Comprehensive multiparameter genetic analysis improves circulating tumor DNA detection in head and neck cancer patients

Introduction: Tumor-specific genetic aberrations in cell-free DNA (cfDNA) from plasma are promising biomarkers for diagnosis of recurrent head and neck squamous cell carcinoma (HNSCC). However, the sensitivity when using somatic mutations only in cfDNA is suboptimal. Here, we combined detection of copy number aberrations (CNAs), human papillomavirus (HPV) DNA and somatic mutations in a single sequencing workflow.

Methods: Pretreatment plasmas of 40 patients and 20 non-cancer controls were used for analysis. Plasma DNA underwent low-coverage whole genome sequencing (lcWGS) to detect both CNAs and HPV-DNA, and deep sequencing to detect mutations in 12 frequently altered cancer driver genes in HNSCC using the same sequencing library. A specific analysis pipeline line was developed for data mining. The corresponding tumors were analyzed using slightly adapted protocols.

Results: Using the developed method, somatic mutations and CNAs were detected in plasma DNA of HNSCC patients in 67% and 52%, respectively. HPV-DNA in plasma was detected in 100% of patients with HPV-positive tumors, and not in plasma of patients with HPV-negative tumors or non-cancer controls. Combined analysis increased the detection rate of tumor DNA in plasma to 78%. The detection rate was significantly associated with the stage of disease of the tumor. Neither HPV status nor location of the primary tumor influenced detection of CNAs or somatic mutations in plasma.

Conclusions: This study demonstrates that the combined analysis of CNAs, HPV and somatic mutations in plasma of HNSCC patients is feasible and contributes to a higher sensitivity of the assay compared to single modality analyses.