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New, targeted cancer therapies focus on specific genetic mutations in the patient’s body in order to fight the disease. These therapies usually also have fewer side-effects than conventional chemotherapy. However, cancer is a complex, dynamic and unpredictable disease with a wide array of embodimentsat the molecular level. For this reason, no single treatment is effective against every type of tumor. In order to effectively treat cancer we need to understand the biological mechanisms behind it. Since every cancer tumor is unique, doctors struggle to find the most suitable personalized treatment plan for each patient. Currently, they rely mostly on their instincts and personal experience to choose the appropriate treatment methods.
Dr. Eric Lester, of the Oncology Care Associates in St. Joseph, Michigan, devised an experiment that illustrates the promise of personalized medicine. He had six patients with advanced, incurable cancer. In order to determine which anti-cancer drugs would benefit each patient, Lester analyzed his patients’ tumors, seeking the expression of genes associated with responsiveness to various anti-cancer drugs. He then based his drug treatment plans on the experiment’s findings.
To analyze gene expression in the tumors Dr. Lester used Affymetrix’s DNA micro-arrays, which are small chips used to measure genetic information on a large scale. Affymetrix’s gene chips can be tagged with hundreds of thousands of gene sequences that will either attract or repel pieces of DNA or RNA from a certain sample. The attraction or repulsion of the DNA and RNA indicate gene mutations (genotype testing) or gene activity patterns (expression testing) in the sample.
Dr. Lester and Craig Webb, Ph.D., Director of Translational Medicine at the Van Andel Research Institute in Grand Rapids, Michigan, surveyed the scientific literature and compiled a list of genes whose expression levels may predict responsiveness to certain drugs against a type of tumors. Webb and Lester compared the tested patients’ personal micro-array results to the pharmaceutical and genomic data bases and determined an individualized treatment plan for each patient. More information on Lester’s study can be found on the Van Andel Research Institute website and on the American Association for Cancer Research website. In some cases, after analyzing the information derived from the chips, the doctors suggested completely different treatment strategies for patients with the same type of cancer.
Out of six patients with advanced cancer that participated in this limited study, four responded better than was expected. This may suggest that a personalized molecular oncology approach, basing chemotherapy on relative gene expression in the tumors, holds a promise even for patients with incurable cancer. However, is it too early to draw unequivocal conclusions regarding the benefits and effectiveness of the new approach. In order to establish the results of this experiment, studies should be held on a large scale and over a long period, in a manner that will enable monitoring the therapy’s comprehensive influence on the patients’ health and life span.
TFOT recently covered a couple of other research projects dealing with chips for detection of cancer biomarkers. These chips include the “lab on a chip” device enabling detection of oral cancer cells, developed at the Texas University, and the Nanocytometer, which locates cancer cells or other specific cells in the blood, developed at the University of California, Berkeley.
Further discussion of personalized gene-chip based treatment can be found in the TFOT forums.
