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April 5, 2026Cancer Research0 citations

Abstract 5307: Analytical performance of an ultrasensitive whole genome sequencing assay for molecular residual disease detection.

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AGAndrew GeorgiadisCGChristopher GrecoCMCynthia Maddox

Key Points

  • The aim is to evaluate the analytical performance of a non-bespoke whole genome sequencing assay for detecting molecular residual disease in non-metastatic cancers after treatment.
  • Utilized ultra-sensitive ctDNA assays for residual tumor detection.
  • Employed PCR-free whole genome sequencing on the Ultima Genomics platform.
  • Sequenced plasma and matched tumor DNA using paired variant calling with DeepVariant algorithm.
  • Analyzed samples for ctDNA status using machine learning models against noncancerous donor samples.
  • Assessed analytical specificity and sensitivity with clinical samples and cell lines.
  • Demonstrated specificity of >99.5% in assessing ctDNA detection.
  • Achieved a 95% limit of detection <5 ppm across tested levels.
  • Supported analytical concordance in plasma samples from various solid tumors.
  • Identified potential for broad utilization of tumor-informed MRD approaches in clinical settings.

Abstract

Abstract In non-metastatic cancers after curative intent intervention, a significant subset of patients retain tumor cells which can lead to disease recurrence. These residual tumor cells can be detected through ultra-sensitive circulating tumor DNA (ctDNA) assays and reported as molecular residual disease (MRD). The most common approaches generally utilize patient-specific, bespoke panels, which have extended turnaround times for initial testing and relatively high cell-free DNA (cfDNA) input requirements. Here we present a non-bespoke approach based on whole genome sequencing (WGS), which leverages native duplex error correction using the Ultima Genomics (UG) sequencing platform for rapid turnaround times for initial testing with low cfDNA input. Specifically, patient tumor, white blood cell, and plasma derived DNA were sequenced to approximately 80x, 30x, and 80x depth, respectively, through a PCR-free WGS workflow on the UG 100 platform. These data were demultiplexed and aligned on-instrument to the hg38 human reference genome. Paired variant calling for matched tumor and white blood cell samples was performed with the UG-adapted DeepVariant algorithm, and subsequently filtered to retain only tumor-specific single nucleotide variants (SNVs). Plasma variant analyses at those tumor-specific SNV positions were performed to leverage the paired plus-minus sequencing (ppmSeq) approach and allowed for ≥Q60 base quality, equating to a theoretical 1x10-6 error rate. ctDNA status and abundance was then assessed based on the level of the sample-specific machine learning model weighted and normalized signal compared to a reference population of noncancerous donor plasma samples (n=85). We assessed analytical specificity for 120 noncancerous donor plasma samples evaluated against clinical whole-genome somatic mutation profiles and demonstrated a specificity 99.5%. Analytical sensitivity for ctDNA detection was assessed using five commercially available cell lines across ten levels between 1 - 500 parts per million (ppm) and demonstrated a 95% limit of detection 5 ppm. Additionally, analytical concordance was evaluated in pre-surgical, treatment naïve plasma samples across a cohort of patients with bladder, breast, colon, and colorectal cancers. Taken together, these data support the significant potential for tumor-informed, non-bespoke MRD approaches for ctDNA detection across a broad range of solid tumor types and curative-intent clinical settings. Citation Format: Andrew Georgiadis, Christopher Greco, Cynthia Maddox, Paul McGregor, Cesar Nalvarte, Kaitlin Victor, Amanda Harvey, Shelby Bain, Robert Summersgill, Ana Perez-Lebron, Liam Cox, Stephen Higgings, David Riley, Samuel Angiuoli, Marcia Eisenberg, Brian Caveney, Eric Severson, Taylor J. Jenson, Shakti Ramkissoon, Mark Sausen. Analytical performance of an ultrasensitive whole genome sequencing assay for molecular residual disease detection abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5307.

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Georgiadis et al. (2026) studied this question.

synapsesocial.com/papers/69d1fdbfa79560c99a0a4064https://doi.org/10.1158/1538-7445.am2026-5307
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Abstract 1136: Analytical evaluation of a whole genome tumor-informed molecular residual disease detection assay with high sensitivity and specificity2026
  2. 2Abstract 2595: A novel dual-strand whole-genome sequencing (WGS) method for ultra-sensitive molecular residual disease detection (MRD)2026
  3. 3Abstract 1121: Detection of postoperative minimal residual disease in colorectal cancer using a novel ultrasensitive whole-genome sequencing-based ctDNA test2026
  4. 4Abstract 7828: Development of a comprehensive tumor-informed ctDNA workflow for ultrasensitive molecular residual disease detection using diverse tumor profiling inputs.2026
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