Based on early work in breast cancer, Dr. Datto and his colleagues hypothesized that clinically relevant bimodal genes exist in epithelial ovarian cancer. Using a large, publically available ovarian cancer microarray dataset, they applied a previously described biomodal index discovery algorithm to evaluate the expression of all genes across 285 samples. They identified many genes with robust patterns of bimodal expression. They also found that a number of genes with bimodal expression patterns are significantly associated with tumor type and/or overall patient survival. When combined into a single sum survival score, the top survival-significant genes identify a clinically distinct molecular subtype of malignant serous ovarian carcinoma.

"From a clinical testing perspective, genes with a continuous pattern of expression can make difficult testing targets. However, the distinction between 'on' or 'off' expression for a particular bimodal gene is relatively straightforward," says Dr. Datto. "This allows clear-cut decision making boundaries and development of precise, reliable testing methods. Bimodal genes may also be candidates for testing by less quantitative methods such as immunohistochemistry."

Several of the bimodal genes that the researchers identified have known roles in tumorigenesis. "This raises the possibility that we have described molecular switch genes that will not only be relevant in the context of ovarian carcinoma, but across multiple tumor types," Dr. Datto concludes.

Source: Eurekalert