CRISPR-Powered Liquid Biopsy Meets Artificial Intelligence: An Integrated Framework for Next-Generation Point-of-Care Sarcoma Detection

Bone and soft tissue sarcomas remain challenging to diagnose and monitor because of their rarity, molecular heterogeneity, low circulating biomarker abundance, and the limited sensitivity of conventional surveillance for microscopic disease. This narrative review synthesizes current evidence on liquid biopsy biomarkers, CRISPR-Cas-based molecular detection, artificial intelligence (AI), nanotechnology, and point-of-care (POC) platforms, with the aim of defining an integrated framework for sarcoma detection and monitoring. Circulating tumor DNA, methylation signatures, fragmentomic profiles, circulating RNAs, extracellular vesicles, and circulating tumor cells provide complementary diagnostic and prognostic information, although most available studies remain small and heterogeneous. CRISPR-Cas9, Cas12a, and Cas13a systems offer complementary strategies for rare-allele enrichment and ultrasensitive DNA or RNA detection, while nanomaterials can further enhance signal transduction and assay miniaturization. AI can integrate mutational, methylomic, fragmentomic, and biosensor-derived features to support classification, risk stratification, treatment-response assessment, and relapse monitoring. Their convergence within microfluidic POC platforms may enable rapid and decentralized testing. However, limited prospective validation, prediction errors, assay standardization, and regulatory challenges currently preclude routine clinical use. Larger multicenter sarcoma-specific studies are required before this framework can inform clinical decision-making.