Gene Signature Predicts Good Outcome In Breast Cancer
Main Category: Breast CancerAlso Included In: Genetics; Cancer / Oncology
Article Date: 14 May 2009 - 6:00 PDT
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Researchers have identified a genetic signature that can predict an improved clinical outcome in patients with breast cancer, and which could help in the development of new targeted therapies.
By analysing the expression of different genes induced by a specific mutation in a molecule called PIK3CA, a critical part of the pathway commonly deregulated in breast cancer, they found that these genes were correlated with an improved clinical outcome in over 1500 women with the disease.
Source
European Society for Medical Oncology
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16 Feb. 2012. <http://www.medicalnewstoday.com/releases/150067.php>
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http://www.medicalnewstoday.com/releases/150067.php.
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Gene Signature Prediction
posted by Gregory D. Pawelski on 22 May 2009 at 7:32 pmWhat do you do when there are too many receptors and the cancer cell still continues to grow and divide?
When considering a 'targeted' cancer drug which is believed to act only upon cancer cells that have a specific genetic defect, it is useful to know if a patient's cancer cells do or do not have precisely that defect. Although presence of a 'targeted' defect does not necessarily mean that a drug will be effective, absence of the targeted defect may rule out use of the drug.
Cancer cells have many mutations in many different pathways, so even if one route or two is shut down by a targeted treatment, the cancer cell may be able to use other routes. Molecular diagnostics often have been mostly or totally ineffective at identifying clinical responders to the various therapies.
Gene-based testing examines a single process within the cell or a relatively small number of processes. The aim is to tell if there is a theoretical predispostion to drug response. It involves the use of dead, formaldehyde preserved cells that are never exposed to 'targeted' drugs. It cannot tells us anything about uptake of a certain drug into the cell or if the drug will be excluded before it can act or what changes will take place within the cell if the drug successfully enters the cell.
It cannot discriminate among the activities of different drugs within the same class. Instead, it assumes that all drugs within a class will produce precisely the same effect, even though from clinical experience, this is not the case. Nor can it tell us anything about drug combinations. Cancer is a complex disease and needs to be attacked on many fronts.
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