Abstract

Deep sequencing is required for the highly sensitive detection of rare variants in circulating tumor DNA (ctDNA). However, there remains a challenge for improved sensitivity and specificity. Maximum-depth sequencing is crucial to detect minority mutations that contribute to cancer progression. The associated costs become prohibitive as the numbers of targets and samples increase. We describe the targeted sequencing of KRAS in plasma samples using an efficient barcoding approach to recover discarded reads marked as duplicates. Combined with an error-removal strategy, we anticipate that our method could improve the accuracy of genotype calling, especially to detect rare mutations in the monitoring of ctDNA.

Details

Title
Asymmetrical barcode adapter-assisted recovery of duplicate reads and error correction strategy to detect rare mutations in circulating tumor DNA
Author
Ahn, Jinwoo 1 ; Hwang, Byungjin 1 ; Ha Young Kim 1 ; Jang, Hoon 1 ; Hwang-Phill, Kim 2 ; Sae-Won, Han 3 ; Tae-You, Kim 4 ; Lee, Ji Hyun 5 ; Bang, Duhee 1 

 Department of Chemistry, Yonsei University, Seoul, Korea 
 Cancer Research Institute, Seoul National University, Seoul, Korea; Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea 
 Cancer Research Institute, Seoul National University, Seoul, Korea; Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea 
 Cancer Research Institute, Seoul National University, Seoul, Korea; Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea; Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea 
 Department of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, Seoul, Korea 
Pages
1-9
Publication year
2017
Publication date
May 2017
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2316421117
Copyright
© 2017. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.