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Category Archives: genome sequencing
[Originally posted on Occam’s Corner at Guardian Science, in February 2014]
In the 2000 M Night Shyamalan film Unbreakable, Samuel L Jackson’s character – a man born with a severe form of brittle bone disease – asks Bruce Willis’s character, ‘if there is someone like me in the world, and I am at one end of the spectrum, couldn’t there be someone else, the opposite of me at the other end? Someone who doesn’t get sick, who doesn’t get hurt like the rest of us?’ Some cancer researchers are trying to answer the same question; however, in real life, it’s just not that easy to unmask a superhero
In June 2013, I described how sequencing the highly abnormal genomes of cancer cells can identify some of the mutations that drive the progress of the disease (and how that’s only the beginning of the story). In the discussion that ensued, reader BlueSky3 commented:
Hope more likely rests in examining the control systems/defence mechanisms of those carrying a hereditary cancer fault which has perhaps persisted in evolutionary time. Not all mutation carriers succumb. Why not?
This comment was so interesting that it’s been percolating at the back of my brain for months. We know that women who inherit a faulty copy of the BRCA1 or BRCA2 gene have a highly elevated risk of developing breast or ovarian cancer – but cancer is not an inevitability. We also know that smokers have a highly elevated risk of developing lung, throat, or oral cancer – but some of them don’t. Why?
The answer lies in the complexity of cancer. The first mutation that starts the first abnormal cell down its path to malignancy can be caused by any number of factors: genetic predisposition, radiation, chemical agents, viruses. Similarly, any number of factors can influence the direction the disease travels thereafter. The first mutated cell has to escape everything the body can throw at it – DNA repair, the shutdown of cell division, programmed cell death, the immune system – before it can become truly dangerous. This complexity creates a number of possible points of intervention. Many, especially those related to the health of the immune system, are at least partially related to lifestyle factors, but in this article I’m going to focus on natural-born superheroes only – that is, those who inherit genetic factors that protect them from cancer.
The suggestion to study people with known cancer predisposition mutations who don’t go on to develop cancer is a great one, but not an easy one. If someone is unaware they have such a mutation, and they remain healthy, doctors and researchers have no way to identify them as a subject of interest. Additionally, many people who do know they have such a mutation can now take preventive measures (such as Angelina Jolie’s recent pre-emptive double mastectomy upon learning her BRCA gene mutation status), and we have no way of knowing whether they would have gone on to develop cancer if these measures had not been taken. All this adds up to a very small sample size to study, which makes the identification of subtle genetic correlations extremely difficult. It is possible, however, to search for “superhero” genes among the much larger general population, and to relate some of the findings back to more specialised populations such as those with inherited mutations in BRCA and other cancer susceptibility genes.
Many years ago, I attended a seminar by local researcher Michael Hayden about using very rare genetic disorders on one end of a spectrum to find new ways to fight very common disorders at the other end of the same spectrum. For instance, Hayden learned of a family with an inherited inability to feel pain, and was able to identify the faulty protein responsible; his lab recently published the results of a preliminary trial of a drug that targets the same protein in people without the disorder, and that may represent an entirely new class of painkillers.)
Unfortunately, finding people with genetic protection from cancer isn’t this straightforward. A person with no ability to feel pain will come to the attention of the medical profession early in life, when they walk for a week on a broken bone or show some other outward sign of their mutation. However, someone with an unusual degree of genetic protection from cancer is unlikely to present in the same way, making it harder to identify the relevant gene variants and to extrapolate from this knowledge to find a way to help prevent cancer in others.
Scientists are a resourceful bunch, though, and we’re starting to make progress despite these limitations. One approach is to look for protective gene variants in the general population, by comparing the gene sequences of people with cancer to those of healthy controls of comparable age and with similar risk factors. For example, in 2004 Angela Cox’s group at the University of Sheffield looked for correlations between breast cancer and the sequences of genes involved in programmed cell death. (This process, also known as apoptosis, is one of the body’s defence mechanisms that a cancer cell must evade if it is to go on to form a tumour. Apoptosis can be triggered by a number of different signalling pathways, each with multiple components; see the diagram for part of the picture.)
Cox’s team found that women who’d inherited a variant called D302H in the apoptosis-related CASP8 gene were less likely to develop breast cancer. This variant has since been shown to correlate with a reduced risk of prostate and other cancers, and in 2010 the Group for Assessment of Hereditary Cancer of Valencia Community reported that “CASP8 D302H polymorphism delays the age of onset of breast cancer in BRCA1 and BRCA2 carriers” – making its carriers not unbreakable, but definitely less fragile than the rest of us.
Like so many others, recent technology advances mean that this field of research is now dominated by large-scale whole-genome studies. In 2013, a major European cancer genetics consortium called COGS(Collaborative Oncological Gene-environment Study) published a series of papers describing the results of a massive genome-wide association study of 100,000 cancer patients and 100,000 healthy controls. The study was designed to identify genetic variants that affect the risk of developing hormonally mediated (ie breast, ovarian and prostate) cancers. As expected, most genetic variants were found to increase the risk of cancer, but a few protective variants were also identified. For example, a variant in a component of the telomerase enzyme, which repairs the protective cap structures at the end of chromosomes, correlated with longer caps and reduced risk of some forms of breast cancer, including BRCA-related breast cancer.
The power of whole genome sequencing is also being applied to the study of people of advanced age who’ve avoided the most common causes of death, including cancer. There are a number of “super-ager” studies of this kind under way, including one at my organisation (I’m not involved with the project in any way, but I hear about it in meetings and in conversations at the pub after work). Dr Angela Brooks-Wilson leads the study, which involves sequencing the genomes of people aged 85 or older who are in good health, and who’ve never been diagnosed with cancer, heart disease, stroke, pulmonary disease, diabetes, or Alzheimer’s disease. It’s early days still, but hopes are high.
Back in June, reader BlueSky3 continued:
We are spending millions on dissecting the ‘cancer genome’ in minute detail and on genome wide association studies, shame a bit of the research money cannot be diverted to genetically dissecting the differences between mutation carriers living into their nineties and their less fortunate relatives who succumb to cancer in their thirties
I hope this article has demonstrated that we are in fact making some progress in this direction. We haven’t found our superhero, and I have no last-minute plot twist up my sleeve – but labs full of everyday heroes are on the case, and this story is bound to have many sequels over the years.
[Originally posted on Occam’s Corner at Guardian Science, in June 2013]
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.