Method development for pancreatic and ovarian cancer baseline ctDNA detection and measurable residual disease monitoring.

BACKGROUND

Pancreatic cancer and ovarian cancer are very challenging to diagnose at early stages. The endoscopic retrieval of biopsy tissue from a suspected benign or malignant lesion is challenging due to the tissue's nature. Therefore, within the Instand-NGS4P framework, we developed Measurable Residual Disease (MRD) prototypes to analyze blood plasma samples, with the aim of cost-effectively supporting the differential diagnosis of suspected pancreatic or ovarian neoplasms.

METHODS

Our MRD prototypes examine blood plasma for mutations in cell-free DNA in specific genes associated with pancreatic neoplasms or ovarian neoplasms, respectively. Unique molecular identifiers (UMIs) are used to enable bioinformatic error correction. Ultra-deep sequencing is demonstrated on sequencing platforms from two different vendors (Illumina and MGI). We provide detailed information on bioinformatic processing of sequencing data to perform error-correction.

RESULTS

Using commercially available reference standards, we demonstrate stable mutation detection down to a variant allele frequency (VAF) of 0.1%. At a coverage of 4,000x duplex consensus reads, only two false positives were observed, which can be efficiently mitigated using an appropriate filtering strategy.

CONCLUSIONS

The technical usability of our MRD prototype has been clearly demonstrated for stable low-level VAF detection in commercial reference samples.