CRISPR-Cas12a/Cas13a in cancer molecular diagnosis
- PMID: 41796733
- DOI: 10.1016/j.cca.2026.120934
CRISPR-Cas12a/Cas13a in cancer molecular diagnosis
Abstract
Cancer remains a leading cause of global mortality, with early diagnosis being pivotal for improving treatment outcomes. Traditional tissue biopsy is limited by its invasiveness, inability to capture tumor heterogeneity, and failure to support dynamic monitoring. Liquid biopsy has emerged as a non-invasive alternative, enabling the analysis of circulating tumor biomarkers (e.g., ctDNA, miRNAs, exosomes) in bodily fluids. However, current liquid biopsy technologies (e.g., NGS, ddPCR) suffer from high costs, complex workflows, poor standardization, and insufficient sensitivity for low-abundance biomarkers. The CRISPR-Cas systems, particularly Cas12a and Cas13a, have revolutionized molecular diagnostics due to their programmable sequence recognition, robust signal amplification via trans-cleavage/collateral cleavage activity, and compatibility with point-of-care testing (POCT). Cas12a targets DNA molecules, enabling sensitive detection of gene mutations and DNA methylation, while Cas13a specifically recognizes RNA, facilitating direct analysis of miRNAs and viral RNAs. Additionally, these systems have been extended to non-nucleic acid biomarkers (e.g., proteins, exosomes) through signal conversion strategies. This review summarizes the latest advances in CRISPR-Cas12a/Cas13a-based biosensors for cancer molecular diagnosis, including the detection of gene mutations, epigenetic modifications, miRNAs, tumor-associated viruses, and non-nucleic acid biomarkers. We critically analyze current challenges (e.g., PAM dependence, matrix interference, multiplexing limitations, clinical validation gaps) and discuss future perspectives, such as engineering PAM-less Cas variants, integrating nanotechnology, microfluidics, and artificial intelligence/artificial intelligence (AI), and advancing clinical standardization. This review aims to provide a comprehensive reference for the development and clinical translation of CRISPR-based cancer diagnostic technologies.
Keywords: AI empowerment; CRISPR-Cas12a; CRISPR-Cas13a; Cancer diagnosis; Clinical translation; Epigenetic detection; Non-nucleic acid biomarkers; Nucleic acid detection; POCT; Tumor-associated viruses.
Copyright © 2026. Published by Elsevier B.V.
Conflict of interest statement
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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