Early detection of lung cancer in high-risk individuals reduces mortality. Low-dose spiral computed tomography (LDCT) is the current standard but suffers from an exceedingly high false-positive rate (>96%) leading to unnecessary and potentially dangerous procedures. We, therefore, set out to develop a simple, noninvasive, and quantitative assay to detect lung cancer. This proof-of-concept study evaluated the sensitivity/specificity of the CyPath Early Lung Cancer Detection Assay to correctly classify LDCT-confirmed cohorts of high-risk control (n = 102) and cancer (n = 26) subjects. Fluorescence intensity parameters of red fluorescent cells (RFCs) from tetra (4-carboxyphenyl) porphyrin (TCPP)-labeled lung sputum samples and subjects' baseline characteristics were assessed for their predictive power by multivariable logistic regression. A receiver operating characteristic curve was constructed to evaluate the sensitivity/specificity of the CyPath assay. RFCs were detectable in cancer subjects more often than in high-risk ones (p = 0.015), and their characteristics differed between cohorts. Two independent predictors of cancer were the mean of RFC average fluorescence intensity/area per subject (p < 0.001) and years smoked (p = 0.003). The CyPath-based classifier had an overall accuracy of 81% in the test population; false-positive rate of 40% and negative predictive value of 83%. The tetra (4-carboxyphenyl) porphyrin -based CyPath assay correctly classified study participants into cancer or high-risk cohorts with considerable accuracy. Optimizing sputum collection, sample reading, and refining the classifier should improve sensitivity and specificity. The CyPath assay thus has the potential to complement LDCT screening or serve as a stand-alone approach for early lung cancer detection.