Synergistic Approaches to Clinical Oncology Biomarker Discovery

Abstract

Biomarkers in the clinical oncology field can have tremendous therapeutic impact especially if the marker is detected before clinical symptoms. This impact can be extended to the evaluation of clinical oncology treatments allowing evaluation of potential compounds to determine their efficacy in the disease treatment. The discovery of clinical biomarkers can consume time, resources and costs. Therefore, it is important that the most effective strategies are employed to discover these biomarkers. These strategies may include the integration of available genomic, proteomic and histopathological technologies, which could reduce the costs and aid in the validation of the biomarker. Certainly the type of biomarker needed to address a particularly defined problem will drive the type of technology. However, a single biomarker to diagnose a specific cancer can be as elusive as relying on a single technology. This review examines some of the technologies used to discover biomarkers and presents the use of combinatorial technical synergies to discover and validate potential clinical oncology biomarkers.

Can Cancer Be Diagnosed With a Blood Test During Routine Examinations?

“…Biomarkers can be used as an aid to diagnose within specific target populations and to determine the effectiveness of treatment and recurrence of disease. A biomarker must be able to be measured with precision so that it can be evaluated objectively and within a clinical setting (Belkowski, Polkovitch, & D'Andrea, 2005). Tumor markers usually are composed of enzymes, structural proteins, cell surface carbohydrate proteins, receptors, or genes (Hoefner, 2005).…”

“…Tissue pathology typically includes the tumor size, grade and node status, steroid receptor status, tumor ploidy, proliferation indexes, inactivation of tumor suppressor genes, and the overexpression of known oncogenes (Belkowski et al, 2005). Tissue pathology typically includes the tumor size, grade and node status, steroid receptor status, tumor ploidy, proliferation indexes, inactivation of tumor suppressor genes, and the overexpression of known oncogenes (Belkowski et al, 2005).…”