Abstract PR08: Validation and clinical implementation of MSK-ACCESS, an ultra-deep sequencing assay for noninvasive somatic mutation profiling

Abstract

Introduction: Circulating cell-free DNA (cfDNA) is a source of tumor-derived DNA to interrogate somatic alterations when tissue is not available or of insufficient quantity for analysis. At MSKCC, we have developed and validated MSK-ACCESS (Analysis of Circulating cfDNA to Evaluate Somatic Status), a targeted next-generation sequencing assay that can detect ultra-low frequency somatic variants in select exons and introns of 129 genes. MSK-ACCESS can identify mutations, copy number alterations, gene fusions, and MSI status in plasma and was recently approved by the NYS-DOH for clinical testing. Here, we present the results of the validation study and our clinical experience with MSK-ACCESS since June 2019. Methods: Target regions from 129 genes were selected to maximize coverage of actionable, oncogenic, and hotspot mutations based on the first 25,000 tumors sequenced using MSK-IMPACT, our institutional clinical sequencing assay. Plasma cfDNA and buffy-coat DNA were extracted from whole blood collected in cell-stabilizing tubes (STRECK BCT cell-free DNA tube). Unique molecular indexes were introduced during DNA library construction, allowing for error suppression from consensus reads collapsed by Marianas, an in-house-developed algorithm. These consensus reads enable variant calling at low allelic frequency (AF) based on a 10−6 background error rate. Results: Analytical validation of MSK-ACCESS demonstrated 93% accuracy (n=100 variants), 99% precision (n=153 variants), and 100% sensitivity based on an assay limit of detection of 0.5% AF (n=19 variants). Variants were detected down to 0.1% AF. To date, 240 clinical cfDNA and matched normal DNA pairs have been sequenced, analyzed for somatic alterations, and clinically reported to guide patient management. Most clinical cases were from lung (55%) or prostate (13%) cancers and submitted for diagnostic purposes (71%). Median raw coverage was 18,367X, and median consensus coverage was 1411X. Mutations were detected in 180 (75%) samples with a median variant AF of 1.8% (0.02% - 95%). Comparison of concurrent commercial plasma testing results to MSK-ACCESS revealed multiple variants that were of clonal hematopoiesis or germline origin incorrectly reported as somatic variants. In the lung cohort, 48 patients had tissue testing with MSK-IMPACT; among 32 patients with a driver alteration detected by MSK-ACCESS, 91% had the identical driver alteration reported by MSK-IMPACT. Additionally, MSK-ACCESS identified a MET exon 14 alteration in one lung cancer patient that led to protocol enrollment and partial response. Conclusions: Liquid biopsy testing using MSK-ACCESS reliably detected clinically actionable mutations, reducing the need for multiple biopsies. These results also illustrate the importance of analyzing a matched normal sample when interpreting cfDNA results and highlight the potential of using cfDNA analysis to guide treatment selection, assess for treatment response, and identify mechanisms of treatment resistance. This abstract is also being presented as Poster A20. Citation Format: A. Rose Brannon, Gowtham Jayakumaran, Monica Diosdado, Yu Hu, Anna Razumova, Fanli Meng, Emily Lebow, Juber Patel, Ian Johnson, Preethi Srinivasan, Maysun Hasan, Jenna-marie Dix, Aijazuddin Syed, Brian Houck-Loomis, Bob T. Li, Charles Rudin, David Solit, Marc Ladanyi, Maria Arcila, Dana Tsui, Ahmet Zehir, Michael Berger, Ryma Benayed. Validation and clinical implementation of MSK-ACCESS, an ultra-deep sequencing assay for noninvasive somatic mutation profiling [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR08.

Deep Learning Model for Tumor Type Prediction using Targeted Clinical Genomic Sequencing Data

“…The success of GDD-ENS in patients with CUP could potentiate the model for classification of early cancer samples, an open area of research for many early detection models. As such, work to expand GDD-ENS to cell-free DNA sequencing data is currently ongoing 41 .…”