The integration of 3D bioprinting technology and CRISPR-Cas9 genome editing has become a game-changing method for creating complex organotypic cancer models. This integrated platform overcomes the drawbacks of traditional 2D culture systems by enabling precise genetic modifications within physiologically relevant, biomimetic tumor microenvironments. Researchers can more precisely recreate tumor progression, oncogenic mutations, cellular heterogeneity, and drug resistance mechanisms by utilizing the structural complexity provided by 3D bioprinting and the specificity of CRISPR-Cas9-mediated gene editing. CRISPR-Cas9 enables specific gene modifications, including oncogene knockout (e.g., MYC, KRAS) or immune checkpoint genes (e.g., PD-1, PD-L1), in 3D-bioprinted structures made from tumorigenic or patient-specific cell populations. It has been demonstrated that these modified models maintain important histopathological and molecular characteristics of original tumors, allowing for accurate high-throughput screening of immunotherapeutics and anticancer drugs. Significantly speeding up the modeling of tumorigenesis, studies using prostate cancer organoids showed gene correction efficiencies ranging from 50 to 90 %. Additionally, in 3D cultures, combinatorial CRISPR-Cas9 editing has demonstrated synergistic drug responses in models of lung and breast cancer, underscoring the platform's potential for discovering new therapeutic targets. Biomaterial-based vectors, like hydrogels and nanocarriers, are being improved to reduce off-target effects and increase intracellular uptake to increase the accuracy and safety of CRISPR delivery. However, issues with scalability, reproducibility, and standardization still exist, requiring ongoing interdisciplinary cooperation to improve downstream validation procedures, gene-editing tactics, and bioink formulations. The potential of CRISPR-Cas9-integrated 3D bioprinting as a state-of-the-art technique for drug discovery and cancer modeling is highlighted in this review. It emphasizes how the platform can speed up translational research in oncology, lessen dependency on animal models, and customize treatment plans. The goal of this review is to present a thorough summary of current developments, technical difficulties, and potential paths forward in this quickly developing field.
| Date: | 2026-02-05 |
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| Authors: | Shukla AK, Shukla S, Upadhyay AM, Nagappan A, Raj Kumar RK. |
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| Ref: | Preprints.org |
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