Background: Despite expected excellent outcomes of surgical resection for early stage rectal cancers, 20% of stage I and II rectal cancers recur. Identifying biologic factors that predict the subset prone to recur could allow more directed therapy. This study identifies a tumor gene expression profile that accurately predicts disease recurrence. Study Design: Stage I/II rectal cancer patients treated by surgery alone at a single institution were included and classified as having recurrent or nonrecurrent cancer. Tumor mRNA was isolated from frozen tissue and evaluated for total genome gene expression by microarray analysis. Background-corrected and normalized microarray data were analyzed using BAMarray software. Selected genes were further analyzed using unsupervised clustering and nearest-centroid classification. A balanced K-fold scoring-pair algorithm using 1,000 independent replications was used for gene signature development. Results: Sixty-nine patients with disease-free survival and 31 patients with recurrent disease were included at a median follow-up of 105 months (interquartile range 114 months) and 32 months (interquartile range 25 months), respectively. Demographics and tumor characteristics between groups were similar. Fifty-two genes from 43,148 probes were differentially expressed, and a 36-gene signature was found to be statistically associated with recurrence using a scoring-pair algorithm. Accuracy to identify recurrence as measured by area under the receiver operating characteristic curve was 0.803. Conclusions: Differential gene expression within rectal cancers is associated with recurrence of early stage disease. A 36-gene signature correlates with an increased risk of more or less aggressive tumor behavior. This information obtainable at biopsy may assist in determining treatment decisions.
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