Established and Emerging Less Invasive Biomarkers and Technologies for Lung Cancer Screening: Puerto Rican Context

Background/Objectives: In Puerto Rico (PR), lung cancer mortality remains high because diagnoses frequently occur at advanced stages. Although low-dose computed tomography (LDCT) lowers lung cancer–specific mortality, this screening is difficult to operationalize locally due to high false-positive rates, radiology capacity constraints, payer limitations, and geographic barriers affecting rural populations. Methods: We performed a narrative review on the literature from 2001–2026 of established and emerging detection strategies—LDCT; serum biomarkers (CEA, CYFRA-21-1, NSE, ProGRP, SCC-Ag, HE4, Hp, TAAb); breath analysis (FeNO and VOCs); and liquid biopsy (ctDNAs/CTCs/miRNAs). We assessed technical performance, feasibility, and health-system fit in PR and then synthesized these findings into an implementable biomarker-first triage workflow for are. Results: Multiplex serum panels analyzed with machine learning outperform single markers and TAAb provide high specificity with biological lead time, supporting their use as a triage gateway before LDCT. Breathomics is also feasible at the point of care. Liquid biopsy has modest sensitivity in very-early disease yet provides molecular adjudication for indeterminate nodules. A stepwise pathway—expanded risk assessment, integrated multi-panel testing in primary care, LDCT reserved for biomarker-positive individuals, and liquid biopsy when imaging is inconclusive—can enrich pre-test probability, reduce unnecessary scans, align with capitation, and protect limited radiology capacity. Conclusions: An integrated, non-invasive, biomarker-first triage model offers a pragmatic, equitable route to earlier lung cancer detection in PR and resource stewardship, while reducing disparities.