ArticleMethods in molecular biology (Clifton, N.J.)2026
Detection of Chimeric RNAs from RNA-Seq Data with ChiTaRS 8.0: Insights for Liquid Biopsy and Drug Target Identification.
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Chimeric RNAs (chiRNAs), generated via genomic rearrangements or splicing events, are increasingly recognized as biomarkers and therapeutic targets in cancer and neurodegenerative disorders. This chapter introduces an integrative framework for high-confidence chiRNA identification leveraging the ChiTaRS 8.0 database and the ChiTaH pipeline. ChiTaRS 8.0 encompasses 47,445 human chiRNAs, 1,055 Hi-C breakpoints, and 1,598 drug targets, while ChiTaH facilitates disease-specific analysis of RNA-seq data from 250 peripheral blood mononuclear cell (PBMC) samples-including glioblastoma and oral squamous cell carcinoma-and 199 healthy controls. Our approach combines reference-based fusion detection, BLAT validation against GRCh38, gene-pair compatibility checks, and protein domain conservation analysis. Functional annotation and protein-protein interaction modeling uncovered oncogenic chiRNAs absent from existing databases, exhibiting tissue-specific patterns. In Alzheimer's disease, liquid biopsy analyses identified unique chimeras-such as ENO1-MCUR1 and APOE-APOE-in cerebrospinal fluid, linked to neurotransmitter pathways and amyloid processing, and absent in healthy samples, highlighting their potential as early biomarkers. We describe a scalable digital hospital framework integrating AI-driven fusion detection, relational databases, and clinical metadata for real-time diagnostics and patient monitoring. This system supports fusion-targeted drug discovery and patient stratification, bridging translational gaps in oncology and neurodegeneration. By coupling computational pipelines with multiomics data, our approach advances personalized medicine while addressing challenges in artifact filtering and functional validation. Ultimately, the ChiTaRS-ChiTaH platform offers a versatile tool for chiRNA discovery and annotation across diverse disease contexts, providing insights into molecular mechanisms and clinical applications.
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