[gdpawel]

The headlong rush to develop tests to identify molecular predisposing mechansims whose presence still does not guarantee that a drug will be effective for an individual patient. Nor can they, for any patient or even large group of patients, discriminate the potential for clinical activity among different agents of the same class.

Genetic profiles are able to help doctors determine which patients will probably develop cancer, and those who will most likely relapse. However, it cannot be suitable for specific treatments for "individual" patients. The NCI has concluded (J Natl Cancer Inst. March 16, 2010), it cannot determine treatment plans for patients. It cannot test sensitivity to any of the targeted therapies. It just tests for "theoretical" candidates for targeted therapy.

The predictions are based on the fact that a higher percentage of people with similar genetic profiles or specific mutations may tend to respond better to certain drugs. This is a refinement of statistical data, like conventional treatment is based on previous randomized clinical trials (population studies). If you are okay with that, it might be worthwhile.

Some molecular tests do utilize living cells, but generally of individual cancer cells in suspension, sometimes derived from tumors and sometimes derived from circulating tumor cells. This was tried with the human clonogenic assay, which had been discredited long ago. Again, traditionally, in-vitro (in lab) "cell-lines" have been studied in 2 dimensions (2D) which has inherent limitations iin applicability to real life 3D in-vivo (in body) states.

The October 2010 Journal of Clinical Oncology published study used immunohistochemical and microarray platforms to identify targetes for drug therapy in a population of previously treated patients. Patients eligible had to have clear disease progression on prior therapy and received at least two prior lines of systemic chemotherapy.

“Success” was defined as a time to progression (TTP) of at least 30% longer than the TTP of the most immediate prior therapy. A total of 18 patients (of 66) achieved this 30% improvement in time to progression. The algorithm compared each patient's last TTP as the denominator and their targeted TTP as the numerator to idenfity a 1.3 fold improvement.

The null hypothesis was 15% or less of the sample would achieve this 1.3 fold improvement with a 90% power, P = .05. Drug selection was hierarchical, with gene array + IHC, followed by IHC alone, followed by gene array alone, with pts failing to provide a result offered physicians choice.

Only 62% of all the accrued patients were treated. The drop out of 40 patients may have served to cull the most vigorous from the herd, introducing a bias for survival regardless of intervention.

The functional profiling platform is not hampered by the problems associated with gene expression tests. That is because they measure the net effect of all processes within the cancer, acting with and against each other in real time, and it tests living cells actually exposed to drugs and drug combinations of interest.

Cancer is already in 3D conformation. Cell-based functional profiling cultures "fresh" live tumor cells in 3D conformation and profiles the function of cancer cells (is the whole cell being killed regardless of the targeted mechanism or pathway). It distinguishes between susceptibility of cancer cells to different drugs in the same class and the susceptibility to combinations. In other words, which combinations are best and in what sequence would they be most effective.

The key to understanding the genome is understanding how cells work. The ultimate driver is a functional profiling (is the cell being killed regardless of the mechanism) as opposed to a molecular profile (does the cell express a particular target that the drug is supposed to be attacking). While a molecular profile tells you whether or not to give "one" drug, a functional profile can find other compounds and combinations and can recommend them from the one assay.

The core of the functional assay 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 one of these pathways, it is important to examine the effects of the drug within the context of the cell. Both genomics and proteomics can identify potential new therapeutic targets, but these targets require the determination of cellular endpoints.

Cell-based functional assays are being used for screening compounds for efficacy and biosafety. The ability to track the behavior of cancer cells permits data gathering on functional behavior not available in any other kind of assay.