This study examines the gene expression profiles of 67 human lung tumors from 56 patients using 24,000-element cDNA microarrays. The gene expression patterns accurately reflected the morphological classification of lung tumors into squamous, large cell, small cell, and adenocarcinoma (AC) subtypes. The analysis further allowed the subclassification of AC into subgroups that correlated with tumor differentiation and patient survival. These findings suggest that gene expression analysis can refine and extend standard pathological analysis. Lung cancer is typically classified into four histologic subtypes: squamous, small cell, large cell, and adenocarcinoma. Squamous and small cell tumors account for about 30% and 18% of all lung cancers, respectively, while adenocarcinomas make up 30% and are thought to arise from epithelial cells in the peripheral airways. Large cell tumors, which constitute 10%, are poorly differentiated and diagnosed by exclusion. The study identified gene expression patterns that corresponded to the major morphological classes of lung tumors. For example, squamous cell carcinomas (SCCs) clustered together, and genes characteristic of SCCs were identified. Similarly, small cell lung cancers (SCLCs) and large cell lung cancers (LCLCs) had distinct gene expression profiles. Adenocarcinomas were further subdivided into three groups based on gene expression, with significant differences in patient survival between these groups. The study found that AC group 1 had the best prognosis, while AC group 3 had the worst. AC group 2 had a good prognosis but was more heterogeneous. The gene expression profiles of these subgroups were associated with different clinical outcomes, suggesting that gene expression analysis could provide a more accurate classification of lung tumors than traditional morphological methods. The study also identified specific genes that were characteristic of each AC subgroup. For example, AC group 3 tumors expressed genes associated with tissue remodeling and metastasis. These findings suggest that gene expression patterns can provide insights into the biological behavior of lung tumors and may help in the development of more effective treatments. The study highlights the importance of gene expression analysis in understanding the molecular basis of lung cancer and its progression.This study examines the gene expression profiles of 67 human lung tumors from 56 patients using 24,000-element cDNA microarrays. The gene expression patterns accurately reflected the morphological classification of lung tumors into squamous, large cell, small cell, and adenocarcinoma (AC) subtypes. The analysis further allowed the subclassification of AC into subgroups that correlated with tumor differentiation and patient survival. These findings suggest that gene expression analysis can refine and extend standard pathological analysis. Lung cancer is typically classified into four histologic subtypes: squamous, small cell, large cell, and adenocarcinoma. Squamous and small cell tumors account for about 30% and 18% of all lung cancers, respectively, while adenocarcinomas make up 30% and are thought to arise from epithelial cells in the peripheral airways. Large cell tumors, which constitute 10%, are poorly differentiated and diagnosed by exclusion. The study identified gene expression patterns that corresponded to the major morphological classes of lung tumors. For example, squamous cell carcinomas (SCCs) clustered together, and genes characteristic of SCCs were identified. Similarly, small cell lung cancers (SCLCs) and large cell lung cancers (LCLCs) had distinct gene expression profiles. Adenocarcinomas were further subdivided into three groups based on gene expression, with significant differences in patient survival between these groups. The study found that AC group 1 had the best prognosis, while AC group 3 had the worst. AC group 2 had a good prognosis but was more heterogeneous. The gene expression profiles of these subgroups were associated with different clinical outcomes, suggesting that gene expression analysis could provide a more accurate classification of lung tumors than traditional morphological methods. The study also identified specific genes that were characteristic of each AC subgroup. For example, AC group 3 tumors expressed genes associated with tissue remodeling and metastasis. These findings suggest that gene expression patterns can provide insights into the biological behavior of lung tumors and may help in the development of more effective treatments. The study highlights the importance of gene expression analysis in understanding the molecular basis of lung cancer and its progression.