How Patient-Derived Models and Advanced Imaging Systems Are Shaping Next-Gen Immunotherapies

Cell and gene therapy (CGT) continues to reshape modern oncology by enabling therapeutic strategies that move beyond nonspecific cytotoxic mechanisms traditionally associated with chemotherapy and radiation. Instead of relying on broad approaches that indiscriminately damage both malignant and healthy cells, platforms such as chimeric antigen receptor T-cell (CAR T-cell) and other engineered lymphocyte products harness immune effector functions to selectively recognize and eradicate tumor cells.

At the same time, gene-editing tools allow direct manipulation of genetic substrates that drive malignant progression, offering the ability to silence oncogenic drivers, restore tumor suppressor activity, or reprogram cellular pathways toward normal function. By integrating immunologic precision with genetic engineering, CGT not only expands the therapeutic arsenal against cancer but also lays the foundation for durable remissions, reduced toxicity, and potentially curative outcomes across a wide spectrum of malignancies.

Since initial explorations in the late 1980s of gene transfer in oncology, CGT modalities have been propelled by innovations such as the clustered regularly interspaced short palindromic repeats–associated protein 9 (CRISPR-Cas9) gene-editing system and FDA approval of multiple CAR T-cell therapies. These developments are widely recognized as milestones in precision cancer treatment.

However, durable responses are still uneven, particularly in solid tumors, and this translational gap has driven the development of advanced preclinical systems that more faithfully model human tumor biology, immune dynamics, and treatment response (Figure 1). Collectively, these preclinical innovations enable researchers to model complex CGT mechanisms with greater accuracy, identify liabilities earlier, and refine therapeutic designs before clinical translation.¹ By improving predictive power across key biological and safety end points, these platforms have the potential to accelerate development timelines and expand the reach of CGT options to a broader range of patients.²

Why are patient-derived and humanized in vivo models important?

Patient-derived xenograft (PDX) models are generated directly from primary patient tumor tissue rather than immortalized cell lines. As a result, these models retain the intratumoral heterogeneity, genomic integrity, and clinical response patterns of the originating malignancy. This fidelity enables a far more accurate prediction of therapeutic responses, evaluation of resistance mechanisms, and definition of biomarker strategies than immortalized cell lines or simple in vitro systems (Figure 2).

PDX platforms have become central to the preclinical assessment of personalized T-cell therapies, including CAR T and tumor-infiltrating lymphocyte (TIL) products. Extensive research has demonstrated that PDX platforms produce some of the most clinically translatable preclinical datasets currently available.³ They support indication selection and patient stratification by identifying tumor subtypes most likely to benefit. Globally, tens of thousands of PDX models have been established, solidifying their role as a foundational workhorse for oncology drug development.

Humanized mouse models enhance the predictive value of PDX systems by incorporating functional human immune components. Through the engraftment of human hematopoietic stem cells into immunodeficient mice, these models generate a reconstituted human immune system capable of supporting robust tumor-immune interactions (Figure 3). Consequently, researchers can evaluate CAR Ts, TILs, and other immune-based therapies within a biological context that closely mirrors the human tumor microenvironment (TME).⁴

Because both tumor cells and immune effectors originate from human sources, these models are particularly well suited for assessing tumor-associated immune responses and immunotherapy performance.⁵ Studies consistently show that humanized systems accelerate the progression of CAR T candidates from proof-of-concept to clinical testing, allowing investigation of CAR T expansion and persistence, tumor-immune crosstalk, and immune-mediated toxicities in vivo. Many researchers now regard humanized systems as the emerging gold standard for in vivo CAR T evaluation.⁶ In a broader sense, humanized PDX platforms are increasingly regarded as the preferred in vivo context for evaluating adoptive cell therapies and combination regimens in immuno-oncology

How do 3D organoid models bridge translational gaps?

3D organoids are miniaturized, self-organizing tissue constructs generated from patient-derived tumors or biopsies, meticulously designed to recapitulate the key architectural, molecular, and functional characteristics of human tissues. Unlike traditional two-dimensional cell cultures, organoids preserve the spatial organization, cellular heterogeneity, and dynamic signaling networks that define native physiology, making them far more representative of in vivo biology.

The ability of 3D organoids to mimic the complexity of human tissue provides researchers with a powerful platform for studying disease progression and therapeutic intervention. This physiological relevance enables scientists to predict patient-specific therapeutic responses and drug efficacy more accurately, reducing the translational gap between preclinical models and clinical outcomes (Figure 4).

Organoids provide several advantages during CGT development, particularly in coculture systems designed to evaluate immune-cell activity. In these settings, organoids reveal complex interactions among CAR Ts, tumor cells, and components of the TME with far greater fidelity than 2D monolayer cultures.⁷ They are especially valuable in the context of solid tumors, where stromal barriers, extracellular matrix density, immunosuppressive factors, and other TME features can impede CAR T infiltration and function. Because patient-specific organoids maintain strong similarity to native tumor and healthy tissues, they enable side-by-side comparisons that facilitate early identification of off-target toxicity.

Due to their ability to bridge mechanistic in vitro studies and in vivo animal models, organoids have rapidly become an integral component of CGT pipelines. Large, well-annotated organoid biobanks now support high-throughput matrix-based screens at early drug discovery stages, reducing timelines and overall development risk.⁸

How does CRISPR-Cas9 gene editing enable precision engineering?

The CRISPR-Cas9 gene-editing system stands as one of the most transformative breakthroughs in contemporary biomedical research. Its remarkable efficiency, programmability, and precision allow for the rapid generation of models with defined genetic alterations, thereby accelerating mechanistic investigations and the optimization of therapeutic strategies.

CRISPR-engineered organoids have emerged as a powerful platform for modeling tumorigenesis and identifying therapeutic vulnerabilities. The convergence of CRISPR-Cas9 as a highly specific gene-editing tool with organoid culture derived from adult stem cells has provided accessible and versatile systems to study organ development and cancer biology (Figure 5). Through sequential knockout and knock-in of driver mutations, researchers have generated genetically modified organoids that, upon xenotransplantation into animal models, faithfully recapitulate the neoplastic progression observed in human tumors.⁹

Beyond disease modeling, CRISPR-Cas9 also enables the design of next-generation cellular therapies with enhanced cytotoxicity, refined targeting precision, and improved safety profiles. Editing strategies that eliminate genes encoding inhibitory receptors, modulate cytokine signaling, or improve safety and control have successfully augmented the antitumor potency of therapeutic T cells. Collectively, these advances are driving the development of more effective and less toxic candidates in the CGT field.

What is the advantage of real-time functional visualization with advanced imaging?

Modern imaging modalities, which include bioluminescence (BLI), fluorescence, magnetic resonance imaging, and positron emission tomography, are essential in preclinical CGT development. These technologies enable real-time visualization of biological processes such as therapeutic trafficking, expansion, and functional engagement. Their complementary strengths allow researchers to integrate molecular, cellular, and anatomical insights, providing a more comprehensive understanding of therapy dynamics in vivo.

BLI, which relies on cells engineered to express luciferase enzymes, has emerged as a cornerstone modality due to its sensitivity, scalability, and suitability for longitudinal analysis. Over the past 2 decades, improvements in BLI technologies have significantly enhanced spatial resolution and enabled interrogation of increasingly complex biological systems.

Bioluminescent organoid systems are particularly valuable for CAR T research. For example, liver cancer patient-derived organoids (PDXOs), engineered to express human CD19, and luciferase have been used effectively to quantify CART cell–mediated cytotoxicity in real time.¹⁰ These platforms provide robust tools for evaluating therapeutic potency, optimizing construct design, and reducing the risk in early-stage development (Figure 6).

How is the CGT sector addressing solid tumor challenges and future directions?

Solid tumor modeling remains a critical frontier in CGT because the unique biology of solid malignancies continues to pose barriers that limit therapeutic efficacy. Unlike hematologic cancers, solid tumors are defined by complex microenvironments that include stromal barriers, hypoxic niches, metabolic constraints, and immunosuppressive signaling networks, all of which hinder immune cell infiltration and persistence. This heterogeneity fosters resistance to treatment and enables immune evasion, making it difficult for engineered cell therapies such as CAR T or T cell receptor–engineered T cells (TCR-Ts) to achieve durable responses.

Robust modeling platforms are therefore essential to replicate these challenges and guide the design of next-generation CGT strategies. By faithfully capturing tumor architecture and microenvironmental dynamics, solid tumor models provide the translational bridge needed to optimize vector delivery, enhance immune cell trafficking, and identify combination regimens that can overcome resistance. In this way, advancing solid tumor modeling is not only about refining preclinical research but also about unlocking the full therapeutic potential of CGT for the majority of patients with cancer, who are affected by solid, rather than hematologic, malignancies.

Future directions in preclinical modeling will require the integration of more sophisticated systems that bridge these gaps.¹¹ Advances in humanized mouse models, patient-derived organoids, and microfluidic “tumor-on-a-chip” technologies offer opportunities to better mimic the structural, cellular, and immunological complexity of human tumors. Incorporating CRISPR-based gene editing into these platforms may further enable precise modeling of tumor heterogeneity and resistance mechanisms.

Additionally, multiscale computational models and AI-driven analytics hold promise to predict therapeutic outcomes and optimize treatment strategies before clinical applications. Collectively, these innovations aim to create preclinical frameworks with greater fidelity to human disease, ultimately accelerating the safe and effective translation of adoptive cell therapies for solid tumors.

Conclusion

Traditional preclinical models, including simple in vitro systems and conventional xenografts, fail to capture the complexity of human tumors, such as intratumoral heterogeneity, stromal interactions, and immune dynamics. This limitation has driven the development of advanced, patient-relevant platforms. Emerging technologies offer more physiologically relevant systems, improving predictive power and mechanistic insight of preclinical CGT studies.

By leveraging these models and techniques, researchers can create preclinical platforms that accelerate CGT development. While each approach provides unique strengths, their integration maximizes translational relevance, helping overcome hurdles in solid tumor research. Strategically combining these technologies enhances the ability to develop effective therapies, reduce attrition rates, and expand the reach of CGT to more patients. As the field continues to advance, such approaches will be essential for translating promising therapies into clinical success.

References

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About the author

Benjamin Wilkin is a product marketing manager at Crown Bioscience.