lunes, 8 de julio de 2013

The cancer genome in context: of mice and mutations | Cath Ennis | Science |

The cancer genome in context: of mice and mutations | Cath Ennis | Science |

The cancer genome in context: of mice and mutations

Sequencing the genomes of cancer cells lets us identify the mutations that drive the disease and develop drugs that target each mutation. But that's just the start of the story …
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Cancer is caused by changes to the cell's DNA – but there's much more to a cancer cell than just its DNA. Image: Richard Wheeler/Zephyris Cancer is a disease of the genome, initiated by mutations in the genes that usually control cell growth and division.
Scientists started to identify the most common mutations found in the most common cancers back in the 1970s, although the limitations of the technology available at the time meant that progress was slow. Drugs that specifically target some of these mutations are already available and prolonging cancer patients' lives. Now, new technologies such as whole-genome DNA sequencing allow us to identify mutations faster and more cost-effectively than ever before – mutations that are already feeding into the early stages of the drug development pipeline.
The first cancer to have every "letter" of its genome sequenced and every mutation recorded was a leukemia, in a study that was published in the journal Nature in 2008. Genomes of other cancers – lung, breast, melanoma – quickly followed, all also published in top-tier journals and heralded in the media as major breakthroughs. Now, just a few years later, the era of cancer genomics research is well established and single-genome studies are already old hat – it takes much larger studies these days, involving the analysis of dozens of cases, to attract the same kind of attention as the early studies. With the first wave of research behind us, several centres around the world are now starting to study how to incorporate genomics into clinical cancer diagnostics and treatment.
The power and the promise of genomics is that, given enough money, we can start to personalise the treatment given to each patient. For instance, imagine a hypothetical mutation already known to be present in 70% of, say, bone cancers. A targeted drug is developed that works well in that 70% of patients, but does nothing for the other 30%, and whose effects (or lack thereof) take weeks or even months to detect. Sequencing newly diagnosed bone tumours before choosing a treatment lets you give the drug to those who will benefit from it, and find another option for the other 30% without having to put them through weeks or months of futile treatment, complete with nasty side-effects. If you also routinely sequence other types of cancer, you might find that 5% of, say, liver tumours contain the same mutation, and can be successfully treated with a bone cancer drug that might not otherwise be offered to liver cancer patients.
If the history of cancer research and treatment has taught us one thing, however, it's that things are never quite that simple.
Take the example of a mutation called BRAF(V600E), which is found in a number of cancers, including melanoma. A drug called vemurafenib that targets this mutation has been developed and works well against melanoma, a notoriously aggressive and hard-to-treat cancer. However, when the same drug was given to patients whose colon cancers also contained the BRAF(V600E) mutation, it didn't work. This puzzle was solved last year by a team who discovered that colon cancer cells contain high levels of a protein called epidermal growth factor receptor that protects them from the effects of vemurafenib; melanoma cells don't contain much of this protein, which explains the difference in response between these two tumour types.
Chalk this one up as a learning experience for a young field; we now know to look at mutations in the context of the other genes and proteins that are active in the whole cell, not as single entities.
There's a lot of useful information still to be gleaned from cancer genomes, and – no doubt – a lot of other learning experiences in our future. But with lives on the line, can we find a way to learn these lessons sooner rather than later?
One intriguing option is to pair cancer genomics with a technique called xenografting, which involves inserting a small piece of a patient's tumour into a mouse. The idea is that the patient's tumour can be sequenced, promising-looking mutations identified, and candidate drugs (and combinations of drugs) tested against that patient's tumour in a number of "avatar mice". This approach can help doctors choose the right treatment for each patient much faster, and with less risk of subjecting them to potentially futile treatments and side-effects; it can also give us early warning of the kind of interplay between a gene mutation and its cellular context seen in the case of BRAF(V600E). As an added bonus, this kind of study – and it is very much in the early research phase at the moment, not part of standard clinical care – can also feed information and tissue samples back to research labs, to help with their work on drug resistance mechanisms and other aspects of the cancer genome in context.
It's early days for the avatar mouse, a model that is not without its problems. From what I understand of xenografting, it's as much art as science; some tumour types refuse to "take", while others start growing immediately. It's also highly likely that the mix of different cell types within the original human tumour changes during the process of implantation into a mouse, meaning that the transplanted tumour might not respond in the same way as the original. But work is under way, and it is going to teach us a lot.
We will need to explore more than one avenue of investigation to counter the manoeuvres of an ever-evolving enemy. Genomics is a powerful tool that is already helping us to make small advances. Considering the genome in context will take us even further.
Cath Ennis is a grant wrangler and project manager in the field of cancer genomics. She was not involved in any way with the studies linked to in this article, and was not directly involved with any of the studies mentioned in passing, although she works with people who were. Readers with an average-to-high tolerance for science geekery, ice hockey, and Game of Thrones chat are encouraged to follow her on Twitter – @enniscath

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