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Integrative identification of non-coding regulatory regions driving metastatic prostate cancer [CRISPR]

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP526055
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Large-scale sequencing efforts have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of variants occur within non-coding genomic regions. We designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Applying this framework to sequencing data from a large prostate cancer patient cohort revealed a large set of candidate drivers. We used (i) in silico analyses, (ii) massively parallel reporter assays, and (iii) in vivo CRISPR interference screens to systematically validate mCRPC drivers. One found enhancer region, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. SF3A1 and CCDC157 promote tumor growth in vivo. We nominated a number of transcription factors, notably SOX6, to regulate expression of SF3A1 and CCDC157. Our integrative approach enables the systematic detection of non-coding regulatory regions that drive human cancers. Overall design: We harvested tumors from xenograft mouse models resulting from subcutaneous injections with C4-2B CRISPRi-ready cells transduced with a targeted validation library. This library contained sequences of interest as well as non-targeting control sgRNAs. An amplicon sgRNA library was then generated from extracted tumor gDNA.
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2025-10-01
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