resistant cells relative to sensitive parental cells and induced following acute exposure of parental cells to drug. In total, 119 genes and 37 genes were identified that correlate with 5FU and Oxaliplatin sensitivity respectively. These data suggest that cancer cells may recruit and activate the expression of a distinct set of genes in transient induction or when selected for resistance to chemotherapy. We propose that this set of genes may represent a distinct molecular signature indicative of drug resistance. Using real time RT PCR, we have successfully validated a representative subset of these genes and calculated r squared values to examine the robustness of our microarray data set. Using Genespring, we have carried out advanced data mining of both the 5-FU and oxaliplatin datasets in a time- and gene-dependent manner. We have used several different clustering methods to identify patterns of gene expression within our datasets. Gene ontology analysis has identified groups of genes involved in response to either oxaliplatin or 5-FU. Furthermore, this analysis has demonstrated that the majority of differential gene expression occurs at 6h in the oxaliplatin dataset and that this is maintained to 24h, whereas the majority of genes are differentially regulated at 24h in the 5-FU dataset. Pathway analysis has further identified several pathways involved in either 5-FU or oxaliplatin response. We are currently testing the predictive accuracy of these genes in a panel of pretreatment metastatic CRC biopsies, using a two-step supervised classification approach. Ultimately, the data from these analyses will be used to design a prospective trial, in which treatment for CRC is administered on the basis of the molecular profile of both tumour and patient.

[Proc Amer Assoc Cancer Res, Volume 47, 2006]