ZIC BC 011137 (ZIC) | |||
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Title | Center for Applied Preclinical Research (CAPR) | ||
Institution | NCI, Bethesda, MD | ||
Principal Investigator | Van Dyke, Terry | NCI Program Director | N/A |
Cancer Activity | N/A | Division | CCR |
Funded Amount | $564,828 | Project Dates | 10/01/2008 - 00/00/0000 |
Fiscal Year | 2014 | Project Type | Intramural |
Research Topics w/ Percent Relevance | Cancer Types w/ Percent Relevance | ||
Cancer (100.0%) Digestive Diseases (5.0%) |
Brain (10.0%) Lung (40.0%) Melanoma (10.0%) Nervous System (10.0%) Ovarian Cancer (30.0%) Pancreas (5.0%) Prostate (5.0%) |
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Research Type | |||
Development and Characterization of Model Systems Application of Model Systems |
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Abstract | |||
At present, significant resources are committed by both academic research and industry to deliver groundbreaking therapeutic and diagnostic strategies aimed at curbing cancer occurrence. Despite the critical mass of available knowledge and technology platforms in the anti-cancer drug development field providing for the development of pathway-targeted therapies, only a few efficacious treatments have been developed. The major preclinical point of the government-regulated process for extensive animal testing of potential anti-cancer therapeutic compounds is directed towards safety assessment prior to the clinical introduction of any new anti-cancer drug. This analytical path of demonstrating the desired drug efficacy while proving it to be non-toxic has been implemented in a number of countries as multiphase clinical trial procedures. The initial stage in drug candidate evaluation demands routine investigation of future therapeutic compounds in animal and cell culture models, primarily to obtain knowledge of non-toxicity ranges, interaction with metabolic pathways, and systemic pharmacological behavior. This phase, termed preclinical characterization, may also provide a fair estimate point for the compounds therapeutic efficacy given the availability of appropriate disease model(s). In general, considering the extremely long (routinely >10 years) and expensive (often in excess of $700 million per drug lead) process to obtain the regulatory approval to market therapeutic compounds, the quality and the scope of efficacy data obtained during the preclinical stages may expedite clinical testing, dramatically increase affordability of downstream drug development steps, and advance the identification of effective cancer therapies. Currently, drug efficacy studies are conducted almost exclusively in xenograft models that employ transformed human cell lines to initiate tumor growth upon injection into immunocompromised animals. Though easily derived, the xenograft models feature multiple intrinsic limitations that jeopardize the predictability of drug testing output data. Xenograft tumors are developed from a genetically heterogeneous cell population that has been maintained in vitro for multiple passages. Moreover, the tumor growth occurs in an ectopic, non-physiological environment in the absence of immune surveillance and systemic interactions with the vascular system. As an alternative source of experimental tumors, animal models of spontaneous carcinogenesis may be also employed, but these models generally lack the reproducibility in timing of tumor onset and feature by heterogeneous tumor characteristics/drug response due to a considerable genetic ""noise"" caused by non-inbred strain background. The drawbacks of the xenograft and the spontaneous tumorigenesis models are largely ameliorated in genetically engineered mouse (GEM) tumor lines, which provide preclinical researchers with the ability to study naturally occurring tumors featuring pathway aberrations typical for similar human cancer types in the context of an appropriate tissue environment in immunocompetent animals. This approach finds ground in the rapidly expanding knowledge base for molecular mechanisms underlying carcinogenesis in human patients and is further fueled by the recent and rapid progress in the methodology and availability of resources to design and construct sophisticated animal models for a broad spectrum of human malignancies. At present, the GEM strategy not only provides an opportunity to combine in transgenic animals multiple genetic aberrations closely matching those detected in human patients, but also the potential to interfere with cancer-related molecular pathways in both a tissue-restricted and time-specific manner, providing genetic evidence for drug target legitimacy. This translates into a more accurate prediction of the dynamics of tumor progression while minimizing individual variations. In contrast to xenograft models, the cancerous les" |