Comparing Aperio and QuPath in the Quantitative Analysis of p53 Immuno Histochemistry in Primary and Metastatic Sarcomas
Bastaic DJ*, Sandusky GE, Rushing D and Baldridge L
ABSTRACT
Soft tissue sarcomas are rare, aggressive malignancies arising from mesenchymal tissues and account for a significant proportion of pediatric cancers. The tumor suppressor protein p53 plays a central role in maintaining genomic stability by regulating cell cycle arrest, DNA repair, and apoptosis. Mutations in TP53 are common in sarcomas and are associated with tumor progression and adverse outcomes. This study evaluated p53 expression in 50 clinical sarcoma specimens, including 28 primary tumors and 22 metastatic lung tumors, using immunohistochemistry and compared quantitative results generated by two digital pathology platforms, Aperio and QuPath. Slides were stained using the DAKO FLEX system and scanned at 20× magnification. Aperio analysis utilized the Positive Pixel Count (V9) algorithm, while QuPath employed a machine learning–based cellular segmentation classifier. Aperio reported p53 positivity rates of 4.83% in primary tumors and 4.65% in metastatic tumors, whereas QuPath detected higher rates of 16.70% and 15.64%, respectively. These findings suggest that segmentation methodology significantly influences quantitative biomarker detection and highlight the importance of platform selection in digital pathology research.
