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Physicians and scientists have recognized for many years that not every patient responds to a given drug in the same way.  Some patients may derive very good therapeutic benefit from a given drug, and others may not.  Similarly, some patients may show severe adverse drug reactions while others experience no side effects. With the tremendous increases in our knowledge of molecular biology, genetics, and genomics in recent years, we are now much better placed to understand the biological reasons for differences in patients’ responses to the same drug, and this is particularly true in the field of oncology.

Imagine a hypothetical scenario in which 10 different genetic variants are involved in the development of cancer. It is possible that a drug already on the market may help patients possessing just one of those variants. The question then becomes: how do we identify patients who should receive the drug?  By taking a tumor biopsy from a patient and looking for the presence or absence of the appropriate genetic biomarker, we may determine which patients should be given the drug, and which ones should not. As real examples, consider crizotinib and vemurafenib, which were approved by the United States Food and Drug Administration (FDA) in 2011 in combination with FDA-approved companion diagnostic tests. Crizotinib is indicated for the treatment of locally advanced or metastatic non–small cell lung carcinoma that is anaplastic lymphoma kinase (ALK)–positive as detected by the associated FDA-approved predictive biomarker test. Vemurafenib, indicated for melanoma, is approved for patients with a certain abnormal variant of the BRAF gene, BRAFV600E, as identified by the associated FDA-approved test. These examples illustrate how cancer genomics has moved into clinical practice.

Now let’s look at this issue from a different but equally important perspective. Imagine a scenario in which a biopharmaceutical company is developing a new oncology drug, and is conducting clinical trials to evaluate whether the drug can provide therapeutic benefit to certain individuals. All previous research had led the company to believe that this drug may provide therapeutic benefit to individuals whose tumor possesses a certain genetic variant. Just as we did in the previous scenario, imagine that there are 10 different variants, and the company believes that the drug will help only individuals with variant A. The most efficient way to determine whether the drug is indeed safe and efficacious is to include only patients with variant A in the clinical trial. If the clinical trial were open to all comers, and only a small and unknown proportion of participants possessed variant A, then even if the drug is highly effective for those with variant A, the aggregated clinical trial results are likely to suggest that the drug is not effective. Moreover, individuals with variants B thru J are unlikely to benefit and may be harmed if treated with the drug.  For these reasons, the trial design should exclude patients with variants B through J.

The question therefore becomes this: when recruiting patients to participate in a clinical trial, how do we ensure that appropriate patients are selected efficiently, even if a relatively rare genetic inclusion criterion must be met? The answer is to pre-profile a large number of patients and create a registry of genetic information such that patients who are genetically appropriate are selected to participate in the trial.

Pre-profiling, which prospectively stratifies patients through genetic screening, provides two significant advantages in the treatment of cancer. First, it provides value to patients and their physicians via access to rapid, broad-based genomic testing of their cancer to see which marketed drugs may provide them with the most therapeutic benefit. Second, it provides the best means of identifying patients who are appropriate for clinical trials involving drugs that are likely to be effective treatments for their cancer.


For further information, read our recent whitepaper: "Oncology pre-profiling: Using genetic biomarkers to pre-identify oncology patients for clinical trials"