Development of 3D-printed microtumours for ex vivo high-throughput analysis of immunotherapies

Cancer immunotherapy has become a powerful component of modern cancer treatment. Nevertheless, preclinical evaluation of new immunotherapies still depends largely on animal models. At the same time, the tumor microenvironment, shaped by its anatomical scale, hierarchical blood and lymphatic vasculature, and complex cell-cell interactions, poses major challenges for in vitro systems. Even advanced cell‑based assays using human‑induced pluripotent stem cells and organoids remain limited in their ability to fully capture and quantify immunotherapy efficacy.

 Building on our recent work, which showed that spatial interactions between tumor cells and the tumor microenvironment critically influence lymphoma development and treatment response (1-3), we aim to develop a bioprinted microtumor model for lymphoma. This model will serve as a proof of concept for using 3D‑bioprinted tumors to test the efficacy and toxicity of immunotherapies.

 In the first phase, we will apply multiplex immunofluorescence analysis to map lymphoma‑induced remodeling of the cellular composition and spatial architecture of the lymph node microenvironment. In the second phase, we will use commercial lymphoma cell lines, immortalized stromal cell lines, and fibroblasts to establish and optimize the bioprinting workflow. After validating the printing protocol, we will incorporate patient‑derived primary lymphoma cells to generate 3D‑bioprinted microtumors for ex vivo drug‑response assays. Dynamic treatment responses will be tracked using live‑cell imaging, and the resulting data will be analyzed with our recently published bioinformatic pipeline (4).

 In the final phase of the project, we will correlate drug‑response profiles of bioprinted microtumors with the corresponding patients’ clinical responses to immunotherapy to determine whether this model can accurately predict treatment outcomes. If successful, this 3D microtumor platform could reduce reliance on animal models, enable direct translation of basic research into personalized therapies, and accelerate the development of effective immunotherapies.

Reference:

1. Czernilofsky F, Mathioudaki A, Jopp-Saile L, Lutz R, Vonficht D, Wang X, . . . Dietrich S. Reprogramming of stroma-derived chemokine networks drives the loss of tissue organization in nodal B cell lymphoma. Nat Cancer. 2026;7(3):538-52.

2. Roider T, Baertsch MA, Fitzgerald D, Vohringer H, Brinkmann BJ, Czernilofsky F, . . . Dietrich S. Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities. Nat Cell Biol. 2024;26(3):478-89.

3. Roider T, Seufert J, Uvarovskii A, Frauhammer F, Bordas M, Abedpour N, . . . Dietrich S. Dissecting intratumour heterogeneity of nodal B-cell lymphomas at the transcriptional, genetic and drug-response levels. Nat Cell Biol. 2020;22(7):896-906.

4. Tran NK, Huynh MK, Kotman AD, Jurgens M, Kurz T, Dietrich S, . . . Qin N. VUScope: a mathematical model for evaluating image-based drug response measurements and predicting long-term incubation outcomes. Bioinformatics. 2026;42(2).