For patients and clinicians hoping that a simple blood draw—or saliva sample, or breath test—could reliably detect lung cancer early, the gap between promising research and clinical reality has been frustratingly wide. This comprehensive review pinpoints exactly why: not a shortage of biomarkers, but a near-total absence of the standardized protocols needed to make those biomarkers trustworthy across laboratories and health systems.
The review systematically maps pre-analytical variability across six non-invasive biofluids—blood, urine, saliva, sputum, exhaled breath condensate, and sweat—examining how collection methods, processing timelines, storage temperatures, and matrix-specific confounders such as hemolysis, salivary enzyme activity, and volatile compound degradation each independently distort biomarker signals. Across five major analytical platforms—qRT-PCR, next-generation sequencing, mass spectrometry, ELISA, and electrochemical biosensors—the authors document significant cross-platform reproducibility failures for six analyte classes including circulating tumor DNA, microRNAs, extracellular vesicles, and volatile organic compounds. The core argument is that biomarker discovery has vastly outpaced the harmonization infrastructure required for clinical implementation.
This is an important diagnostic medicine problem that extends well beyond lung cancer. The liquid biopsy field broadly suffers from what might be called a 'replication debt'—hundreds of discovery cohorts generating exciting sensitivities and specificities that collapse when independently validated, often because pre-analytical handling was never controlled or reported. For lung cancer specifically, where five-year survival jumps from roughly 10% at late-stage diagnosis to over 60% at localized detection, the clinical stakes of resolving this are enormous. The review's value lies less in new data and more in constructing a systematic framework clinicians and laboratory directors can use to audit their own workflows. Key limitations: as a review rather than an original trial, it cannot quantify the aggregate effect size of pre-analytical noise across real-world cohorts. Still, for any institution building a liquid biopsy program, this represents essential infrastructure guidance—incremental in science, but potentially high-impact in practice.