Measurable Residual Disease method development for pancreatic and ovarian cancer detection

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 cancerous lesion is challenging due to the nature of the tissue. Therefore, within the INSTAND-NGS framework, we developed Measurable Residual Disease (MRD) prototypes for examining 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 that are associated with pancreatic neoplasms or with 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, MGI). We provide detailed information on bioinformatic processing of the sequencing data to perform the sequencing error corrections. Results: Using commercially available reference standards, we demonstrate stable mutation detection down to 0.1% variant allele frequency (VAF) for both, pancreatic and ovarian cancer panels, on both MGI and Illumina platforms. Conclusions: The technical usability of our MRD prototype has been clearly demonstrated for stable ultra-low VAF detection in commercial reference samples.