Asymmetric CRISPR Approach for Nucleic Acid Quantification

About This Grant

Abstract The quantitative detection of nucleic acids plays an increasingly important role in the early detection and screening of cancers. Although the real-time quantitative PCR method has become the gold standard for nucleic acid quantification, its reliance on expensive equipment and trained personnel limits its use in resource-limited settings. Recently, CRISPR technology has emerged as a simple and powerful tool for highly sensitive and specific nucleic acid detection when combined with nucleic acid pre-amplification. However, due to the incorporation of the pre-amplification step, CRISPR-based detection methods require multiple operations and lack the quantitative detection capabilities needed for nucleic acid targets. Therefore, developing a simple and sensitive CRISPR approach for the quantitative detection of nucleic acid biomarkers (e.g., microRNAs) remains a challenge. Recent studies have demonstrated that exosomal microRNAs (exo-miRNAs) are promising liquid biopsy biomarkers for detecting cancer progression and assessing therapy efficacy with high sensitivity and specificity. However, current methods for exo-miRNA detection often require expensive equipment and specialized expertise, hindering their widespread clinical application. Here, we propose to study an asymmetric CRISPR approach for the quantitative detection of nucleic acids (e.g., exo-miRNAs). Furthermore, we will integrate the asymmetric CRISPR assay into a microfluidic chip to develop an asymmetric CRISPR diagnostic platform for exo-miRNA profiling in clinical blood samples. As an example application, we will adapt our asymmetric CRISPR diagnostic platform for the non-invasive early detection of breast cancer—the most commonly diagnosed cancer in the world—and rigorously validate its clinical application. Ultimately, the success of our proposed project will enable clinical translation, facilitating the development of a simple, sensitive, nucleic acid-based molecular detection method for early cancer detection and personalized medicine.