Molecular Profiling Can Accurately Predict Survival In Colon Cancer Patients
Main Category: Colorectal CancerAlso Included In: GastroIntestinal / Gastroenterology; Cancer / Oncology
Article Date: 27 Sep 2007 - 17:00 PDT
Researchers in The Netherlands have developed a method of accurately predicting which patients with colon cancer are most likely to have their disease recur after surgery and who would, therefore, be likely to benefit from additional chemotherapy.
Led by Professor Rob Tollenaar at Leiden University Medical Center and Dr Laura Van 't Veer at The Netherlands Cancer Institute, they have analysed for the first time the different expressions of genes in the entire genome of tumour tissues from 121 patients with stage II colon cancer who had not received adjuvant chemotherapy.
Prof Tollenaar, who is head of sections endocrine, gastrointestinal and oncologic surgery in the department of surgery, told a news briefing at the European Cancer Conference (ECCO 14) in Barcelona, today (Tuesday) that the full-genome molecular expression profiling had identified two groups of patients that had distinct clinical outcomes.
"Patients with stage II colon cancer have an overall five-year survival of about 80%," he explained. "So far, no randomised clinical trials has shown significant benefit from giving adjuvant chemotherapy. Three-quarters of patients are cured by surgery alone and, therefore, less than 25% of patients would benefit from additional chemotherapy.
"Our analysis showed a cluster of 75% of the patients, of whom approximately 90% were likely to survive for at least five years with no distant metastases. In the second cluster of the remaining 25% of the patients, only about 65% of them had five-year survival without distant metastases, and this is the group who would be likely to benefit from adjuvant chemotherapy.
"This is the first time that the identification of a poor survival group has been based on genome-wide expression analysis and, therefore, it relates tumour biology more accurately to the outcome of disease."
Further analysis of the results showed that patients in the "poor outcome" group were over three times (3.2) more likely to develop metastases than the patients in the "good outcome" group. This method of identifying "poor outcome" patients was better at predicting which patients should have adjuvant chemotherapy than the commonly-used method that follows recommendations from the American Society of Clinical Oncology (ASCO).
The researchers checked their findings against information from another set of colon cancer patients that had been published in the Journal of Clinical Oncology in 2005. Prof Tollenaar said: "In these stage II colon cancer patients, the five-year metastasis-free survival prediction was confirmed; for the good outcome group, five-year survival was 90% and for the poor outcome group it was 40%. This was important validation of our own results."
From the genome-wide analysis, the researchers identified a subset of 100 genes that were able to predict outcome equally as well as the full-genome molecular expression profile. Many of these genes are know to regulate the Epithelial-Mesenchymal transition (EMT) - a programme of cell development that is thought to be a driving force behind the development of metastases in colorectal cancer.
Prof Tollenaar said that although his research predicted outcome of disease in patients who had not received adjuvant chemotherapy, more work would need to be done to identify the molecular profile for those patients who would actually benefit from chemotherapy.
Before the results of this research could start to be used in the clinic, Prof Tollenaar said two things needed to happen: "Current, ongoing validation studies required to confirm our findings have to be completed, and the test needs to be developed into a robust diagnostic device. The molecular profiling company Agendia BV of Amsterdam has taken this up and it is likely to be available in early 2008."
As to whether these findings would save large numbers of colon cancer patients from unnecessary chemotherapy, Prof Tollenaar said: "This depends greatly on the current practice in different European countries. For example, in Spain 60% of stage II colon cancer patients receive adjuvant chemotherapy, while in The Netherlands only 20% do. So in some countries it will result in a decrease in the number of patients receiving chemotherapy and in others, an increase; but both outcomes will result in a more accurate selection of patients."
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Visitor Opinions In Chronological Order (2)
Genomic And Cellular Profiling Tests
posted by Gregory D. Pawelski on 27 Sep 2007 at 10:20 pmThe new genomic tests, Oncotype DX and MammaPrint for breast cancer, and Lung Metagene Predictor for lung cancer, can help find out if a cancer patient will benefit from chemotherapy or not, and if they do (high risk patients), further pre-tests can help see what treatments have the best opportunity of being successful. If patients are low risk, they do not need chemotherapy.
Hopefully, this genetic test will go the same way in telling physicians which high risk colon cancer patients will likely benefit from chemotherapy (identify patients who are likely to have a recurrence if treated with surgery alone) and which ones do not need to be unnecessarily exposed to toxic chemotherapy cocktails.
A number of surgeons are on a campaign to encourage other surgeons to obtain and analyze fresh tissues for both cell culture assay and genetic testing. They look at the results of these assays very carefully in the context of other known prognostic factors and often choose agents based on the patient's profiles.
What needs to be done is to sort out what's the best profile in terms of which patients benefit from this drug or any other drug. Can they be combined? What's the proper way to work with these new drugs?
If a drug works extremely well for a certain percentage of cancer patients, identify which ones. If one drug or another is working for some people (not average populations) then obviously there are others out there who would also benefit.
What's good for the group (population) may not be good for the individual, affirms that in the tactic of using "fresh" biopsied cells to predict which cancer treatments will work best for the individual patient, these "smart" drugs have to get inside the cells in order to "target" anything.
Upgrading clinical therapy by using drug sensitivity assays measuring "cell death" of three dimensional microclusters of live "fresh" tumor cells, 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.
Drug sensitivity tests support the idea that a marginal benefit in terms of overall survival is observed in cancer patients with normal prognoses, but there are marked survival benefits for cancer patients with poor prognoses.
Every cancer patient should have his/her own unique chemotherapy trial based on consultation of pathogenic profiles and drug sensitivity testing data. Having some foreknowledge of a given agent's expected result before its administration would benefit the individual patient.
These are laboratory tests, used as a tool for the oncologist. The oncologist should take advantage of all the tools available to him/her to treat a patient.
Functional Profiling With Cell Culture Assays For Targeted Drug Therapy
posted by Gregory D. Pawelski on 4 Oct 2007 at 10:54 pmFindings presented at the American Society of Clinical Oncology (ASCO) Gastrointestinal Cancers Symposium in Orlando, Florida, January 27, 2007, concluded that Functional Profiling with cell culture assays is relevant for the study of both "conventional" and "targeted" antineoplastic drug agents (antitumor and antiangiogenic activity of gefitinib, erlotinib, sunitinib, sorafenib and bevacizumab in primary cultures of "fresh" human tumors).
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 Funtional 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 Funtional Profiling technique is that it can show this in the "population" of cells.
The Funtional 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.
http://www.asco.org/portal/site/ASCO/menuitem.64cfbd0f85cb37b2eda2be0aee37a01d/?vgnextoid=09f8201eb61a7010VgnVCM100000ed730ad1RCRD&vmview=vm_search_results_view&selectedConfs=&SearchFilter=Speaker&SearchTerm=weisenthal
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