a setback in "personalized" cancer treatments

gdpawel said:

How Bright Promise in Cancer Testing Fell Apart
It's not just Potti, and it's not just microarrays. The whole concept of using molecular "signatures" of any kind to do anything beyond the most straightforward of cases (i.e. single gene mutations, etc.) is so flawed that everyone should have seen the problems at the beginning.

The reason what no one seemingly sees it now can be explained by the facts that the technology itself is so elegant and beautiful. But a beautiful biological technology is no different than a beautiful computer technology -- it's not worth much without some very good applications ("apps"), and personalized molecular medicine is still waiting for its first killer app.

Until such time as cancer patients are selected for therapies predicated upon their own unique biology (and not population studies), we will confront one targeted drug after another.

The solution to this problem has been to investigate the targeting agents in each individual patient's tissue culture, alone and in combination with other drugs, to gauge the likelihood that the targeting will favorably influence each patient's outcome.

Functional profiling results to date in patients with a multitude type of cancers suggest this to be a highly productive direction.

http://cancerfocus.org/forum/showthread.php?t=3174

Personalized Cancer Treatment
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 from a medical oncologist friend of mine. 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.