Oncology represents a particular attractive area for application of the Aptamarker™ platform for several reasons. Aptamarkers™ have the capacity to bind to a wide variety of molecules including other oligonucleotides (including non-coding RNA), metabolites, proteins, and complexes among these molecules. The key to Aptamarker performance is the establishment of effective contrasts in phenotype. Given the existence of such contrasts, aptamers can be selected that will bind to proteins that exhibit different epitopes as the result of an oncogenic mutation and fusion proteins resulting from oncogenic translocations.
A key difficulty with early detection is low abundance of oncogenic biomarkers in blood. Aptamarkers overcomes this difficulty by imposing counter selection for aptamers between individuals affected and not affected by the disease, followed by a PCR amplification. This selection process is carried out for at least ten cycles leading to an enrichment of Aptamarkers of at least ten orders of magnitude. This places low abundance targets on an equivalent abundance to abundant proteins in blood.
Identification of cancer type:
A key to effective treatment of cancer is early identification of the type of cancer presented. The Aptamarker approach can be applied to blood based on contrasts between individuals affected by different types of the same tissue specific cancer. These fingerprints could then be used as an early guide for confirmation of appropriate treatment.
It is often difficult to demonstrate a therapeutic effect of a cancer treatment without imaging a tumour. Aptamarkers could be used to characterize blood based fingerprints of the pathology across individuals, and then to quantify a decrease in the presence of these biomarkers as a result of treatment.
At present it is difficult to predict individual response to chemotherapy. Some individuals are capable of tolerating a higher dose than is initially applied, while others have difficulty with even low initial doses. It would be feasible to use Aptamarkers to identify differences in the blood that are correlated with tolerance to chemotherapy.