Molecular Staging and the Selection of Therapy for Non-Small Cell Lung Cancer

Prognostic significance of global histone modifications in resected squamous cell carcinoma of the esophagus

Patterns of global histone modifications have been recently suggested as outcome predictors in cancer patients. To date, there has been no report on the prognostic significance of global histone modifications in esophageal squamous cell carcinoma. We investigated the role of global histone modification as outcome predictor in patients undergoing esophagectomy for esophageal squamous cell carcinoma. A retrospective clinicopathologic analysis was undertaken of 97 patients with esophageal squamous cell carcinoma who recovered from esophagectomy. Immunohistochemical expression of five histone modification markers, acetylated histone 3 lysine 18 (H3K18Ac), acetylated histone 4 lysine 12 (H4K12Ac), dimethylated histone 4 arginine 3 (H4R3diMe), dimethylated histone 3 lysine 4 (H3 K4diMe), and trimethylated histone 3 lysine 27 (H3K27triMe) was assessed in paraffin-embedded tumor samples. Results were analyzed in relation to patients' clinicopathologic parameters. There was a positive relationship between tumor differentiation and H3K18Ac (P<0.001), H4R3diMe (P=0.003), and H3K27triMe (P<0.001). Expression of H3K27triMe correlated positively with nodal (N) status (P=0.012) and stage (P=0.025). Univariate analysis showed that better survival in patients with low expression of H3K18Ac (P=0.038) and H3K27triMe (P=0.003). Multivariate analysis showed that nodal status, metastasis status (M), and expression of H3K27triMe predicted survival independently (P<0.001, P=0.016, and 0.048, respectively). Low expression of H3K18Ac and H3K27triMe correlated with better prognosis of patients with esophageal squamous cell carcinoma, especially for those of early stages. We hypothesize that expression of H3K27triMe may be considered as a significant survival predictor for patients with esophageal squamous cell carcinoma.

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.