Aug 2026· Cell Reports Physical Science· 35 references
RNA Interference and Gene Delivery
Abstract
Lipid nanoparticles (LNPs) are promising non-viral vectors for central nervous system (CNS) gene therapy, but effective delivery is limited by the blood-brain barrier and cell-type specificity. Here, we combined intracranial delivery with high-throughput, cluster-based screening and machine learning to identify LNP formulations optimized for functional neuronal gene-editing activity. We screened 720 LNP formulations for their ability to transfect neurons and deliver genetic payloads efficiently. Following this, cluster-mode intracranial screening enabled targeted delivery to specific brain regions, including the ventral posteromedial nucleus (VPM) and hippocampus, and efficiently narrowed hundreds of candidates to single optimized formulations. Optimized LNPs achieved approximately 20% gene editing, measured as functional activity, in targeted areas and exhibited neuron- and astrocyte-enriched transfection patterns. These results demonstrate that intracranial delivery, combined with machine-learning-guided optimization, can identify LNPs capable of precise cell- and region-preferential gene delivery, supporting the development of targeted therapies for neurological disorders.
It is concluded that bridging the gap between foundational CRISPR research and its real-world applications is imperative and future efforts should focus on democratizing tools via open-source platforms, advancing delivery systems, and fostering sustainable innovation through synthetic biology integration to fully realize the transformative potential of genome editing in organisms beyond model organisms.
S. Sarsaiya, Archana Jain, Jishuang Chen et al.· Biotechnology Advances· 2 citations
It is argued that formation of a tumour-intrinsic niche is a prerequisite for BRAF-mutant CRC seeding to distant organs and that interference with niche formation may help avoid metastatic relapse.
J. Bugter, L. El Bouazzaoui, E. Küçükköse et al.· bioRxiv· 2 citations
This review summarizes emerging therapeutic strategies for EOC, their mechanisms of action, and their potential to overcome treatment resistance, and covers molecularly targeted therapies, immunotherapies, metabolic and epigenetic approaches, cellular and gene therapies, targeted drug-delivery systems, and locoregional and physical modalities.
Zofia Pietrasik, Mikołaj Kapała, Joanna Pietrasik et al.· Cancers· 0 citations
Genetic engineering (GE) and gene editing may endow traits to trees such as increased biomass and the production of novel biomaterials. Long-lived organisms such as trees might be subject to biotechnology-related risks that could be different than those of annual row crops. Those risks could be relevant to production in engineered plantations and beyond plantations to natural forests. Therefore, appropriate risk regulation is important to assure biosafety of commercialized engineered trees. In addition to gene flow via sexual reproduction, vegetative reproduction might play an additional role in environmental "exposure" risk relative to transgene dispersal in GE tree plantations. While vegetative reproduction is beneficial for preserving desired genetic traits during tree propagation, it may lead to proximal clonal spread in the field. Although the environmental risks associated with vegetative reproduction of GE trees are recognized in commercial forestry, there are few field-based environmental risk assessment (ERA) studies on dispersal risks of self-propagated GE trees. GE or gene editing of target genes involved in the vegetative propagation processes may be useful to mitigate environmental risks of clonal spread through vegetative reproduction. This review provides updates for recent field test results of GE and gene edited trees. Gene candidates related to vegetative reproduction including adventitious shooting (AS) and adventitious rooting (AR) are discussed herein as a means to mitigate unintended clonal spread from GE tree plantations.
Findings establish Cas7-11 as a precise and efficient RNA knockdown tool for functional studies in embryonic development and stem cell biology, providing a versatile alternative to DNA-based gene-editing approaches.
Huan Yan, Imtiaz Ul Hassan, Kai Yan et al.· Cell & Bioscience· 0 citations
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
MIT News · Artificial Intelligence· news.mit.eduAug 17, 2026