Early Cancer Detection Beyond Static Screening: Longitudinal Monitoring, Molecular Biomarkers, and the Limits of Precision Surveillance

Dario Rusciano.

Abstract

Early cancer detection has traditionally relied on episodic screening strategies applied to broad population categories and interpreted against fixed diagnostic thresholds. Although these approaches have reduced mortality in selected settings, they generally detect disease only after anatomical, biochemical, or molecular abnormalities have become sufficiently pronounced to cross predefined cut-offs. Recent advances in genomics, liquid biopsy, and metabolomic profiling have prompted renewed interest in whether earlier detection could be improved not only by adding new biomarkers, but also by changing the logic through which biomarker information is interpreted.

This review examines several complementary dimensions of early tumorigenesis that may inform such a shift, including inherited susceptibility, somatic field evolution, circulating tumor DNA (ctDNA) dynamics, and metabolic remodeling. Germline variants may help refine baseline risk and surveillance intensity, whereas field cancerization and mutational signatures highlight that malignant transformation often develops within spatially and temporally altered tissues before overt cancer becomes clinically detectable. ctDNA offers an important tool for tracking molecular residual disease and clonal persistence, but its utility in very early detection remains constrained by low tumor shedding and biological heterogeneity. Emerging metabolomic and microbiome-related studies further suggest that volatile organic compound (VOC) profiles may reflect tumor-associated ecosystem changes, although this area remains exploratory and far from clinical standardization.

Rather than arguing for a single transformative assay, this review considers whether future early-detection strategies may benefit from combining longitudinal biomarker trajectories, individualized baseline interpretation, germline risk information, and selected multi-omic signals within risk-adapted surveillance models. At present, however, important limitations remain, including assay sensitivity in low-burden disease, falsepositive management, overdiagnosis, and uneven clinical validation across platforms. Early detection is therefore better understood not as a solved technological problem, but as an evolving effort to interpret biological change earlier, more accurately, and with greater clinical discipline.