Poster presented at the 34th EORTC-NCI-AACR Symposium, ENA 2022
Anna Pokorska-Bocci¹, Sandrine Micallef¹, Mariola Dymkowska¹, Yuval Gabay², Roman Gluskin², Avi Laniado², Efrat Dicker², Amit Bart², Tomer Dicker², Ifat Rotbein², Albert Achtenberg², Ori Zelichov²
¹Debiopharm International SA, Lausanne, Switzerland,
²Nucleai, Tel Aviv, Israel
Introduction
DLBCL is the most common type of Non-Hodgkin’s lymphoma, accounting for 30-40% of cases.
Despite improvements in survival with standard of care treatment, up to 40% of patients have relapsed and/or refractory (R/R) disease.
A Phase 2 Study (NCT02564744) evaluated the efficacy of naratuximab emtansine, an anti-CD37 ADC, in combination with rituximab, in 80 patients with R/R DLBCL.
We performed an exploratory, retrospective analysis of the study to find pathology-based biomarkers predictive of response.
Deep learning (DL) models were used to extract spatial features from whole slide images (WSI) stained with CD37 and CD20, and their predictive role was evaluated.