Molecular staging for survival prediction of colorectal cancer patients

Abstract

Purpose: The Dukes' staging system is the gold standard for predicting colorectal cancer prognosis; however, accurate classification of intermediate-stage cases is problematic. We hypothesized that molecular fingerprints could provide more accurate staging and potentially assist in directing adjuvant therapy.

Methods: A 32,000 cDNA microarray was used to evaluate 78 human colon cancer specimens, and these results were correlated with survival. Molecular classifiers were produced to predict outcome.

Results: Molecular staging, based on 43 core genes, was 90% accurate (93% sensitivity, 84% specificity) in predicting 36-month overall survival in 78 patients. This result was significantly better than Dukes' staging (P = .03878), discriminated patients into significantly different groups by survival time (P < .001, log-rank test), and was significantly different from chance (P < .001, 1,000 permutations). Furthermore, the classifier was able to discriminate a survival difference in an independent test set from Denmark. Molecular staging identifies patient prognosis (as represented by 36-month survival) more accurately than the traditional clinical staging, particularly for intermediate Dukes' stage B and C patients. The classifier was based on a core set of 43 genes, including osteopontin and neuregulin, which have biologic significance for this disease.

Conclusion: These data support further evaluation of molecular staging to discriminate good from poor prognosis patients, with the potential to direct adjuvant therapy.