Two people can have very different responses to the same drug and treatment. It
is becoming clearer that the different responses relate to a person's genetic
The treatment of breast cancer is one of the first to take into account a person's genetics.
Her-2 is one example of a molecule that is different in different tumors. Her-2 binds to signals outside the cell, and triggers cell growth and division. Normal cells have very low levels of this protein; tumor cells often have high levels.
Herceptin is a drug that targets Her-2. If a tumor is growing because of high levels of Her-2, tumor growth can be halted by Herceptin.
On the other hand, if a tumor’s growth is due to changes in a different protein, Herceptin will have no effect.
Only 25% of breast cancers have high levels of Her-2 proteins. Giving herceptin to people with normal Her-2 levels has no effect on the cancer.
As scientists learn more about the molecular basis of cancer, doctors will increasingly be able to tailor treatment to a specific individual. Microarrays are one tool that can be used to study the molecular profile of a specific tumor.
Cold Spring Harbor Laboratory
This is some microarray data from a series of patients with sporadic breast tumors. Each row is an individual tumor and each column is a gene within this tumor.
The investigators in this particular study examined a microarray of about 25,000 independent genes and then selected a subset of these genes based on their ability to essentially classify the patients based on the probability with which the tumor will progress or metastasize.
Red designates genes that have gone up relative to the reference standard, whereas green designates a gene that has gone down and the relative intensity of that color suggests the magnitude.
One thing that you can see quite clearly is that despite the fact that all of these are cancers derived from patients with a very similar pathology, node negative breast cancer, the gene expression patterns just based on the intensity of the red and green are quite different.
Based on this set of genes one can see big differences between the molecular pattern of these tumors and as these investigators noted, this correlates with the probability with which the disease will progress, within five year of being diagnosed. Why is this important? Clearly it shows that despite the fact that these patients have similar pathologies they're molecularly very different.
This information in the future could allow oncologist to decide whether or not additional therapy, for example chemotherapy, would be required. In the case of those patients that had the good prognostic gene expression pattern, would perhaps not require chemotherapy in addition to surgery and therefore they would be spared the devastating side effects of that therapy.
By understanding the nature of some of the genes that go up in these poor prognosis tumors it might be ultimately possible to design drugs that would specifically target these genes and then treat those cancers in a more rational way.