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--- |\n| AI-driven CRISPR strategies in breast cancer: Organoid modeling, adaptive editing, and precision delivery\u003Cbr>Anmar Ghanim Taki 1*, Abdulkareem Shareef 2, Vimal Arora 3, Rami Oweis 4, 5, S. Renuka Jyothi 6, Udaybir Singh 7, Samir Sahoo 8, Ashish Singh Chauhan 9, Guzal Klebleeva 10, Hayder Naji Sameer 11, Ahmed Yaseen 12, Zainab H. Athab 13, Mohaned Adil 14\u003Cbr>1 Department of Radiology Techniques, Health and Medical Techniques College, Alnoor University, Nineveh, Iraq\u003Cbr>2 Ahl al bayt University, Kerbala, Iraq\u003Cbr>3 University Institute of Pharma Sciences, Chandigarh University, Mohali, Punjab, India\u003Cbr>4 Modern College of Business and Science, Muscat, Oman\u003Cbr>5 On Sabbatical Leave, from Jordan University of Science and Technology, Irbid, Jordan\u003Cbr>6 Department of Biotechnology and Genetics, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India\u003Cbr>7 Center for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India\u003Cbr>8 Department of General Medicine, IMS and SUM Hospital, Siksha ‘O’Anusandhan (Deemed to be University), Bhubaneswar, Odisha-751003, India\u003Cbr>9 Uttaranchal Institute of Pharmaceutical Sciences, Division of Research and Innovation, Uttaranchal University, Dehradun, Uttarakhand, India\u003Cbr>10 Department of Skin and Venereal Diseases, Samarkand State Medical University, Samarkand, Uzbekistan\u003Cbr>11 Collage of Pharmacy, National University of Science and Technology, Dhi Qar, 64001, Iraq\u003Cbr>12 Gilgamesh Ahliya University, Baghdad, Iraq\u003Cbr>13 Department of Pharmacy, Al-Zahrawi University College, Karbala, Iraq\u003Cbr>14 Pharmacy College, Al-Farahidi University, Baghdad, Iraq |  |  |  |\n| A RT I C L E I N F O\u003Cbr>Article type:\u003Cbr>Review\u003Cbr>Article history:\u003Cbr>Received: Aug 7, 2025\u003Cbr>Accepted: Oct 19, 2025\u003Cbr>Keywords:\u003Cbr>Artificial intelligence Breast neoplasms Circadian rhythm CRISPR-Cas systems Gene editing\u003Cbr>Gene knockout techniques Neoplasm dormancy Triple negative breastneoplasms |  | \u003Cbr>A B ST R A CT\u003Cbr>Triple-negative breast cancer (TNBC) is defined by profound heterogeneity, dormant metastatic reservoirs, and rapid therapy resistance. Building on our AI-Driven CRISPR Strategies in Breast Cancer framework, CRISPR–Cas9 is emerging as more than a gene-editing tool, capable of restoring circadian integrity, eliminating dormant clones, and re-programming immune surveillance. A structured PubMed, Scopus, and [ClinicalTrials.gov](ClinicalTrials.gov) review through 2025 integrated mechanistic, preclinical, and early clinical evidence. Beyond standard knockout, base, and prime editing, we highlight chrono-genomic repair of BMAL1/PER2, dormancy-focused synthetic-lethality screens, and genomic-collapse tactics for BRCA1-deficient tumors. Adaptive AI pipelines that iteratively refine guide RNAs and exosome-mimetic carriers, incorporating Boolean logic gates, were also evaluated for self-regulated, tumor-specific delivery. Proof-of-concept studies show that HER2 deletion, TP53 rescue, and ABCB1 silencing enhance chemosensitivity across luminal, HER2-positive, and TNBC models. Circadian restoration expands therapeutic windows and delays relapse in xenografts. Dormancy-directed CRISPR screens reveal unique vulnerabilities in disseminated tumor cells, whereas genomic collapse selectively destroys BRCA1-mutant clones. Integration with CAR-T cells and antibody–drug conjugates amplifies cytotoxicity, and transient nanoparticle or exosome systems improve solid-tumor penetration while minimizing off-target events. CRISPR–Cas9 is transitioning from a molecular scalpel to an adaptive, self-learning therapeutic ecosystem. By uniting AI-guided design, circadian reprogramming, dormancy eradication, and logic-gated delivery, the strategies detailed here define a next-generation precision-oncology paradigm capable of ","cbCaiun59qOUvLfA","https://ap.wps.com/l/cbCaiun59qOUvLfA","pdf",1612484,21,"English","# Introduction\n# Article Type and History\n## Review Focus and Keywords\n# Abstract\n## Mechanistic and preclinical evidence\n## Early clinical and delivery strategies\n# Citation Information","[{\"question\":\"What is the core therapeutic problem addressed in the review?\",\"answer\":\"The review targets triple-negative breast cancer driven by tumor heterogeneity, dormant metastatic reservoirs, and rapid therapy resistance, which contribute to relapse and limited durability of treatment.\"},{\"question\":\"Which CRISPR editing concepts beyond standard knockout are emphasized?\",\"answer\":\"Beyond knockout, base, and prime editing, the review highlights chrono-genomic repair (e.g., BMAL1/PER2), dormancy-focused synthetic-lethality screens, and genomic-collapse approaches for BRCA1-deficient tumors.\"},{\"question\":\"How does the review describe AI-guided strategies for CRISPR delivery and targeting?\",\"answer\":\"It evaluates adaptive AI pipelines that iteratively refine guide RNAs and use exosome-mimetic carriers, including logic-gated design for self-regulated, tumor-specific delivery to improve penetration and reduce off-target events.\"}]","AI-driven CRISPR strategies in breast cancer - Organoid modeling, adaptive editing, and precision delivery | PDF",1790084246,53]