Lung cancer staging in the genomics era

The search for clinically applicable biologic markers or tumor signatures sufficiently powered as prognosticators of tumor behaviors or responses to therapeutic interventions has significantly advanced in scope and sophistication in the last 10 years. The TNM system, examining of tumor tissues to identify histopathologic features that could be correlated with tumor biology and outcome, could be improved by the immunohistochemical assessment of individual marker proteins or painstaking sequencing of candidate genes (one at a time) from tumor tissues. Large-scale investigation of the gene or protein expression profiles using genomics or proteomics technology may further improve risk stratification and assessment of therapeutic response. Although the gene expression profiling studies summarized in this article are exciting and initially serve as proofs of concept that large-scale mining of the genome and the transcriptome yields clinically useful data, the technology is still evolving and standardization is still needed for large-scale studies and data validation. As a proof of principle, studies have been performed to demonstrate that it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study, and to demonstrate significant, albeit incomplete, agreement of gene expression patterns related to lung cancer biology and predictive of treatment outcomes via cross-study comparative analysis. Leading the concerted efforts of molecular characterization of lung cancer is the National Cancer Institute Director's Challenge Program: Toward A Molecular Classification of Cancer. The ultimate goal of molecular staging, envisioned as a combination of traditional TNM classification bolstered with gene/protein unique expression signatures, is to classify patients who have lung cancer on the basis of tumor biology, for better risk stratification and treatment using targeted patient-tailored therapeutics based on unique genotypes of individual tumors.