Whole Cell Profiling

Looking for others with your cancer? Want to help others? Enter info here.

Whole Cell Profiling

Postby gdpawel » Fri Aug 11, 2006 2:28 pm

Researchers have seen that whether a tumor was a breast tumor, prostate tumor, lung tumor, ovarian tumor or lymphoma, it didn't correlate to how the cancers interacted with standard anticancer drugs. Their findings suggest that traditional cancer treatments, which have established different drug regimens for breast, lung, lymphoma or ovarian cancer, for example, should be replaced with therapies that use drugs deemed to be of highest benefit based on the tumor's pharmacologic profile. Treatment choice would be determined by how each patient's tumor reacts to anticancer drugs, regardless of the tumor's anatomical origin.

The drug effect is independent of where the tumor came from in the body. Under current treatment selection methods virtually no chemotherapeutic drug has been successful in more than 50 percent of patients with advanced cancer. But instead of considering a drug that works only ten percent of the time a failure, it would be better to consider such a drug effective for one in ten tumors and to search for the agents among the current arsenal of chemotherapeutic drugs that will work for the rest. Having a good tumor-drug match not only would improve survival rates, it would be cost-effective, and the high cost of the newer cancer therapies reinforces the necessity of choosing the right therapy the first time around.

The introduction of new "targeted" drugs has not been accompanied by specific predictive tests allowing for a rational and economical use of the drugs. Given the technical and conceptual advantages of Cell Culture Assay Tests together with their performance and the modest efficicay of therapy prediction on analysis of genome expression, there is reason for a renewal in their interest for optimized use of medical treatment of malignant disease.

Clinical study results published at the annual meeting of the American Society of Clinical Oncology (ASCO) show that a new laboratory test called EGFRx ™, has accurately identified patients who would benefit from treatment with the molecularly-targeted anti-cancer therapies. The finding is important because the EGFRx ™ test, which can also be applied to many emerging targeted cancer drugs, could help solve the growing problem of knowing which patients should receive costly, new treatments that can have harmful side-effects and which work for some but not all cancer patients who receive them. The test can discriminate between the activity of different targeted drugs and identify situations in which it is advantageous to combine the targeted drugs with other types of cancer drugs.

The new test relies upon what is called "Whole Cell Profiling" in which living tumor cells are removed from an individual cancer patient and exposed in the laboratory to the new drugs. A variety of metabolic and apoptotic measurements are then used to determine if a specific drug was successful at killing the patient's cancer cells. The whole cell profiling method differs from other tests in that it assesses the activity of a drug upon combined effect of all cellular processes, using combined metabolic and morphologic endpoints. Other tests, such as those which identify DNA or RNA sequences or expression of individual proteins often examine only one component of a much larger, interactive process.

The whole cell profiling method makes the statistically significant association between prospectively reported test results and patient survival. Using the EGFRx ™ assay and the whole cell profiling method, can correlate test results which 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.

Over the past few years, researchers have put enormous efforts into genetic profiling as a way of predicting patient response to targeted therapies. However, no gene-based test has been described that can discriminate differing levels of anti-tumor activity occurring among different targeted therapy drugs. Nor can an available gene-based test identify situations in which it is advantageous to combine a targeted drug with other types of cancer drugs. So far, only whole cell profiling has demonstrated this critical ability.

Not only is this an important predictive test that is available "today," but it is also a unique tool that can help to identify newer and better drugs, evaluate promising drug combinations, and serve as a "gold standard" correlative model with which to develop new DNA, RNA, and protein-based tests that better predict for drug activity.

These "targeting" drugs are expensive, costing patients and insurance carriers $5,000 to $7,000 or more per month of treatment. Patients, physicians, insurance carriers, and the FDA are all calling for the discovery of predictive tests that allow for rational and cost-effective use of these drugs.

The whole cell profiling approach, holds the key to solving some of the problems confronting a healthcare system that is seeking ways to best allocate available resources while accomplishing the critical task of matching individual patients with the treatments most likely to benefit them.

Genomic testing is not the answer, without cell culture analysis. In developing a program to discover gene expression microarrays, which predict for responsiveness to drug therapy, the way to identify informative gene expression patterns is to have a gold standard and that cell culture assays are by far the most powerful, efficient, useful gold standard to have.

The assay is the only assay that involves direct visualization of the cancer cells at endpoint. This allows for accurate assessment of drug activity, discriminates tumor from non-tumor cells, and provides a permanent archival record, which improves quality, serves as control, and assesses dose response in vitro (includes newly-emergent drug combinations).

Last edited by gdpawel on Sat Dec 16, 2006 1:24 am, edited 2 times in total.

Clinical Validation of Cell Culture Assays

Postby gdpawel » Sat Sep 02, 2006 11:58 am

There was a recent study describing correlations between cell culture assay results (cell death in response to Iressa exposure) and survival of 31 patients with non-small cell lung cancer who had received extensive prior chemotherapy. These correlations were based on the actual assay results which had been reported, in real time, prospectively to the doctors who had ordered the assay laboratory tests. There were striking correlations between test results and patient survival (not just response).

By inhibiting anti-apoptosis with Iressa (or even Tarceva), the cells undergo apoptosis and die. And it is detected at the whole cell level in the cell culture assays and reported out - prospectively - that this correlates strikingly with patient survival. Not only is it a very important predictive test, but it is a unique tool for identifying newer, better drugs, testing drug combinations, and serving as a "gold standard" to develop new DNA, RNA, and protein-based tests of drug activity.

EGF-targeted drugs (Iressa, Tarceva, Erbitux) are poorly-predicted by measuring the ostensible target (EGFR), but can be well-predicted by measuring the effect of the drugs on the function of "live" cells. Epidermal Growth Factor (EGF) is a receptor on many normal tissues/cells, and also on many cancer cells. It is a growth hormone, locally secreted by cells. It attaches to a receptor on the cell membrane called Epidermal Growth Factor Receptor (EGFR). It then activates so-called signalling pathways within the cell, a cascade of biochemical events, including phosphorylation of proteins, leading to cell growth/proliferation/division. One type of an enzyme which is involved in the pathway which is involved in protein phosphorylation is called tyrosine kinase.

The assay is the only test that involves direct visualization of the cancer cells at endpoint. This allows for accurate assessment of drug activity, discriminates tumor from non-tumor cells, and provides a permanent archival record, which improves quality, serves as control, and assesses dose response in vitro (includes newly-emergent drug combinations).

Iressa (gefitinib) or Tarceva (erlotinib) induced cell death in short term fresh tumor cultures predicts for long term patient survival in previoulsy-treated non-small cell lung cancer.

Sub-category: Non-Small Cell Lung Cancer

Category: Lung Cancer

Meeting: 2006 ASCO Annual Meeting

Abstract No: 17117

Author (s): L. M. Weisenthal

Abstract: Gefitinib (GEF) may act by inhibiting anti-apoptotic signals transduced by mutant EGFR kinase (Science 305:1163,04). Cell culture assays with cell death endpoints could be informative for GEF activity.

Methods: We tested 568 biopsies of fresh human tumors (TUM) with 2 concentrations of GEF (22 and 11 µg/ml) for 96 hrs, each with 2 separate cell death endpoints (DISC and MTT). Results classified as resistant (RES), intermediate (INT), or sensitive (SEN) based on means and standard deviations of training set data, reported prospectively to 3 different physicians: surgeon, pathologist, and oncologist. Assay evaluability rate > 90%.

Results: Based on overall % control cell death, the following TUM showed (on average) no greater RES or SEN than the universe of 568 assays: NSCLC (n = 72), colon (33), breast (106), ovarian (109), melanoma (23), pancreatic (20), endometrial (12). The following showed (on avg) significantly greater RES: soft tissue sarcomas (n = 24), carcinoid/islet (16), renal (15), and mesothelioma (8). For NSCLC, there was no avg difference between female (32) vs male (35) or untreated (34) vs previously treated (38). For 32 unRxd pts with survival data, there was no significant difference in overall surv for 20 pts with prospectively reported GEF RES (GR) assays vs 12 pts with SEN or INT (GSI) assays. For 31 pts with prior chemoRx (med surv = 155 days), there was significant survival disadvantage for 14 pts with prospectively reported GR vs 17 pts with GSI (median 85 vs 380 days, P2 < 0.0001, HR 3.7; 95% C.I. 2.6-19). For pts with known post-assay Rx, there were 7 pts with GSI subsequently receiving GEF or erlotinib (ERLOT), with med surv = 485 days; 9 pts with GSI not receiving GEF or ERLOT, med surv = 135 days; 10 pts with GR not receiving GEF or ERLOT, med surv = 76 days, and 3 pts with GR receiving GEF or ERLOT, med surv = 75 days. Survival of group of 7 pts was significantly greater than those of groups of 9, 10, and 3 pts (P2 = 0.037, P2 < 0.0001, and P2 = 0.0008, respectively.

Conclusions: GEF-induced cell death in cultures of fresh TUM from prev-treated NSCLC pts may identify pts with favorable prognosis, particularly when treated with GEF or ERLOT.

Last edited by gdpawel on Tue Feb 27, 2007 6:29 pm, edited 1 time in total.

Clinical Validation of Cell Culture Assays

Postby gdpawel » Wed Feb 14, 2007 1:25 pm

Recent findings presented at the American Society of Clinical Oncology (ASCO) Gastrointestinal Cancers Symposium in Orlando, Florida concluded that Functional Profiling (whole cell profiling) with cell culture assays is relevant for the study of both "conventional" and "targeted" antineoplastic drug agents.

Cell Culture 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 publicatons showing significant correlations between cell-death assay results and patient response and survival.

The Whole Cell Profiling technique is a cell-death endpoint assay in which drug effect upon cancer cells is visualized directly. Photomicrographs of actual tumor cells sometime show that the exact same identical individual culture well, shows some clusters have taken up vast amounts of a drug, while right next door, clusters of the same size, same appearance, same everything haven't taken up any of the drug.

So it doesn't matter if there is a "target" molecule (protein or receptor) in the cell that the targeted drug is going after, if the 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, drug resistance is multifactorial. The advantage of the Whole Cell Profiling technique is that it can show this in the "population" of cells.

The Whole Cell Profiling technique makes the statistically significant association between prospectively reported test results and patient survival. It can correlate test results which 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 test to determine the efficacy of these drugs in a patient could be the first crucial step in personalizing treatment to the individual.

Functional profiling (FP) with cell culture assays for targeted drug therapy.
Sub-category: Translational research
Category: Colon and Rectum
Meeting: 2007 Gastrointestinal Cancers Symposium

Abstract No: 440
Author(s): L. M. Weisenthal

Abstract: Introduction: We studied the relevance of FP for standard and targeted drugs.

Methods: Drugs were tested against fresh human tumor microclusters, with 96 hr drug exposures and multiple FP endpoints (MTT, DISC, resazurin, and/or ATP).

Results: In 65 previously chemonaive stage 4 colon cancer patients, those with FP assays showing 5FU results in the most resistant tertile had inferior overall survival, compared to pts without 5FU resistance (303 days vs. 686 days, H.R. 2.1, 95% C.I. 1.2 - 5.0, P2=0.011). In subset analysis restricted only to 53 pts who subsequently died (eliminating potential surgical cures), the respective results were 292 vs 493 days, HR 1.5 - 6.9, P2=0.0021. We applied FP to test targeted agents, including gefitinib, erlotinib, sunitinib, sorafenib, and bevacizumab. Gefitinib was tested against > 700 fresh tumor specimens; we reported striking correlations between gefitinib activity and overall pt survival in non-small lung cancer (2006 ASCO Annu Mtg, Abst 17117). Gefitinib and erlotinib are moderately cross resistant (R2=0.48, n paired comparisons=190). Gefitinib/sunitinib (R2=0.20, n=46) and erlotinib/sunitinib (R2=0.12, n=44) are largely non-cross resistant. We also developed a new microvascular viability assay (MVVA) to test microvascular cells present in tumor clusters. In the MVVA, bevacizumab was tested in 81 fresh tumor specimens (including 15 GI). Bevacizumab was nontoxic to the tumor cells, but often strikingly toxic to microvascular cells present within the same tumor clusters. Grading on a 0-4 scale, there was absent (Gr 0) effect in 23 specimens, weak (Gr 1-2) effect in 28, and a strong (Gr 3-4) effect in 26. In contrast to bevacizumab, neither sunitinib (n=87) nor sorafenib (n=20) showed selective effects against microvascular cells compared to tumor cells.

Conclusions: We cannot rule out a cytostatic effect of sunitinib or sorafenib on tumor microvascular cells. However, our results imply that the antitumor effects of bevacizumab are predominately mediated through antimicrovascular effects, while effects of sunitinib and sorafenib may be mediated largely through tumor cell apoptosis. We conclude that FP is relevant for the study of both traditional and targeted antineoplastic agents.

http://www.weisenthal.org/Tokyo_Cancer_ ... enthal.pdf

What is the Clinical Relevance of Gene Profiling?

Postby gdpawel » Thu Nov 08, 2007 2:27 pm

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.
Active Member
Active Member
Posts: 36
Joined: Tue Jul 10, 2007 11:18 pm
Cancer Diagnosis: Ovarian primary, metastatic to lung, brain mets, then Leptomeningeal Carcinomatous
Relationship To Patient: Husband

Return to Seeking Others - Helping Others

Who is online

Users browsing this forum: No registered users and 1 guest