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The analytical validation is reported for a targeted methylation-based cell-free DNA multi-cancer early detection test designed to detect cancer and predict the cancer signal origin (tissue of origin). A machine-learning classifier was used to analyze the methylation patterns of >105 genomic targets covering >1 million methylation sites. Analytical sensitivity (limit of detection [95% probability]) was characterized with respect to tumor content by expected variant allele frequency and was determined to be 0.07%-0.17% across five tumor cases and 0.51% for the lymphoid neoplasm case. Test specificity was 99.3% (95% confidence interval, 98.6-99.7%). In the reproducibility and repeatability study, results were consistent in 31/34 (91.2%) pairs with cancer and 17/17 (100%) pairs without cancer; between runs, results were concordant for 129/133 (97.0%) cancer and 37/37 (100%) non-cancer sample pairs. Across 3- to 100-ng input levels of cell-free DNA, cancer was detected in 157/182 (86.3%) cancer samples but not in any of the 62 non-cancer samples. In input titration tests, cancer signal origin was correctly predicted in all tumor samples detected as cancer. No cross-contamination events were observed. No potential interferent (hemoglobin, bilirubin, triglycerides, genomic DNA) affected performance. The results of this analytical validation study support continued clinical development of a targeted methylation cell-free DNA multi-cancer early detection test., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: GA, WL, FEO, MR, PS, JRB, LE, GN, AM, PWM and NH are former employees of GRAIL, LLC and may have equity in the company. MHM is a consultant to Delfi Diagnostics and to Fellow Health and a former employee of GRAIL, LLC, with equity in all three companies. AMA is an advisor to Foresite Labs, San Francisco, California and Boston, Massachusetts, and a former employee of GRAIL, LLC, and holds equity in both companies. All other authors are employees of GRAIL, LLC, with equity in the company. GRAIL, LLC is a subsidiary of Illumina, Inc. currently held separate from Illumina Inc. under the terms of the Interim Measures Order of the European Commission dated 29 October 2021., (Copyright: © 2023 Alexander et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test., Competing Interests: Declaration of interests A.J., O.V., E.H., J.F.B., S.G., Q.L., N.Z., E.T.F., K.N.K., H.A., C.B., D.C., K.D., S.F., C.H., R.J., B.J., S.T., C.M., V.D., J.N., O.S., E.S., A.S., S.S., K.K.S., V.N., A.P.F., T.C.C., S.B., N.H., M.D., Z.D., and M.P.H. are employees of GRAIL, LLC, with equity in Illumina, Inc. C.M. also holds stock in Novartis, Clovis, Cara, Gilead, and Bluebird. M.C.L. is an uncompensated consultant for GRAIL, LLC. The Mayo Clinic was compensated for M.C.L.’s and D.D.T.’s advisory board activities for GRAIL, LLC. E.A.K. is a consultant for GRAIL, LLC. D.A.R. is a consultant for Ipsen. M.A.S. is a consultant for Celgene, Millennium, and Syros Pharmaceuticals. A.M.A. was previously employed by GRAIL, LLC; has equity in Illumina, Inc.; is currently employed by Illumina, Inc.; and is an advisor to and an equity holder in Foresite Labs and Myst Therapeutics. M.V.S. is an employee of and holds stock in McKesson Corporation, and is a clinical adviser for GRAIL, LLC. D.A.B. is a co-owner of Berry Consultants, LLC. A.H.B. is a consultant for Pfizer, Merck, Bayer, and Astellas Pharmaceuticals. C.S. holds stock in Illumina, Inc., Epic Biosciences, and Apogen Biotech; receives grants from Pfizer and AstraZeneca; receives honoraria or consultant fees from Roche Ventana, Celgene, Pfizer, Novartis, Genentech, and BMS; and is a co-founder of Achilles Therapeutics. S.G., O.V., A.P.F., A.J., K.D., V.N., J.F.B., C.M., E.H., Q.L., N.Z., P.F., and O.S. are inventors on pending patent applications related to this work, for which GRAIL, LLC, has ownership rights. GRAIL, LLC, a subsidiary of Illumina, Inc., is currently held separate from Illumina, Inc., under the terms of the Interim Measures Order of the European Commission dated October 29, 2021. C.S. recieved grant support from AstraZeneca, Boehringer-Ingelheim, Bristol Myers Squibb, Pfizer, Roche-Ventana, Invitae (previously Archer Dx Inc), and Ono Pharmaceutical; is an AstraZeneca Advisory Board member and Chief Investigator for the AZ MeRmaiD 1 and 2 clinical trials and is also Co-Chief Investigator of the NHS Galleri trial funded by GRAIL and a paid member of GRAIL’s Scientific Advisory Board (SAB); received consultant fees from Achilles Therapeutics (also SAB member), Bicycle Therapeutics (also a SAB member), Genentech, Medicxi, Roche Innovation Centre – Shanghai, Metabomed, and the Sarah Cannon Research Institute; received honoraria from Amgen, AstraZeneca, Pfizer, Novartis, GlaxoSmithKline, MSD, Bristol Myers Squibb, Illumina, and Roche-Ventana; had stock options in Apogen Biotechnologies and GRAIL until June 2021, and currently has stock options in Epic Bioscience, Bicycle Therapeutics, and Achilles Therapeutics; and is a co-founder of Achilles Therapeutics; holds patents relating to assay technology to detect tumour recurrence (PCT/GB2017/053289), targeting neoantigens (PCT/EP2016/059401), identifying patent response to immune checkpoint blockade (PCT/EP2016/071471), determining HLA LOH (PCT/GB2018/052004), predicting survival rates of patients with cancer (PCT/GB2020/050221), and identifying patients who respond to cancer treatment (PCT/GB2018/051912); holds US patent relating to detecting tumour mutations (PCT/US2017/28013), methods for lung cancer detection (US20190106751A1); and holds both a European and US patent related to identifying insertion/deletion mutation targets (PCT/GB2018/051892). C.S. is a Royal Society Napier Research Professor (RSRP\R\210001) and has received funding from the Francis Crick Institute that receives its core funding from Cancer Research UK (CC2041), the UK Medical Research Council (CC2041), and the Wellcome Trust (CC2041); Cancer Research UK (TRACERx [C11496/A17786], PEACE [C416/A21999], and CRUK Cancer Immunotherapy Catalyst Network); Cancer Research UK Lung Cancer Centre of Excellence (C11496/A30025); the Rosetrees Trust, Butterfield and Stoneygate Trusts; NovoNordisk Foundation (ID16584); Royal Society Professorship Enhancement Award (RP/EA/180007); National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre; the Cancer Research UK-University College London Centre; Experimental Cancer Medicine Centre; the Breast Cancer Research Foundation (US) (BCRF-22-157); Cancer Research UK Early Detection and Diagnosis Primer Award (Grant EDDPMA-Nov21/100034); The Mark Foundation for Cancer Research Aspire Award (Grant 21-029-ASP); Stand Up To Cancer-LUNGevity American Lung Association Lung Cancer Interception Dream Team Translational Research Grant (Grant Number: SU2C-AACR-DT23-17); and an ERC Advanced Grant (PROTEUS) from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 835297)., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

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. 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. 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%). 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. NCT02889978. • In a validation study, an MCED test identified a diversity of cancer signals with high specificity. • The MCED test predicted the origin of the cancer signal with high accuracy across multiple cancer types. • Results support the use of this MCED test on a population scale as a complement to existing single-cancer screening tests. [ABSTRACT FROM AUTHOR]