Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Mini Oral session: Haematological malignancies

623MO - Machine learning-based prediction of germinal center, MYC/BCL2 double protein expressor status, and MYC rearrangement from whole slide images in DLBCL patients


12 Sep 2022


Mini Oral session: Haematological malignancies


Laboratory Diagnostics;  Pathology/Molecular Biology

Tumour Site



Charlotte Syrykh


Annals of Oncology (2022) 33 (suppl_7): S283-S294. 10.1016/annonc/annonc1055


C. Syrykh1, J. Schiratti2, E. Brion2, C. Joubert3, M. Baia4, L. Marlot5, C. Maussion2, L. Danneaux2, S. Bologna6, J. Briere7, P. Dartigues8, P. Gaulard9, C. Haioun9, F. Jardin10, T. Molina11, H. Tilly10, E. Gomez5, D. Sondaz5, C. Copie-Bergman12, C. Laurent13

Author affiliations

  • 1 Anatomical Pathology, IUCT Oncopole, LYSA, 31059 - Toulouse/FR
  • 2 R&d, OWKIN, 75010 - Paris/FR
  • 3 Anatomical Pathology, LYSARC (The Lymphoma Academic Research Organisation), 69495 - Pierre-Bénite/FR
  • 4 Anatomical Pathology, LYSARC (The Lymphoma Academic Research Organisation), Pierre-Bénite/FR
  • 5 Anatomical Pathology, Institut CARNOT CALYM, Pierre-Bénite/FR
  • 6 Anatomical Pathology, CHU Brabois, 54500 - Vandoeuvre-lès-Nancy/FR
  • 7 Anatomical Pathology, Hôpital St Louis, Paris/FR
  • 8 Anatomical Pathology, INSTITUT GUSTAVE ROUSSY, 94800 - Villejuif/FR
  • 9 Anatomical Pathology, Centre Hospitalier Universitaire Henri-Mondor AP-HP, 94010 - Créteil/FR
  • 10 Anatomical Pathology, Centre Henri Becquerel, 76038 - Rouen/FR
  • 11 Anatomical Pathology, Institut Necker Enfant Malades, 75993 - Paris/FR
  • 12 Anatomical Pathology, LYSA (The Lymphoma Study Association), Pierre-Bénite/FR
  • 13 Anatomical Pathology, IUCT Oncopole, LYSA, Toulouse/FR


Login to access the resources on OncologyPRO.

Abstract 623MO


Diffuse Large B-Cells Lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma in adults (30-40%). In the 2016 World Health Organization (WHO), DLBCL are classified into 3 molecular subtypes according to cell of origin (COO), germinal-center, activated B-cell like and unclassified, based on gene-expression profiling (GEP). In daily routine, COO classification is replaced by immunochemistry (IHC) stains using the Hans algorithm based on the expression of CD10, BCL6 and MUM1 proteins. In addition, co-expression of BCL2 and MYC proteins is of prognostic value and defines the double-protein expressors (DPE) subtypes, associated with worse prognosis. Fluorescent In Situ Hybridization (FISH) is mandatory in the workup of DLBCL to detect MYC and BCL2 and/or BCL6 rearrangements.


565 whole-slide images (WSI) stained with hematoxylin/eosin from the LYSA trial “GHEDI” (Deciphering the Genetic Heterogeneity of Diffuse large B-cell lymphoma in the rituximab era) dataset were analyzed. A Deep Learning (DL) model was trained to predict COO and DPE status, the presence of MYC rearrangements (no MYC rearrangement/MYC-Single Hit or HGBL-Double Hit/Triple Hit) and expression of BCL6, CD10 and MUM1 proteins from WSI. Performance was evaluated using several repetitions of stratified five-fold cross-validation.


The DL model achieved a ROC AUC of 0.624 for GC, 0.687 for DPE, and 0.675 for MYC rearrangement. Using Cox proportional hazard model, predictions of DPE status (HR=0.38, P=.016), and MYC rearrangements (HR=5.23, P<.001) and MUM1 expression (HR=2.80, P=.027) were associated with worse overall survival.


Our study demonstrates the predictive power of DL applied to WSI to predict DLBCL subtypes. Such predictive models could be used to augment pathologists analysis capacities, especially when IHC staining or FISH are not available.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Institut Carnot CALYM.




J. Schiratti: Financial Interests, Institutional, Full or part-time Employment: Owkin. E. Brion: Financial Interests, Institutional, Full or part-time Employment: Owkin. C. Maussion: Financial Interests, Institutional, Full or part-time Employment: Owkin. L. Danneaux: Financial Interests, Institutional, Full or part-time Employment: Owkin. All other authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.