Cancer Genetics and Epigenetics, 2025, Vol.13, No.1, 41-49 http://medscipublisher.com/index.php/cge 46 Non-viral vectors based on nanomaterials have become an alternative due to their scalable production and low immunogenicity. However, its targeting efficiency still needs to be optimized to ensure the safe delivery of the editing components (Wei et al., 2020; Allemailem et al., 2022). The research and development of intelligent responsive nanocarriers is gradually breaking through the delivery technology bottleneck by enhancing the cell absorption and controlled-release capabilities. 5.3 Ethical controversies and implementation obstacles in clinical transformation The clinical application of CRISPR therapy faces severe ethical controversies and regulatory barriers. The irreversible genetic modification that may be caused by gene editing has led to widespread concerns about its long-term safety. Regulatory authorities require that CRISPR-based treatment regimens must pass a strict safety verification and efficacy evaluation system, resulting in a complex approval process and prolonged cycle (Chen et al., 2019; Balon et al., 2022). These normative requirements have promoted the standardization process of the transformation from basic research to clinical practice. The individualized treatment demands derived from tumor heterogeneity pose multiple challenges to the development of standardized CRISPR protocols. The genetic diversity of patients and the complexity of the tumor microenvironment require the formulation of individualized intervention plans (Chen et al., 2019; Balon et al., 2022). Furthermore, the existing medical system has a weak ability to integrate gene therapy technology, and new diagnosis and treatment pathways need to be established to promote the clinical application and transformation of the technology. 6 Future Prospects for Breast Cancer Treatment 6.1 Development of individualized CRISPR treatment framework The development of an individualized CRISPR treatment framework will become an important breakthrough direction in precision medicine for breast cancer. Through the dynamic adaptation of gene editing strategies to the genetic characteristics of patients, it is expected to achieve customized and precise intervention. This system is based on the systematic identification of patient-specific oncogenic mutations and genetic variations to achieve targeted regulation of core oncogenic pathways. This individualized plan not only reduces the risk of off-target, but also delays the evolution process of drug resistance and significantly improves the therapeutic efficacy (Chen and Zhang, 2018; Hazafa et al., 2020; Sabit et al., 2021). The integration of multi-omics data can optimize the accuracy of the treatment plan. The optimal editing targets were screened through genome-wide characteristic analysis to ensure that the intervention was both specific and effective. This strategy not only enhances the accuracy of treatment, but also provides a new dimension for analyzing the mechanism of breast cancer occurrence, facilitating the discovery of new targets (Liu et al., 2019; Singh et al., 2021). 6.2 Target discovery through the integration of intelligent computing and multi-omics The collaborative application of artificial intelligence and multi-omics data injects new impetus into the identification of breast cancer targets. AI algorithms, by integrating big data of the genome, transcriptome and proteome, can analyze molecular interaction networks that are difficult to identify by traditional methods. This data-driven model can rapidly locate the key hub genes regulating the progression of breast cancer (Sharma et al., 2020; Allemailem et al., 2022; Misra et al., 2023). The combination of artificial intelligence analysis data and CRISPR precise editing technology has significantly shortened the functional verification cycle of candidate targets. This integration strategy not only deepens the understanding of the mechanism of tumor occurrence, but also promotes the continuous improvement of personalized treatment plans. With the continuous innovation of AI technology, its synergy with the CRISPR system will reconstruct the methodological system of breast cancer research (Hazafa et al., 2020; Balon et al., 2022).
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