The headlong rush to develop companion diagnostics to identify molecular
predisposing mechanisms still does not guarantee that a cancer drug will be
effective for an individual cancer patients. Nor can they discriminate the
potential for clinical activity among different cancer agents of the same
class.
The drug discovery model has been limited to one gene/protein, one target,
one drug. The "cell" is a system, an integrated, interacting network of genes,
proteins and other cellular constituents that produce functions. You need to
analyse the systems' response to drug treatments, not just one target or
pathway.
Uncovering the genetic differences that determine how a person responds to a
drug, and developing tests, or biomarkers, for those differences, is proving
more challenging than ever. As a result, patients with cancer are still being
prescribed medicines on a trial-and-error basis.
The key to understanding the genome is understanding how cells work. The
ultimate driver is "functional" diagnostics (is the cell being killed regardless
of the mechanism) as opposed to "target" diagnostics (does the cell express a
particular target that the drug is supposed to be attacking).
While a "target" diagnostic test tells you whether or not to give "one" drug,
a "functional" diagnostic test can find other compounds and combinations and can
recommend them from the one test.
The core of functional diagnostics 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 thereapeutic targets,
but these targets require the determination of cellular endpoints.
Cell-based functional diagnostics 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
testing.
The cell "function" methodology measures 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.
It would be more advantageous to sort out what's the best "profile" in terms
of which patients benefit from this drug or that drug. Can they be combined?
What's the proper way to work with all the new drugs? If a drug works extremely
well for a certain percentage of cancer patients, identify which ones and
"personalize" their treatment.
It may be very important to zero in on different genes and proteins. However,
when actually taking the "targeted" drugs, do the drugs even enter the cancer
cell? Once entered, does it immediately get metabolized or pumped out, or does
it accumulate? In other words, will it work for every patient?
All the validations of this gene or that protein provides us with a variety
of sophisticated techniques to provide new insights into the tumorigenic
process, but if the "targeted" drug either won't "get in" in the first place or
if it gets pumped out/extruded or if it gets immediately metabolized inside the
cell, it just isn't going to work.
DNA microarray work will prove to be highly complementary to the parellel
breakthrough efforts in targeted therapy through cell function
analysis.