Personalized Cancer Medicine Is Here, NOW!

[gpawelski]

As we enter the era of "personalized" medicine, it is time to take a fresh look at how we evaluate treatments for cancer patients. More emphasis is needed matching treatment to the patient. Patients would certainly have a better chance of success had their cancer been chemo-sensitive rather than chemo-resistant, where it is more apparent that chemotherapy improves the survival of patients, and where identifying the most effective chemotherapy would be more likely to improve survival.

Findings presented at the Annual Meeting of the European Society for Clinical Investigation in Uppsala, Sweden and the Annual Meeting of the American Assoication for Cancer Research (AACR) in San Diego, CA concluded that "functional profiling" with cell-based assays is relevant for the study of both "conventional" and "targeted" anti-neoplastic drug agents (anti-tumor and anti-angiogenic activity) in primary cultures of "fresh" human tumors.

Cell-based Assays with "cell-death" endpoints can show disease-specific drug activity, are useful clinical and research tools for "conventional" and "targeted" drugs, and provide unique information complementary to that provided by "molecular" tests. There have been more than 25 peer-reviewed publications showing significant correlations between cell-death assay results and patient response and survival.

Many patients are treated not only with a "targeted" therapy drug like Tarceva, Avastin, or Iressa, but with a combination of chemotherapy drugs. Therefore, existing DNA or RNA sequences or expression of individual proteins often examine only one compenent of a much larger, interactive process. The oncologist might need to administer several chemotherapy drugs at varying doses because tumor cells express survival factors with a wide degree of individual cell variability.

There is a tactic of using biopsied cells to predict which cancer treatments will work best for the patient, by taking pieces of live "fresh" tumor tissue, applying different chemotherapy treatments to it, and examining the results to see which drug or combination of drugs does the best job killing the tumor cells. A cell-based assay test with "functional profiling," using a cell-death endpoint, can help see what treatments will not have the best opportunity of being successful (resistant) and identify drugs that have the best opportunity of being successful (sensitive).

Funtional profiling measures the response of the tumor cells to drug exposure. Following this exposure, they measure both cell metabolism and cell morphology. The integrated effect of the drugs on the whole cell, resulting in a cellular response to the drug, measuring the interaction of the entire genome. No matter which genes are being affected, functional profiling is measuring them through the surrogate of measuring if the cell is alive or dead.

For example, the epidermal growth factor receptor (EGFR) is a protein on the surface of a cell. EGFR-inhibiting drugs certainly do target specific genes, but even knowing what genes the drugs target doesn't tell you the whole story. Both Iressa and Tarceva target EGFR protein-tyrosine kinases. But all the EGFR mutation or amplificaton studies can tell us is whether or not the cells are potentially susceptible to this mechanism of attack. They don't tell you if Iressa is better or worse than Tarceva or other drugs which may target this. There are differences. The drugs have to get inside the cells in order to target anything. So, in different tumors, either Iressa or Tarceva might get in better or worse than the other. And the drugs may also be inactivated at different rates, also contributing to sensitivity versus resistance.

As an example of this testing, researchers have tested how well a pancreatic cancer patient can be treated successfully with a combination of drugs commonly used to fight lung, pancreatic, breast, and colorectal cancers. The pre-test can report prospectively to a physician specifically which chemotherapy agent would benefit a cancer patient. Drug sensitivity profiles differ significantly among cancer patients even when diagnosed with the same cancer.

The funtional profiling technique makes the statistically significant association between prospectively reported test results and patient survival. It can correlate test results that are obtained in the lab and reported to physicians prior to patient treatment, with significantly longer or shorter overall patient survival depending upon whether the drug was found to be effective or ineffective at killing the patient's tumor cells in the laboratory.

This could help solve the problem of knowing which patients can tolerate costly new treatments and their harmful side effects. These "smart" drugs are a really exciting element of cancer medicine, but do not work for everyone, and a pre-test to determine the efficacy of these drugs in a patient could be the first crucial step in personalizing treatment to the individual.

Literature Citation:

Functional profiling with cell culture-based assays for kinase and anti-angiogenic agents Eur J Clin Invest 37 (suppl. 1):60, 2007

Functional Profiling of Human Tumors in Primary Culture: A Platform for Drug Discovery and Therapy Selection (AACR: Apr 2008-AB-1546)

[gpawelski]

The "forest and trees" analogy can explained the fact that conventional chemo treatments try to kill "all" cancerous cells (along with non-cancerous cells). The whole forest of cells. The new "targeted" drugs go after a "pathway" within or on cancerous cells. Hence the "trees" instead of the "forest."

With "functional" cell-based assays, the "forest" is looked at and not the "trees." There are many pathways to altered cellular (forest) function (hence all the different "trees" which correlate in different situations). The "functional" profiling technique of cell-death assays, measures what happens at the end (the effects on the forest), rather than the status of the individual trees. Cancer is a complex disease and needs to be attacked on many fronts.

Cancer therapy needs to be thought of "outside the box" with "personalized" treatments for "individual" patients, and requires a combination of novel diagnostics and therapeutics. If "some" drugs are working for "some" people (not average populations), then obviously there are others out there who would also benefit. Who are those that would benefit? All the more reason to test the tumor first.

A cell culture assay with "functional" profiling, using a cell-death endpoint, can help see what treatments will not have the best opportunity of being successful (resistant) and identify drugs that have the best opportunity of being successful (sensitive). Cell "function" analysis doesn't claim to have a perfect model, but all retrospective studies have documented that killing cells in the test tube does correlate with dead cancer cells in the patient.

"Funtional" profiling measures the response of the tumor cells to drug exposure. Following this exposure, they measure both cell metabolism and cell morphology. The integrated effect of the drugs on the whole cell (forest), resulting in a cellular response to the drug, measuring the interaction of the entire genome. No matter which genes are being affected (trees), "functional" profiling is measuring them through the surrogate of measuring if the cell is alive or dead.

For example, the epidermal growth factor receptor (EGFR) is a protein on the surface of a cell. EGFR inhibiting drugs certainly do target specific genes, but even knowing what genes the drugs target doesn't tell you the whole story. Both Iressa and Tarceva target EGFR protein-tyrosine kinases. But all the EGFR mutation or amplificaton studies can tell us is whether or not the cells are potentially susceptible to this mechanism of attack.

It doesn't tell you if Iressa is better or worse than Tarceva or other drugs which may target this. There are differences. The drugs have to get inside the cells in order to target anything. So, in different tumors, either Iressa or Tarceva might get in better or worse than the other. And the drugs may also be inactivated at different rates, also contributing to sensitivity versus resistance.

In an example of this testing, researchers have tested how well a pancreatic cancer patient can be treated successfully with a combination of drugs commonly used to fight lung, pancreatic, breast and colorectal cancers. The pre-test can report prospectively to a physician specifically which chemotherapy agent would benefit a cancer patient. Drug sensitivity profiles differ significantly among cancer patients even when diagnosed with the same cancer. One-size-does-not-fit-all.

[gpawelski]

Personalized Cancer Medicine: Diagnostics Trumps Pharmaceutics

The very idea of "personalized" medicine scares the hell out of the pharmaceuticals. It represents a radical departure in the pharma business model. Thanks to advances in biology and genetics, upcoming and existing technologies for personalizing cancer diagnosis and drug treatments are very real.

The key hurdle for these technologies is overcoming the pharmaceutical industry's prevailing blockbuster economic model of the last twenty years. As one peruses the internet, they can see drug companies and so-called industry experts rush to suggest that personalized medicine and their blockbuster model are incompatible. Tests to identify individuals most likely to benefit from chemotherapy will certainly cut into their old and antiquated model.

The spate of recent blockbuster "miracle" drugs has failed to show statistical survival benefit anywhere close to a majority of patients. These drugs actually did work miracles, in "some" patients. How do the drug companies respond when tests show their drug to be highly effective, but only in 11% of the potential patient population, a fraction of affected patients? Charging significantly more for those therapies will only work to a point. Personalized medicine will take the wind out of the sails of big pharma.

Pharmaceutical companies and their industry shills will try to buck the trend as long as they can, but many realize that personalized treatments are inevitable and are making their way into a new paradigm of cancer treatment. The pharmaceutical industry will need to transform itself as "business as usual," it will no longer be good enough. The old pharma "blockbuster" business model is incompatible with personalized medicine. Diagnostics will almost certainly trump pharmaceutics.

http://meeting.ascopubs.org/cgi/content ... uppl/17117