In a new clinical trial for prostate cancer, scientists will capture rare tumor cells circulating in patients’ blood, analyze them using a specialized microchip, and use the results to try to predict how well the patient will respond to a drug. The trial reflects a new phase of personalized medicine for cancer, enabled by microfluidics technologies that can isolate scarce cancer cells and detect very small changes in gene expression. Physicians ultimately hope these chips can become a routine part of clinical care for cancer. “We need to be able to profile the tumor at the time we are considering treatment,” says Howard Scher, chief of the Genitourinary Oncology Service at Memorial Sloan-Kettering Cancer Center, where the trial will take place.
The study will focus on men with a difficult to treat form of prostate cancer that has failed to respond to other therapies. Changes in gene expression might help determine whether a specific drug will be effective–for example, if a patient has high levels of a receptor for androgen hormones, a drug that inhibits signaling of that receptor is more likely to work well. “We want to know why they don’t respond to therapy and what therapies would be best for them,” says Martin Fleisher, chairman of the Department of Clinical Laboratories at Sloan. “We collect tumor cells from blood, and do a gene analysis to find out what genes are overexpressed and whether or not they would be candidates for certain types of targeted therapies that would beat down their cancer.”
The effectiveness of different cancer drugs can vary based on the molecular characteristics of the cancer, such as the presence of a certain hormone or genetic mutation. Physicians already do some molecular analysis of cancer tissue to select the best drug for a patient. Herceptin, for example, is used to treat breast cancer in women with a particular protein in their tumors. And lung cancer patients with a mutation in the gene for the epidermal growth factor receptor are more likely to respond to a drug called Iressa than patients without it. But these treatments are chosen based on analysis from tumor biopsies, which isn’t always possible.
Analyzing tumor cells in blood presents two major challenges. Tumor cells are found at very low concentrations in the blood–about one in ten million cells–making it difficult to isolate them. And the small numbers of cells must be analyzed in very low volumes. In the last year, Sloan scientists and others have developed ways to capture these cells using antibodies that detect a molecular marker present only in cancer cells.
In the new Sloan study, scientists face an even more challenging problem–they must detect differences in gene expression, rather than a specific genetic mutation, such as the mutation linked to Iressa responsiveness in lung cancer. Scher and collaborators will use a microfluidics chip made by Fluidigm, a South San Francisco, CA- based company . DNA from each cell is filtered into one of 96 tiny channels on one side of the chip, while reagents flow in from 96 channels on the other side. A precise plumbing system then combines the molecules in different combinations, generating about 9,000 simultaneous reactions. Each reaction takes a volume of just nanoliters–about the size of a period–rather than the microliter volume typical of most commercial fluidics devices. The chip, which costs about $300, “can detect differences in gene expression that are as subtle as twofold with very good accuracy,” says Gajus Worthington, Fluidigm’s president, CEO, and co-founder.
Researchers plan to analyze levels of about 30 genes in each patient, including genes involved in production of testosterone and in cell signaling. Expression of these genes has been shown in animal models to predict how well a tumor will respond to a drug called dasatinib, which is approved for treatment of chronic myelogenous leukemia and in late stage clinical trials for prostate cancer.
The microfluidics technology could also be used to examine other properties of tumor cells. Scientists might look for changes in gene expression that suggest a cancer has metastasized, or whether a tumor has evolved specific mutations that make it resistant to specific drugs.
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