Personalized Medicine

Pharmacogenomics

  • Fig. 1: TPMT, thiopurine methyltransferase is the enzyme that metabolizes the drug mercaptopurine to an inactive metabolite. An inherited polymorphism in TPMT (TPMT*3A) decreases the metabolic activity of the enzyme. Therefore the polymorphism predisposes a leukemia patient treated with mercaptopurine, to experience increased cytotoxicity due to the enzyme’s inability to metabolize the drug.
  • Ogechi N. Ikediobi PharmD, PhD, Assistant Clinical Professor of Pharmacy, University of California

The goal of personalized medicine is to utilize an individual's genetic makeup for appropriate disease diagnosis and treatment. That goal has been made more possible with the completion of the Human Genome Project. The advances in human genetics has led to the creation of startup companies offering consumers and clinicians a DNA testing service for the purpose of assessing treatment outcome and disease risk. Some of those tests, especially those related to treatment outcome are of clinical value. However at this stage, the tests of disease risk offer a false sense of scientific progress and ought to be more regulated. As we are still in the discovery phase of personalized medicine, it is important that the commercial aspects of this endeavor be touted as such. Ultimately, education of the next generation of health care providers will provide a base of individuals equipped to assess the validity and usefulness of these genomic tests in the clinic.

Treatment Outcome


Using the individual's genome to predict treatment outcome is a reality in the field of oncology. Indeed many of the first examples of utilizing genetic information to predict a patient's response to therapy were elucidated with anti-cancer drugs [1]. The examples can be divided into two: firstly, the influence of inherited ­genetic variation on drug response and secondly, the influence of somatic (tumor) genetic variation on drug response. One of the first notable examples was the elucidation that inherited variation in the gene TPMT that metabolized the drug mercaptopurine was responsible for the severe toxicity (myelosuppression, increased risk of secondary cancers) experienced by a subgroup of acute lymphoblastic leukemia patients treated with the drug (fig. 1). That observation led to an FDA approved genetic test for TPMT. Another example involves inherited variation in the promoter of the gene UGT1A1, responsible for the ­metabolism of the active metabolite of the drug irinotecan. Irinotecan is used to treat patients with colorectal cancer. However, a subgroup of patients experience severe neutropenia and life-threatening diarrhea after receiving standard doses of irinotecan.

It was found that variation in the gene, UGT1A1, could for the most part predict those who may experience those severe side effects. Therefore, there is now an FDA approved genetic test for UGT1A1 that is used prior to the initiation of irinotecan therapy in patients with metastatic colorectal cancer [1].

In the past decade, there has been a paradigm shift in the classification of cancers and that led to changes in the development of anti-cancer drugs. The shift involved the elucidation of key signaling proteins, namely kinases, mutated in cancer cells but unaltered in the normal cell. Those mutant kinases were then used as a starting point from which to design drugs that preferentially target the ­altered proteins present in the tumor with less harm to normal cells. That led to the design of biologics such as trastuzumab, a monoclonal antibody, designed to inhibit the action of overexpressed ERBB2 (HER-2) protein in metastatic breast cancer. In fact, trastuzumab ­became the first biologic agent that had a genetic test accompany its use. Following on, more such biologics and small molecule inhibitors of kinases have been developed and are in clinical use. For example, the use of imatinib, a small molecule inhibitor of BCR-ABL for the treatment of chronic myeloid leukemia, the use of cetuximab a monoclonal antibody against EGFR in the treatment of colorectal cancer, and the use of gefitinib and erlotinib, small molecular inhibitors against EGFR in the treatment of lung cancer [1].

Disease Risk

Personalized medicine is the idea that knowledge of one's genome will aid in improving individual disease risk assessment, diagnosis, and ultimately treatment. The idea was touted as one of the fruits of the human genome project. Eight years later, we are closer to understanding which genes or combinations of genes and their variants may confer risk of common complex diseases such as diabetes and cancer [2, 3]. However, as is the case with any scientific endeavor, the studies need replication in multiple ethnic groups in order for a truly ‘representative' genetic test to be used to predict disease risk. On the other hand, however, the public's perception of scientific progress in personalized medicine is skewed by the rapid emergence of DNA testing companies. The San Francisco Bay Area is rife with many, most notably 23&Me and Navigenics, advertising directly to consumers the ease with which one can submit a DNA sample (cheek swab, saliva) and for now less than US-$ 500 get results of their risk for up to 92 diseases [4, 5]. But what is the accuracy of these disease risk assessments? That sentiment was echoed earlier this year when the states of California and New York temporarily suspended the sales of such tests due to fears surrounding the accuracy of the tests and their results [6]. Of course, one may think that doing such tests of disease risk is as mild as genetic ancestry as is purported by 23andMe (Navigenics actually employs genetic counselors to interpret disease risk). But the contrary is the case. Disease risk assessment, except for a handful of monogenic disorders, as of yet cannot be deciphered for the majority of people based on looking at a smattering of SNPs across the genome.

Therefore a positive disease risk assessment as determined from a 23&Me test may cause psychological harm to an individual, especially when counseling about such information is not offered by DNA testing companies. In the case where the individual with a positive disease risk seeks counseling from their physician, who did not order such test and is unaware of its interpretation, is it the responsibility of the physician to ­explain what the test ­results mean? It is a fact that in the U.S. most practicing health care professionals were not trained in ­genomics or interpretation of genomic tests. Therefore, it is highly unlikely that one's physician will be able to provide ­adequate counseling or interpretation of such test results. The more likely event is that the next generation of health care professionals, who will be more familiar with such tests, will be better equipped to assess the utility of such genomic tests in the clinic. In the meantime, the issues surrounding the accuracy of such tests and the role of DNA testing companies will need to be fleshed out.

Discussion

It is clear that advances have been made in the field of personalized medicine as pertains to pharmacologic treatment and disease risk assessment; more so in the former. However, much still remains to be done. It is important that as scientific discoveries are made, they not be so quickly adapted into the commercial sector without rigorous validation and replication to ensure the accuracy of such ­genetic factors as predictors of disease or treatment outcome. It is true that even with FDA approved genetic tests that predict toxicity to drugs such as irinotecan, much still has to be done to ­adequately assess all genetic variants in the gene, UGT1A1 that correlate with toxicity to irinotecan; at present, only one ­locus of the promoter is assessed from which to predict therapeutic outcome. At the same time, it is an exciting time in the field because as the technological ­advances of whole genome ­sequencing become a reality, it will make it much easier and less costly, perhaps, to perform more complete studies of association between genotypes and phenotypes in health and disease. As a corollary, we must be cognizant of the fact that disease risk and indeed treatment outcome cannot solely be predicted by genetics but that the environment also plays a role in modifying phenotypes.

References
[1] Ikediobi O.N.: Pharmacogenomics J 8, 305-314 (2008)
[2] Scott L.J. et al.: Science 316, 1341-1345 (2007)
[3] Gudmundsson J. et al.: Nat Genet 40, 281-283 (2008)
[4] 23andMe Website. www.23andme.com/. Accessed December 7, 2008
[5] Navigenics Website. www.navigenics.com/. Accessed December 7, 2008
[6] Ikediobi O.N.: Pharmacogenomics J, Epub ahead of print (2008)

Authors

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