Nov. 19, 2001 STANFORD, Calif. - Researchers at the Stanford University Medical Center have uncovered a group of genes that could distinguish between different forms of lung cancer. This finding may help doctors predict individual treatment strategies and may someday lead to better lung cancer drugs.
"What this means is that we can distinguish between different types of lung cancers, which was not possible before, and that those differences have clinical consequences," said David Botstein, MD, professor of genetics and senior author on the study, published in the Proceedings of the National Academy of Sciences on Nov. 13.
Doctors currently categorize lung tumors into one of four types: small cell, squamous cell, large cell and adenocarcinoma. When doctors diagnose a small-cell tumor, they can provide a fairly accurate prognosis. But other tumor types, particularly adenocarcinomas, respond very differently to standard treatment.
"Lung adenocarcinomas may appear morphologically similar, however, the patients differ in survival and possibly drug sensitivity," said Mitchell Garber, a post-doctoral student and first author on the paper. "At present, the pathologist cannot determine patient survival for those diagnosed with adenocarcinoma."
Garber thought these differences may arise from gene variations within the tumor. If that's the case, doctors would have an additional tool for distinguishing how tumors will grow, helping to determine the best course of treatment for each patient. "The short-term goal is to know the fingerprint of a tumor that has a poor prognosis," Garber said. "That will give the clinician an incentive to look a little harder within this patient for additional tumors."
To find out whether genetic differences exist between lung tumors, Garber obtained RNA from 67 lung tumor samples and six normal lung samples. RNA is produced by active genes and can be used to identify which genes are being expressed in a given sample. He then exposed the RNA samples to a gene chip - a glass slide dotted with 17,108 human genes. If a sample contained RNA corresponding to a gene on the chip, the RNA would bind to the spot and produce a visible signal. The bigger the signal, the more RNA, and therefore the more gene expression. With this technique, Garber grouped his samples according to those that expressed a similar subset of genes.
In most cases, samples that had been assigned to the same category by light microscopy also fell into the same genetic grouping. The adenocarcinoma samples, however, fell into three distinct genetic subtypes. Patients within those subtypes had different outcomes, so knowing a subtype can give doctors useful information about how the cancer will progress. Patients with a subtype 1 tumor had about 40 percent survival over a five-year period, whereas none of the patients with subtype 3 survived during that same period. All patients with subtype 2 tumors were still alive at the end of the study.
Garber said that tumors in subtypes 1 and 3 were initially diagnosed with different stages of the disease. Those in subtype 3 all had more advanced tumors while those in subtype 1 had less advanced tumors, consistent with the survival rates of the two groups. However, those in subtype 2 had a mixture of more advanced and less advanced tumors. Without the genetic analysis, doctors would not have classified these patients in similar subtypes, nor would they have predicted survival.
Botstein said this ability to distinguish between lung tumors could help doctors target therapy. "For those in the subset lucky enough not to have such serious disease, you may want to consider a much less toxic treatment option," he said.
He noted that while adenocarcinomas account for 30 percent of all lung tumors, they comprise 56 percent of lung samples in this study. He predicts that a larger, more representative trial would uncover similar genetic subtypes within other tumor categories.
In addition to predicting a tumor's seriousness, future drug trials can test the drug's effect in the different genetic subtypes. "A treatment may work on one subtype but not on another," Botstein said. "You could see some application of this sooner rather than later."
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