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Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients
BACKGROUND: Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor f...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165771/ https://www.ncbi.nlm.nih.gov/pubmed/34059130 http://dx.doi.org/10.1186/s13073-021-00898-8 |
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author | Tsui, Dana W. Y. Cheng, Michael L. Shady, Maha Yang, Julie L. Stephens, Dennis Won, Helen Srinivasan, Preethi Huberman, Kety Meng, Fanli Jing, Xiaohong Patel, Juber Hasan, Maysun Johnson, Ian Gedvilaite, Erika Houck-Loomis, Brian Socci, Nicholas D. Selcuklu, S. Duygu Seshan, Venkatraman E. Zhang, Hongxin Chakravarty, Debyani Zehir, Ahmet Benayed, Ryma Arcila, Maria Ladanyi, Marc Funt, Samuel A. Feldman, Darren R. Li, Bob T. Razavi, Pedram Rosenberg, Jonathan Bajorin, Dean Iyer, Gopa Abida, Wassim Scher, Howard I. Rathkopf, Dana Viale, Agnes Berger, Michael F. Solit, David B. |
author_facet | Tsui, Dana W. Y. Cheng, Michael L. Shady, Maha Yang, Julie L. Stephens, Dennis Won, Helen Srinivasan, Preethi Huberman, Kety Meng, Fanli Jing, Xiaohong Patel, Juber Hasan, Maysun Johnson, Ian Gedvilaite, Erika Houck-Loomis, Brian Socci, Nicholas D. Selcuklu, S. Duygu Seshan, Venkatraman E. Zhang, Hongxin Chakravarty, Debyani Zehir, Ahmet Benayed, Ryma Arcila, Maria Ladanyi, Marc Funt, Samuel A. Feldman, Darren R. Li, Bob T. Razavi, Pedram Rosenberg, Jonathan Bajorin, Dean Iyer, Gopa Abida, Wassim Scher, Howard I. Rathkopf, Dana Viale, Agnes Berger, Michael F. Solit, David B. |
author_sort | Tsui, Dana W. Y. |
collection | PubMed |
description | BACKGROUND: Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. METHODS: Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES). RESULTS: cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score<5), 29 had sufficient material to be re-analyzed using a less comprehensive but more sensitive assay, MSK-ACCESS, which revealed somatic mutations in 14/29 (48%). Conversely, 5 patients without alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches. CONCLUSIONS: cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-021-00898-8. |
format | Online Article Text |
id | pubmed-8165771 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81657712021-06-01 Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients Tsui, Dana W. Y. Cheng, Michael L. Shady, Maha Yang, Julie L. Stephens, Dennis Won, Helen Srinivasan, Preethi Huberman, Kety Meng, Fanli Jing, Xiaohong Patel, Juber Hasan, Maysun Johnson, Ian Gedvilaite, Erika Houck-Loomis, Brian Socci, Nicholas D. Selcuklu, S. Duygu Seshan, Venkatraman E. Zhang, Hongxin Chakravarty, Debyani Zehir, Ahmet Benayed, Ryma Arcila, Maria Ladanyi, Marc Funt, Samuel A. Feldman, Darren R. Li, Bob T. Razavi, Pedram Rosenberg, Jonathan Bajorin, Dean Iyer, Gopa Abida, Wassim Scher, Howard I. Rathkopf, Dana Viale, Agnes Berger, Michael F. Solit, David B. Genome Med Research BACKGROUND: Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. METHODS: Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES). RESULTS: cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score<5), 29 had sufficient material to be re-analyzed using a less comprehensive but more sensitive assay, MSK-ACCESS, which revealed somatic mutations in 14/29 (48%). Conversely, 5 patients without alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches. CONCLUSIONS: cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-021-00898-8. BioMed Central 2021-05-31 /pmc/articles/PMC8165771/ /pubmed/34059130 http://dx.doi.org/10.1186/s13073-021-00898-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Tsui, Dana W. Y. Cheng, Michael L. Shady, Maha Yang, Julie L. Stephens, Dennis Won, Helen Srinivasan, Preethi Huberman, Kety Meng, Fanli Jing, Xiaohong Patel, Juber Hasan, Maysun Johnson, Ian Gedvilaite, Erika Houck-Loomis, Brian Socci, Nicholas D. Selcuklu, S. Duygu Seshan, Venkatraman E. Zhang, Hongxin Chakravarty, Debyani Zehir, Ahmet Benayed, Ryma Arcila, Maria Ladanyi, Marc Funt, Samuel A. Feldman, Darren R. Li, Bob T. Razavi, Pedram Rosenberg, Jonathan Bajorin, Dean Iyer, Gopa Abida, Wassim Scher, Howard I. Rathkopf, Dana Viale, Agnes Berger, Michael F. Solit, David B. Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients |
title | Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients |
title_full | Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients |
title_fullStr | Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients |
title_full_unstemmed | Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients |
title_short | Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients |
title_sort | tumor fraction-guided cell-free dna profiling in metastatic solid tumor patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165771/ https://www.ncbi.nlm.nih.gov/pubmed/34059130 http://dx.doi.org/10.1186/s13073-021-00898-8 |
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