A Patient-Derived Xenograft Repository Capturing Clinical and Molecular Heterogeneity of Large B-cell Lymphoma.

Authors

Haopeng Yang, Kotaro Arita, Kevin Bowman, Dai Chihara, Jared Henderson, Griffin Rost, Estela Rojas, Sydney Parsons, Priya Lakra, Aneela Syeda Abedin, Sattva S Neelapu, Paolo Strati, Loretta J Nastoupil, Luis E Fayad, Swaminathan P Iyer, Maria Alma Rodriguez, Fredrick B Hagemeister, Luis Malpica, Hun Lee, Laura K Hilton, David W Scott, R Eric Davis, Christopher R Flowers, Jason R Westin, Giorgio Inghirami, Francisco Vega, Michael R Green

Published in

Blood cancer discovery. Pages OF1-OF16. Jun 24, 2026. Epub Jun 24, 2026.

Abstract

Large B-cell lymphomas (LBCL) are a clinically and molecularly diverse group of malignancies with a rapidly evolving therapeutic landscape that has introduced new areas of clinical need, such as post-CD19 chimeric antigen receptor T (CART19) progression. Patient-derived xenograft (PDX) models are an important tool for mechanistic studies and preclinical evaluation of new therapies and can be generated from a variety of clinical contexts that capture tumor-intrinsic resistance mechanisms. We therefore undertook a comprehensive effort to generate PDX models that encompass the molecular landscape of LBCLs and include important clinical scenarios for new drug development. Here, we describe the first 48 models within this publicly available repository, capturing the transcriptional and genetic subsets of LBCL. These models also include 23 generated from post-CART19 progression patient biopsies, which reproduce patterns of progression driven by CD19 mutation or expression loss, as well as tumor cell-intrinsic CART19 resistance that we validated in vivo.
Here, we describe X-LYMPH (Xenografts of Lymphoma), a publicly available and molecularly annotated PDX repository that captures the heterogeneity of LBCL. X-LYMPH includes models of CAR T-cell resistance, providing a shared foundation for mechanistic research and therapeutic development for lymphomas.

PMID:
42341086
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.

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