This year a total of 1,638,910 new cases of cancer and 577,190 deaths from cancer are projected to occur in the United States.1
Although overall cancer incidence rates have remained relatively stable from 2004 through 2008, cancer death rates have decreased by more than 1.5% per year for both men and women. Most patients with cancer receive treatment based on results from studies performed on hundreds, if not thousands, of similar patients, but not based on the genetics or biology of individuals or their disease.1
However, cancer is clearly a heterogeneous disease whose presentation and response are likely determined by the patient's underlying genetics or biology. The past decade has witnessed unprecedented discovery and development of prognostic and predictive biomarkers that now offer an opportunity to stratify patients for risk of progression, to direct treatments to those most likely to respond, and to reduce unnecessary treatment toxicities caused by ineffective treatments that are not going to be associated with improved outcome.2
Thus, truly personalized oncology medicine is now considered a realistic approach for helping patients with cancer.3,4
This strategy has been enhanced by investment in projects such as The Cancer Genome Atlas (TGCA),5
which take advantage of high-throughput sequencing of specific genes in human tumors, in genome-wide surveys of chromosomal abnormalities, and in the development of gene expression data.5
Genome-wide data from these types of studies have contributed to the discovery of prognostic and potentially predictive biomarkers and the delineation of pathways that appear to drive the oncogenic phenotype (). Moreover, specific somatic mutations in genes encoding signaling molecules and their respective pathways have led to the development of small molecule antagonists and several targeted therapies aimed at these mutations and pathways (). The molecular heterogeneity of cancer resulting from the acquisition of multiple genetic alterations that contribute to the development of the tumor underlies the heterogeneity of patient outcomes and response to therapy. Thus, it is clear that cancer is not a single disease but rather a collection of diseases with unique characteristics.6,7
Major Pathways Impacted by Somatic Genetic Changes
Three major challenges impede the implementation of these stunning advances in cancer genomics and hinder fundamental changes in clinical practice. First, there is a need to develop validated predictive biomarkers by matching existing therapies with data on individual patient outcomes. Second, there is a critical need to develop strategies linking genomic data to clinical outcomes data such that evidence for test utility can be evaluated systematically. Some of this evidence will be developed in the context of prospective clinical trials that test the hypothesis that biomarker-informed care is superior to the current standard-of-care methods—the highest level of evidence derived from comparative effectiveness research (CER). For ethical reasons or reasons of feasibility, in many situations, this evidence will need to be developed in the context of large observational cohort studies that are rich in genomic data and clinical and patient-reported outcomes measures. In either case, this would mean routinely obtaining tumor tissue by invasive biopsies—a major hurdle for combining genomic data with clinical outcomes data. Finally, there is the challenge of rigorously evaluating evidence consistently across organizations and making recommendations that drive the appropriate adoption of these novel biomarkers into clinical practice guidelines and clinical use.
There is growing optimism about the successful application of genomic understanding and modern technology so that treatment choices are based on the individual and the biology of their disease and not based on a population. However, without the ability to test hypotheses for clinical and molecular subsets of patients in both clinical trial and real-world settings, oncology will remain a population-based approach and not an individualized one. The current emphasis in CER represents, perhaps paradoxically, an opportunity to catalyze the development of the data that will enable our ability to stratify oncology populations more robustly than before and drive the current cancer practice toward personalized medicine.