Prognostic value and computer image analysis of p53 in mantle cell lymphoma

P53 prognostic cut-off values differ between studies of mantle cell lymphoma (MCL), and its immunohistochemistry (IHC) interpretation is still based on semiquantitative estimation, which might be inaccurate. This study aimed to investigate the optimal cut-off value for p53 in predicting prognosis of patients with MCL and the possible use of computer image analysis to identify the positive rate of p53. We calculated p53 positive rate using QuPath software and compared it with the data obtained by manual counting and semiquantitative estimation. Survival curves were generated by using the Youden index and the Kaplan-Meier method. The chi-squared (chi(2)) test was used to compare MIPI, Ann Arbor stage, and cell morphology with p53. Spearman rank correlation test and Bland-Altman analysis were used to compare manual counting, computer image analysis and semiquantitative estimation, as well as the consistency between different observers. The optimal cut-off value of p53 for predicting prognosis was 20% in MCL patients. Patients with p53 >= 20% had a significantly worse overall survival (OS) than those with p53 <20% (P < 0.0001). MCL patients with MIPI intermediate to high risk, Ann Arbor stage III-IV and blastoid/pleomorphic variant cell morphology had more p53 >= 20%. There was a strong correlation between computer image analysis and manual counting of p53 from the same areas in MCL tissues (Spearman's rho = 0.966, P < 0.0001). The results of computer analysis are completely consistent between observers, and computer image analysis of Ki-67 can predict the prognosis of MCL patients. MCL patients with p53 >= 20% had a shorter OS and a tendency for MIPI intermediate to high risk, Ann Arbor stage III-IV, and blastoid/pleomorphic variant. Computer image analysis could determine the actual positive rate of p53 and Ki-67 and is a more attractive alternative than semiquantitative estimation in MCL.

Automated summary

This study aimed to investigate the optimal cut-off value for p53 in predicting prognosis of MCL patients and the feasibility of using computer image analysis to determine the positive rate of p53. The results showed that setting the cut-off value of p53 at 20% can effectively predict the prognosis of MCL patients. Additionally, computer image analysis can replace semiquantitative estimation and has better prospects in MCL.