PMC

The figure outlines the various scientific, non-scientific and social problems that severely hamper the planning and successful execution of clinical trials.

Patient tumor samples, either resected or biopsied, are transplanted and propagated in immunocompromized mice. The mice with the implanted tumors are then used as an in-vivo system for drug testing. Several therapeutic agents are then tested, as cocktails in various combinations and concentrations, for efficacy and safety in these mice. Therapies that cause tumor regression in the murine system help build a clinical rationale that is then applied to the patient from whom the tumor sample was derived. Using this method, each patient would have an individualized in-vivo mouse, allowing for a large number of drug compounds to be evaluated for efficacy relatively quickly, resulting in the identification of a safe, targeted therapeutic regimen for the patient. The use of these mouse avatars would ensure that a patient is not given chemotherapeutic agents that are predicted to be ineffective or toxic as determined in the murine system.

The concept of co-clinical trials advocates an integration of preclinical murine and clinical human trials in an attempt to accelerate the drug development and testing process. As part of co-clinical trials, both genetically engineered mouse models (GEMMs) that mirror a patient’s tumor genotype and xenograft models for the transplantation and propagation of the patient’s tumor are employed. Therapeutic agents that are efficacious in these mouse models are then applied to the patient population. This approach is complemented with standard molecular profiling and imaging techniques. Similar to the PDTX models, such a system allows for identification of biomarkers and potential resistance pathways. Although this concept seems more resource intensive when compared to the xenograft models, it allows for a more comprehensive approach towards clinical management of cancer. The use of GEMMs facilitates the identification of genetic modifiers, compensatory signaling pathways to therapeutic response and genetically-determined prognostic factors. This newly emerging concept attempts to bridge the gap between cancer biologists and oncologists and proposes a large-scale multi-centre collaborative approach to effectively treat cancer.

The patient tumor is resected—a part of it is subjected to standard molecular profiling techniques and part of it is prepared for transplantation into immunocompromized mice. The patient tumor is analyzed for mutational status, copy number variations and is characterized at the nucleic acid and protein level using gene expression arrays and proteomics-based approaches. Another portion of the tumor is xenografted and propagated in immunocompromized mice through several generations (F₀…F₃). The propagated tumors are isolated from the F₃ generation and are characterized like the human tumors. The molecular profile of the human tumor is superimposed on the profile of the murine tumors. A high degree of concordance between the human and murine tumor profiles helps establish the mouse as a faithful model of the human cancer. Downstream bioinformatics analyses of data obtained after murine molecular profiling helps identify drug targets. Therapeutic agents against these targets are then evaluated for safety and efficacy in these F₃ mice. Comparative analyses of drug-sensitive and resistant tumors could result in the identification of biomarkers that predict therapeutic response. Validation of such biomarkers may then be used to stratify patient populations in clinical trials in the future. The mice having tumors that are drug-sensitive are treated continually with a that particular therapeutic agent to anticipate and identify potential resistance pathways much before drug-resistance is observed in the clinical setting. Drugs efficacious in these resistant tumors are then determined and kept ready in case of emergence of resistance in the patient. In this way, PDTX models are useful not only for the identification of drug targets but also to determine predictive biomarkers and possible molecular changes and signaling pathways conferring resistance.