predicting who will respond to docetaxel

[Lani]

Molecular fingerprint of breast-cancer drug resistance can predict response to treatment [Eureka News Service]
Barcelona, Spain: A way of predicting which patients will respond well to treatment with a common chemotherapy drug used in breast cancer was unveiled at the European Cancer Conference (ECCO 14) today (Monday 24 September). Dr Iain Brown, from the University of Aberdeen, Aberdeen, Scotland, told the conference that he and his colleague, Dr Andrew Schofield, had identified two genes that could identify which cells would be resistant and which would respond to docetaxel.
Docetaxel is one of the most effective chemotherapy treatments in advanced breast cancer. It works by binding to cell components called microtubules, and stabilising them so that they do not disassemble. They then accumulate within the cell and bring about apoptosis, or cell death. "However, up to half of all patients treated with this drug will develop resistance, and hence the treatment will fail," said Dr Brown.
The scientists decided to look for a specific genetic make-up in patients where docetaxel treatment had failed, in the hope that this might explain why they became resistant to the drug. They used micro-array analysis, a technique that allowed them to look at every known gene in our cells at once, to identify genes that were significantly associated with such resistance.
"By going back to the laboratory, using breast cancer cell lines, we can eliminate much of the variation in gene expression found in different patients, and thus remove a lot of 'background noise'," said Dr Brown. "We developed a unique model of docetaxel resistance in breast cancer from two different cell lines made resistant to the drug by exposing them to increasing concentrations of the drug. This model has also allowed us to test cells which are resistant to low levels of the drug and cells which are resistant to high levels."
Drs Brown and Schofield now intend to carry the research further, by applying their findings to patient samples to see whether the gene set they have discovered has the ability to predict response to docetaxel in a patient who has undergone treatment with the drug. "At the moment we have only tested this in cell lines," said Dr Brown, "but we do believe these results may be translated into the clinical setting and benefit the patient. In essence, we have taken a clinical problem back to the laboratory, and now we intend to take this back to the bedside."
The scientists will start collecting tissue samples from patients within the next six months. "If we find the same results in patient samples, we would expect that a simple test for docetaxel resistance could be developed and in clinical use within the next five years," said Dr. Brown. Such a test would mean that those who would not benefit from docetaxel chemotherapy could be spared its side effects, and also reduce costs for healthcare providers.
"We think that the changes we have found may represent common drug resistance mechanisms in breast cancer cells," said Dr Brown. "We are currently looking at these findings in other cancer types, especially those which are also treated with docetaxel, to see if the results may have a potential in other areas. This is the first time that the genetic pathways involved in the evolution of acquired resistance to docetaxel have been identified in a docetaxel resistant cell line model."
ABSTRACT: Molecular profile of acquired docetaxel resistance in breast cancer cells [European Cancer Organization]
Introduction: Docetaxel is one of the most active agents used in the treatment of breast cancer. However, tumours may be resistant, or develop resistance, to docetaxel during treatment. The mechanisms of resistance to docetaxel, whether innate or acquired, are poorly understood. The purpose of this study was to investigate the genetic pathways involved in docetaxel resistance using a unique model of docetaxel resistance, which we have developed in breast cancer cells.
Methods: We made two human breast cancer cell lines, MCF-7 and MDA-MB-231, resistant to docetaxel by exposure to increasing docetaxel concentrations. The resultant sublines were able to withstand 30 ?M of docetaxel. Alterations of gene expression were determined using Affymetrix Genechip cDNA microarrays, and subsequently validated by RT-PCR and western analysis.
Results: After firstly selecting out gene changes that were common between both sets of sensitive cell lines and their resistant sublines (>2 fold), further normalisation and statistical filtering (p < 0.01) identified 124 probe-sets that were commonly changed in both resistant cell lines. Further statistical analyses were carried out on the gene list using ANOVA (assuming unequal variances) and the Benjamin-Hobbson false discovery rate was applied as a multiple correction factor with a significance level of p < 0.01. This identified a 14 probe-set, encoding 10 genes (including p-glycoprotein), which were significantly associated with resistance to docetaxel. These genes are currently being validated at the mRNA and protein level.
Conclusions: These changes, therefore, may represent common mechanisms of resistance in breast cancer cells. In addition, this is the first description, using microarray analysis, to identify the genetic pathways involved in the evolution of acquired resistance to docetaxel in a cell line model of resistance.

[gdpawel]

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 Microarray 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.

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.

Gene expression assays can be either probing for the specific RNA messengers (messenger RNA) or it can mean looking for the proteins themselves. Many have hoped that molecular tests would hold the key to success, particularly as more specific drugs are designed to hit the molecular changes that are responsible for the uncontrolled growth of cancer cells. Like testing breast cancer for the presence of hormone receptors and over-expression of growth factor receptors. However, most drugs cannot be looked at in this way.

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.

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