---------- Forwarded message ----------
From: HubMed - breast cancer <rssfwd@rssfwd.com>
Date: Sat, Feb 16, 2008 at 8:08 PM
Subject: Molecular prediction of the therapeutic response to neoadjuvant chemotherapy in breast cancer.
To: mesothelioma77@gmail.com
[1]Breast Cancer. 2008 Feb 15;
Nagasaki K, Miki Y
Breast cancer is considered to be relatively sensitive to chemotherapy, and multiple combinations of cytotoxic agents are used as standard therapy. Chemotherapy is applied empirically despite the observation that not all regimens are equally effective across the population of patients. Up to date clinical tests for predicting cancer chemotherapy response are not available, and individual markers have shown little predictive value. A number of microarray studies have demonstrated the use of genomic data, particularly gene expression signatures, as clinical prognostic factors in breast cancer. The identification of patient subpopulations most likely to respond to therapy is a central goal of recent personalized medicine. We have designed experiments to identify gene sets that will predict treatment-specific response in breast cancer. Taken together with our recent trial about the construction of a high-throughput functional screening system for chemo-sensitivity related genes, studies for drug sensitivity will provide rational strategies for establishment of the prediction system with high accuracy, and identification of ideal targets for drug intervention.
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Source: http://www.hubmed.org/display.cgi?uids=18274834
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From: HubMed - breast cancer <rssfwd@rssfwd.com>
Date: Sat, Feb 16, 2008 at 8:08 PM
Subject: Molecular prediction of the therapeutic response to neoadjuvant chemotherapy in breast cancer.
To: mesothelioma77@gmail.com
[1]Breast Cancer. 2008 Feb 15;
Nagasaki K, Miki Y
Breast cancer is considered to be relatively sensitive to chemotherapy, and multiple combinations of cytotoxic agents are used as standard therapy. Chemotherapy is applied empirically despite the observation that not all regimens are equally effective across the population of patients. Up to date clinical tests for predicting cancer chemotherapy response are not available, and individual markers have shown little predictive value. A number of microarray studies have demonstrated the use of genomic data, particularly gene expression signatures, as clinical prognostic factors in breast cancer. The identification of patient subpopulations most likely to respond to therapy is a central goal of recent personalized medicine. We have designed experiments to identify gene sets that will predict treatment-specific response in breast cancer. Taken together with our recent trial about the construction of a high-throughput functional screening system for chemo-sensitivity related genes, studies for drug sensitivity will provide rational strategies for establishment of the prediction system with high accuracy, and identification of ideal targets for drug intervention.
___
Source: http://www.hubmed.org/display.cgi?uids=18274834
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