Detection of ovarian cancer using chemometric analysis of proteomic profiles

Chemometric analysis is used to discriminate between ovarian cancer patients and unaffected controls. In particular, Partial Least Squares–Discriminant Analysis (PLS–DA), and its more recent extension, OPLS–DA, are applied to 100 biopsy-proven cancer patients and 91 controls selected from the Ovarian Dataset 8-7-02 (http://home.ccr.cancer.gov/ncifdaproteomics/ppatterns.asp). Diagnostic models built on a representative training set of approximately 50% of the samples yield both 100% sensitivity and specificity when applied to a blind test set containing the remaining samples. The OPLS–DA model is particularly impressive. The approach presented here, which is widely used in the related field of metabonomics, has the advantage that the entire proteomic profile of 15,154 m/z values is analysed simultaneously in a single step. There is no requirement for prior variable selection or stepwise regression techniques and the results are easily interpretable in terms of simple plots. The most important biomarkers for distinguishing the control and cancer groups have m/z values less than 700.