Cancer metastasis remains the principal driver of cancer mortality worldwide. Despite significant progress in targeted therapies and immunotherapies, the ability of tumors to spread to distant organs continues to challenge clinicians and researchers alike. Understanding why some cancer cells evade immune surveillance, survive in hostile microenvironments, and colonize new tissues requires experimental systems that reflect the complex physiology of human tumors. Increasingly, researchers are turning to human-relevant models—3D cultures, organoids, and organ-on-chip platforms—to bridge the gap between conventional laboratory studies and patient outcomes. These systems enable studies under conditions that approximate the spatial, metabolic, and immunological gradients present in real tumors, offering critical insight into metastasis biology.
Regulatory guidance has also begun to align with this scientific shift. The U.S. Food and Drug Administration has emphasized the value of human-representative models in drug development, highlighting organoids and organ-on-chip systems as key tools for evaluating therapeutics and improving the predictive value of preclinical studies. According to the FDA’s 2023 framework, these models provide an opportunity to assess safety and efficacy in a more physiologically relevant context, potentially reducing the translational gap between preclinical and clinical results. This regulatory momentum underscores the growing recognition that accurate modeling of human tumor biology is essential for both mechanistic discovery and therapeutic evaluation.
From 3MIC to Tumor-Immune Insights
During her postdoctoral training at New York University, Libi Anandi contributed to this evolving field through the development of 3MIC, an ex vivo tumor model published in Life Science Alliance (“Direct visualization of emergent metastatic features within an ex vivo model of the tumor microenvironment”). The system enables researchers to observe, in real time, how tumor cells respond to gradients of oxygen and nutrients, revealing how environmental stressors can drive plasticity, invasiveness, and other emergent metastatic behaviors. Notably, the study recapitulated the role of immune cells—particularly macrophages—in modulating tumor behavior under metabolic stress, demonstrating that interactions within the tumor microenvironment can significantly influence metastatic potential independent of genetic mutations.
The team observed that established therapies such as Taxol, while effective under standard conditions, were markedly less potent against cancer cells deprived of nutrients and oxygen. Their findings also confirmed that known metastasis‑promoting factors—such as low oxygen—are faithfully recapitulated in the 3MIC. Notably, the data suggested that hypoxia may indirectly enhance metastatic behavior by lowering the pH of the local tumor environment and making it more acidic. Together, these results indicate that diminished drug responses in metastatic cancers may arise from adaptive cellular states shaped by the microenvironment, rather than from limited drug accessibility.
In a recent discussion, Anandi emphasized the rationale behind the study: “Two-dimensional cultures provide limited insight because they fail to replicate the the complexity of living tissues. Conventional cell culture systems do not capture the natural gradients of oxygen, nutrients, or immune signals that shape cellular behavior in vivo. With the 3MIC system, we can overcome these limitations by reliably recreating these conditions and observing how tumor cells behave and interact with other components of the tumor milieu—including immune cells—in a more physiologically realistic context.” She notes that while 3MIC represents a substantial advance, it is not a complete replication of the in vivo environment. “Every model simplifies reality,” she says, “but the goal is to capture enough physiological relevance to provide actionable insights. The more accurately we can mimic the tumor microenvironment, the more meaningful our findings become for understanding disease and developing interventions.”
The platform also provides a tool to explore tumor-immune interactions at a mechanistic level. By allowing visualization of how metabolic stress shapes tumor behavior in the presence of immune cells, researchers can investigate both the drivers of metastasis and potential points of therapeutic intervention. This approach reflects a broader trend in cancer research: integrating immunology and microenvironmental biology into the study of metastatic progression to better predict therapy responses.
Advancing Therapeutic Understanding
Anandi’s work at UT Southwestern builds on these foundations, with a current focus on natural killer (NK) cells, a component of the innate immune system capable of identifying and eliminating tumor cells without prior sensitization. Although NK cell-based therapies show promise, its largely unknown how the tumor microenvironment impacts their function. Anandi and her team aim to uncover strategies to enhance immune activity and inhibit metastatic progression. “Our objective is to design systems that help us understand why immune responses fail and how we might restore them,” she explains. “It’s not just about observing tumor cells in isolation; it’s about capturing the interactions that ultimately determine disease progression.”
The broader scientific landscape reinforces the importance of this approach. Metastatic breast cancer, for instance, remains largely incurable and is a leading cause of death among women worldwide. Current therapies benefit only subsets of patients, highlighting the need for experimental systems that can predict responses, identify resistance mechanisms, and guide therapeutic innovation. Advanced ex vivo models, by recapitulating microenvironmental conditions, offer a means to test drug efficacy and immune-modulating strategies in contexts that more closely resemble patient tumors.
Anandi situates her work within these trends, noting that recent regulatory and methodological shifts have created both opportunities and challenges for researchers. “The FDA’s emphasis on human-relevant models is encouraging because it aligns scientific and translational priorities. Our models are now not only useful for mechanistic studies but also for assessing therapeutic interventions in a way that can inform regulatory decisions,” she says. This convergence between experimental science and regulatory guidance represents a critical juncture for cancer research, providing a framework in which physiologically relevant models can influence both discovery and development pipelines.
Integrating Models, Data, and Translational Insights
Beyond methodology, Anandi emphasizes data integration and systems-level thinking. Modern cancer research generates extensive molecular and genomic datasets, but these data are only as informative as the models in which they are interpreted. “We produce enormous amounts of molecular and single-cell data,” she explains. “Without contextualizing those findings within physiologically relevant models, we risk missing the dynamics that actually drive metastasis and therapeutic resistance.” Tools such as single-cell RNA sequencing, CRISPR-based perturbations, and computational modeling complement ex vivo platforms, allowing researchers to connect mechanistic insights with functional outcomes.
The translational potential of this approach is significant. By observing how tumor cells adapt to stress and interact with immune cells, researchers can identify vulnerabilities that might be targeted therapeutically. For instance, metabolic or immune modulators could be tested in ex vivo systems to evaluate their capacity to reduce metastatic potential before moving into in vivo studies or clinical trials. This iterative cycle—modeling, testing, refining—represents a pragmatic pathway for bridging laboratory discoveries and clinical application.
Building the Next Generation of Translational Tools
Importantly, Anandi stresses the incremental nature of scientific progress. “We’re building tools, testing hypotheses, refining models. Each experiment contributes a piece to the puzzle,” she notes. While advances may not immediately translate into patient treatments, the accumulation of mechanistic insight and model development lays the foundation for more predictive and effective therapeutic strategies.
Her current research trajectory continues this line of inquiry. At UT Southwestern, Anandi is expanding her focus on tumor–immune interactions, with particular interest in how microenvironmental pressures influence NK cell activity and metastatic behavior. By developing more sophisticated ex vivo systems that incorporate immune, stromal, and metabolic components, her work seeks to provide both mechanistic understanding and practical frameworks for evaluating immunotherapies. “The goal is to create models that are not only accurate but also versatile, capable of informing drug discovery, testing therapeutic combinations, and refining immunotherapy approaches,” she explains.
This integration of model development, mechanistic study, and translational relevance reflects broader momentum within the field. Researchers increasingly recognize that success in oncology depends on experimental systems that capture human tumor complexity while remaining scalable and reproducible. The convergence of human-relevant models, computational analysis, and regulatory guidance signals a paradigm shift: one in which the predictive power of preclinical studies can be enhanced, therapeutic candidates can be prioritized more effectively, and mechanistic insights can be directly connected to clinical outcomes.
Looking forward, Anandi situates her work within this broader trajectory. “We’re at a point where models that were once considered experimental are becoming central to how we ask questions and interpret results,” she notes. Her ongoing projects aim to further explore tumor heterogeneity, immune modulation, and metastatic drivers, building on the conceptual and methodological advances of the 3MIC platform. The research is guided by a principle that scientific rigor and physiological relevance are not mutually exclusive—they are complementary.
By focusing on human-relevant modeling, mechanistic insight, and translational applicability, this work exemplifies the direction in which metastasis research is moving. It demonstrates that incremental, carefully designed studies can illuminate complex biological processes and provide actionable insights for therapeutic development. As Anandi observes, “Each tumor sample represents a unique biological context. Capturing that complexity is essential if we want to understand metastasis and develop strategies that truly work.”
Across the field, laboratories are increasingly adopting similar approaches, integrating microenvironmental modeling, immune biology, and computational tools. The goal is to move beyond simplified systems and embrace experimental designs that respect the inherent complexity of human tumors. In doing so, researchers hope to better predict therapy responses, identify mechanisms of resistance, and ultimately improve patient outcomes.
Anandi’s work is one example of this broader trend. By combining ex vivo modeling, immune-focused studies, and systems-level analysis, she illustrates how researchers can interrogate metastatic behavior in a human-relevant context. The result is a research trajectory that aligns scientific discovery with translational potential, offering a framework for both understanding disease and evaluating therapeutic strategies.
In laboratories across the world, this reimagined approach to cancer research is gaining momentum. By prioritizing physiological relevance, integrating mechanistic insights, and aligning with regulatory expectations, scientists are building the next generation of experimental tools to understand and combat metastasis. As the field continues to evolve, platforms like 3MIC demonstrate how careful modeling, rigorous experimentation, and strategic translational focus can advance both knowledge and therapeutic potential in oncology.
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