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Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay
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 ta...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104288/ https://www.ncbi.nlm.nih.gov/pubmed/37058491 http://dx.doi.org/10.1371/journal.pone.0283001 |
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author | Alexander, Gregory E. Lin, Wendy Ortega, Fabian E. Ramaiah, Madhuvanthi Jung, Byoungsok Ji, Lijuan Revenkova, Ekaterina Shah, Payal Croisetiere, Christian Berman, Jennifer R. Eubank, Lane Naik, Gunjan Brooks, Jacqueline Mich, Andrea Shojaee, Seyedmehdi Ronaghi, Neda Chawla, Hemanshi Hou, Xinyi Liu, Qinwen Yakym, Christopher-James A. V. Moradi, Patriss Wais Halks-Miller, Meredith Aravanis, Alexander M. Parpart-Li, Sonya Hunkapiller, Nathan |
author_facet | Alexander, Gregory E. Lin, Wendy Ortega, Fabian E. Ramaiah, Madhuvanthi Jung, Byoungsok Ji, Lijuan Revenkova, Ekaterina Shah, Payal Croisetiere, Christian Berman, Jennifer R. Eubank, Lane Naik, Gunjan Brooks, Jacqueline Mich, Andrea Shojaee, Seyedmehdi Ronaghi, Neda Chawla, Hemanshi Hou, Xinyi Liu, Qinwen Yakym, Christopher-James A. V. Moradi, Patriss Wais Halks-Miller, Meredith Aravanis, Alexander M. Parpart-Li, Sonya Hunkapiller, Nathan |
author_sort | Alexander, Gregory E. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10104288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-101042882023-04-15 Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay Alexander, Gregory E. Lin, Wendy Ortega, Fabian E. Ramaiah, Madhuvanthi Jung, Byoungsok Ji, Lijuan Revenkova, Ekaterina Shah, Payal Croisetiere, Christian Berman, Jennifer R. Eubank, Lane Naik, Gunjan Brooks, Jacqueline Mich, Andrea Shojaee, Seyedmehdi Ronaghi, Neda Chawla, Hemanshi Hou, Xinyi Liu, Qinwen Yakym, Christopher-James A. V. Moradi, Patriss Wais Halks-Miller, Meredith Aravanis, Alexander M. Parpart-Li, Sonya Hunkapiller, Nathan PLoS One Research Article 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. Public Library of Science 2023-04-14 /pmc/articles/PMC10104288/ /pubmed/37058491 http://dx.doi.org/10.1371/journal.pone.0283001 Text en © 2023 Alexander et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Alexander, Gregory E. Lin, Wendy Ortega, Fabian E. Ramaiah, Madhuvanthi Jung, Byoungsok Ji, Lijuan Revenkova, Ekaterina Shah, Payal Croisetiere, Christian Berman, Jennifer R. Eubank, Lane Naik, Gunjan Brooks, Jacqueline Mich, Andrea Shojaee, Seyedmehdi Ronaghi, Neda Chawla, Hemanshi Hou, Xinyi Liu, Qinwen Yakym, Christopher-James A. V. Moradi, Patriss Wais Halks-Miller, Meredith Aravanis, Alexander M. Parpart-Li, Sonya Hunkapiller, Nathan Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay |
title | Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay |
title_full | Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay |
title_fullStr | Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay |
title_full_unstemmed | Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay |
title_short | Analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free DNA–based targeted methylation assay |
title_sort | analytical validation of a multi-cancer early detection test with cancer signal origin using a cell-free dna–based targeted methylation assay |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104288/ https://www.ncbi.nlm.nih.gov/pubmed/37058491 http://dx.doi.org/10.1371/journal.pone.0283001 |
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