Identification of MUM1 as a prognostic immunohistochemical marker in follicular lymphoma using computerized image

Luc Xerri1, Emmanuel Bachy2, Bettina Fabiani3

  • 1Departments of Bio-Pathology, Molecular Oncology, Hematology, and Tumor Immunology, Institut Paoli-Calmettes and Aix-Marseille Université, 13009 Marseille, France.

Human Pathology
|August 24, 2014
PubMed

Insights

MUM1 expression in follicular lymphoma (FL) tissues is a strong predictor of patient outcomes, indicating a shorter progression-free survival. This finding highlights MUM1 as a robust immunohistochemical marker for FL prognosis.

Area of Science:

  • Oncology
  • Hematology
  • Immunohistochemistry

Background:

  • Previous studies suggested MUM1+ cells in follicular lymphoma (FL) tissues correlate with poor prognosis, but Ki-67's predictive value is uncertain.
  • The prognostic significance of these markers in FL requires further validation.

Purpose of the Study:

  • To determine the predictive value of MUM1 and Ki-67 expression in patients with follicular lymphoma.
  • To validate MUM1 as a prognostic marker in a separate FL cohort.

Main Methods:

  • Immunohistochemistry was used to analyze MUM1 and Ki-67 expression in biopsy samples from 434 patients in the PRIMA trial and 138 patients in the FL2000 trial.
  • Computerized image analysis quantified positive staining.
  • Multivariate Cox regression models were employed for prognostic analysis.

Main Results:

  • High MUM1 positivity (≥0.80%) and Ki-67 positivity (≥10.25%) were associated with shorter progression-free survival (PFS) in the PRIMA cohort.
  • In multivariate analysis of the PRIMA cohort, only MUM1 remained statistically significant for PFS.
  • High MUM1 positivity was significantly associated with shorter PFS and showed a trend toward shorter overall survival in the FL2000 cohort, confirmed by multivariate analysis.

Conclusions:

  • MUM1 is a strong and robust predictive immunohistochemical marker for follicular lymphoma.
  • MUM1 expression levels can aid in predicting progression-free survival and overall survival in FL patients.

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