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p53 Overexpression and Thymoma Prognosis

  • Achille Pich
  • Roberto Chiarle
  • Luigi Chiusa
  • Manuela Motta
  • Giorgio Palestro

Summary

Overexpression of the p53 protein has been retrospectively investigated in 90 surgically resected thymomas at diagnosis, using the monoclonal antibody DO7 on routinely processed specimens. p53 accumulation was compared with tumour clinicopathological features, DNA flow cytometry content and cell proliferative activity, assessed by the counts of the argyrophilic nucleolar organizer regions (AgNORs). The purpose was to verify whether the overexpression of the p53 protein could offer additional prognostic information. p53 accumulation was detected in 48 cases (53.4%). No association was found between p53 overexpression and thymoma clinicopathologic features, although p53 protein tended to be more frequently expressed in invasive (61.4%) than noninvasive cases (45.7%, p=0.19) and in DNA aneuploid (71.4%) than diploid cases (48.7%, p=0.15). A strong association was found between p53 immunostaining and AgNOR counts: p53 positive cases had higher AgNOR counts (6.34) than p53 negative thymomas (5.36, p=0.012). In univariate analysis, the 10 year survival rates were significantly higher (83%) for p53 negative than for p53 positive patients (52%, p=0.019). AgNOR counts, tumour DNA content, histological subtypes of the American classification, clinical stage and invasion were also strongly associated with survival. In the multivariate analysis, only tumour stage (p<0.001) and AgNOR counts (p=0.009) retained an independent prognostic significance. Our results indicate that tumour invasion and cell proliferative activity are the most significant parameters predicting survival in thymoma. p53 overexpression is directly correlated to cell proliferative activity and may be regarded as an additional, although not independent, prognostic factor.

Keywords

Thymic Carcinoma Cell Proliferative Activity AgNOR Count Argyrophilic Nucleolar Organizer Region Tumour Clinicopathological Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Achille Pich
    • 1
  • Roberto Chiarle
    • 1
  • Luigi Chiusa
    • 1
  • Manuela Motta
    • 1
  • Giorgio Palestro
    • 1
  1. 1.Department of Biomedical Sciences and Human Oncology, Section of PathologyUniversity of TurinTorinoItaly

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