Optimizing Nanopore sequencing-based detection of structural variants enables individualized circulating tumor DNA-based disease monitoring in cancer patients

Jose Espejo Valle-Inclan,Martijn P Lolkema,Lisanne F Van Dessel,Wigard P Kloosterman,Christina Stangl,John W M Martens,Chris J De Witte,Sam De Blank,Maurice P H M Jansen,Roel Janssen,Anouk C De Jong,Jean C A Helmijr,Markus J Van Roosmalen,Ivo Renkens

doi:10.1186/s13073-021-00899-7

Abstract

Here, we describe a novel approach for rapid discovery of a set of tumor-specific genomic structural variants (SVs), based on a combination of low coverage cancer genome sequencing using Oxford Nanopore with an SV calling and filtering pipeline. We applied the method to tumor samples of high-grade ovarian and prostate cancer patients and validated on average ten somatic SVs per patient with breakpoint-spanning PCR mini-amplicons. These SVs could be quantified in ctDNA samples of patients with metastatic prostate cancer using a digital PCR assay. The results suggest that SV dynamics correlate with and may improve existing treatment-response biomarkers such as PSA.https://github.com/UMCUGenetics/SHARC.

Highlights

The detection of cancer recurrence as well as accurate and fast monitoring of response to treatment currently lacks sensitivity for detection of changes over time [1, 2]
A single nanopore run on the MinION or GridION platforms typically generates between 5–15 Gbs of data [33], corresponding to 1.5–5x coverage of the human genome
A classification and filtering pipeline is applied to enrich for somatic Structural variant (SV) breakpoints irrespective of corresponding germline data (Fig. 1b)

Summary

Introduction

The detection of cancer recurrence as well as accurate and fast monitoring of response to treatment currently lacks sensitivity for detection of changes over time [1, 2]. Liquid biopsies, which can be used to detect circulating tumor DNA (ctDNA) from body fluids, such as blood, in a minimally invasive manner, are a promising approach to improve monitoring of tumor burden over time [3, 4]. Genomic structural variations (SVs) represent tumor- and ctDNA-specific biomarkers to detect and quantify ctDNA with high sensitivity in liquid biopsies [7,8,9,10]. Besides some recurrent driver SV events that functionally impact tumorigenesis, the vast majority of these somatic SVs are patient- and tumor-specific passenger events [13], which may be valuable biomarkers for tumor load tracing. SVs form a unique breakpoint junction between two joined DNA strands

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Discussion

Conclusion