In:
PLOS ONE, Public Library of Science (PLoS), Vol. 18, No. 4 ( 2023-4-14), p. e0283001-
Abstract:
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 〉 10 5 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.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0283001
DOI:
10.1371/journal.pone.0283001.g001
DOI:
10.1371/journal.pone.0283001.g002
DOI:
10.1371/journal.pone.0283001.g003
DOI:
10.1371/journal.pone.0283001.g004
DOI:
10.1371/journal.pone.0283001.g005
DOI:
10.1371/journal.pone.0283001.g006
DOI:
10.1371/journal.pone.0283001.g007
DOI:
10.1371/journal.pone.0283001.t001
DOI:
10.1371/journal.pone.0283001.t002
DOI:
10.1371/journal.pone.0283001.t003
DOI:
10.1371/journal.pone.0283001.s001
DOI:
10.1371/journal.pone.0283001.s002
DOI:
10.1371/journal.pone.0283001.s003
DOI:
10.1371/journal.pone.0283001.s004
DOI:
10.1371/journal.pone.0283001.s005
DOI:
10.1371/journal.pone.0283001.s006
DOI:
10.1371/journal.pone.0283001.s007
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2267670-3
Bookmarklink