Literature DB >> 35918462

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

Yue-Hua Zhang1, Li-Min Gao2, Xiao-Yu Xiang1, Wen-Yan Zhang1, Wei-Ping Liu3.   

Abstract

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 (χ2) 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.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Computer image analysis; Mantle cell lymphoma; P53; Prognosis

Mesh:

Substances:

Year:  2022        PMID: 35918462     DOI: 10.1007/s00277-022-04922-8

Source DB:  PubMed          Journal:  Ann Hematol        ISSN: 0939-5555            Impact factor:   4.030


  15 in total

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Journal:  Blood       Date:  2007-10-25       Impact factor: 22.113

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Journal:  Blood       Date:  2017-12-01       Impact factor: 22.113

7.  SOX11 and TP53 add prognostic information to MIPI in a homogenously treated cohort of mantle cell lymphoma--a Nordic Lymphoma Group study.

Authors:  Lena Nordström; Sandra Sernbo; Patrik Eden; Kirsten Grønbaek; Arne Kolstad; Riikka Räty; Marja-Liisa Karjalainen; Christian Geisler; Elisabeth Ralfkiaer; Christer Sundström; Anna Laurell; Jan Delabie; Mats Ehinger; Mats Jerkeman; Sara Ek
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8.  QuPath: Open source software for digital pathology image analysis.

Authors:  Peter Bankhead; Maurice B Loughrey; José A Fernández; Yvonne Dombrowski; Darragh G McArt; Philip D Dunne; Stephen McQuaid; Ronan T Gray; Liam J Murray; Helen G Coleman; Jacqueline A James; Manuel Salto-Tellez; Peter W Hamilton
Journal:  Sci Rep       Date:  2017-12-04       Impact factor: 4.379

9.  Prognostic significance of p53, Sox11, and Pax5 co-expression in mantle cell lymphoma.

Authors:  Caixia Jing; Yuhuan Zheng; Yu Feng; Xia Cao; Caigang Xu
Journal:  Sci Rep       Date:  2021-06-07       Impact factor: 4.379

10.  p53 is associated with high-risk and pinpoints TP53 missense mutations in mantle cell lymphoma.

Authors:  Joana M Rodrigues; May Hassan; Catja Freiburghaus; Christian W Eskelund; Christian Geisler; Riikka Räty; Arne Kolstad; Christer Sundström; Ingrid Glimelius; Kirsten Grønbaek; Anna Kwiecinska; Anna Porwit; Mats Jerkeman; Sara Ek
Journal:  Br J Haematol       Date:  2020-08-04       Impact factor: 8.615

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