The authors questioned whether the human genome contributes to disease risk prediction and concluded, based on 1 study, that genomic risk information does not improve patient outcomes. They did not discuss genes that predict risk for colon and other cancers, coronary artery disease, or neurodevelopmental conditions.
The authors did discuss breast cancer; however, their statement that the discovery of BRCA1 has not led to new targets ignores the field of synthetic lethality in breast and ovarian cancer,2 such as BRCA mutations and poly (adenosine diphosphate ribose) polymerase inhibitors. Improved prediction and diagnosis of diseases is prerequisite to better therapy.
Joyner and Paneth also asked whether gene-based drug targeting improves outcome and concluded that it has done little to help patients. They failed to discuss specific molecularly targeted drugs, such as imatinib and erlotinib, which have led to long-term survival in patients with chronic myeloid leukemia, or crizotinib, which has led to long-term remission of lung cancer in patients with mutations of epidermal growth factor receptor or EML4_ALK fusion gene.3
Further advances in molecular biology–based immunotherapy and combination therapies resulted in a complete remission rate of 22% in patients with metastatic melanoma.4 Precision medicine has been successfully used across a wide spectrum of illnesses, including gene therapy in patients with hemophilia and Leber congenital amaurosis.3
In addition, the authors cited tamoxifen and warfarin studies as examples of pharmacogenomics with negative findings and omitted successful applications of pharmacogenomics, such as with thiopurines.5
Joyner and Paneth argued that current approaches ignore the patient as a whole. We submit that an individual’s phenotype and genomics give physicians added tools to individualize therapy. Although each “tool” needs to be clinically effective, it is only when the entire contents of the clinical “toolbox” are used that a patient can be treated as a whole.
We agree that caution is prudent for any new field or technology, but to state that personalized medicine will have minimal effect on public health ignores promising data that are being generated through basic science and clinical studies.