A Blood-based Assay for Detection of Patients with Advanced Adenomas
Journal Title
Cancer Research Communications
Publication Type
Online publication before print
Abstract
Screening for colorectal cancer (CRC) with blood-based testing should detect advanced adenomas (AAs), facilitating more effective cancer prevention. We evaluated four different methods to detect AAs in plasma: (a) a machine-learning algorithm, SignaL (Signatures of fragment Length), based on cell-free DNA (cfDNA) fragmentation; (b) a "Protein-17" assay measuring 17 cancer-associated proteins; (c) a Global Aneuploidy Score (GAS); and (d) cfDNA mutation analysis querying 15 genes commonly mutated in CRC. Existing data from study populations with and without cancer were utilized to determine 99.5% specificity thresholds. We studied 40 AA cases and 32 colonoscopy-negative controls. SignaL detected 9/40 AAs (22.5%, 95%CI: 12.3-37.5%) at 100% specificity (95%CI: 89.3-100%). Protein-17 detected 5/40 AAs (12.5%, 95%CI: 5.5-26.1%) including three cases not identified by SignaL, at 100% specificity (95%CI: 89.3 to 100%). GAS detected 11/40 AAs (27.5%, 95%CI: 16.1-42.8%), but resulted in 2/32 positive controls (93.8% specificity, 95%CI: 79.9-98.3%). Combining SignaL, the Protein-17 assay, and GAS at the 99.5% specificity thresholds resulted in detection of 16/40 AAs (40%, 95% CI:26.3-55.4%) at 93.8% specificity (95% CI: 79.9% to 98.3%). Of 32/40 evaluable AA plasma samples, only one was cfDNA mutation positive at 0.01 level of significance. A blood-based assay based on the analysis of repeated sequence elements plus proteins appears to be able to detect a considerable fraction of patients with AA at relatively high specificity. Large, prospective studies are required to determine whether this approach can add to the options currently available for screening patients for pre-malignant lesions of the colon.
Department(s)
Medical Oncology
Open Access at Publisher's Site
https://doi.org/10.1158/2767-9764.Crc-24-0398
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