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Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts
Published on: April 29, 2014
A histology-based model for predicting microsatellite instability in colorectal cancers
Angela Hyde1, Daniel Fontaine, Susan Stuckless
1Discipline of Genetics, Memorial University of Newfoundland, St John's, Newfoundland, Canada.
The American Journal of Surgical Pathology
|November 26, 2010
Summary
A new model, PREDICT, accurately identifies high microsatellite instability (MSI-H) colorectal cancers (CRCs) using histology. PREDICT outperforms existing methods, aiding in prognosis and Lynch syndrome identification.
Area of Science:
- Oncology
- Pathology
- Genetics
Background:
- High microsatellite instability (MSI-H) in colorectal cancers (CRCs) is clinically significant for prognosis, chemotherapy response, and Lynch syndrome identification.
- Existing predictive models for MSI-H CRCs have limitations in accuracy and scope.
Purpose of the Study:
- To compare and improve existing pathology models for predicting MSI-H CRCs.
- To develop a novel histological model for MSI-H CRC prediction.
Main Methods:
- Two existing models (Revised Bethesda Guidelines, MsPath) and novel histological features were evaluated in a CRC cohort (N=710).
- A new model, PREDICT (Pathologic Role in Determination of Instability in Colorectal Tumors), was developed incorporating new features.
- PREDICT was validated in an independent CRC cohort (N=276).
Main Results:
- Tumor histology proved a superior predictor of MSI status compared to personal/family cancer history.
- PREDICT demonstrated higher sensitivity and specificity (97.4%, 53.9% in development; 96.9%, 76.6% in validation) than MsPath and Revised Bethesda Guidelines.
- Histological features like peritumoral lymphocytic reaction and plasma cell infiltration were key in PREDICT.
Conclusions:
- PREDICT is a superior histological model for identifying MSI-H CRCs.
- The developed model enhances the ability to predict MSI status, aiding clinical management and genetic counseling.
