Personalized Medicine for Breast Cancer
Personalized Medicine is a rapidly advancing field of health care that emphasizes the tailoring of all treatments and interventions to a specific individual. One of the first areas that the concept of personalized medicine has been applied to is breast cancer. Breast cancer is a widespread disease, that can currently be treated with several different drugs. However, until recently, there was no way to determine which drug worked best for an individual cancer patient. Now several tests based on genetics and proteomics have reached the market. These tests, particularly proteomic based tests, can predict which drugs will work for an individual with a high degree of accuracy. As new technologies emerge and mature, oncologists will be able to prescribe treatments specific to an individual, resulting in better effectiveness and avoiding wasted time, and undo side effects. Being able to pinpoint effective treatments will also result in substantial cost savings.
Cancer is a highly individualized disease The American Cancer Society estimates that close to 1.5 million people are diagnosed with cancer annually in the U.S. and more than 550,000 die as a result of the disease. In 2009, the National Institutes of Health estimated the 2008 direct medical costs (total of all health expenditures) were $93.2 billion with the total cost (including lost productivity due to illness and death) of $228.1 billion. These costs are growing, driven by increases in early detection and an aging population.
Since every tumor has distinct characteristics, targeted drug treatment is the preferred approach. Effective treatment relies on selecting a specific drug that targets a patient’s unique tumor(s). Unfortunately, there are often significant side effects, as well as costs that can exceed $30,000 per year for one patient. The need for multiple target identification is critical. It is no longer sufficient to merely identify a person who may or may not have cancer. Now, the challenge is to develop individualized treatment regimens that will effectively treat that patient’s disease.
Anticancer drugs are approved by FDA on the basis of the clinical trial results from a population of cancer patients. A 20-30% response rate may win a drug regimen FDA approval. These population-based results cannot be applied directly to individual patients because cancer is a highly individualized disease.
Currently, there is no standard procedure for optimal chemotherapy treatment selection.
A number of commercialized prognostic and predictive tests based on the genomic classification of breast cancer have entered the expanding market for diagnostics. Tests based on immunohistochemistry (IHC) and Fluorescent in situ Hybridization (Fish) currently dominate the breast cancer diagnostic testing landscape. In this context, these two techniques are most often used to evaluate HER-2 or hormone-receptor status. Evaluations of test results allow clinicians to accurately select patients likely to benefit from the corresponding therapy. This market is currently dominated by large, established companies offering FDA approved products.
More recently, a number of commercialized prognostic and predictive tests based on the genomic classification of breast cancer have entered the expanding market for diagnostics. Genomic assays examine the expression of a unique set of genes that may indicate the recurrence of cancer or potential response to treatment. These assays are currently used primarily to predict recurrence of breast cancer and are being extended to indications of hormonal and HER-2 receptor status. Competition in this segment is based on introduction of assays using different and more numerous gene sets.
The leaders in the current genomic market are Genomic Health, which offers the Oncotype Dx assay and Agendia, which offers the Mammaprint assay. These tests analyze gene expression and are currently geared towards predicting the recurrence of breast cancer. Although genomics are a promising technology, certain limitations exist. These assays are, in general, applicable to only a subset of cancer patients and are far from being standardized. They demonstrate significant variability and, since tissue is homogenized for this type of analysis, all sense of tissue topography and heterogeneity are lost. Interpretation of gene based assays may also prove to be difficult. A single gene can produce a variety of different proteins, indicating the potential of a given cancer cell.
Personalized Medicine for Breast Cancer