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Data · dataset · 2022

Prediction model for malignant pulmonary nodules based on cfMeDIP-seq and machine learning

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Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a new bisulfite-free technique, which can detect the whole-genome methylation of blood cell-free DNA (cfDNA).

Description

Using this technique, we identified differentially methylated regions (DMR) of cfDNA between lung tumors and normal controls. Based on the top 300 DMR, we built a random forest prediction model, which was able to distinguish malignant lung tumors from normal controls with high sensitivity and specificity of 91.0% and 93.3% (AUROC curve of 0.963).

In summary, we reported a non–invasive prediction model that had good ability to distinguish malignant pulmonary nodules.

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Provenance · 1 source records, 13 field assertions
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ScienceDB10.57760/sciencedb.0573712 d agoJSON v1
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