| 2 | Programmable endonuclease combined with isothermal polymerase amplification to selectively enrich for rare mutant allele fractions显示文摘Liquid biopsy is a highly promising method for non-invasive detection of tumor-associated nucleic acid fragments in body fluids but is challenged by the low abundance of nucleic acids of clinical interest and their sequence homology with the vast background of nucleic acids from healthy cells.Recently,programmable endonucleases such as clustered regularly interspaced short palindromic repeats(CRISPR)associated protein(Cas)and prokaryotic Argonautes have been successfully used to remove background nucleic acids and enrich mutant allele fractions,enabling their detection with deep next generation sequencing(NGS).However,the enrichment level achievable with these assays is limited by futile binding events and off-target cleavage.To overcome these shortcomings,we conceived a new assay(Programmable Enzyme-Assisted Selective Exponential Amplification,PASEA)that combines the cleavage of wild type alleles with concurrent polymerase amplification.While PASEA increases the numbers of both wild type and mutant alleles,the numbers of mutant alleles increase at much greater rates,allowing PASEA to achieve an unprecedented level of selective enrichment of targeted alleles.By combining CRISPR-Cas9 based cleavage with recombinase polymerase amplification,we converted samples with0.01%somatic mutant allele fractions(MAFs)to products with 70%MAFs in a single step within 20 min,enabling inexpensive,rapid genotyping with such as Sanger sequencers.Furthermore,PASEA's extraordinary efficiency facilitates sensitive real-time detection of somatic mutant alleles at the point of care with custom designed Exo-RPA probes.Real-time PASEA'performance was proved equivalent to clinical amplification refractory mutation system(ARMS)-PCR and NGS when testing over hundred cancer patients'samples.This strategy has the potential to reduce the cost and time of cancer screening and genotyping,and to enable targeted therapies in resource-limited settings. | Junman Chen Tian Qiu Michael G.Mauk Zheng Su Yaguang Fan Dennis J.Yuan Qinghua Zhou Youlin Qiao Haim H.Bau Jianming Ying Jinzhao Song | 2022 | Chinese Chemical Letters2022，33，8： | 0 |
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