Engineering the tumor microenvironment via 3D multicellular bioprinting for personalized immunotherapy assessment and resistance deciphering

Immunotherapy has emerged as the cornerstone of antitumor therapeutics, embodying the most promising path for future oncology (1). However, empirical evidence from clinical practice underscores a pronounced randomness in its efficacy, with objective response rates (ORRs) remaining disappointingly modest for the majority of solid tumors. For instance, intrahepatic cholangiocarcinoma (iCCA) is highly heterogeneous and rich in pro-fibrotic stroma. Existing clinical data show that approximately 67% iCCA patients develop immunoresistance (primary and adaptive) after immune checkpoint inhibitor (ICI) treatment (2). As with other malignancies, the real culprit for immunoresistance is the complex tumor microenvironment (TME), yet we are short on methods to fully understand it (3). There is an urgent need for a reliable platform that can faithfully recapitulate and modify the specific TME, thereby enabling deeper insights into it, individualized assessments of ICIs, and personalized investigations into the mechanisms of immunoresistance and their potential reversal.

Necessity of personalized immunotherapy efficacy and resistance exploration

Immunotherapies like programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1)/cytotoxic T-lymphocyte associated protein 4 (CTLA-4) inhibitors have transformed cancer management within the past decade, yet primary/acquired resistance affects over 70% of patients due to TME immunosuppression involving exhausted T cells, M2 macrophages, and regulatory T cells (Tregs) (4). Immunoresistance in iCCA represents the paramount impediment to its current clinical management, emblemizing a microcosm of challenges in tumor immunotherapy. ICCA exemplifies a typical immune “cold” tumor, in which nearly half of patients belong to the desolate type. Existing systemic combination regimens yield efficacy rates not exceeding 30%, with most iCCA patients forfeiting critical therapeutic windows amid empirically driven treatments. Even patients who initially respond may develop adaptive resistance during subsequent therapy, further deteriorating their overall prognosis (5).

Reconstructing patient-derived tumor models and immune microenvironments in vitro to simulate drug actions, evaluate therapeutic efficacy, and provide individualized clinical guidance represents a critical strategy for overcoming this challenge, holding significant scientific value. Furthermore, through systematic analysis and evaluation during simulated drug interventions in vitro, the mechanisms underlying immunoresistance can be thoroughly investigated, potentially revealing strategies to reverse it. Achieving these objectives—particularly at the intersection of personalized drug sensitivity testing and resistance mechanism elucidation—is expected to transform the field of contemporary clinical tumor immunotherapy and basic oncological research.

Superiority of three-dimensional (3D) multicellular bioprinting over conventional models in recapitulating TME

Traditional 2D Petri dish cell culture models fail to recapitulate the TME due to its spatial constraints and contact inhibition of non-cancerous cells, leading to poor translational relevance, while patient-derived organoids (PDOs) suffer from low success rates (often below 50%), lack of reproducibility, and absence of vascularization or immune components (6). Patient-derived xenograft (PDX) models, though preserving heterogeneity, require months for establishment, have engraftment rates under 30%, and involve ethical issues with animal use. Meanwhile, the paradox of PDX-based immunotherapy testing remains unsolved, since PDX models are usually generated on immunodeficient mice. The undeniable truth is that all these preclinical models, despite their various innate advantages, are neither reliable nor competent to meet actual clinical needs for individualized treatment or further research. With limited success rates, a time-consuming process, and inherent limitations of the modeling approach, existing models fail to remedy substantial clinical gaps, especially in the era of immunotherapy.

Conversely, 3D bioprinting achieves an over 95% success rate, 90% cell viability, and model construction in hours using patient-derived primary cells mixed with gelatin-alginate. We pioneered the establishment of the world’s first 3D-bioprinted hepatocellular carcinoma model (7). Subsequently, further research developed dozens of additional tumor models, including those for gallbladder cancer, liver metastatic cancer, and gastric cancer, etc. The results consistently demonstrated that 3D tumor models can reliably recapitulate the biological characteristics of their parental tumors in vitro while maintaining the high efficiency and success rate. Yet existing 3D bioprinted tumor models focus on single or limited cell types, such as primary tumor cells in gelatin-alginate hydrogels via extrusion printing, enabling drug testing but overlooking immune dynamics. Multi-cellular bioprinting enables precise spatial control of various cells and extracellular matrix (ECM) to mimic native TME architecture. Advances include co-cultures of cancer cells with fibroblasts or endothelial cells, revealing stroma-induced chemoresistance, yet immune cells remain underexplored.

To advance towards the directions in 3D bioprinting immuno-models by transitioning bioinks from single primary tumor cells to hybrid compositions incorporating cancer-associated fibroblasts (CAFs), peripheral blood mononuclear cells (PBMCs), T cells, NK cells, and diverse immunomodulatory cells, thereby better recapitulating TME crosstalk like PD-L1 upregulation and cytokine storms. Building on individualized immunotherapy drug-sensitivity testing, we can even actively explore resistance mechanisms in non-responsive patients and potentially develop targeted interventions to reverse immunoresistance.

Multicellular 3D bioprinting model for immunotherapy assessment

Multicellular 3D bioprinting enables the co-culture of patient-derived primary tumor cells with autologous immune cells and ECM in a meticulously designed and flexible manner, making it possible to accurately mimic the tumor and immune microenvironment in vitro. Taking iCCA as an example, one of the most particular features of iCCA is the pro-fibrotic texture due to the inherent enrichment of CAFs. By bioprinting multicellular constructs comprising primary tumor cells, CAFs, and autologous PBMCs, recapitulating the spatial distribution of tumor cells and CAFs and their interactions, it is possible to perform patient-specific ICIs sensitivity assessment.

Critically, 3D multicellular bioprinting offers a powerful modeling platform, a practical access for deciphering the mechanisms of both primary and acquired immunoresistance. For instance, the primary immunoresistance is frequently observed in the “desolate” or “cold” phenotype of iCCA patients, which is characterized by a dense peritumoral stromal barrier, predominantly composed of CAFs, which physically impedes infiltrating immune cells and contributes to therapeutic resistance. By employing bioprinted multicellular systems, researchers can systematically modulate key parameters—such as spatial cell distribution and stromal density—to delineate the necessary conditions for effective immune infiltration and activation. This facilitates the exploration of interventions designed to reconfigure the TME and potentially overcome resistance. Another significant advantage of this methodology is the potential for personalized oncology. Coupled with the high reproducibility and scalability of 3D bioprinting, it holds the prospective potential to deconstruct and address the unique resistance profile of individual patients against specific therapeutic agents. The realization of this capability would represent a profound advancement in precision cancer medicine.

Designed TME facilitates more precise basic tumor-immunology research

Leveraging the flexibility of 3D multicellular bioprinting will greatly facilitate basic research in tumor immunology. Taking CAFs in iCCA as an example, carefully designed architectures and spatial layouts can be used to generate models with markedly distinct overall structures and cellular distributions, thereby enabling investigation of whether specific spatial configurations drive immune exclusion—that is, how the spatial organization of CAFs physically segregates immune cells and induces immune resistance (8).

For instance, two models can be precisely constructed: one in which CAFs form a peripheral barrier encapsulating tumor cells (“immune-excluded type”), and another in which CAFs and tumor cells are uniformly intermixed (highly fibrotic type). By co-culturing these models with patient-derived T cells and applying ICIs, one can quantify T-cell infiltration efficiency and analyze how, under defined spatial configurations, CAF paracrine signaling [such as transforming growth factor-beta (TGF-β) and C-X-C motif chemokine ligand 12 (CXCL12)] and matrix remodeling are enhanced. This line of investigation can directly test the hypothesis that a “spatial barrier” underlies therapeutic resistance and can provide rigorous experimental evidence to support combination strategies targeting CAF-derived barriers, such as co-administration of FAK or CXCR4 inhibitors. As another example, the dynamic evolution of the microenvironment during treatment and the mechanisms of acquired resistance can be elucidated by constructing a three-stage dynamic 3D bioprinting system: starting from an initial co-culture model, introducing activated antigen-specific T cells to mimic therapeutic attack, and ultimately collecting and analyzing the surviving “resistant” constructs. Longitudinal single-cell sequencing and metabolic profiling of this system aim to reveal how immune pressure drives CAFs toward pro-fibrotic or pro-inflammatory phenotypic transitions, triggers upregulation of alternative immune checkpoint pathways (such as TIGIT and TIM-3), and induces reprogramming of the tumor metabolic microenvironment. Such a model can prospectively simulate the clinical evolution of resistance, identify key dynamic molecular switches, and thereby guide the design of temporally optimized combination treatment strategies to prevent or reverse resistance.

Summary

Immunotherapy has already become the central modality in anticancer treatment, with targeted therapy, chemotherapy, and other approaches increasingly regarded as sensitizing or synergistic strategies that augment immune-based treatments. The establishment of individualized tumor immune microenvironment models and the elucidation of patient-specific mechanisms of immune resistance will greatly advance researchers’ understanding of the tumor immune microenvironment and improve clinical outcomes for patients. As a representative success at the interface of medicine and engineering, 3D bioprinting has, through intensive efforts in recent years, enabled the development of numerous in vitro models for a wide range of malignancies and has already achieved initial clinical translation. In the future, the use of multicellular bioprinting to reconstruct personalized tumor immune microenvironments ex vivo will become a crucial foundation for individualized tumor immunotherapy, and, when integrated with technologies such as single-cell omics and spatial transcriptomics, will also serve as an indispensable core platform for uncovering mechanisms of immunoresistance in tumors and advancing related research.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, HepatoBiliary Surgery and Nutrition. The article did not undergo external peer review.

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-2026-0163/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Nishida N. Advancing the management of hepatocellular carcinoma: surrogate markers and predictive biomarkers for survival on immunotherapy. Hepatobiliary Surg Nutr 2025;14:311-5. [Crossref] [PubMed]
2. Tomlinson JL, Valle JW, Ilyas SI. Immunobiology of cholangiocarcinoma. J Hepatol 2023;79:867-75. [Crossref] [PubMed]
3. Viganò L, Risi L, Ammirabile A. New perspectives in biology-driven treatment of cholangiocarcinoma: from oncological resectability to genetic breakthroughs and AI-powered imaging. Hepatobiliary Surg Nutr 2025;14:703-8. [Crossref] [PubMed]
4. Binnewies M, Roberts EW, Kersten K, et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med 2018;24:541-50. [Crossref] [PubMed]
5. Beri N. Immune checkpoint inhibitors in cholangiocarcinoma. Immunotherapy 2023;15:541-51. [Crossref] [PubMed]
6. Du L, Dong J, Du S. Organoid models for T cell-based immunotherapy in hepatobiliary cancers. Hepatobiliary Surg Nutr 2025;14:1042-4. [Crossref] [PubMed]
7. Xie F, Sun L, Pang Y, et al. Three-dimensional bio-printing of primary human hepatocellular carcinoma for personalized medicine. Biomaterials 2021;265:120416. [Crossref] [PubMed]
8. Cantallops Vilà P, Ravichandra A, Agirre Lizaso A, et al. Heterogeneity, crosstalk, and targeting of cancer-associated fibroblasts in cholangiocarcinoma. Hepatology 2024;79:941-58. [Crossref] [PubMed]