Speaker
Description
Transforming Pre-Clinical Drug Testing: 3D Bioprinted Patient-Derived Breast Cancer Models on a Microfluidic Device
Pragati Sharma1 and Subha Narayan Rath1
1Regenerative Medicine and Stem Cell Laboratory (RMS), Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Sangareddy 502284, Telangana, India.
Correspondence: Subha Narayan Rath, Email: subharath@bme.iith.ac.in
Abstract
Introduction: Cancer shows high genetic and phenotypic diversity between people, generating a need for personalized therapy. Three-dimensional bioprinting represents an efficient and advanced technique for precisely recapitulating the cancer microenvironment. Bioprinting on a microfluidic device addresses the challenge of the availability of a limited number of primary cancer cells derived from biopsy or surgically resected cancer tissue. This study is a step forward in creating a pipeline that uses patient cells to develop models for personalized breast cancer drug testing.
Methods: In this study, primary cancer cells were isolated from biopsy and surgically resected breast cancer tissues. To establish bioprinted constructs for personalized drug testing, we employed an extrusion-based 3D bioprinting method using gelatin methacryloyl-based bioink and primary breast cancer cells. Cell proliferation, protein expression, and anticancer drugs were investigated in these 3D cancer models.
Results: Our results demonstrate the successful long-term expansion of primary cancer cells isolated from cancer tissue. The cells are derived from multiple breast cancer patients, each diagnosed with a different grade of carcinoma. Patient-derived models exhibit dissimilar viability, proliferation, and gene expression. Treatment with well-known breast cancer chemotherapeutic drugs at clinically relevant dosages resulted in heterogeneous drug responses among different patient-derived cancer models.
Discussion: The result of this study supports the establishment of an expandable 3D in vitro cancer model for drug screening. The resulting bioprinted cancer model on a microfluidic chip showed diverse responses elicited by patient-derived cancer cells, reproducing patient-specific cancer conditions and providing robust outcomes. Features exhibited by our bioprinted cancer model correlate with the clinical diagnosis mentioned in the histopathological reports of patients. This study addresses the need for a co-clinical trial platform that can prospectively evaluate the effectiveness of drug profiling on cancer-derived cells to decide patient treatment. By adding other cell types of the cancer microenvironment, this model can be advanced to a heterotypic one.
References:
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