Purpose: Patients with localized esophageal carcinoma have a 5-year survival rate of less than 20%. Patients are often treated similarly (ie, with preoperative chemoradiotherapy) but the outcomes vary greatly. Chemoradiotherapy and surgery can result in significant undesirable consequences. Currently, however, there are no tools to help select optimum therapy. We hypothesized that gene expression profiling could provide clues and biomarkers for selection of therapy. Methods: Pretreatment endoscopic cancer biopsies from 19 patients (16 with adenocarcinoma, two with squamous cell carcinoma, and one with adenosquamous carcinoma) enrolled onto a preoperative chemoradiotherapy protocol were profiled using oligonucleotide microarrays. Surgical specimens following therapy were assessed for the degree of pathologic response. On the basis of array data, selected genes were analyzed by polymerase chain reaction. Results: Unsupervised hierarchical cluster analysis segregated the cancers into two molecular subtypes, each consisting 10 and nine specimens, respectively. Most cancers (five of six) that had pathologic complete response (pathCR) clustered in molecular subtype I. Subtype II, with one exception, consisted cancers that had less than pathCR (< pathCR). Using a combination marker approach, levels of PERP, S100A2, and SPRR3 allowed discrimination of pathCR from < pathCR with high sensitivity and specificity (85%). Pathway analysis identified apoptotic pathway as one of the key functions downregulated in molecular type II in comparison with type I. Conclusion: These encouraging, albeit preliminary, data suggest that expression profiling may distinguish cancers with different pathologic outcome. This is the first report to show subtypes of esophageal cancers with distinct molecular signatures. The potential of PERP, S100A2, and SPRR3 as biomarkers of pathCR warrants further validation.
ASJC Scopus subject areas
- Cancer Research