Copy Number Alteration Profiling from Plasma cfDNA WES in Advanced NSCLC

Area of Science:

• Genomics
• Molecular Biology
• Cancer Research

Background:

• Circulating cell-free DNA (cfDNA) sequencing is a minimally invasive method for tumor genome profiling.
• Detecting copy number alterations (CNAs) from cfDNA whole-exome sequencing (WES) faces challenges from noise and guanine-cytosine (GC)-related bias.

Purpose of the Study:

• To develop and evaluate an advanced pipeline for robust CNA detection in advanced non-small cell lung cancer (NSCLC) using cfDNA WES.
• To address the technical challenges associated with CNA detection in cfDNA WES data.

Main Methods:

• Characterized read count patterns in cfDNA WES data.
• Developed and applied an advanced pipeline incorporating locally estimated scatterplot smoothing (LOESS)-based GC bias correction.
• Evaluated CNA detection accuracy, reproducibility, and concordance with The Cancer Genome Atlas (TCGA) data.

Main Results:

• Read count signals strongly correlated with GC content.
• LOESS-based GC bias correction effectively reduced false positives and improved CNA detection.
• cfDNA CNA profiles were reproducible within patients and showed strong concordance with TCGA tissue-level patterns for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

Conclusions:

• The developed cfDNA WES pipeline enables robust CNA detection in NSCLC.
• GC bias correction is crucial for accurate CNA profiling from cfDNA WES.
• cfDNA WES is a practical and minimally invasive alternative for genomic characterization of NSCLC.