Analytical validation of a novel multi-analyte plasma test for lung nodule characterization

Nanoparticle-Based Bioaffinity Assays: From the Research Laboratory to the Market

Advances in the development of new biorecognition elements, nanoparticle-based labels as well as instrumentation have inspired the design of new bioaffinity assays. This review critically discusses the potential of nanoparticles to replace current enzymatic or molecular labels in immunoassays and other bioaffinity assays. Successful implementations of nanoparticles in commercial assays and the need for rapid tests incorporating nanoparticles in different roles such as capture support, signal generation elements, and signal amplification systems are highlighted. The limited number of nanoparticles applied in current commercial assays can be explained by challenges associated with the analysis of real samples (e.g., blood, urine, or nasal swabs) that are difficult to resolve, particularly if the same performance can be achieved more easily by conventional labels. Lateral flow assays that are based on the visual detection of the red-colored line formed by colloidal gold are a notable exception, exemplified by SARS-CoV-2 rapid antigen tests that have moved from initial laboratory testing to widespread market adaption in less than two years.

Accurate diagnosis of pulmonary nodules using a noninvasive DNA methylation test

BACKGROUNDCurrent clinical management of patients with pulmonary nodules involves either repeated low-dose CT (LDCT)/CT scans or invasive procedures, yet causes significant patient misclassification. An accurate noninvasive test is needed to identify malignant nodules and reduce unnecessary invasive tests.METHODWe developed a diagnostic model based on targeted DNA methylation sequencing of 389 pulmonary nodule patients' plasma samples and then validation in 140 plasma samples independently. We tested the model in different stages and subtypes of pulmonary nodules.RESULTSA 100-feature model was developed and validated for pulmonary nodule diagnosis; the model achieved a receiver operating characteristic curve-AUC (ROC-AUC) of 0.843 on 140 independent validation samples, with an accuracy of 0.800. The performance was well maintained in (a) a 6 to 20 mm size subgroup (n = 100), with a sensitivity of 1.000 and adjusted negative predictive value (NPV) of 1.000 at 10% prevalence; (b) stage I malignancy (n = 90), with a sensitivity of 0.971; (c) different nodule types: solid nodules (n = 78) with a sensitivity of 1.000 and adjusted NPV of 1.000, part-solid nodules (n = 75) with a sensitivity of 0.947 and adjusted NPV of 0.983, and ground-glass nodules (n = 67) with a sensitivity of 0.964 and adjusted NPV of 0.989 at 10% prevalence. This methylation test, called PulmoSeek, outperformed PET-CT and 2 clinical prediction models (Mayo Clinic and Veterans Affairs) in discriminating malignant pulmonary nodules from benign ones.CONCLUSIONThis study suggests that the blood-based DNA methylation model may provide a better test for classifying pulmonary nodules, which could help facilitate the accurate diagnosis of early stage lung cancer from pulmonary nodule patients and guide clinical decisions.FUNDINGThe National Key Research and Development Program of China; Science and Technology Planning Project of Guangdong Province; The National Natural Science Foundation of China National.