Diagnostics of lung cancer by fragmentated blood circulating cell-free DNA based on machine learning methods.

ABSTRACT:

Introduction

Minimally invasive diagnostics based on liquid biopsy makes it possible early detection of lung cancer (LC). The blood plasma circulating cell-free DNA (cfDNA) fragments reflect the genome and chromatin status and are considered as integral cancer biomarkers and the biological entities for 'cancer-of-origin' prediction. The aim of this work is to create a method for processing next-generation sequencing (NGS) data and an interpretable binary classification model (CM), which analyzed cfDNA fragmentation features for distinguishing healthy subjects and subjects with LC.

Methods

148 healthy subjects and 138 subjects with LC were included in the study. cfDNA fractions, isolated from blood plasma biospecimens, were used for DNA libraries preparations and NGS on the N

SUBMITTER: Meshkov IO 

PROVIDER: S-EPMC11813899 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature