Background: The aim of this study was to correlate immunostaining expression profiles with histological grade using a predictive model.
Patients and methods: Samples were collected from 69 women with endometrial cancer. Immunostaining for expression of estrogen receptor (ER), progesteron receptor (PR), Ki67 and p53 in grade 1 or 2 and grade 3 tumors were compared. After determining optimal immunostaining cut-offs, we built a model to predict the final histological grade.
Results: Higher immunostaining of ER and PR was found in grade 1 or 2 (p=0.01) compared with grade 3 tumors. Higher immunostaining for Ki67 (p<0.0001) and p53 (p<0.001) was found in grade 3 than in grade 1 or 2 tumors. The recursive partitioning model predicted a grade 1 or 2 tumor in 98% of cases when Ki67 and p53 were underexpressed. The mis-classification rate was 13%.
Conclusion: Our results show that integrating immunohistochemical profiles in a simple predictive model could help predict the final histological grade of endometrial tumors, especially for grade 1 or 2.
Keywords: Endometrial cancer; Ki67; estrogen receptor; histological grade; immunohistochemistry; p53; predictive model; progesteron receptor.