Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set
E A Klein, D Richards, A Cohn, M Tummala, R Lapham, D Cosgrove, G Chung, J Clement, J Gao, N Hunkapiller, A Jamshidi, K N Kurtzman, M V Seiden, C Swanton, M C Liu, E A Klein, D Richards, A Cohn, M Tummala, R Lapham, D Cosgrove, G Chung, J Clement, J Gao, N Hunkapiller, A Jamshidi, K N Kurtzman, M V Seiden, C Swanton, M C Liu
Abstract
Background: A multi-cancer early detection (MCED) test used to complement existing screening could increase the number of cancers detected through population screening, potentially improving clinical outcomes. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was a prospective, case-controlled, observational study and demonstrated that a blood-based MCED test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin (CSO) with high accuracy. The objective of this third and final CCGA substudy was to validate an MCED test version further refined for use as a screening tool.
Patients and methods: This pre-specified substudy included 4077 participants in an independent validation set (cancer: n = 2823; non-cancer: n = 1254, non-cancer status confirmed at year-one follow-up). Specificity, sensitivity, and CSO prediction accuracy were measured.
Results: Specificity for cancer signal detection was 99.5% [95% confidence interval (CI): 99.0% to 99.8%]. Overall sensitivity for cancer signal detection was 51.5% (49.6% to 53.3%); sensitivity increased with stage [stage I: 16.8% (14.5% to 19.5%), stage II: 40.4% (36.8% to 44.1%), stage III: 77.0% (73.4% to 80.3%), stage IV: 90.1% (87.5% to 92.2%)]. Stage I-III sensitivity was 67.6% (64.4% to 70.6%) in 12 pre-specified cancers that account for approximately two-thirds of annual USA cancer deaths and was 40.7% (38.7% to 42.9%) in all cancers. Cancer signals were detected across >50 cancer types. Overall accuracy of CSO prediction in true positives was 88.7% (87.0% to 90.2%).
Conclusion: In this pre-specified, large-scale, clinical validation substudy, the MCED test demonstrated high specificity and accuracy of CSO prediction and detected cancer signals across a wide diversity of cancers. These results support the feasibility of this blood-based MCED test as a complement to existing single-cancer screening tests.
Clinical trial number: NCT02889978.
Keywords: cancer; cell-free nucleic acids; liquid biopsy; machine learning; methylation; multi-cancer early detection.
Conflict of interest statement
Disclosure EAK is a consultant for GRAIL, Inc.; DC is a consultant for Pfizer and Merck; AJ and KNK are full-time employees of GRAIL, Inc. and have stock in Illumina and GRAIL, Inc.; JG and NH are full-time employees of GRAIL Inc. and own stock in GRAIL, Inc. MVS has stock in McKesson Corporation, is a clinical adviser for GRAIL, Inc. and a director of Next Oncology and Nemucore Medical Innovations; CS has stock in GRAIL, Inc., Epic Biosciences and Apogen Biotech, grants from Pfizer and AstraZeneca, received honoraria or consultant fees from Roche Ventana, Celgene, Pfizer, Novartis, Genentech, and BMS, and is a co-founder of Achilles Therapeutics; MCL participated as an advisory board member for GRAIL, Inc. All other authors have declared no conflicts of interest.
Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.
Source: PubMed