Literature DB >> 27377132

Combine and conquer: challenges for targeted therapy combinations in early phase trials.

Juanita S Lopez1, Udai Banerji1.   

Abstract

Our increasing understanding of cancer biology has led to the development of molecularly targeted anticancer drugs. The full potential of these agents has not, however, been realised, owing to the presence of de novo (intrinsic) resistance, often resulting from compensatory signalling pathways, or the development of acquired resistance in cancer cells via clonal evolution under the selective pressures of treatment. Combinations of targeted treatments can circumvent some mechanisms of resistance to yield a clinical benefit. We explore the challenges in identifying the best drug combinations and the best combination strategies, as well as the complexities of delivering these treatments to patients. Recognizing treatment-induced toxicity and the inability to use continuous pharmacodynamically effective doses of many targeted treatments necessitates creative intermittent scheduling. Serial tumour profiling and the use of parallel co-clinical trials can contribute to understanding mechanisms of resistance, and will guide the development of adaptive clinical trial designs that can accommodate hypothesis testing, in order to realize the full potential of combination therapies.

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Mesh:

Year:  2016        PMID: 27377132      PMCID: PMC6135233          DOI: 10.1038/nrclinonc.2016.96

Source DB:  PubMed          Journal:  Nat Rev Clin Oncol        ISSN: 1759-4774            Impact factor:   66.675


  113 in total

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  76 in total

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Review 2.  Predictive approaches for drug combination discovery in cancer.

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5.  Mechanisms of resistance to EZH2 inhibitors in diffuse large B-cell lymphomas.

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6.  New Dual CK2/HDAC1 Inhibitors with Nanomolar Inhibitory Activity against Both Enzymes.

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8.  Synchronous Chemoradiation Nanovesicles by X-Ray Triggered Cascade of Drug Release.

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9.  Improving anticancer activity towards colon cancer cells with a new p53-activating agent.

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Journal:  Mol Cancer Ther       Date:  2018-10-03       Impact factor: 6.261

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