Prediction of Response to Paclitaxel by ChemoFx assay Correlates with Estrogen Recept

[Hopeful]

http://www.abstracts2view.com/sabcs0...u=SABCS09L_244

Hopeful

[gdpawel]

There have been attempts to develop molecular-based tests to examine a broader range of chemotherapeutic drugs. New technologies for measuring the expression (biological activity) of literally hundreds to thousands of genes as part of a single test. There are two main technologies involved: RT-PCR (reverse transcription polymerase chain reaction) and DNA microarray.

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. 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.

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. 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. Recently, other researchers have pointed to the limitations of 2D "cell-line" study and chemotherapy to more correctly reflect the human body.

All DNA or RNA-type tests are based on "population" research (not individuals). They base their predictions 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 not really "personalized" medicine, but a refinement of statistical data.

The cell "function" method 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" assay (is the cell being killed regardless of the mechanism) as opposed to a "target" assay (does the cell express a particular target that the drug is supposed to be attacking). While a "target" assay tells you whether or not to give "one" drug, a "functional" assay 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.

The reason for at least a "tru-cut" biopsied tumor specimen is that "real life" 3D analysis makes functional profiling indicative of what will happen in the body. It tests fresh "live" cells in their 3 dimensional (3D), floating clusters (iin their natural state). Upgrading clinical therapy by using drug sensitivity assays measuring cell-death of 3 dimenionsl microclusters of live "fresh" tumor cells can improve the conventional situation by allowing more drugs to be considered.

We are forced to confront the realization that genotype does not equal phenotype. The particular sequence of DNA that an organism possess (genotype) does not determine what bodily or behaviorial form (phenotype) the organism will finally display. Among other things, environmental influences can cause the suppression of some gene functions and the activation of others. Out knowledge of genomic complexity tells us that genes and parts of genes interact with other genes, as do their protein products, and the whole system is constantly being affected by internal and external environmental factors.

The gene may not be central to the phenotype at all, or at least it shares the spotlight with other influences. Environmental tissue and cytoplasmic factors clearly dominate the phenotypic expression processes, which may in turn, be affected by a variety of unpredictable protein-interaction events. This view is not shared by all molecular biologists, who disagree about the precise roles of genes and other factors, but it signals many scientists discomfort with a strictly deterministic view of the role of genes in an organism's functioning.

Until such time as cancer patients are selected for therapies predicated upon their own unique biology (and not population studies), we will confront one targeted drug after another. The solution to this problem has been to investigate the targeting agents in each individual patient's tissue culture, alone and in combination with other drugs, to gauge the likelihood that the targeting will favorably influence each patient's outcome. Functional profiling results to date in patients with a multitude type of cancers suggest this to be a highly productive direction.

Sources:

JNCI J Natl Cancer Inst (2010) doi: 10.1093/jnci/djq306

J Thorac Cardiovasc Surg 2007;133:352-363. Chemotherapy Resistance and Oncogene Expression in NSCLC.

J Clin Onco, 2006 ASCO Annual Meeting Proceedings Part 1. Vol 24, No. 18S (June 20 Supplement), 2006: 17117. Genfitinib-induced cell death in short term fresh tumor cultures predicts for long term patient survival in previously-treated NSCLC.

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

Weisenthal Cancer Group, Huntington Beach, CA and Departments of Clinical Pharmacology and Oncology, Uppsala University, Uppsala, Sweden. Current Status of Cell Culture Drug Resistance Testing (CCDRT) May, 2002.

[gdpawel]

As Dr. Robert Nagourney, medical and laboratory director at Rational Therapeutics, and instructor of Pharmacology at the University of California, Irvine School of Medicine describes it, recent press coverage from the San Antonio Breast Cancer Symposium (SABCS) touched upon the development of multi-gene predictors for clinical response in breast cancer.

One report from that meeting described correlations between a laboratory assay model in use at the University of Pittsburgh and microarray analyses. However, the suggestion that this laboratory technique - described by its proponents as a chemosensitivity assay - could accurately identify gene profiles that would predict response seems at odds with the current literature.

Although the press coverage concluded that this technique showed “promising performance” it was largely exploratory and defined by the authors as a “validation study.”

What is interesting is that a team of highly reputable investigators from M.D. Anderson recently reported a very negative study using a similar approach of identifying target genes in cell lines and then correlating them with patient outcomes.

In the paper, published in the June 2010 issue of Breast Cancer Research and Treatment (Liedtke, C. et al. Breast Cancer Res Treat. 2010 Jun; 121(2):301-9) the authors reported “cell line derived predictors of response to four commonly used chemotherapy drugs did not predict response accurately in patients.”

Indeed, differential gene expression seemed only to correlate with paclitaxel. The authors found that false discovery rates were high for all other drugs tested. Thus, the report from the SABCS will need to be carefully examined to determine whether truly relevant clinically predictive information can be provided by this particular laboratory platform.

[Rich66]

from the abstract:

Conclusions: ER status appears to predict in part, the response of breast cancer cells to paclitaxel as determined by the ChemoFx assay. ER-negative breast cancer cells are more likely to be responsive, which is consistent with established clinical findings.

[gdpawel]

The proteomic platform does not clarify how the response to targeted drugs compares with that to chemotherapy, combinations, or other targeted therapies. There is a challenge to identify which patients the targeted treatment will be effective. There are any number of variables that affect drugs, including the rate of excretion of the drugs by the kidneys and liver, protein binding and a myriad of other biological factors. In the body, these cells interact with and are supported by other living cells, both malignant and non-malignant cells.

[Rich66]

Yes...functional profile best...but biology guided guessing better than blind chance when FP not possible. Hard to emulate various growth factors and interactions in lab based FP too. Aint nuttin' perfect.

[gdpawel]

And that's the reason for testing a "fresh" live sample of a patient's tumor (3D analysis). Cancer is already in 3D conformation. When you profile cultures "fresh" live in 3D conformation, it measures the function of cancer cells (is the whole cell being killed regardless of the targeted mechanism or pathway). Real life 3D analysis makes functional profiling indicative of what will happen in the body. It tests cells in their three-dimensional (3D), floating clusters (in their natural state - not dead cells, not monolayered cells, not cell lines).

Researchers at Johns Hopkins and Washington University at St. Louis have recently found out, our body is 3D, not 2D in form, undoubtedly, this novel step better replicates that of the human body. Traditionally, in-vitro (in lab) cell-lines have been studied in two-dimensions (2D) which has inherent limitations in applicability to real life 3D in-vivo (in body) states. Recently, other researchers have pointed to the limitations of 2D cell line study and chemotherapy to more correctly reflect the human body.

And other recent studies have shown that three-dimensional (3D) tissue culture models have an invaluable role in tumor biology, providing some very important insights into cancer biology. As well as increasing our understanding of homeostasis, cellular differentiation and tissue organization, they provide a well defined environment for cancer research in contrast to the complex host environment of an in vivo model.

Due to their enormous potential 3D tumor cultures are currently being exploited by many branches of biomedical science with therapeutically orientated studies becoming the major focus of research. Recent advances in 3D culture and tissue engineering techniques have enabled the development of more complex heterologous 3D tumor models. The surgical specimen is the "personalized" part of personlized cancer medicine. The tissue, carefully excised by the surgeon and analyzed by the pathologist is the source of crucial information that informs the decisions and actions of medical oncologists.

[Trish]

Is it possible that having anti estrogens with paclitaxel would be beneficial for ER+ tumours? Or is that too much of a leap?
Trish

[Rich66]

No leap. Makes sense. But in your case..considered pushing back on things with antiestrogen = anti her2?

TAM + Hercept
AI + Tykerb
Tykerb + anti estrogen
Tykerb/Hercept + anti estrogen and/or AI
Add metformin to any of the above

[schoolteacher]

Rich,

Glad to see you posting on the board. I have been wondering where you were.

I tried to get the doctor to let me have metformin my last visit, and he wouldn't.

Amelia

[gdpawel]

Rich

Sometime back, you asked me if there was any discussion at the 2009 Breast Cancer Symposium about ongoing support for metformin. Dr. Herman Kattlove, former medical editor for the American Cancer Socity, wrote in his private blog that he read an recent article touting the benefits of metformin (glucophage) in preventing cancer.

From what he gleamed in the article, almost all the evidence for cancer prevention by metformin comes from studies of people with diabetes. Diabetics are known to have higher rates of certain cancers - liver, pancreas, endometrium, colon/rectum, breast and bladder.

The issues for the speculation why this happens is the higher blood sugar in diabetics - sugar feeds cancer. The other issue is the higher amounts of insulin in their blood. People with type 2 diabetes have higher than normal amounts of insulin in their blood and the problem is they can't use it properly - they are relatively insensitive to insulin.

A large study of metformin and cancer was published in the November 2010 issue of the journal, Cancer Prevention Reserach. It was a meta-analysis which the authors reviewed and reported on all the well-documented studies of metformin and cancer in diabetics. They found that diabetic patients treated with metformin were about 25% less likely to develop or die from the typeical cancers found in diabetics.

The reason metformin reduces the cancer rate isn't known, however, scientists think it may be related to lower blood insulin levels or some interference with the cancer cells ability to use glucose. It is also known that metformin will slow cancer cell growth in test tubes and in mice.

The bigger issue Kattlove suggests is whether it will block cancer growth in non-diabetic people. Metformin is not an innocuous drug. It does interfere with metabolism - good for diabetics but who knows for non-diabetics?

NCI is sponsoring a study where metformin is being added to the usual drugs in patients with early stage breast cancer to prevent the cancer from coming back. Half the patients will get metformin and the rest will receive a placebo. It may take 5-10 years. In the meantime, he suggested forgetting about the drug. We just don't know if it will work and it may be harmful, unless you have adult-onset diabetes.

Greg

[Rich66]

Docs positions will obviously vary in this territory, even more than they do with "established" regimens. Does Kattlove use any off label treatments? I think the adjuvant setting would have a different level of criteria than metastatic. Approved and commonly used drugs may be equally or more unpredictable, with far higher toxicity. Considering the info available at this point and the fact that many cancer patients already take it, I'm comfortable with mom having taken it for about a year at a low dose. This isn't fully up to date but provided background:
http://her2support.org/vbulletin/showthread.php?t=39740
Note that there seems to be more than insulin/sugar in play regarding benefit.