The Utility of Cell-Free DNA (cfDNA) Fragmentomics as a Novel Biomarker for Early Cancer Detection: A Systematic Review of Analytical Validity and Clinical Potential

Abstract

Background: Despite advancements in medicine, cancer still ranks among the top leading causes of death globally, especially in relation to the chances of survival, which are greatly influenced by early diagnostics. The existing approaches suffer from the necessity for invasive procedures, the resulting high cost associated with them, as well as the accuracy potential limits. The cell-free DNA fragmentomics approach, based on the fragmentation status in the bloodstream, has emerged as a promising candidate.

Methods: A systematic review of the published scientific literature between 2020–2025 was performed on studies identified via search in the biomedical databases PubMed, Embase, and the Cochrane Library. The inclusion criteria included primary research studies assessing cfDNA fragmentomics for the early diagnosis of cancer that quantitatively reported performance accuracy (Sensitivity, Specificity, AUC values). Results were extracted. Results: Analysis of the latest findings shows that fragmentomics-based approaches are able to provide excellent diagnostic performance with AUC values between 0.85 and 0.99 in various types of cancers such as lung cancer, pancreatic cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma. High sensitivity (45% to 99%) and specificity (83% to 99%) are achieved using ultra-low coverage sequencing approaches between 0.05× to 5×. An important development has been the use of machine learning methodologies to combine multi-modal variables such as fragment length, end motif information, nucleosome occupancy data, and methylation_pattern_inferred variables. There are studies on its use in the clinic at various levels. Various platforms are currently under review.

Conclusion: CfDNA fragmentomics is a paradigm-shifting, analytically valid, and promising early cancer detection method. Its cost-effectiveness, high-throughput processing capacity, and ability to detect early-stage and biomarker-negative cancers make it ready for future screening paradigms. Further studies focusing on its validation across varied populations will unravel its ultimate potential benefit in combating cancer-related fatalities.