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Abstract
Background Current efforts in oncologic drug testing and discovery rely on highly versatile testing models, especially for understanding the pathophysiology of cancers. While the use of three-dimensional (3D) patient-derived tumoroids (PDTs) allows for representative tumor modelling, mimicking variations in microenvironmental oxygenation and immune conditions allows for further tumoral recapitulation and diversity. We have established a PDT-based platform with or without additional basal/peri-cellular oxygen perfusion, with the presence and absence of allogenic immune components. Using these model platforms, we investigated the growth profiles of soft tissue sarcoma PDTs in variable states of oxygenation and immunocompetence. The goal behind building this advanced platform is to enable tumor microenvironmental (TME) interactions-based studies and pave way for both the accurate testing of existing therapeutic options and the discovery of novel oncological immuno-therapeutics.
Methods Four types of 3D PDT-Scaffold-based platforms were prepared with Human Uterine Adenosarcoma tumoroids. Baseline static, apical oxygenation studies were performed on standard well plates, while additional basal/peri-cellular oxygenation studies were conducted in a dynamic matrix-liquid-liquid interface by using an in-well perfusion method with the aid of synthetic hemoglobin. Furthermore, the presence and absence of peripheral blood mononuclear cells (PBMCs) and PBMC activators established the model’s immunocompetence state. The following four groups: 1) S-PDT-V3a (without oxygenation, without PBMCs); 2) S-PDT-V3b (without oxygenation, with PBMCs); 3) S-PDT-V3c (with oxygenation, without PBMCs); and 4) S-PDT-V3d (with oxygenation, with PBMCs) were assessed for tumoroid size and volume via phase contrast imaging across timepoints (Days 1, 3 & 7) to establish respective growth profiles. Statistical analysis was done using One-way ANOVA followed by student t test for comparison analysis for significance in n=3 replicates (p<0.05).
Results Differences in tumoroid size/volume plateaus were observed due to the presence of oxygenation and PBMCs (figures 1–3). Generally, tumoroids were observed to grow faster in static models with hypoxic states (**p=0.005). Addition of PBMCs alters growth rate in both static and dynamic model systems over time (*p<0.05).
Conclusions The establishment of TME modifications amongst 3D PDT Platforms via oxygenation and immunocompetence variations allows for unique tumoroid conditioning for immuno-oncological studies. Recapitulating oxygenation states adds an essential dimension for immune function assessment under conditions of hypoxia normally observed in a tumor. Further investigations would be carried out to determine the effects of specific immune components and differential oxygenation over extended periods of time.
Histo-morphological growth profile of various soft tissue sarcoma models. Phase Contrast images (4x) of Human Uterine Adenosarcoma models show a slower growth rate in oxygen perfused dynamic models (C, D) in comparison to the static models (A, B). The presence of PBMCs seems to further influence the growth rate over time both in the static and dynamic models.
Growth Profiles of 4 types of soft tissue sarcoma models based on various oxygenation and immune states. PDT models grown with (dynamic model) or without oxygenation (static model) demonstrating impact of Hypoxia on PDT volume (p<0.05). Additional models incorporating PBMCs in static and dynamic models exhibit a delay in tumor growth in comparison due to the presence of the immune system (p<0.05). Data was analyzed using One Way ANOVA followed by comparison of individual groups using student’s t test.
Growth Profiles of 4 types of soft tissue sarcoma models based on various oxygenation and immune states. PDT models grown with (dynamic model) or without oxygenation (static model) demonstrating impact of Hypoxia on PDT size (p<0.05). Additional models incorporating PBMCs in static and dynamic models exhibit a slowing in tumor growth in comparison due to the presence of the immune system (p<0.05). Data was analyzed using One Way ANOVA followed by comparison of individual groups using student’s t test.
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