Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses
Abstract
We have generated a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, we analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct subclasses of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.
Carcinoma of the lung claims more than 150,000 lives every year in the United States, thus exceeding the combined mortality from breast, prostate, and colorectal cancers (1). The current lung cancer classification is based on clinicopathological features. More fundamental knowledge of the molecular basis and classification of lung carcinomas could aid in the prediction of patient outcome, the informed selection of currently available therapies, and the identification of novel molecular targets for chemotherapy. The recent development of targeted therapy against the Abl tyrosine kinase for chronic myeloid leukemia illustrates the power of such biological knowledge (2).
Lung carcinomas are usually classified as small-cell lung carcinomas (SCLC) or non-small-cell lung carcinomas (NSCLC). Neuroendocrine features, defined by microscopic morphology and immunohistochemistry, are hallmarks of the high-grade SCLC and large-cell neuroendocrine tumors and of intermediate/low-grade carcinoid tumors (3). NSCLC is histopathologically and clinically distinct from SCLC, and is further subcategorized as adenocarcinomas, squamous cell carcinomas, and large-cell carcinomas, of which adenocarcinomas are the most common (3).
The histopathological subclassification of lung adenocarcinoma is challenging. In one study, independent lung pathologists agreed on lung adenocarcinoma subclassification in only 41% of cases (4). However, a favorable prognosis for bronchioloalveolar carcinoma (BAC), a histological subclass of lung adenocarcinoma, argues for refining such distinctions (5, 6). In addition, metastases of nonlung origin can be difficult to distinguish from lung adenocarcinomas (7, 8).
The development of microarray methods for large-scale analysis of gene expression (9–12) makes it possible to search systematically for molecular markers of cancer classification and outcome prediction in a variety of tumor types (13–19). Currently, the only effective prognostic indicator for NSCLC in clinical use is surgical–pathological staging (20). However, the simultaneous analysis of a large number of independent clinical markers may offer a powerful adjunct approach in surgical–pathological staging.
Here we report a gene expression analysis of 186 human carcinomas from the lung, in which we provide evidence for biologically distinct subclasses of lung adenocarcinoma.
Click here to view.Acknowledgments
We offer special thanks to David Livingston, who has stimulated and coordinated this project funded by U01 CA84995 from the National Cancer Institute. The work was also supported in part by Millennium Pharmaceuticals, Affymetrix, and Bristol-Myers Squibb. M.M. is a Pew Scholar in the Biomedical Sciences.
Abbreviations
SCLC | small-cell lung carcinomas |
NSCLC | non-small-cell lung carcinomas |
CM | colon metastases |
BAC | bronchioloalveolar carcinoma |
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