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International Journal of Bioprinting Bioprint micro breast cancer

in alisertib’s effect on the proliferation of ER+/HER2- findings, particularly in the resistance of PMCaTs to 5-FU
cells (MCF-7) and triple-negative cells (MDA-MB-231). during invasion and the prediction of in vivo drug response,
38
The similar response at lower drug concentrations in offered significant insights into the model’s applicability for
our study suggests a drug-resistant characteristic in the therapeutic evaluation. These findings provide statistical
bioprinted tissues, potentially masking differences between evidence supporting the utility of PMCaTs in assessing
cell types. While the exact mechanism behind this drug drug effectiveness and resistance patterns, enhancing the
resistance has not been systematically investigated, we model’s relevance for preclinical studies.
predict that the native-like structure, combined with
the microenvironment—encompassing CAFs and To further elucidate the model’s predictive accuracy
microvasculature—may contribute to it. However, it is and therapeutic potential, more comprehensive future
worth noting that the results from the PMCaTs more closely quantitative studies need to be designed. These studies are
matched the outcomes from the phase 2 clinical trials, expected to not only validate the preliminary findings but
which indicated the responsiveness of ER+/HER2- cells also expand our understanding of the utility of PMCaTs
to alisertib. This suggests that our PMCaTs may have the across a wider range of cancer treatment scenarios.
potential to predict drug responses seen in clinical settings. 4. Conclusion

Our preliminary findings, which align with outcomes
from human clinical trials, underscore the potential of our The utilization of established cancer cell lines provides a
PMCaTs model as a significant advancement in cancer robust foundation for advancing cancer research. A distinct
research. This comparative analysis is crucial, as it not advantage of our methodology is that it can rival models
only validates the model’s fidelity to native-like tumor made with primary cells in predicting in vivo conditions.
characteristics but also indicates its promising capacity Crucially, this is achieved while mitigating the challenges
for predicting human drug responses. The retrospective of sample variability. Furthermore, our approach leverages
matches to clinical outcomes highlight the model’s the more abundant resource of established cancer cell lines
relevance and applicability, setting a foundation for its use compared to primary cells. The vast existing profile data
in preclinical evaluations. associated with these cell lines complement our approach,
enhancing the depth and reliability of our models. Although
However, these observations are based on initial data further optimization and rigorous validation of the PMCaT
and the forward-predictive power of our PMCaT model model remain essential, we believe that as we progress, our
for drug responses warrants further exploration. To fully method has the potential to influence the methodologies of
harness the potential of our model in aligning with clinical therapeutic research and drug testing in oncology.
realities and enhancing patient treatment strategies, future
work will concentrate on optimizing drug concentrations Acknowledgments
for more accurate predictions. Additionally, conducting
more extensive quantitative studies is essential to verify the Not applicable.
reliability of PMCaTs in drug response prediction, aiming
to bridge the gap between experimental modeling and Funding
clinical application effectively. This project was funded by the Peabody Foundation, Inc.,

Collectively, our study presents a comprehensive the Anthony and Constance Franchi Fund for Pediatric
investigation into the capabilities of the DVDOD Orthopaedics, the Massachusetts General Hospital
bioprinting technique in constructing PMCaTs with a Department of Orthopaedic Surgery, and University of
focus on breast cancer. The results span both quantitative Miami Medical Center and Jackson Memorial Hospital
and non-quantitative aspects, contributing to a holistic Department of Orthopaedics.
understanding of the potential of 3D bioprinted models.
Non-quantitative analyses, including viability and Conflict of interest
structure under fluorescent microscopy, morphology and Dr. Brian E. Grottkau is the founder of 3D Biotherapeutics,
proliferation patterns, establishment of PMCaTs with Inc. Dr. Yonggang Pang and Zhixin Hui declare no conflict
microvasculature, and the dynamics of drug penetration, of interest.
underscored the technique’s efficacy in replicating intricate
in vivo-like tumor environments. These findings highlight Author contributions
the successful incorporation of heterogeneous cell
populations and the formation of hypoxia zones, which Conceptualization: Yonggang Pang, Brian E. Grottkau,
are crucial for modeling cancer’s complexity. Quantitative Zhixin Hui

Volume 10 Issue 3 (2024) 569 doi: 10.36922/ijb.2911