'We are in a new era of the life sciences, but in no area of research is the promise greater than in personalised medicine', said Barack Obama, as a Senator introducing the bill that became the Genomics and Personalized Medicine Act 2007.
The soaring promises made by personalised medicine advocates are probably loftier than in any other medical or scientific realm today. Francis Collins, former co-director of the Human Genome Project, wrote: 'We are on the leading edge of a true revolution in medicine, one that promises to transform the traditional "one size fits all" approach into a much more powerful strategy' (1).
Certainly vast sums are pouring into personalised medicine - plans to spend $416 million on a four-year plan were announced in December 2011 by the US National Institutes of Health, and private sector interest is also intense. But does the science bear out the claim that there's a genuine paradigm shift toward personalised genetic medicine?
That's the question I ask in my forthcoming book 'Me Medicine vs. We Medicine: Reclaiming Biotechnology for the Common Good (to be published in May 2013, Columbia University Press). After offering an evidence-based reality check for 'Me Medicine', I argue that we need to look not only to the science, but also the economics and politics of personalised medicine if we want to understand its much-touted appeal.
As of March 2012, genetic tests and molecular diagnostics only applied to about 2 percent (%) of the US population (2). A Harris poll of 2,760 patients and physicians in early 2012 indicated that doctors had only recommended personal genetic tests for 4% of their patients: hardly the stuff of a paradigm shift - at least not yet.
The most recent policy update from the American Society of Clinical Oncology accepts that genetic testing for personal cancer susceptibility is now a routine part of clinical care, especially for high-penetrance mutations such as the BRCA1 and BRCA2 genes that are implicated in some breast and ovarian cancers. However, the Society also notes that such cancers are comparatively rare, and that there is little clinical value in testing for the many relatively common single nucleotide polymorphisms (SNPs) associated with cancer as the risk from each individual SNP is too small for clinical decision-making.
In pharmacogenetics, clinical genetic typing is used to determine a patient's probable response to drugs, such as cancer treatments, to tailor the pharmaceutical regime. It might be possible, for example, to identify patients who are genetically programmed to respond more quickly to chemotherapy and to give them lighter dosages, to avoid the worst side effects. In oncology, there is the additional goal of adjusting the treatment to the genome of the cancer, which differs from the patient's normal cells. This dual approach is crucial because cancer is so heterogeneous, even in patients with the same diagnosis.
After sequencing the genomes of breast cancers from fifty patients, researchers found only 10% of the tumours had more than three mutations in common (3). A genome-wide analysis of kidney tumours from four patients showed a single tumour can have many different genetic mutations at various locations, two-thirds of which were not repeated in the same tumour (4). A pharmacogenetic drug that targets one mutation in a tumour may therefore not work on others.
The former head of the American Society of Clinical Oncology, George Sledge, declared that the only cancers that have been outwitted so far by pharmacogenetics are the 'stupid' ones, namely the minority of cancers caused by mutations in only one or two genes. 'One danger of stupid cancer is that it makes us feel smarter than we are', Sledge concedes ruefully (5). That overconfidence is obvious in many of the more exaggerated paeans to personalised medicine.
If the scientific evidence alone fails to bear out the bigger claims for personalised medicine, why is there such great interest? We need to look to social and economic factors as well as scientific ones. For a pharmaceutical industry facing the expiry of patent protection on many of its best-selling blockbuster drugs, new markets have to be found. By breaking an existing medication down into different 'size ranges', and by persuading customers that they cannot simply rely on a 'one-size-fits-all product', pharmaceutical companies can create new niche markets.
It would be even more advantageous for the pharmaceutical industry if individual patients could be persuaded to pay for genetic typing out of their own pockets to find out which of the niche pharmaceuticals best fits them. Now that the $1000 whole-genome test has become a reality, direct-to-consumer genetic testing may well extend its reach from subsets of SNPs to whole-genome mapping. Diagnostic costs could be transferred from the public health system or insurers to the individual, leaving some excluded from insurance coverage on the basis of their genetic profile.
The largely ignored economic reality of personalised genetic medicine is that the more personalised it becomes, the narrower the range of customers grows, and therefore the less incentive there is for pharmaceutical companies to produce drugs that smaller-sized patient groups may require. Alternatively, personalised cancer drugs may shoot up in price. Oral anti-tumour drugs, including Gleevec, have gone up by over 76% since 2006 (6). The drug Xalkori, developed for a small group of lung cancer patients carrying a particular mutation, costs $9,600 per month (6) - a high price driven by the small potential market of fewer than 10,000 patients (7). How likely is it that US insurers or the UK's NICE (National Institute for Health and Clinical Excellence) will pay out such a price?
Patients' enthusiasm for pharmacogenetics would take quite a dent if they saw it as a rationale for denying them therapy, but in an era of cost-cutting, that could well be the shape of things to come. Personalised medicine pushes all the right buttons in our psyches; the ones marked 'choice' and 'autonomy'. But we should be careful what we wish for.
Sources and References
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4) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing
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1) The language of life: DNA and the revolution in personalized medicine
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3) Fifty genomes sequences reveal breast cancer’s complexity
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5) Cancer's New Era Of Promise And Chaos
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6) Personalized medicine in oncology: next generation
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7) Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer
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2) Personalized medicine: Trends and prospects for the new science of genetic testing and molecular diagnostics
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