Abstract:
Cancer is the second leading cause of death worldwide. Significant progress has been made in recent decades in cancer research and treatment strategies, transforming this condition from a fatal diagnosis into a manageable one. However, not all types of cancer are curable. The majority of solid tumors are distinguished by a high degree of inter- and intratumoral heterogeneity, a factor that poses a significant challenge to treatment efficacy. This complexity is attributable to the inherent plasticity of cancer cells and the influence of the tumor microenvironment. Consequently, cancer cells rapidly develop resistance mechanisms to treatment strategies. A significant percentage of drugs that demonstrate substantial promise in pre-clinical models often prove ineffective when translated to clinical application or are accompanied by severe off-target effects. This can be linked to the lack of translatable pre-clinical models that can replicate the complexity and heterogeneity of a cancer patient’s disease.
Ovarian cancer exemplifies this translational gap and is among the most lethal gynecologic malignancies. It is characterized by high intratumoral heterogeneity and, due to unspecific symptoms, is often diagnosed in advanced stages when metastasis has already occurred. Despite the promising first line response rate, over 70 % of patients relapse and develop a resistance to chemotherapy, contributing to a dismal five-year survival rate of only 26 – 42%.
To address the need for physiologically relevant, human centered, and individualized testing systems, we developed a perfusable microfluidic chip platform that enabled the integration of patient-derived ovarian cancer microtumors (OvCa PDM). OvCa PDM preserve histopathological and immunohistological features of the primary tumors, tumor microenvironment and extracellular matrix components. Embedded within a biomimetic hydrogel in a three-dimensional environment, OvCa PDM remained viable for at least 14 days and supported various analyses, such as measuring tumor specific cell death, profiling cytokine and chemokine secretion kinetics, and immunofluorescence-based assessment of immune cell recruitment.
The advanced OvCa PDM on-chip platform enabled the evaluation of patient-specific synergistic effects of immune checkpoint inhibitors in combination with chemotherapy. By leveraging autologous immune cells, the system facilitates a comprehensive analysis of immune-mediated treatment effects, including tumor–immune cell interactions and therapeutic efficacy. The platform allows for the functional stratification of patients into responders and non-responders across monotherapy and combination treatment regimens. Furthermore, treatment-specific differences in immune responses were identified, encompassing distinct cytokine and chemokine secretion patterns, differential immune cell recruitment, and varying tumor-infiltrating lymphocyte compositions.
These insights provide a deeper understanding of individual variability in treatment responses and the mechanisms underlying resistance. Ultimately, this model supports the development of personalized therapeutic strategies by enabling pre-clinical assessment of patient-specific responses. Additionally, it offers a valuable tool for the discovery of predictive biomarkers associated with treatment efficacy and resistance.
Organ-on-chip