Comparison of evaluation techniques, including digital image analysis, for MYC protein expression by immunohistochemical stain in aggressive B-cell lymphomas

Meghan Hupp, Sarah Williams, Brian Dunnette, Katelyn M. Tessier, Elizabeth L. Courville

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Incorporation of an MYC immunohistochemical stain in the workup of large B-cell lymphomas has become common in hematopathology practice. Evaluation of this stain can be difficult because of staining heterogeneity and can have interobserver variability, particularly when performed on the entire tumor sections. We identified 87 cases of aggressive B-cell lymphoma (34 core needle and 53 excisional biopsies) and compared the following methods of MYC immunohistochemical staining evaluation: the original pathologist's interpretation, a systematic retrospective method of evaluation by manual analysis, and a retrospective method of evaluation by digital image analysis (using scanned slides analyzed via the Aperio Nuclear algorithm). Overall, concordance among these methods was around 80% with κ statistics showing good agreement. However, nearly one-third of our cases had a percent MYC positivity in the 30% to 50% range, and for these cases, concordance among the various methods was marginal/poor. This suggests limited utility as a prognostic or predictive marker using 40% as a cutoff value. In our series, core biopsy specimens were poor predictors of MYC gene rearrangement, and there was no association between MYC immunohistochemical stain and MYC gene gain/amplification. Our retrospective digital image analysis showed strong correlation in MYC percent positivity with our retrospective manual review (correlation coefficient of 0.90) and similar concordance to pathologist interpretation as among pathologists, suggesting that digital image analysis is a viable alternative to manual determination of MYC percent positivity. Digital image analysis provides further opportunities for more sophisticated and standardized scoring systems, which may be helpful in future prognostic/predictive studies.

Original languageEnglish (US)
Pages (from-to)124-132
Number of pages9
JournalHuman pathology
StatePublished - Jan 2019

Bibliographical note

Funding Information:
Funding/Support: Research reported in this publication was supported by the National Institutes of Health (NIH) (Grant P30 CA77598) using the Biostatistics and Bioinformatics Core–shared resource of the Masonic Cancer Center, University of Minnesota and by the National Center for Advancing Translational Sciences of the NIH (Award No. UL1TR000114). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.


  • Diffuse large B-cell lymphoma
  • Digital image analysis
  • High-grade B-cell lymphoma
  • Immunohistochemistry
  • MYC
  • Prognosis


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