Abstract

A highly sensitive and highly multiplexed quantification technique for nucleic acids is necessary to predict and evaluate cancer treatment by liquid biopsy. Digital PCR (dPCR) is a highly sensitive quantification technique, but conventional dPCR discriminates multiple targets by the color of the fluorescent dye of the probe, which limits multiplexing beyond the number of colors of fluorescent dyes. We previously developed a highly multiplexed dPCR technique combined with melting curve analysis. Herein, we improved the detection efficiency and accuracy of multiplexed dPCR with melting curve analysis to detect KRAS mutations in circulating tumor DNA (ctDNA) prepared from clinical samples. The mutation detection efficiency was increased from 25.9% of the input DNA to 45.2% by shortening the amplicon size. The limit of detection of mutation was improved from 0.41 to 0.06% by changing the mutation type determination algorithm for G12A, resulting in a limit of detection of less than 0.2% for all the target mutations. Then, ctDNA in plasma from pancreatic cancer patients was measured and genotyped. The measured mutation frequencies correlated well with those measured by conventional dPCR, which can measure only the total frequency of KRAS mutants. KRAS mutations were detected in 82.3% of patients with liver or lung metastasis, which was consistent with other reports. Accordingly, this study demonstrated the clinical utility of multiplex dPCR with melting curve analysis to detect and genotype ctDNA from plasma with sufficient sensitivity.

Details

Title
Efficient and accurate KRAS genotyping using digital PCR combined with melting curve analysis for ctDNA from pancreatic cancer patients
Author
Tanaka, Junko 1 ; Nakagawa, Tatsuo 1 ; Harada, Kunio 1 ; Morizane, Chigusa 2 ; Tanaka, Hidenori 3 ; Shiba, Satoshi 4 ; Ohba, Akihiro 2 ; Hijioka, Susumu 2 ; Takai, Erina 5 ; Yachida, Shinichi 6 ; Kamura, Yoshio 1 ; Ishida, Takeshi 1 ; Yokoi, Takahide 1 ; Uematsu, Chihiro 1 

 Hitachi, Ltd., Center for Digital Services - Healthcare, Research & Development Group, Kokubunji, Japan (GRID:grid.417547.4) (ISNI:0000 0004 1763 9564) 
 National Cancer Center Hospital, Department of Hepatobiliary and Pancreatic Oncology, Chuo-ku, Japan (GRID:grid.272242.3) (ISNI:0000 0001 2168 5385) 
 Osaka University Graduate School of Medicine, Department of Cancer Genome Informatics, Suita, Japan (GRID:grid.136593.b) (ISNI:0000 0004 0373 3971); Osaka University Graduate School of Medicine, Department of Otorhinolaryngology-Head and Neck Surgery, Suita, Japan (GRID:grid.136593.b) (ISNI:0000 0004 0373 3971) 
 National Cancer Center Research Institute, Division of Genomic Medicine, Chuo-ku, Japan (GRID:grid.272242.3) (ISNI:0000 0001 2168 5385) 
 Osaka University Graduate School of Medicine, Department of Cancer Genome Informatics, Suita, Japan (GRID:grid.136593.b) (ISNI:0000 0004 0373 3971) 
 Osaka University Graduate School of Medicine, Department of Cancer Genome Informatics, Suita, Japan (GRID:grid.136593.b) (ISNI:0000 0004 0373 3971); National Cancer Center Research Institute, Division of Genomic Medicine, Chuo-ku, Japan (GRID:grid.272242.3) (ISNI:0000 0001 2168 5385) 
Pages
3039
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2778491864
Copyright
© The Author(s) 2023. 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.