Predictive accuracy is the only data existing to validate the Oncotype DX test, which wasn't a prospective study and certainly wasn't a "real world" study. The Oncotype DX test has been independently validated by the original laboratory group which published the results.
The other molecular-targeted breast prognostic test Mammostrat is validated with the usual, retrospective, non-randomized study using archival tissues and uniform batch processing and slide interpretation. It utilizes five immunohistochemical (IHC) biomarkers to classify patients into high, moderate, or low-risk categories for disease recurrence.
No one is seriously proposing that any of the molecular tests now available (Oncotype DX, EGFR amplification/mutation) should have to be proven efficacious, as opposed to merely accurate, before they are used in clinical decisions regarding treatment selection.
These new gene expression profiling tests enable the oncologist and breast cancer surgeon to more accurately determine who should be treated and who should not be treated with chemotherapy, but they cannot predict chemo response (clinical responders).
The OncotypeDX test is somewhat problematic. I think that work like this is tremendously important, but it is an example of herd mentality thinking, which almost always causes problems. There's been a stampede to endorse it, and many laudatory comments were made about it at the Ovarian Cancer State of the Science meeting in Bethesda in 2005.
I did get to read all the supplemental materials with the New England Journal of Medicine (NEJM) article. All of the assays were completed in a two week period on specimens archived from the 1980s. So all were done by the same team within a short time. The same pathologist did the micro-dissection of the paraffin slides. It was all retrospective and about as non-real world as you can get.
In the real world, specimens are accessioned in real time over days, weeks, months, and years. The people working on the different days are different. The assay is very complicated (the CEO even made a big point of how complicated it was, to justify the pricing). It involves a whole lot of steps and a whole lot of micropipetting. As far as for quality control, they stated that only two specimens had been tested twice (again, within a very narrow time frame) to affirm reproducibility.
Then, when they applied the same test at a later time to a slightly different patient population (at MD Anderson, rather than at the National Surgical Adjuvant Breast and Bowel Project), the correlations were not significant. And the only thing the test was useful for was identifying a small group of patients who ostensibly don't need tamoxifen and/or anastrozole therapy.
The challenge is to identify which patients the targeted treatment will be most effective. Tumors can become resistant to a targeted treatment, or the drug no longer works, even if it has previously been effective in shrinking a tumor. Drugs are combined with existing ones to target the tumor more effectively. Most cancers cannot be effectively treated with targeted drugs alone.
What is needed is to measure the net effect of all processes within the cancer, acting with and against each other in real time, and test living cells actually exposed to drugs and drug combinations of interest. The key to understanding the genome is understanding how cells work. How is the cell being killed regardless of the mechanism?
The core understanding is the cell, composed of hundreds of complex molecules that regulate the pathways necessary for vital cellular functions. If a targeted drug could perturb any of these pathways, it is important to examine the effects of drug combinations within the context of the cell. Both genomics and proeomics can identify potential therapeutic targets, but these targets require the determination of cellular endpoints.
Sources:
JNCI J Natl Cancer Inst (2010) doi: 10.1093/jnci/djq306
Eur J Clin Invest, Volume 37(suppl. 1):60, April 2007
BMJ 2007;334(suppl 1):s18 (6 January), doi:10.1136/bmj.39034.719942.94
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