Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Rational Manual and Automated Scoring Thresholds for the Immunohistochemical Detection of TP53 Missense Mutations in Human Breast Carcinomas

Rational Manual and Automated Scoring Thresholds for the Immunohistochemical Detection of TP53... Missense mutations in TP53 are common in human breast cancer, have been associated with worse prognosis, and may predict therapy effect. TP53 missense mutations are associated with aberrant accumulation of p53 protein in tumor cell nuclei. Previous studies have used relatively arbitrary cutoffs to characterize breast tumors as positive for p53 staining by immunohistochemical assays. This study aimed to objectively determine optimal thresholds for p53 positivity by manual and automated scoring methods using whole tissue sections from the Carolina Breast Cancer Study. p53-immunostained slides were available for 564 breast tumors previously assayed for TP53 mutations. Average nuclear p53 staining intensity was manually scored as negative, borderline, weak, moderate, or strong and percentage of positive tumor cells was estimated. Automated p53 signal intensity was measured using the Aperio nuclear v9 algorithm combined with the Genie histology pattern recognition tool and tuned to achieve optimal nuclear segmentation. Receiver operating characteristic curve analysis was performed to determine optimal cutoffs for average staining intensity and percent cells positive to distinguish between tumors with and without a missense mutation. Receiver operating characteristic curve analysis demonstrated a threshold of moderate average nuclear staining intensity as a good surrogate for TP53 missense mutations in both manual (area under the curve=0.87) and automated (area under the curve=0.84) scoring systems. Both manual and automated immunohistochemical scoring methods predicted missense mutations in breast carcinomas with high accuracy. Validation of the automated intensity scoring threshold suggests a role for such algorithms in detecting TP53 missense mutations in high throughput studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Immunohistochemistry & Molecular Morphology Wolters Kluwer Health

Rational Manual and Automated Scoring Thresholds for the Immunohistochemical Detection of TP53 Missense Mutations in Human Breast Carcinomas

Loading next page...
 
/lp/wolters-kluwer-health/rational-manual-and-automated-scoring-thresholds-for-the-a1mKMJnXE7

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Wolters Kluwer Health
Copyright
Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
ISSN
1062-3345
eISSN
1533-4058
DOI
10.1097/PAI.0000000000000207
pmid
26200835
Publisher site
See Article on Publisher Site

Abstract

Missense mutations in TP53 are common in human breast cancer, have been associated with worse prognosis, and may predict therapy effect. TP53 missense mutations are associated with aberrant accumulation of p53 protein in tumor cell nuclei. Previous studies have used relatively arbitrary cutoffs to characterize breast tumors as positive for p53 staining by immunohistochemical assays. This study aimed to objectively determine optimal thresholds for p53 positivity by manual and automated scoring methods using whole tissue sections from the Carolina Breast Cancer Study. p53-immunostained slides were available for 564 breast tumors previously assayed for TP53 mutations. Average nuclear p53 staining intensity was manually scored as negative, borderline, weak, moderate, or strong and percentage of positive tumor cells was estimated. Automated p53 signal intensity was measured using the Aperio nuclear v9 algorithm combined with the Genie histology pattern recognition tool and tuned to achieve optimal nuclear segmentation. Receiver operating characteristic curve analysis was performed to determine optimal cutoffs for average staining intensity and percent cells positive to distinguish between tumors with and without a missense mutation. Receiver operating characteristic curve analysis demonstrated a threshold of moderate average nuclear staining intensity as a good surrogate for TP53 missense mutations in both manual (area under the curve=0.87) and automated (area under the curve=0.84) scoring systems. Both manual and automated immunohistochemical scoring methods predicted missense mutations in breast carcinomas with high accuracy. Validation of the automated intensity scoring threshold suggests a role for such algorithms in detecting TP53 missense mutations in high throughput studies.

Journal

Applied Immunohistochemistry & Molecular MorphologyWolters Kluwer Health

Published: Jul 1, 2016

References