PubMed HealthSearch

PubMed · 42486091

Base editing for precision therapeutics.

Abstract

Base editing (BE), the precise installation of single-nucleotide changes in DNA or RNA without inducing double-strand breaks, holds substantial therapeutic promise for correcting single-nucleotide variants, which constitute more than half of the known pathogenic genetic variants. Recent advances have improved base editor specificity, efficiency, and delivery, enabling clinically oriented procedures. Clinically, BE has shown early success or strong translational promise in sickle cell disease, β-thalassemia, leukemia (via CAR T and epitope engineering), hypercholesterolemia (PCSK9 and ANGPTL3), alpha-1-antitrypsin deficiency, and glycogen storage disease type Ia. Key remaining challenges include bystander editing within the activity window, residual off-target DNA and RNA editing, delivery constraints (payload size, tissue targeting, and redosing limits), immunogenicity, and the need for durable long-term safety evidence across relevant cell types and disease contexts. Continued technological refinements, careful preclinical validation, and rigorous clinical assessment will be essential to fully realize BE's transformative potential in precision medicine.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Moksada Regmi, Kuiying Ma, Changhao Bi, Xueli Zhang, Dongdong Zhao, Lingling Yu, Huihui Yang, Ningli Wang, Chenlong Yang. 2026-07-22. Base editing for precision therapeutics.. https://doi.org/10.1016/j.xgen.2026.101298

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans