
Research article
Select search scope: search across all journals or within the current journal


The global burden of chronic and genetic kidney diseases poses a significant challenge to healthcare systems. Current therapies, including dialysis, transplantation, and supportive pharmacotherapies, cannot halt disease progression or address root causes, especially in monogenic disorders like Alport syndrome and Fabry disease. Adeno-associated virus (AAV)-based gene therapy is promising, enabling targeted correction of underlying genetic defects. However, renal delivery faces challenges, including cellular heterogeneity, anatomical barriers, and pre-existing immunity. This review evaluates advances in AAV capsid engineering to overcome these obstacles, focusing on strategies to enhance kidney-specific tropism, transduction efficiency, and immune evasion. We outline the evolution from conventional serotype selection to precision engineering via rational design, directed evolution, and in silico approaches. Artificial intelligence (AI) has emerged as a pivotal accelerator, with machine learning models and generative frameworks enabling data-efficient capsid optimization despite limited datasets. Multimodal AI, reinforcement learning, and agentic systems can refine renal targeting by balancing glomerular penetration, cell specificity, and safety. Future progress relies on scaling high-quality datasets through collaborative consortia, lab-in-the-loop validation, and explainable AI. By combining capsid engineering with renal pathophysiology insights, this roadmap paves the way for curative AAV therapies that move beyond current suboptimal treatments to correct underlying pathogenic mechanisms.
Rheumatoid arthritis is a chronic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. Although biological disease-modifying anti-rheumatic drugs (DMARDs) have transformed treatment, their systemic immunosuppression, high cost, and incomplete efficacy in certain joints remain significant challenges. To address these limitations, we developed a localized gene therapy using the human indoleamine 2,3-dioxygenase (
Emerging evidence suggests CAR-NK cell therapy shows great promise in cancer treatment. ROBO1 is highly expressed in various cancer types, including glioblastoma, hepatocellular carcinoma, lung cancer, breast cancer, and uterine cancer. Our and other laboratories’ studies have shown that ROBO1 CAR-NK cells exhibit promising tumor therapeutic effects. However, the results still have some limitations. Cbl-b, an E3 ubiquitin ligase, has been reported to negatively regulate NK cell activation, homeostasis, and antitumor immunity.
1
Therefore, we attempted to further enhance the antitumor activity of ROBO1 CAR-NK92 cells by knocking out
Site-specific integration of large genes in human primary stem cells remains a significant challenge in gene therapy, particularly for treating multiallelic diseases. Gene editing efficiency in primary stem cells is heavily influenced by the delivery strategy, which often faces issues with programmability, efficiency, and specificity. Here, we developed a dual-viral delivery system, targeted integration via virus-like particles and integrase-deficient lentivirus (TIVID). This system combines virus-like Cas9 edit particles for delivering Cas9/sgRNA ribonucleoprotein complexes and integrase-deficient lentiviral vectors for delivering HDR donor templates. The TIVID system achieves a knock-in efficiency of 65% ± 5% in human induced pluripotent stem cells (iPSCs). In erythroid progenitor HUDEP2 cells, TIVID mediates precise integration of a 7.1 kb HBB-GFP cassette (from cut site to cut site) at the
To treat patients affected with bestrophinopathies caused by mutations in the
Comprehensive recombinant adeno-associated virus characterization is essential for establishing the knowledge base required to ensure clinical safety and efficacy, yet current long-read methods suffer from library preparation biases that obscure genome integrity. We present AviNP-seq, a blindspot-free nanopore sequencing framework utilizing one-end-sufficient ligation and Cas9–ribonucleoprotein (RNP) linearization to minimize terminal selection. Applied to a 1.5–6.5 kb panel, AviNP-seq delineates a sharp packaging cliff at 5.0–5.2 kb and reveals that sequence structure modulates integrity by 2–5× at fixed lengths. It unmasks covalent head-to-tail tandems in sub-3 kb vectors, detecting them with significantly higher sensitivity than PacBio HiFi. The Cas9–RNP step boosts ligation yield ∼7-fold, providing an unbiased assessment of genome integrity (≥95% inverted terminal repeat [ITR]-to-ITR). In addition, the assay quantifies plasmid impurities down to 0.05% with linear response. By integrating integrity mapping, tandem detection, and impurity profiling into a rapid (<36 h), low-input workflow, AviNP-seq provides a robust analytical tool to guide vector design and de-risk early-stage process development.