Current Preclinical Models in Oncology-Enhancing Predictivity for Translational Success

Presented By: 
Benjamin Cuiffo

Overview: The success rate of potential novel anti-cancer therapeutics has historically been low, hovering around 5%, and is attributed, at least in part, to the widespread use of readily available but imperfect models at the preclinical phase. We now appreciate that tumor environment and location are of critical importance to the growth, progression and therapeutic response of cancer. For these reasons, the translational predictivity of preclinical efficacy studies is enhanced when cancer cells of a particular tissue origin are assayed following implantation at the corresponding orthotopic site, as opposed to as subcutaneous grafts. Unfortunately, the relative inaccessibility of many organs (e.g. pancreas, brain, bone, etc.), makes delivery of cancer cells to these sites technically challenging and obfuscates subsequent monitoring of tumor growth kinetics. Ultimately, these limitations have stifled the development of efficacious therapeutic agents for cancers of these origins. The use of patient-derived xenograft lines, transduced bioluminescent reporter proteins, and expertise in delivering cancer cells to orthotopic sites has revolutionized our ability to assay the efficacy of potential anti-cancer agents. We will discuss the current generation of specialized preclinical oncology models that more closely recapitulate the clinical condition and offer enhanced predictive potential for development of novel therapies.

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