CHAPEL HILL -- A new study has identified three subtypes of non-small-cell lung cancer tumors, a finding that may provide valuable clinical information about patient survival in early- or late-stage disease, how likely the cancer is to spread and whether the tumor will prove resistant to chemotherapy.
A report of the study, led by researchers at the University of North Carolina at Chapel Hill's Lineberger Comprehensive Cancer Center, appears in the November issue of the Journal of Clinical Oncology.
Currently, lung cancer treatment decisions are based largely on the location and size of the tumor and if it has spread, or metastasized. And, lung tumor cells are diagnosed by their appearance under a microscope. About 20 percent of these tumors are classified as small-cell carcinomas; the rest fall into a catch-all diagnosis, non-small-cell carcinoma (NSCLC), for which therapies often lead to unpredictable results.
"We are frequently surprised with the range of responses that our patients' non-small-cell carcinomas have. Some are very responsive to treatment, some metastasize early, and we have no way of sorting this out up front," said study lead author Dr. David Neil Hayes, assistant professor of medicine in the division of hematology/oncology in UNC's School of Medicine. To that end, Hayes and his colleagues used a relatively new technology, DNA microarray analysis, which allows researchers to identify a tumor's genetic pattern.
"We found that among patients who have tumors that look similar under a microscope there are dramatically different gene expression patterns," Hayes said. "But what's more interesting is that we see evidence that these genetic patterns are associated with significant differences in tumor behavior, which could not be anticipated by any conventional testing method."
The tumor subtypes, named bronchioid, squamoid and magnoid, according to their genetic pattern, also correlated with clinically relevant events, such as stage-specific survival and metastatic pattern.
For example, bronchioid tumors were associated with the likelihood of improved survival in early-stage disease, while squamoid tumors were associated with better survival in advanced disease.
And although some early-stage bronchioid tumors appear less likely to spread to the brain, they also may be the same tumors that are least likely to respond to chemotherapy because they express many genes associated with resistance to common chemotherapy agents.
"While this is still very preliminary, we hope to take these gene expression patterns and attempt to define a very simple, reproducible system that will allow us to unravel the complex patterns of how the tumors progress and how they respond to therapy," Hayes said.
"If we can pigeonhole these tumors right from the start, then we can become much more rational in our decision making for treatment and our ability to tell patients what to anticipate in terms of their risk, likelihood of recurrence and response to therapy," Hayes said. "That's the goal."
The new study evaluated lung cancer DNA microarray data sets from the University of Michigan, Stanford University and the Dana-Farber Cancer Institute in Boston, Mass. A total of 231 microarrays, each with 2,553 genes were analyzed. Hayes and his colleagues noted that the three new subtypes were robust and could be found frequently. All were identified in each of the data sets.
Embargoed until 6:00 p.m. EST Oct. 30, 2006
Co-authors on the study were Dr. Mark A. Socinski and Dr. Charles Perou from UNC's Lineberger Comprehensive Cancer Center; Drs. Mathew Meyerson, Katsuhiko Naoki and Arindam Bhattacharjee from the Dana-Farber Cancer Institute and Harvard Medical School; Dr. Stefano Monti from the Massachusetts Institute of Technology; and Dr. Giovanni Parmigiani from the Johns Hopkins University School of Medicine.
Funding for the research came from the Director's Challenge Program of the National Cancer Institute, part of the National Institutes of Health.
UNC School of Medicine contact: Les Lang
UNC Lineberger Center contact: Dianne Shaw, (919)-966-7834, firstname.lastname@example.org
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