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Published in: Breast Cancer Research and Treatment 1/2017

01-02-2017 | Preclinical study

Use of droplet digital PCR for quantitative and automatic analysis of the HER2 status in breast cancer patients

Authors: Kazutaka Otsuji, Takeshi Sasaki, Atsushi Tanaka, Akiko Kunita, Masako Ikemura, Keisuke Matsusaka, Keiichiro Tada, Masashi Fukayama, Yasuyuki Seto

Published in: Breast Cancer Research and Treatment | Issue 1/2017

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Abstract

Purpose

Digital polymerase chain reaction (dPCR) has been used to yield an absolute measure of nucleic acid concentrations. Recently, a new method referred to as droplet digital PCR (ddPCR) has gained attention as a more precise and less subjective assay to quantify DNA amplification. We demonstrated the usefulness of ddPCR to determine HER2 gene amplification of breast cancer.

Methods

In this study, we used ddPCR to measure the HER2 gene copy number in clinical formalin-fixed paraffin-embedded samples of 41 primary breast cancer patients. To improve the accuracy of ddPCR analysis, we also estimated the tumor content ratio (TCR) for each sample.

Results

Our determination method for HER2 gene amplification using the ddPCR ratio (ERBB2:ch17cent copy number ratio) combined with the TCR showed high consistency with the conventionally defined HER2 gene status according to ASCO-CAP (American Society of Clinical Oncology/College of American Pathologists) guidelines (P<0.0001, Fisher’s exact test). The equivocal area was established by adopting 99% confidence intervals obtained by cell line assays, which made it possible to identify all conventionally HER2-positive cases with our method. In addition, we succeeded in automating a major part of the process from DNA extraction to determination of HER2 gene status.

Conclusions

The introduction of ddPCR to determine the HER2 gene status in breast cancer is feasible for use in clinical practice and might complement or even replace conventional methods of examination in the future.
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Metadata
Title
Use of droplet digital PCR for quantitative and automatic analysis of the HER2 status in breast cancer patients
Authors
Kazutaka Otsuji
Takeshi Sasaki
Atsushi Tanaka
Akiko Kunita
Masako Ikemura
Keisuke Matsusaka
Keiichiro Tada
Masashi Fukayama
Yasuyuki Seto
Publication date
01-02-2017
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 1/2017
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-016-4092-5

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