Personalized Medicine in Oncology: Ethical Implications for the Delivery of Healthcare

Nathalie Egalite; Iris Jaitovich Groisman; Beatrice Godard


Personalized Medicine. 2014;11(7):659-668. 

In This Article

Personalized Medicine & its Benefits on Cancer Treatment

Several approaches have been used over the years in the quest for treating cancer, including surgery, radiation and an array of pharmacological treatments. The application of chemotherapy protocols has been widely used, showing, in many cases, equally poor treatment responses and patient quality of life, with the latter being due to the medications' secondary effects.[1] There are uneven results when applying similar therapies for different and related types of tumors, showing that cancer treatments seem to be particularly suited to a more personalized approach.

There is a history of stratified and even personalized management of cancer found in the ways that cancers have been classified based on type, stage and tumor subtype.[2] Current personalized management denotes a variety of methods comprising the identification of cancer risk in a population, testing of biomarkers in order to identify proper therapy (targeted therapy), recognizing the genes linked to drug response (pharmacogenetics/genomics) and analyzing tissues in order to detect recurrence before developing physical symptomatology. The molecular characterization of a tumor in order to select the most appropriate therapy together with a pharmacogenomic analysis denotes that thinking of the patient from a genome-based perspective has long been taking place.

The evolution of personalized cancer treatment could be exemplified by the management of newly diagnosed patients with chronic myeloid leukemia. The treatment has moved from the general approach using hydroxyurea, IFN-α or allogeneic stem cell transplantation to highly targeted therapies with tyrosine kinase inhibitors (TKIs).[3] Interestingly, while imatinib is the first TKI therapy for chronic myeloid leukemia, approximately 20% of patients do not respond to this treatment, probably due to more 'personal' (individual) mutations in the BCR-ABL oncogene, which are currently driving the evolution of second-line TKI therapy.[3]

Meyer et al. defined personalized medicine as a "comprehensive, prospective approach to prevent, diagnose, and treat disease by using each person's unique clinical, genetic, genomic, and environmental information".[4] Some examples of current pharmacological personalized medicine therapies in oncology clinical practice in North America are the use of trastuzumab (breast cancer), imatinib (chronic myeloid leukemia), panitumumab (colorectal cancer), vemurafenib (malignant melanoma) and crizotinib (large-cell lymphoma and non-small-cell lung cancer).[5,6] These and similar therapies based on determining the patient's molecular and genetic cancer markers help to provide refined treatment decisions for those affected with life-threatening conditions. The characterization of patients' molecular and genetic disease profiles is achieved with 'companion diagnostic tests', which are categorized as prognostic, predictive or both.[5,7] These tests comprise technologies that identify changes in DNA and RNA, epigenetic modifications, altered signaling pathways and protein and metabolic tumor biomarkers. Their use requires evaluation, quality control, standardization and approval from health regulatory organizations.[7] Assessments leading to treatment selection that have been of predictive potential for specific patients[3] when accurate and standardized "allow for proper classification of patients"[5] and for disease management geared towards personalization.

Increased recognition of the benefits of selecting personalized tests and treatments in order to improve health outcomes has been underscored by the development of professional guidelines and recommendations. Such recommendations, which not only guide clinical decision-making, but also impact treatment reimbursement decisions,[5,8] remain necessary for the seamless integration of personalized medicine into cancer care. Examples of recommendations for specific tests and associated treatments in the USA and Canada nevertheless lag behind the release of new treatments (Table 1). Meanwhile, finding currently unknown genetic variants related to cancer (sub)types and drug responses in affected individuals will lead to more tailored prognostic, diagnostic and treatment approaches; this would improve the determination of the susceptibility to cancer risk, allowing for the detection of recurrence prior to symptomatology and the identification of cancer risk in populations.

The future of oncology will thus be particularly affected by the potential of emerging genomic technologies involving the massive parallelization of DNA sequencing, known as next-generation sequencing (NGS), through which "millions of sequences can be produced at once more efficiently and accurately".[9] Among the NGS approaches used to identify rare genetic penetrant mutations are whole-exome sequencing, whole-genome sequencing and gene expression profiling using disease-targeted panels. Their use in research allows greater DNA sequencing depth of coverage and the detection of low-level genetic heterogeneity. Recent personalized oncology research using NGS technologies includes studies characterizing patient genomes,[10] sequencing tumors[11] and identifying possible candidate genes.[12] NGS is expected to contribute to a deeper knowledge of the already-identified epigenetic causes of cancer[13] and environmental influences, as well as to ascertaining new patient subsets by means of family cohort studies.[14] The awareness of known disease-associated genes translates into a greater ability to interpret findings in a clinical context.[15]

The proliferation of NGS will likely impact on the provision of oncology treatments. A personalized approach to cancer care based on genomic medicine could be considered to be a continuum between the identification of populations (individuals) who are at risk, a more inclusive integration of patients in clinical trials and the implementation of personalized healthcare programs. In order to provide optimal personalized cancer patient care, there is a need for genomic infrastructure that includes a wide range of resources (e.g., storage and handling of data, patient recontact and practitioner education in genomics,[16] including pharmacists who will be increasingly required to interpret pharmacogenomic tests[17]). In addition, cutting-edge oncology treatment brings with it ethical challenges, particularly with regards to informed consent, privacy concerns for patients and their family, the return of clinically significant results and the cost and access to healthcare resources.