Abstract B028: Analytical validation of tumor-informed whole genome sequencing analyses for detection of molecular residual disease in solid tumors
Authors: Victor Kaitlin , Georgiadis Andrew , Verner Ellen , Simmons Antoine , Riley David , White James R , Greco Christopher , Cox Liam , Fox Jesse , Jackson Jennifer B , Severson Eric A , Caveney Brian J , Eisenberg Marcia , Jensen Taylor J , Ramkissoon Shakti , Angiuoli Samuel V , Greer Amy , Valkenburg Kenneth , Sausen Mark 
Published: November 2024

Abstract
Introduction: Across all patients diagnosed with solid tumors, approximately two-thirds initially present with locoregional disease and are potentially eligible for curative-intent intervention. However, there is a significant subset of patients for which residual tumor cells remain afterwards, potentially leading to disease recurrence. It has been reported that these residual tumor cells, representative of molecular residual disease (MRD), can be detected through analyses of circulating tumor DNA (ctDNA), often earlier than can be achieved through radiographic imaging or clinical presentation. Methods: Labcorp Plasma Detect was utilized to analyze patient-matched tumor, germline (white blood cells), and cell-free or contrived DNA samples through whole genome sequencing at approximately 80x, 40x, and 30x depth, respectively. Raw sequencing data were demultiplexed and trimmed for read quality, then aligned to the hg19 human reference genome. Tumor-specific single nucleotide variants were identified from the tumor and germline datasets and used to determine the presence of cancer within cell-free or contrived DNA samples through a random forest machine learning model. ctDNA status was determined based on the level of signal compared to a reference cohort of noncancerous donor plasma samples (n=80). Results: Analytical specificity was determined through analysis of five noncancerous donor plasma samples with five replicates each, evaluated against 60 somatic mutation profiles obtained from patients with stage III colon cancer, demonstrating a specificity of 99.4% (835/840). Analytical sensitivity was assessed using three contrived cell line models from breast and melanoma tumors, analyzed across three tumor content levels with five replicates at each level and resulted in a limit of detection of 0.005% tumor content using a 100% hit-rate model. Precision, repeatability, and reproducibility were demonstrated within and across runs, operators, and instruments, resulting in a 100% detection rate at 0.05% tumor content with a coefficient of variation of 8.5%. Finally, analytical accuracy compared to an independent tumor-informed ctDNA MRD approach was determined through analysis of 39 clinical cases obtained from patients with bladder, breast, colorectal, and lung cancer, yielding a positive percent agreement of 91% (10/11) and negative percent agreement of 100% (24/24). The prognostic value of ctDNA MRD was demonstrated in stage III colon cancer and clinical validation results for HPV-negative head and neck squamous cell carcinoma will be presented separately. Conclusions: There is 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. These data demonstrate the analytical performance of Labcorp Plasma Detect in a CAP/CLIA laboratory for pan-solid tumor research use together with investigational use in early stage colon cancer to support the interventional MEDOCC-CrEATE clinical trial.
Citation Format: Kaitlin Victor, Andrew Georgiadis, Ellen Verner, Antoine Simmons, David Riley, James R White, Christopher Greco, Liam Cox, Jesse Fox, Jennifer B Jackson, Eric A Severson, Brian J Caveney, Marcia Eisenberg, Taylor J Jensen, Shakti Ramkissoon, Samuel V Angiuoli, Amy Greer, Kenneth Valkenburg, Mark Sausen. Analytical validation of tumor-informed whole genome sequencing analyses for detection of molecular residual disease in solid tumors [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B028.