- Microarray analysis reliably characterizes lung cancer
Adenocarcinomas are the most common type of lung cancer. They have distinct biochemical and histologic features. Although panels of experts have classified them into subtypes based on their histologic features, little evidence supports the reliability of existing morphologic classification schemes. In clinical practice, such detailed classification is consequently ignored. DNA microarrays promise to precisely identify tumors, but results of microarray studies can vary considerably.
Dr. D. Neil Hayes and colleaques at the University of North Carolina at Chapel Hill have reviewed three microarray studies from the University of Michigan, Stanford University and the Dana-Farber Cancer Institute. In this review, they statistically analyzed the studies to find similarities in gene expression. They identified three new subtypes that can be recognized by DNA microarrays and called them bronchoid, squamoid and magnoid.
The studies involved patients of a similar demographic. Each study used a single brand or type of microarray, and the reviewers examined only genes that were present in all three microarrays.
The reviewers statistically selected 231 microarray runs, each for a separate adenocarcinoma. That number included 31 Stanford, 72 Michigan and 128 Dana-Farber adenocarcinomas. Of those tumors, they found 2553 genes that reliably represented adenocarcinomas.
They further analyzed the reliable genes and grouped them into the bronchoid, squamoid and magnoid subtypes. Hundreds of genes accurately differentiated each of these subtypes. They correlated with factors that include the likelihood of survival at each cancer stage and the probability and location of metastasis. In particular, patients with bronchoid tumors tended to fare better with early-stage cancer, whereas those with squamoid tumors had a greater chance of survival after their cancer became more advanced. The reviewers concluded that their classification scheme reliably characterizes adenocarcinomas. (Journal of Clinical Oncology, Nov. 1, 2006, pp. 5079-5090).
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