Literature DB >> 21427550

Molecular tumor profiling for prediction of response to anticancer therapies.

Zenta Walther1, Jeffrey Sklar.   

Abstract

Personalized medicine in the treatment of cancer is based on the recognition that molecularly targeted therapies are most effective in patients whose tumors carry specific genetic or genomic alterations. These alterations, which often activate oncogenes that encode the components of signal transduction pathways, serve as predictive markers for sensitivity or resistance of individual tumors to drugs that target such pathways. In the recent past, individual mutations and other changes within tumors have been assayed to determine the likelihood of response or nonresponse to specific targeted therapies. However, with the development of increasing numbers of molecularly targeted drugs, attention has shifted to high-throughput testing of tumors for dozens of predictive markers. This approach to predictive testing has been termed molecular tumor profiling. This review describes the background to this field, the principal markers analyzed, and the methodologies that are being utilized or are under development for tumor profiling.

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Year:  2011        PMID: 21427550     DOI: 10.1097/PPO.0b013e318212dd6d

Source DB:  PubMed          Journal:  Cancer J        ISSN: 1528-9117            Impact factor:   3.360


  13 in total

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9.  A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction.

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Journal:  PLoS One       Date:  2014-06-30       Impact factor: 3.240

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