Our research has demonstrated that many of the same genes associated with the normal growth of embryonic stem cells are abnormally reactivated by cancer cells. Under this premise, we have established a proprietary dataset using RNA microarray technology; this dataset contains expression levels of over 47,000 genes in over 450 unique samples, representing both normal and cancerous tissues and cell lines, including multiple human embryonic stem cell lines. This broad, bioinformatics-based approach has allowed us to identify numerous genes abnormally activated in cancer or tumor cells; many of these genes have not been previously associated with cancer. Moreover, expression of a large subset of these genes is conserved across numerous cancer types (e.g. cancers of the breast, colon, ovaries, etc.), suggesting these genes may control fundamental processes during cancer growth and progression. This gene expression data presents numerous diagnostic product opportunities, such as tests designed to:

  • Screen patient samples for the presence of cancer,
  • Determine which treatment courses have highest chances for producing a favorable response in individual patients, or
  • Monitor for recurrence of a patients cancer.

Our current development strategy for cancer diagnostic products is to evaluate and validate specific diagnostic products based on unmet medical need, market size and ease of use.