The Validity Of Diagnostic Testing

[gpawelski]

The traditional criteria ever used to evaluate laboratory tests has been the predictive "accuracy" of the test. None of the available laboratory tests used in the selection of treatments for cancer patients have ever been tested for "efficacy." This includes estrogen receptor, progesterone receptor, Her2/neu, Oncotype DX, MammaPrint, EGFR amplification/mutation, immunohistochemical (IHC) staining for tumor classification, Cell Culture Assays, Bacterial Culture and Sensitivity Testing, CT, MRI and Pet Scans to measure tumor response to treatment. The only data supporting any of them relate to test "accuracy."

Oncotype Dx and MammaPrint, laboratory tests, are a tool for the oncologist. The oncologist should take advantage of all the tools available to him/her to treat a patient. And since studies show that only 20-30% of patients do respond to chemotherapy that is available to them, there should be due consideration to looking at the advantage of molecular and cellular assay tests to the resistance that has been found to chemotherapy drugs.

The MammPrint, looking at the expression of 70 genes linked to breast cancer, can accurately assess a patient's risk of recurrence or death. The correlations of this are vastly superior to those obtained with standard prognostic markers.

The 70 genes in a woman's tumor analyzed by MammaPrint predict the 10-year survival of the patient at a significance level over three times greater than existing methods and with an accuracy level of 96.7% as determined by a study published in the New England Journal of Medicine.

Existing methods can't distinguish the patients with a high risk for recurrence from those with low risk with comparable accuracy. This new gene expression profiling test enables the oncologist and breast surgeon to more accurately determine who should be treated.

These tests have been shown to be superior over conventional assessment of risk of future metastatic disease, such as histological assessment of tumor aggressiveness (by grade). However, one gets more accurate information when using intact RNA isolated from "fresh" tissue than from using degraded RNA, which is present in paraffin-fixed tissues.

These tests have enormous implications for the short-term future of cancer research in general, and is one of the truly great cancer breakthroughs of our time. The DNA microarray test will prove to be highly complementary to the parellel breakthrough efforts in targeted therapy through cell culture assays like the EGFRx™ Assay.

For the vast majority of cancer patients, the cancer will not recur regardless of whether they receive chemotherapy. So they are exposed needlessly to the treatment, which can cause myelosuppression, mucositis, cardiac problems, peripheral neuropathy, central neurotoxicity, or leukemia. Doctors cannot tell, however, which patients need chemotherapy. These new genomic tests are supposed to tell physicians which cancer patients will benefit from chemotherapy and which ones do not need to be unnecessarily exposed to toxic chemotherapy cocktails.

Because of this, there is a good portion of cancer patients that are either undertreated or overtreated because there was no adequate information on who will recur. The Oncotype DX and MammaPrint can enhance the ability to distinguish between low risk and high risk patients. However, these tests do not predict which patients will benefit from chemotherapy (i.e. which patients are chemosensitive).

These tests don't do anything to indicate if chemotherapy would or would not be helpful for those patients at higher risk for recurrence, much less which chemotherapy would be most likely to be helpful. A genomic test can help to find out if a cancer patient will benefit from chemotherapy or not, and if they do, Cell Culture Assays can help see what treatments have the best oportunity of being successful.

Patients in the high-risk group, who would benefit from chemotherapy can be pre-tested to see what treatments have the best opportunity of being successful, and offers a better chance of tumor response resulting in progression-free survival, while those in the lower-risk groups can be spared the unnecessary toxicity, particularly associated with ineffective treatment.

Cell Culture Assays (like the EGFRx™ Assay) can report prospectively to a physician specifically which chemotherapy agent would benefit a high risk cancer patient by testing that patient’s "live" cancer cells. Drug sensitivity profiles differ significantly among cancer patients even when diagnosed with the same cancer. Knowing the drug sensitivity profile of a specific cancer patient allows the treating oncologists to prescribe chemotherapy that will be the most effective against the tumor cells of that patient.

Every breast cancer patient should have her own unique chemotherapy trial based on consultation of pathogenic profiles and drug sensitivity testing data. Research and application of these tests are being encouraged by growing patient demands, scientific advances and medical ethics. These tests are not a luxury but an absolute necessity, and a powerful strategy that cannot be overlooked.

[gpawelski]

The Microarray (gene chips) is a device that measures differences in gene sequence, gene expression or protein expression in biological samples. Microarrays may be used to compare gene or protein expression under different conditions, such as cells found in cancer.

Hence 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.

In the new paradigm of requiring a companion diagnostic as a condition for approval of new targeted therapies, the pressure is so great that the companion diagnostics they’ve approved often have been mostly or totally ineffective at identifying clinical responders (durable and otherwise) to the various therapies.

Cancer cells often have many mutations in many different pathways, so even if one route is shut down by a targeted treatment, the cancer cell may be able to use other routes. Targeting one pathway may not be as effective as targeting multiple pathways in a cancer cell.

Another challenge is to identify for which patients the targeted treatment will be 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. Understanding “targeted” treatments begins with understanding the cancer cell.

If you find one or more implicated genes in a patient's tumor cells, how do you know if they are functional (is the encoded protein actually produced)? If the protein is produced, is it functional? If the protein is functional, how is it interacting with other functional proteins in the cell?

All cells exist in a state of dynamic tension in which several internal and external forces work with and against each other. Just detecting an amplified or deleted gene won't tell you anything about protein interactions. Are you sure that you've identified every single gene that might influence sensitivity or resistance to a certain class of drug?

Assuming you resolve all of the preceeding issues, you'll never be able to distinguish between susceptibility of the cell to different drugs in the same class. Nor can you tell anything about susceptibility to drug combinations. And what about external facts such as drug uptake into the cell?

Gene profiling tests, important in order to identify new therapeutic targets and thereby to develop useful drugs, are still years away from working successfully in predicting treatment response for individual patients. Perhaps this is because they are performed on dead, preserved cells that were never actually exposed to the drugs whose activity they are trying to assess.

It will never be as effective as the cell culture method, which exists today and 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.

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. If one drug or another is working for some patients then obviously there are others who would also benefit. But, what's good for the group (population studies) may not be good for the individual.

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 above that achieved with "best guess" empiric chemotherapy through clinical trials.

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.

To overcome the problems of heterogeneity in cancer and prevent rapid cellular adaptation, oncologists are able to tailor chemotherapy in individual patients. This can be done by testing "live" tumor cells to see if they are susceptible to particular drugs, before giving them to the patient. DNA microarray work will prove to be highly complementary to the parellel breakthrough efforts in targeted therapy through cell function analysis.

As we enter the era of "personalized" medicine, it is time to take a fresh look at how we evaluate new medicines and treatments for cancer. More emphasis should be put on matching treatment to the patient, through the use of individualized pre-testing.

Upgrading clinical therapy by using drug sensitivity assays measuring "cell death" of three dimensional microclusters of "live" fresh tumor cell, can improve the situation by allowing more drugs to be considered. The more drug types there are in the selective arsenal, the more likely the system is to prove beneficial.