Literature DB >> 23509311

Development of therapeutic combinations targeting major cancer signaling pathways.

Timothy A Yap1, Aurelius Omlin, Johann S de Bono.   

Abstract

Signaling networks play key homeostatic processes in living organisms but are commonly hijacked in oncogenesis. Prominent examples include genetically altered receptor tyrosine kinases and dysregulated intracellular signaling molecules. The discovery and development of targeted therapies against such oncogenic proteins has imparted clinical benefit. Nevertheless, concerns remain about the limited single-agent efficacy and narrow therapeutic indices of many of these antitumor agents. Moreover, it is apparent that oncogenic proteins comprise complex signaling networks that interact through crosstalk and feedback loops, which modify therapeutic vulnerability. These complexities mandate the study of drug combinations, which will also become necessary to reverse tumor drug resistance. Here, we outline the challenges associated with rational drug codevelopment strategies, with a focus on the importance of analytically validated biomarkers for patient selection and pharmacokinetic-pharmacodynamic (PK-PD) studies. Overall, the most informative clinical studies of novel combinations will have the following characteristics: robust scientific hypotheses leading to their selection; supportive preclinical data from contextually appropriate preclinical model systems; sufficient preclinical PK data to inform on the risk of drug-drug interactions; and detailed PD studies to determine the biologically active dose range for each agent. Toward this end, several novel clinical trial designs may be envisioned to accelerate successful drug combination development while minimizing the risk of late drug combination attrition. Although considerable challenges remain, these efforts may enable important steps to be taken toward more durable therapeutic control of many cancers.

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Year:  2013        PMID: 23509311     DOI: 10.1200/JCO.2011.37.6418

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  100 in total

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