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Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients

The identification and quantification of actionable mutations are of critical importance for effective genotype-directed therapies, prognosis and drug response monitoring in patients with non-small-cell lung cancer (NSCLC). Although tumor tissue biopsy remains the gold standard for diagnosis of NSCL...

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Autores principales: Tran, Le Son, Pham, Hong-Anh Thi, Tran, Vu-Uyen, Tran, Thanh-Truong, Dang, Anh-Thu Huynh, Le, Dinh-Thong, Nguyen, Son-Lam, Nguyen, Ngoc-Vu, Nguyen, Trieu-Vu, Vo, Binh Thanh, Dao, Hong-Thuy Thi, Nguyen, Nguyen Huu, Tran, Tam Huu, Nguyen, Chu Van, Pham, Phuong Cam, Dang-Mai, Anh Tuan, Dinh-Nguyen, Thien Kim, Phan, Van Hieu, Do, Thanh-Thuy Thi, Truong Dinh, Kiet, Do, Han Ngoc, Phan, Minh-Duy, Giang, Hoa, Nguyen, Hoai-Nghia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913927/
https://www.ncbi.nlm.nih.gov/pubmed/31841547
http://dx.doi.org/10.1371/journal.pone.0226193
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author Tran, Le Son
Pham, Hong-Anh Thi
Tran, Vu-Uyen
Tran, Thanh-Truong
Dang, Anh-Thu Huynh
Le, Dinh-Thong
Nguyen, Son-Lam
Nguyen, Ngoc-Vu
Nguyen, Trieu-Vu
Vo, Binh Thanh
Dao, Hong-Thuy Thi
Nguyen, Nguyen Huu
Tran, Tam Huu
Nguyen, Chu Van
Pham, Phuong Cam
Dang-Mai, Anh Tuan
Dinh-Nguyen, Thien Kim
Phan, Van Hieu
Do, Thanh-Thuy Thi
Truong Dinh, Kiet
Do, Han Ngoc
Phan, Minh-Duy
Giang, Hoa
Nguyen, Hoai-Nghia
author_facet Tran, Le Son
Pham, Hong-Anh Thi
Tran, Vu-Uyen
Tran, Thanh-Truong
Dang, Anh-Thu Huynh
Le, Dinh-Thong
Nguyen, Son-Lam
Nguyen, Ngoc-Vu
Nguyen, Trieu-Vu
Vo, Binh Thanh
Dao, Hong-Thuy Thi
Nguyen, Nguyen Huu
Tran, Tam Huu
Nguyen, Chu Van
Pham, Phuong Cam
Dang-Mai, Anh Tuan
Dinh-Nguyen, Thien Kim
Phan, Van Hieu
Do, Thanh-Thuy Thi
Truong Dinh, Kiet
Do, Han Ngoc
Phan, Minh-Duy
Giang, Hoa
Nguyen, Hoai-Nghia
author_sort Tran, Le Son
collection PubMed
description The identification and quantification of actionable mutations are of critical importance for effective genotype-directed therapies, prognosis and drug response monitoring in patients with non-small-cell lung cancer (NSCLC). Although tumor tissue biopsy remains the gold standard for diagnosis of NSCLC, the analysis of circulating tumor DNA (ctDNA) in plasma, known as liquid biopsy, has recently emerged as an alternative and noninvasive approach for exploring tumor genetic constitution. In this study, we developed a protocol for liquid biopsy using ultra-deep massively parallel sequencing (MPS) with unique molecular identifier tagging and evaluated its performance for the identification and quantification of tumor-derived mutations from plasma of patients with advanced NSCLC. Paired plasma and tumor tissue samples were used to evaluate mutation profiles detected by ultra-deep MPS, which showed 87.5% concordance. Cross-platform comparison with droplet digital PCR demonstrated comparable detection performance (91.4% concordance, Cohen’s kappa coefficient of 0.85 with 95% CI = 0.72–0.97) and great reliability in quantification of mutation allele frequency (Intraclass correlation coefficient of 0.96 with 95% CI = 0.90–0.98). Our results highlight the potential application of liquid biopsy using ultra-deep MPS as a routine assay in clinical practice for both detection and quantification of actionable mutation landscape in NSCLC patients.
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spelling pubmed-69139272019-12-27 Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients Tran, Le Son Pham, Hong-Anh Thi Tran, Vu-Uyen Tran, Thanh-Truong Dang, Anh-Thu Huynh Le, Dinh-Thong Nguyen, Son-Lam Nguyen, Ngoc-Vu Nguyen, Trieu-Vu Vo, Binh Thanh Dao, Hong-Thuy Thi Nguyen, Nguyen Huu Tran, Tam Huu Nguyen, Chu Van Pham, Phuong Cam Dang-Mai, Anh Tuan Dinh-Nguyen, Thien Kim Phan, Van Hieu Do, Thanh-Thuy Thi Truong Dinh, Kiet Do, Han Ngoc Phan, Minh-Duy Giang, Hoa Nguyen, Hoai-Nghia PLoS One Research Article The identification and quantification of actionable mutations are of critical importance for effective genotype-directed therapies, prognosis and drug response monitoring in patients with non-small-cell lung cancer (NSCLC). Although tumor tissue biopsy remains the gold standard for diagnosis of NSCLC, the analysis of circulating tumor DNA (ctDNA) in plasma, known as liquid biopsy, has recently emerged as an alternative and noninvasive approach for exploring tumor genetic constitution. In this study, we developed a protocol for liquid biopsy using ultra-deep massively parallel sequencing (MPS) with unique molecular identifier tagging and evaluated its performance for the identification and quantification of tumor-derived mutations from plasma of patients with advanced NSCLC. Paired plasma and tumor tissue samples were used to evaluate mutation profiles detected by ultra-deep MPS, which showed 87.5% concordance. Cross-platform comparison with droplet digital PCR demonstrated comparable detection performance (91.4% concordance, Cohen’s kappa coefficient of 0.85 with 95% CI = 0.72–0.97) and great reliability in quantification of mutation allele frequency (Intraclass correlation coefficient of 0.96 with 95% CI = 0.90–0.98). Our results highlight the potential application of liquid biopsy using ultra-deep MPS as a routine assay in clinical practice for both detection and quantification of actionable mutation landscape in NSCLC patients. Public Library of Science 2019-12-16 /pmc/articles/PMC6913927/ /pubmed/31841547 http://dx.doi.org/10.1371/journal.pone.0226193 Text en © 2019 Tran et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Tran, Le Son
Pham, Hong-Anh Thi
Tran, Vu-Uyen
Tran, Thanh-Truong
Dang, Anh-Thu Huynh
Le, Dinh-Thong
Nguyen, Son-Lam
Nguyen, Ngoc-Vu
Nguyen, Trieu-Vu
Vo, Binh Thanh
Dao, Hong-Thuy Thi
Nguyen, Nguyen Huu
Tran, Tam Huu
Nguyen, Chu Van
Pham, Phuong Cam
Dang-Mai, Anh Tuan
Dinh-Nguyen, Thien Kim
Phan, Van Hieu
Do, Thanh-Thuy Thi
Truong Dinh, Kiet
Do, Han Ngoc
Phan, Minh-Duy
Giang, Hoa
Nguyen, Hoai-Nghia
Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients
title Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients
title_full Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients
title_fullStr Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients
title_full_unstemmed Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients
title_short Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients
title_sort ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital pcr for detection and quantification of circulating tumor dna from lung cancer patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913927/
https://www.ncbi.nlm.nih.gov/pubmed/31841547
http://dx.doi.org/10.1371/journal.pone.0226193
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