The Age of Personalised Medicine
Back in 2003, an extraordinary step for medicine and long awaited scientific feat was accomplished. Scientists had drawn up a complete road map of the human genome. The Human Genome Project, which took 14 years to complete, delivered a genetic blueprint for the 20,000 genes contained within the DNA code, giving scientists unprecedented insight into its complexity.
Over the last decade, several international projects have been launched to sequence and compare thousands of human genomes, spanning multiple ethnic and geographical populations. This technology fast-tracked the detection of genes, or more often, sets of genes, that are associated with disease traits.
Common genetic variants (known as polymorphisms) that could have a range of impacts on gene function, from none to major, were identified in individuals and whole populations at variable frequencies. This finding in particular represented a game changer for medicine, in that a person’s DNA might be used to identify biomarkers that could predict disease course, and subsequently guide treatment according to that patient’s genetic make-up.
In recent times, the concept that this genetic roadmap can be harnessed to personalise medicine to an individual is becoming realised, and there is a major effort underway in medical research to translate this to the clinic (National Health and Medical Research Council 2011).
For instance, cancer is a complex disease that is largely determined by genetic mutations, which can be inherited (‘germline mutation’), or arise sporadically (‘somatic mutation’). Different genetic mutations may be responsible for the same anatomical cancer, but genetic testing (based on DNA sequencing) can group these tumours into sub-types based on the exclusivity of gene variants to that tumour. For example, breast cancer is not a single entity, but exists in multiple forms depending on the gene/s and corresponding cell types that are disrupted. As such, prognostic genomic testing is available to characterise breast tumours into sub-types according to their genomic signature (Dai et al. 2015).
Pharmacogenetics is Born
Based on genetic testing, pharmacogenetics specifically targets a medicine to a disease sub-type. The utility of personalised medicine to treat common cancers has been particularly promising in lung, melanoma, breast, thyroid and colorectal cancers, which are each driven by differing and multiple gene variants.
Pharmacogenetics is further used as a tool to predict patient sensitivity to a medicine. Common genetic variants present in drug metabolising enzymes can significantly impact the level of enzyme function. This results in highly mixed responses to medicines based on that individual’s ability to break down and activate the given medication.
An example is tamoxifen treatment of oestrogen-positive breast cancers, in which response amongst women is variable. This may be explained by the presence of genetic variants in the metabolic enzyme, P450 2D6. Thus tamoxifen may be more or less effective based on the P450 2D6 genetic variant found in that patient. Another example is the use of the anti-coagulant warfarin to prevent blood clotting. Genetic testing for common variants in two genes, CYP2C9 and VKORC1, may predict response to warfarin and hence could be used to administer the optimal dose. This would lower the risk of thrombosis but also reduce unwanted side-effects such as bleeding. Currently, the overall benefit of such genetic testing for both medicines is under scrutiny (Bardia & Stearns 2010; Lee & Klein 2013); however, it is highly likely that this type of analysis will become the future norm for determining sensitivity to a range of medicines.
Personalised Medicine in the Clinic
Personalised medicine has utility in treating both genetic and non-genetic disorders, whereby clinical genetic testing can provide many benefits:
- Screening, diagnostic and prognostic tests for common diseases associated with multiple underlying genetic variants. This includes determining disease risk, predicting the severity of disease, and offering genetics-based informed treatment regimes
- Improved medicine targeting and dose management. This increases the likelihood of achieving an optimal therapeutic outcome and reducing undesirable medicine side-effects. Patients who would not benefit from a medicine are not treated with it
- Predicting severe allergies to specific treatments. Genetic testing is used to establish hypersensitivity to some medications, including Abacavir (HIV drug) and carbamazepine (an anticonvulsant used to treat epilepsy)
- Lowered cost to healthcare due to improved treatment, minimised medication and fewer side effects.
Mapping the human genome has been a huge step forward for medical research but has lain ahead unchartered waters for how to best use this information. The potential however is great, and patients are already benefiting from treatments in which ‘a one-size-fits-all’ system is being fast superseded by tailored approaches to patient care.
- Bardia, A & Stearns, V 2010, ‘Personalized Tamoxifen: A Step Closer But Miles To Go’, Clinical Cancer Research, vol. 16, no. 17, pp. 4308-10, viewed 14 November 2016, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980759/
- Dai, X, Li, T, Bai, Z, Yang, Y, Liu, X, Zhan, J & Shi, B 2015, ‘Breast Cancer Intrinsic Subtype Classification, Clinical Use and Future Trends’, American Journal of Cancer Research,, vol. 5, no. 10, pp. 2929-43, viewed 14 November 2016, https://www.ncbi.nlm.nih.gov/pubmed/26693050
- Lee, MT & Klein, TE 2013, ‘Pharmacogenetics of Warfarin: Challenges and Opportunities’, Journal of Human Genetics, vol. 58, no. 5, pp. 334-8, viewed 14 November 2016, https://www.ncbi.nlm.nih.gov/pubmed/23657428
- National Health and Medical Research Council 2011, Clinical Utility of Personalised Medicine, NHMRC, Australian Government, Canberra, ACT, viewed 14 November 2016, https://www.nhmrc.gov.au/…medicine_feb_2011.pdf