دورية أكاديمية

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities.

التفاصيل البيبلوغرافية
العنوان: Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities.
المؤلفون: Rui-Ru Ji, de Silva, Heshani, Yisheng Jin, Bruccoleri, Robert E., Jian Cao, Aiqing He, Wenjun Huang, Kayne, Paul S., Neuhaus, Isaac M., Ott, Karl-Heinz, Penhallow, Becky, Cockett, Mark I., Neubauer, Michael G., Siemers, Nathan O., Ross-Macdonald, Petra
المصدر: PLoS Computational Biology; Sep2009, Vol. 5 Issue 9, p1-12, 12p, 6 Graphs
مستخلص: The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data. [ABSTRACT FROM AUTHOR]
Copyright of PLoS Computational Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
قاعدة البيانات: Complementary Index
الوصف
تدمد:1553734X
DOI:10.1371/journal.pcbi.1000512