This study developed a patient-specific induced pluripotent stem cell (iPSC)-based multi-organoid system that integrates pharmacokinetic/pharmacodynamic (PK/PD) modeling with gene correction strategies, enabling precise therapeutic evaluation for NF1-mutant breast cancer and demonstrating a novel paradigm for individualized cancer treatment.
Literature Overview
This article, 'Personalized pharmacokinetic–pharmacodynamic guided therapy via an induced pluripotent stem cell–derived multi-organoid platform in NF1-mutant breast cancer,' published in Signal Transduction and Targeted Therapy, reviews and summarizes research on a personalized pharmacokinetic/pharmacodynamic (PK/PD) assessment and treatment optimization platform for NF1-mutant breast cancer, built using a patient-specific induced pluripotent stem cell (iPSC)-derived network of intestinal, hepatic, and renal organoids (NOCS). The study integrates genomic analysis, exon-skipping therapy, and small-molecule inhibitor screening, revealing a synergistic anti-tumor effect of Paxalisib combined with NF1 exon-skipping therapy, validated in patient-derived tumor models. This platform provides a preclinical in vitro system capable of simulating drug absorption, distribution, metabolism, and excretion (ADME), advancing the development of personalized cancer therapeutic strategies.Background Knowledge
Neurofibromin, encoded by the NF1 gene, functions as a GTPase-activating protein that negatively regulates the Ras signaling pathway. Loss-of-function mutations in NF1 lead to sustained activation of the Ras/PI3K/AKT and MAPK pathways, promoting tumor proliferation, survival, and drug resistance, and are commonly observed in various solid tumors, including breast cancer. NF1-mutant breast cancer is characterized by high invasiveness and poor response to targeted therapies, resulting in unfavorable clinical outcomes. Although inhibitors targeting the PI3K/mTOR pathway have been developed, their efficacy remains limited due to feedback activation and pathway redundancy, often leading to drug resistance. Gene correction strategies, such as antisense oligonucleotide (ASO)-mediated exon skipping, which restore the reading frame and produce truncated yet functional proteins, have been applied in neuromuscular disorders but remain in early exploration for cancers, particularly NF1-related malignancies. However, the lack of preclinical models that simultaneously recapitulate systemic drug metabolism and tumor-specific responses has hindered the evaluation of such therapies. Organoid technology combined with iPSCs enables the generation of multi-tissue models from patient somatic cells, but single-organoid systems fail to replicate complex inter-organ interactions. Microphysiological systems (MPS), such as organ-on-a-chip platforms, allow multi-organ integration and dynamic substance exchange, offering a promising avenue for constructing personalized PK/PD models. This study establishes a NOCS platform integrating intestinal, hepatic, renal, and tumor models to enable end-to-end personalized prediction from genotype to drug response.
Research Methods and Experiments
The research team reprogrammed somatic cells from a breast cancer patient with a germline NF1 mutation into iPSCs, which were then differentiated into intestinal, hepatic, and renal organoids to construct a networked organoid culture system (NOCS). Whole-exome sequencing confirmed the presence of an NF1 c.165_166insCT frameshift mutation in the patient’s tumor tissue, along with activating mutations in PIK3CA and ERBB2. Exon-skipping gene therapy strategies were designed and screened using ASO and U7-snRNA systems, with their inhibitory effects on the PI3K-AKT pathway validated in patient-derived tumor spheroid models. The NOCS platform was used to evaluate the absorption, metabolism, and pharmacokinetic profiles of multiple PI3K/mTOR inhibitors, combined with in vitro efficacy assays to identify the optimal drug candidate. Finally, the synergistic anti-tumor efficacy of Paxalisib combined with exon-skipping therapy was validated in patient-derived tumor models.Key Conclusions and Perspectives
Research Significance and Prospects
This study represents the first integration of an iPSC-derived multi-organoid system with PK/PD modeling for developing personalized therapeutic strategies in NF1-mutant breast cancer. The platform not only assesses systemic drug exposure but also incorporates gene correction approaches, providing a functional validation tool for 'genotype-matched therapy.' Compared to traditional animal models or single-organ metabolic systems, NOCS more closely mimics human physiology, reducing prediction errors caused by species differences.
Future applications of this platform could extend to other hereditary cancers or diseases with abnormal drug metabolism, enabling optimization of personalized drug regimens, prediction of drug toxicity, and novel drug development. When combined with high-throughput screening and AI algorithms, it may enable automated treatment recommendations. Furthermore, incorporating immune organoids or vascularized systems could further enhance the physiological relevance of the model, advancing precision medicine from 'static genetic testing' toward 'dynamic functional validation.'
Conclusion
This study established a patient-specific iPSC-derived multi-organoid network system (NOCS) for personalized pharmacokinetic–pharmacodynamic (PK/PD) guided therapy in NF1-mutant breast cancer. By integrating intestinal, hepatic, and renal organoids, the platform simulates drug absorption, metabolism, and excretion in vivo, enabling individualized prediction of drug exposure. The study revealed that NF1 mutations not only drive tumor progression but also affect the expression and function of drug metabolism-related genes. By designing an exon-skipping therapy to restore NF1 function and combining it with the NOCS platform to identify the optimal small-molecule inhibitor, Paxalisib, the study achieved a synergistic effect between gene correction and targeted therapy. This work not only provides a potential treatment strategy for patients with NF1-mutant breast cancer but also establishes an integrated precision oncology framework linking 'genotype–metabolism–pharmacodynamics.' The platform holds broad application potential in guiding personalized medication, drug development, and toxicity assessment, driving precision medicine toward functional and dynamic approaches.
