Data from A Noninvasive Circulating Tumor DNA Methylation Classifier to Identify Benign Pulmonary Nodules

<jats:p>&lt;div&gt;Abstract Purpose:&lt;p&gt;Low-dose computed tomography suffers from a high false-positive rate in the evaluation of pulmonary nodules. Circulating tumor DNA (ctDNA) methylation is a promising complementary biomarker, but its detection is hindered by the highly fragmented nature of ctDNA.&lt;/p&gt; Experimental Design:&lt;p&gt;We developed single-strand amplification methylation-targeted sequencing (SAMT-Seq), optimized for methylation detection in fragmented ctDNA. Lung cancer–specific methylation markers were identified from in-house cohort and The Cancer Genome Atlas database and validated in paired tissue and plasma samples from 30 patients with early-stage lung cancer. A panel of 30 key markers was selected using least absolute shrinkage and selection operator (LASSO) regression in a training cohort (&lt;i&gt;n&lt;/i&gt; = 239). A Gaussian process classifier was developed and validated in two independent cohorts (&lt;i&gt;n&lt;/i&gt; = 59 and &lt;i&gt;n&lt;/i&gt; = 207).&lt;/p&gt; Results:&lt;p&gt;SAMT-Seq demonstrated superior analytic sensitivity and on-target efficiency compared with a standard commercial Swift method. The 30-marker classifier yielded area under the curve values of 0.95, 0.95, and 0.92 in the training cohort and validation cohorts 1 and 2, respectively. Notably, it maintained robust performance across nodule types (solid/subsolid), sizes, smoking status, and &lt;i&gt;in situ&lt;/i&gt; carcinoma. With a predefined threshold, the model achieved specificity of 100% and 92.16% in validation cohort 1 and 2, respectively, suggesting its potential utility in reducing false-positive classifications.&lt;/p&gt; Conclusions:&lt;p&gt;We developed a high-specificity ctDNA methylation classifier that serves as a practical, complementary tool for risk stratification of pulmonary nodules, with the potential to significantly reduce unnecessary invasive procedures. Ongoing prospective diagnostic validation studies are evaluating its clinical performance.&lt;/p&gt;&lt;/div&gt;</jats:p>