New method may allow personalised clinical trials for cancer therapies
Combining new techniques researchers observed that a targeted drug affects even genetically identical cells differently
- Date : 20 Aug 2012
- Topic : Personalised medicine
A new tool to observe cell behaviour has revealed surprising clues about how cancer cells respond to therapy and may offer a way to further refine personalised cancer treatments. The approach, developed by investigators at Vanderbilt-Ingram Cancer Centre, shows that erlotinib – a targeted therapy that acts on an epidermal growth factor receptor mutated in some cancers – doesn't simply kill tumour cells as was previously assumed. The drug also causes some tumour cells to go into a non-dividing (quiescent) state or to slow down their rate of division. This variability in cell response to the drug may be involved in cancer recurrence and drug resistance, the authors suggest.
The new tool, reported August 12 in Nature Methods, may offer ways to improve personalised cancer therapy by predicting tumour response and testing combinations of targeted therapies in an individual patient's tumour. In the personalised approach to cancer treatment, a patient's tumour is analysed for a set of mutations to which there are matching drugs that act on those mutations. According to senior author of the article Dr Vito Quaranta, professor of cancer biology, this approach has worked rather well for many cancers that carry specific mutations.
The prevailing view has been that targeted therapies kill all the cells harbouring a particular mutation. But even if the tumour is composed entirely of genetically identical cells, which is unlikely, a drug will not affect all cells the same way. Some of these cells may die, some may just stop dividing, and some may keep dividing, but more slowly. However, no current tests can provide an accurate, detailed picture of cell behaviour needed to understand tumour response to drugs.
Combination of powerful automated, time-lapse microscopy with analytical tools and software
The investigators led by first author Darren Tyson, PhD, research assistant and professor of cancer biology, combined powerful automated, time-lapse microscopy with analytical tools and software they developed. Using these techniques, they could capture the behaviour of lung cancer cells every six to 10 minutes for up to 10 days. As they expected, the targeted therapy by erlotinib killed some cells, while others became quiescent. They observed that the drug even affected genetically identical cells differently. In these clearly genetically identical cells, they get completely different responses. This suggests that there are other things besides genetics that have to be taken into account.
What those other factors are remains unclear, but the investigators are conducting follow- up experiments to determine what might underlie this differential response. And presumably, it is those (quiescent) cells that ultimately result in tumour recurrence.
Quaranta and colleagues hope to take the technology into small clinical trials to test whether it can predict a patient's response to therapy. They hope that they might be able to forecast what the response is going to be. Their method could tell oncologists how long a patient's tumour will respond to a given therapy before it recurs. Such information could also help determine which patients will require more aggressive treatment and researchers believe the assay will be able to test combinations of drugs on a patient's tumour cells to find the right combination to induce a response. They are hoping that this assay – or some implementation of this assay – will eventually work like a personalised clinical trial.
Graduate student Peter Frick and data analyst Shawn Garbett were co-authors on the paper. The research was supported by a grant from the USA National Institutes of Health/ National Cancer Institute Integrative Cancer Biology Program (CA113007).
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