The genes used in this classifier were selected by performing Cox regression analysis on gene expression and clinical data from a large series of stage
1-4 colon cancer patients.
A predictive algorithm was trained
using information from the 163 genes found to be related to patient outcome.
This algorithm was then applied to genomic profile data from independent
validation cohort of stage 2 and 3 colon cancer. The highly significant
results reveal that ColonPRS is a powerful and accurate predictor of
Multivariate analysis indicates that the classifier is able to identify
patients at high or low risk of relapse, independent to age, gender, stage and grade.
The output of the 163-gene algorithm is a unique prognostic index (range: -2.0 to
+2.0) that correlates with increased risk of recurrence.
A gene expression heatmap of the 163-gene signature in data from 151 colon cancer
patients. Red = high gene expression, Green = low gene expression.
Patients/rows are ordered by increasing prognostic Index, as determined by each
patient's expression of the 163 gene set. Recurrence events (within 5 years)
are indicated to the right of the heatmap and can be seen to increase in frequency
proportional to the prognostic index. the prognostic index.
Van Laar, R.K., An online gene expression assay for determining adjuvant therapy
eligibility in patients with stage 2 or 3 colon cancer.
British Journal of Cancer (2010) [Link]
Kaplan Meier analysis of the predicted risk groups for the 163-gene classifier applied
to the training and validation series are shown below. Each series is analyzed by
clinical stage and then by the combination of clinical stage and gene expression
Multivariate analysis of risk group predictions revealed that individuals with a
high-risk colon tumor (according to the 163-gene prognostic index) is at ~3-4 times
greater risk of disease recurrence and disease-specific death during the 5 year
period following initial treatment.
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