OncoCyte’s diagnostics are based on:
- Non-invasive liquid biopsies using blood or urine
- Proprietary set of cancer biomarkers
- Gene expression classifier
Non-invasive liquid biopsies move the standard of care away from risky, more costly procedures that take tissue from the tumor for biopsies to a simple blood draw or urine specimen.
The company’s work is based on a proprietary set of cancer markers characterized, in part, by broad gene expression patterns in numerous cancer types. The Company’s biomarkers were discovered as a result of ongoing research within OncoCyte on the gene expression patterns associated with embryonic stem cell development. Additionally, lung biomarkers were discovered through extensive research and collaborative agreements with The Wistar Institute.
Internal research has demonstrated that many of the same genes associated with normal growth during embryonic stem cell development were found to be abnormally reactivated by cancer cells. These genes regulate such diverse processes as cell proliferation, cell migration, and blood vessel formation. Many of these genes have not been previously associated with cancer. Moreover, expression of a large subset of these genes is observed across numerous cancer types (e.g., cancers of the breast, colon, ovaries, etc.), suggesting that these genes may control fundamental processes during cancer growth and progression. In addition to their potential value in developing diagnostic biomarkers, an understanding of the pattern of expression of these genes may also enable the development of powerful new cancer immunotherapies that target rapidly proliferating cancer cells.
Using a proprietary mathematical algorithm called a Gene Expression Classifier; this data is compared with gene expression patterns exhibited by cancer tissues that get picked up in blood or urine. The result is the discovery of a set of key biomarkers that can be used to detect the early presence or absence of cancer. The end result of our development work will be to develop diagnostics that report out on the probability of the patient having the specific type of cancer.