Getting to the heart of anthracyclines
Certain genetic differences could predispose patients to the side effects of some chemotherapy drugs.
Many cancers, including leukaemia, lymphoma and breast cancer, are treated with potent chemotherapy drugs such as anthracyclines. However, anthracyclines have strong side effects known as anthracycline cardiotoxicity, which affect the health of the heart. Almost half of the patients given high doses of anthracyclines develop chronic heart failure.
While anthracycline cardiotoxicity is very common, people’s genes may contribute to how sensitive they are to these drugs but it is not understood which genes can cause this effect. Previous studies using only a small number of participants have not been able to pin down the genetic factors that make some patients respond well to anthracyclines, and others prone to developing heart failure when taking these drugs.
To find out which genes affect anthracycline cardiotoxicity, Knowles, Burrows et al. transformed blood cells from 45 individuals into stem cells, which were then developed into heart muscle cells. Then, the activity of genes was analyzed by measuring the amount of RNA (the template molecules used to make proteins) produced by those genes.
After the cells had been exposed for 24 hours to the anthracycline drug doxorubicin, hundreds of gene activity differences could be found in the heart muscle cells between individuals. Some of these differences were linked to poorer health of the cells after treatment with the drug. As a result, a number of genetic variants that could predispose patients to the side effects of doxorubicin were discovered. The experiments also revealed how doxorubicin disrupts an important process that separates ‘junk’ parts of the RNA from the parts that are used as a template for proteins.
Being able to predict who is likely to be sensitive to drugs such as doxorubicin could help doctors to tailor chemotherapy treatments more effectively, minimising the risk of heart failure. In future, larger studies could lead to accurate predictions of a patient’s response to a particular chemotherapy drug to personalize their cancer treatment.
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