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cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution

PURPOSE: Cell-free DNA (cfDNA) offers a noninvasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including minimal residual disease (MRD), recurrence, evolution, and seco...

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Autores principales: Li, Shuo, Zeng, Weihua, Ni, Xiaohui, Zhou, Yonggang, Stackpole, Mary L., Noor, Zorawar S., Yuan, Zuyang, Neal, Adam, Memarzadeh, Sanaz, Garon, Edward B., Dubinett, Steven M., Li, Wenyuan, Zhou, Xianghong Jasmine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126584/
https://www.ncbi.nlm.nih.gov/pubmed/35149536
http://dx.doi.org/10.1158/1078-0432.CCR-21-1242
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author Li, Shuo
Zeng, Weihua
Ni, Xiaohui
Zhou, Yonggang
Stackpole, Mary L.
Noor, Zorawar S.
Yuan, Zuyang
Neal, Adam
Memarzadeh, Sanaz
Garon, Edward B.
Dubinett, Steven M.
Li, Wenyuan
Zhou, Xianghong Jasmine
author_facet Li, Shuo
Zeng, Weihua
Ni, Xiaohui
Zhou, Yonggang
Stackpole, Mary L.
Noor, Zorawar S.
Yuan, Zuyang
Neal, Adam
Memarzadeh, Sanaz
Garon, Edward B.
Dubinett, Steven M.
Li, Wenyuan
Zhou, Xianghong Jasmine
author_sort Li, Shuo
collection PubMed
description PURPOSE: Cell-free DNA (cfDNA) offers a noninvasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including minimal residual disease (MRD), recurrence, evolution, and second primary cancers. EXPERIMENTAL DESIGN: Three simulation datasets were generated from 26 patients with cancer to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n = 76) from patients with cancer (n = 35) with six different cancer types were used for performance validation during various treatments. RESULTS: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fractions ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fractions ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods. CONCLUSIONS: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA.
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spelling pubmed-91265842022-05-23 cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution Li, Shuo Zeng, Weihua Ni, Xiaohui Zhou, Yonggang Stackpole, Mary L. Noor, Zorawar S. Yuan, Zuyang Neal, Adam Memarzadeh, Sanaz Garon, Edward B. Dubinett, Steven M. Li, Wenyuan Zhou, Xianghong Jasmine Clin Cancer Res Precision Medicine and Imaging PURPOSE: Cell-free DNA (cfDNA) offers a noninvasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including minimal residual disease (MRD), recurrence, evolution, and second primary cancers. EXPERIMENTAL DESIGN: Three simulation datasets were generated from 26 patients with cancer to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n = 76) from patients with cancer (n = 35) with six different cancer types were used for performance validation during various treatments. RESULTS: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fractions ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fractions ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods. CONCLUSIONS: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA. American Association for Cancer Research 2022-05-02 2022-02-10 /pmc/articles/PMC9126584/ /pubmed/35149536 http://dx.doi.org/10.1158/1078-0432.CCR-21-1242 Text en ©2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.
spellingShingle Precision Medicine and Imaging
Li, Shuo
Zeng, Weihua
Ni, Xiaohui
Zhou, Yonggang
Stackpole, Mary L.
Noor, Zorawar S.
Yuan, Zuyang
Neal, Adam
Memarzadeh, Sanaz
Garon, Edward B.
Dubinett, Steven M.
Li, Wenyuan
Zhou, Xianghong Jasmine
cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution
title cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution
title_full cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution
title_fullStr cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution
title_full_unstemmed cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution
title_short cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution
title_sort cftrack: a method of exome-wide mutation analysis of cell-free dna to simultaneously monitor the full spectrum of cancer treatment outcomes including mrd, recurrence, and evolution
topic Precision Medicine and Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126584/
https://www.ncbi.nlm.nih.gov/pubmed/35149536
http://dx.doi.org/10.1158/1078-0432.CCR-21-1242
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