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.
Graphical abstract
Similar content being viewed by others
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- MCL:
-
Mantle cell lymphoma
- OS:
-
Overall survival
- χ2:
-
Chi-squared
- NHL:
-
Non-Hodgkin lymphoma
- MIPI:
-
Mantle cell lymphoma prognostic index
- IHC:
-
Immunohistochemistry
- WHO:
-
World Health Organization
- EDTA:
-
ethylenediaminetetraacetic acid
- DAB:
-
diaminobenzidine
- AUC:
-
area under the ROC curve
- NA:
-
not applicable
- CI:
-
confidence interval
References
Jain P, Wang M (2019) Mantle cell lymphoma: 2019 update on the diagnosis, pathogenesis, prognostication, and management. Am J Hematol 94(6):710–725. https://doi.org/10.1002/ajh.25487
Hermine O, Hoster E, Walewski J, Bosly A, Stilgenbauer S, Thieblemont C, Szymczyk M, Bouabdallah R, Kneba M, Hallek M, Salles G, Feugier P, Ribrag V, Birkmann J, Forstpointner R, Haioun C, Hänel M, Casasnovas RO, Finke J, Peter N, Bouabdallah K, Sebban C, Fischer T, Dührsen U, Metzner B, Maschmeyer G, Kanz L, Schmidt C, Delarue R, Brousse N, Klapper W, Macintyre E, Delfau-Larue MH, Pott C, Hiddemann W, Unterhalt M, Dreyling M (2016) Addition of high-dose cytarabine to immunochemotherapy before autologous stem-cell transplantation in patients aged 65 years or younger with mantle cell lymphoma (MCL Younger): a randomised, open-label, phase 3 trial of the European Mantle Cell Lymphoma Network. Lancet (London, England) 388(10044):565–575. https://doi.org/10.1016/s0140-6736(16)00739-x
X-q LI, G-d LI, Z-f GAO, X-g ZHOU, X-z ZHU (2012) Distribution pattern of lymphoma subtypes in China: a nationwide multicenter study of 10002 cases. Journal of Diagnostics Concepts & Practice 11(02):111–115
Hoster E, Dreyling M, Klapper W, Gisselbrecht C, van Hoof A, Kluin-Nelemans HC, Pfreundschuh M, Reiser M, Metzner B, Einsele H, Peter N, Jung W, Wörmann B, Ludwig WD, Dührsen U, Eimermacher H, Wandt H, Hasford J, Hiddemann W, Unterhalt M (2008) A new prognostic index (MIPI) for patients with advanced-stage mantle cell lymphoma. Blood 111(2):558–565. https://doi.org/10.1182/blood-2007-06-095331
Hoster E, Rosenwald A, Berger F, Bernd HW, Hartmann S, Loddenkemper C, Barth TF, Brousse N, Pileri S, Rymkiewicz G, Kodet R, Stilgenbauer S, Forstpointner R, Thieblemont C, Hallek M, Coiffier B, Vehling-Kaiser U, Bouabdallah R, Kanz L, Pfreundschuh M, Schmidt C, Ribrag V, Hiddemann W, Unterhalt M, Kluin-Nelemans JC, Hermine O, Dreyling MH, Klapper W (2016) Prognostic value of Ki-67 Index, cytology, and growth pattern in mantle-cell lymphoma: results from randomized trials of the European Mantle Cell Lymphoma Network. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 34(12):1386–1394. https://doi.org/10.1200/jco.2015.63.8387
Dreyling M, Campo E, Hermine O, Jerkeman M, Le Gouill S, Rule S, Shpilberg O, Walewski J, Ladetto M (2017) Newly diagnosed and relapsed mantle cell lymphoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology 28 (suppl_4):iv62-iv71. https://doi.org/10.1093/annonc/mdx223
Rodrigues JM, Hassan M, Freiburghaus C, Eskelund CW, Geisler C, Räty R, Kolstad A, Sundström C, Glimelius I, Grønbaek K, Kwiecinska A, Porwit A, Jerkeman M, Ek S (2020) p53 is associated with high-risk and pinpoints TP53 missense mutations in mantle cell lymphoma. Br J Haematol 191(5):796–805. https://doi.org/10.1111/bjh.17023
Stefancikova L, Moulis M, Fabian P, Ravcukova B, Vasova I, Muzik J, Malcikova J, Falkova I, Slovackova J, Smardova J (2010) Loss of the p53 tumor suppressor activity is associated with negative prognosis of mantle cell lymphoma. Int J Oncol 36(3):699–706. https://doi.org/10.3892/ijo_00000545
Jing C, Zheng Y, Feng Y, Cao X, Xu C (2021) Prognostic significance of p53, Sox11, and Pax5 co-expression in mantle cell lymphoma. Sci Rep 11(1):11896. https://doi.org/10.1038/s41598-021-91433-7
Aukema SM, Hoster E, Rosenwald A, Canoni D, Delfau-Larue MH, Rymkiewicz G, Thorns C, Hartmann S, Kluin-Nelemans H, Hermine O, Dreyling M, Klapper W (2018) Expression of TP53 is associated with the outcome of MCL independent of MIPI and Ki-67 in trials of the European MCL Network. Blood 131(4):417–420. https://doi.org/10.1182/blood-2017-07-797019
Nordström L, Sernbo S, Eden P, Grønbaek K, Kolstad A, Räty R, Karjalainen ML, Geisler C, Ralfkiaer E, Sundström C, Laurell A, Delabie J, Ehinger M, Jerkeman M, Ek S (2014) SOX11 and TP53 add prognostic information to MIPI in a homogenously treated cohort of mantle cell lymphoma–a Nordic Lymphoma Group study. Br J Haematol 166(1):98–108. https://doi.org/10.1111/bjh.12854
Choe JY, Yun JY, Na HY, Huh J, Shin SJ, Kim HJ, Paik JH, Kim YA, Nam SJ, Jeon YK, Park G, Kim JE (2016) MYC overexpression correlates with MYC amplification or translocation, and is associated with poor prognosis in mantle cell lymphoma. Histopathology 68(3):442–449. https://doi.org/10.1111/his.12760
Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA (2017) WHO classification of tumors of haematopoietic and lymphoid tissues. Revised 4th Edition. IARC press, Lyon, France
Kämmerer U, Kapp M, Gassel AM, Richter T, Tank C, Dietl J, Ruck P (2001) A new rapid immunohistochemical staining technique using the EnVision antibody complex. The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society 49(5):623–630. https://doi.org/10.1177/002215540104900509
Bankhead P, Loughrey MB, Fernández JA, Dombrowski Y, McArt DG, Dunne PD, McQuaid S, Gray RT, Murray LJ, Coleman HG, James JA, Salto-Tellez M, Hamilton PW (2017) QuPath: open source software for digital pathology image analysis. Sci Rep 7(1):16878. https://doi.org/10.1038/s41598-017-17204-5
Paulik R, Micsik T, Kiszler G, Kaszál P, Székely J, Paulik N, Várhalmi E, Prémusz V, Krenács T, Molnár B (2017) An optimized image analysis algorithm for detecting nuclear signals in digital whole slides for histopathology. Cytometry Part A : the journal of the International Society for Analytical Cytology 91(6):595–608. https://doi.org/10.1002/cyto.a.23124
DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44(3):837–845
Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8(2):135–160. https://doi.org/10.1177/096228029900800204
Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet (London, England) 1(8476):307–310
Zelenetz AD, Gordon LI, Chang JE, Christian B, Abramson JS, Advani RH, Bartlett NL, Budde LE, Caimi PF, De Vos S, Dholaria B, Fakhri B, Fayad LE, Glenn MJ, Habermann TM, Hernandez-Ilizaliturri F, Hsi E, Hu B, Kaminski MS, Kelsey CR, Khan N, Krivacic S, LaCasce AS, Lim M, Narkhede M, Rabinovitch R, Ramakrishnan P, Reid E, Roberts KB, Saeed H, Smith SD, Svoboda J, Swinnen LJ, Tuscano J, Vose JM, Dwyer MA, Sundar H (2021) NCCN Guidelines® insights: b-cell lymphomas, Version 5.2021. Journal of the National Comprehensive Cancer Network : JNCCN 19 (11):1218–1230. https://doi.org/10.6004/jnccn.2021.0054
Slotta-Huspenina J, Koch I, de Leval L, Keller G, Klier M, Bink K, Kremer M, Raffeld M, Fend F, Quintanilla-Martinez L (2012) The impact of cyclin D1 mRNA isoforms, morphology and p53 in mantle cell lymphoma: p53 alterations and blastoid morphology are strong predictors of a high proliferation index. Haematologica 97(9):1422–1430. https://doi.org/10.3324/haematol.2011.055715
Abrisqueta P, Scott DW, Slack GW, Steidl C, Mottok A, Gascoyne RD, Connors JM, Sehn LH, Savage KJ, Gerrie AS, Villa D (2017) Observation as the initial management strategy in patients with mantle cell lymphoma. Annals of oncology : official journal of the European Society for Medical Oncology 28(10):2489–2495. https://doi.org/10.1093/annonc/mdx333
Kimura Y, Sato K, Arakawa F, Karube K, Nomura Y, Shimizu K, Aoki R, Hashikawa K, Yoshida S, Kiyasu J, Takeuchi M, Nino D, Sugita Y, Morito T, Yoshino T, Nakamura S, Kikuchi M, Ohshima K (2010) Mantle cell lymphoma shows three morphological evolutions of classical, intermediate, and aggressive forms, which occur in parallel with increased labeling index of cyclin D1 and Ki-67. Cancer Sci 101(3):806–814. https://doi.org/10.1111/j.1349-7006.2009.01433.x
Naso JR, Povshedna T, Wang G, Banyi N, MacAulay C, Ionescu DN, Zhou C (2021) Automated PD-L1 scoring for non-small cell lung carcinoma using open-source software. Pathology oncology research : POR 27:609717. https://doi.org/10.3389/pore.2021.609717
Duan K, Jang GH, Grant RC, Wilson JM, Notta F, O’Kane GM, Knox JJ, Gallinger S, Fischer S (2021) The value of GATA6 immunohistochemistry and computer-assisted diagnosis to predict clinical outcome in advanced pancreatic cancer. Sci Rep 11(1):14951. https://doi.org/10.1038/s41598-021-94544-3
Klapper W (2011) Histopathology of mantle cell lymphoma. Semin Hematol 48(3):148–154. https://doi.org/10.1053/j.seminhematol.2011.03.006
Acknowledgements
Not applicable.
Funding
This study was supported by the National Natural Science Foundation of China (81900197) and the Science and Technology Program of Sichuan Province (2020YJ0104).
Author information
Authors and Affiliations
Contributions
YHZ, LMG, and WPL contributed to the conceptual design of the study. YHZ and XYX were involved in data acquisition. YHZ, WYZ, and LMG were involved in data analysis and interpretation. YHZ and LMG were involved in writing and editing the manuscript. YHZ, XYX, WYZ, LMG, and WPL reviewed the manuscript. This study was supervised by WPL and LMG.
Corresponding authors
Ethics declarations
Ethics approval and consent to participate
The present study was approved by the Institutional Review Board of West China Hospital of Sichuan University (WCH2021-00333). All subjects signed informed consent forms before participating.
Consent for publication
All subjects signed informed consent forms before participating.
Competing interests
The authors declare no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yue-Hua Zhang and Li-Min Gao are co-first authors.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhang, YH., Gao, LM., Xiang, XY. et al. Prognostic value and computer image analysis of p53 in mantle cell lymphoma. Ann Hematol 101, 2271–2279 (2022). https://doi.org/10.1007/s00277-022-04922-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00277-022-04922-8