Generation of mixed ovarian cancer and fibroblast spheroids by bioprinting

Three-dimensional tumour–stroma models are urgently needed to improve the predictive power of preclinical drug screening in ovarian cancer, a disease with high mortality and limited therapeutic success. Here, we present a droplet-bioprinted ovarian cancer model incorporating OVCAR-4 cells expressing nano-luciferase and primary cancer-associated fibroblasts (CAFs) embedded within a collagen (Telecol)-based hydrogel. Using the CELLINK BIO X system, we generated reproducible mini-spheroids with controlled architecture, enabling systematic evaluation of cancer and CAF cell density and chemotherapeutic response. Bioprinted spheroids showed good reproducibility across plates when bioink volume and printing conditions were stable. Increasing cancer cell density produced a non-linear rise in luminescence, and this could be at least partially corrected by normalisation to initial cell number. CAFs consistently and robustly enhanced cancer cell growth in a ratio-dependent manner, and confocal imaging revealed that CAFs frequently organised into encapsulating structures around cancer clusters, forming stromal niches associated with matrix contraction and increased cancer–CAF interface. However, CAFs did not protect cancer cells against carboplatin, as drug sensitivity remained comparable in monoculture and CAF co-cultures. This suggests that CAF-driven growth support and CAF-driven chemoresistance are mechanistically separable in this model. Together, this work establishes a mechanically tunable, spatially defined bioprinted ovarian cancer–CAF model that captures key stromal interactions which are not reproduced in studies using CAF conditioned media alone, while remaining compatible with automated, higher-throughput workflows.

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Publication Details

Journal
In vitro models
Published
2026-03-03
DOI
https://doi.org/10.1007/s44164-026-00107-z
Primary Topic
3D Printing in Biomedical Research
Type
article
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article

Generation of mixed ovarian cancer and fibroblast spheroids by bioprinting

Alan Richardson, Arjan Atwal
In vitro models
3D Printing in Biomedical Research
article

Generation of mixed ovarian cancer and fibroblast spheroids by bioprinting

Alan Richardson, Arjan Atwal
article en

Abstract

Three-dimensional tumour–stroma models are urgently needed to improve the predictive power of preclinical drug screening in ovarian cancer, a disease with high mortality and limited therapeutic success. Here, we present a droplet-bioprinted ovarian cancer model incorporating OVCAR-4 cells expressing nano-luciferase and primary cancer-associated fibroblasts (CAFs) embedded within a collagen (Telecol)-based hydrogel. Using the CELLINK BIO X system, we generated reproducible mini-spheroids with controlled architecture, enabling systematic evaluation of cancer and CAF cell density and chemotherapeutic response. Bioprinted spheroids showed good reproducibility across plates when bioink volume and printing conditions were stable. Increasing cancer cell density produced a non-linear rise in luminescence, and this could be at least partially corrected by normalisation to initial cell number. CAFs consistently and robustly enhanced cancer cell growth in a ratio-dependent manner, and confocal imaging revealed that CAFs frequently organised into encapsulating structures around cancer clusters, forming stromal niches associated with matrix contraction and increased cancer–CAF interface. However, CAFs did not protect cancer cells against carboplatin, as drug sensitivity remained comparable in monoculture and CAF co-cultures. This suggests that CAF-driven growth support and CAF-driven chemoresistance are mechanistically separable in this model. Together, this work establishes a mechanically tunable, spatially defined bioprinted ovarian cancer–CAF model that captures key stromal interactions which are not reproduced in studies using CAF conditioned media alone, while remaining compatible with automated, higher-throughput workflows.

In vitro models
Keele University (GB)
Zero hunger
Openalex Percentile: Top 38%
3D Printing in Biomedical Research
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