Kazuto Nishio

Kindai University Faculty of Medicine
Country flagJapan

Research Interests

Explore related searches

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Articles (15)

Precise biomarkers for predicting the therapeutic efficacy of molecularly targeted drugs are limited at the protein level; thus, it has been important to broadly scrutinize individual cancer driver gene mutations for effective cancer treatments. Multiplex cancer genome profiling can comprehensively identify gene mutations that are therapeutic targets using next-generation sequencing (NGS). In addition, circulating tumor DNA (ctDNA) is a DNA fragment released into the blood by tumor cell-derived cell death or apoptosis. Liquid biopsy with ctDNA is a novel clinical test for identifying genetic mutations in an entire population noninvasively, in real-time, and heterogeneously. Although there are several reports on ctDNA, fewer have evaluated ctDNA with NGS before an initial treatment for breast cancer patients. Therefore, we examined whether analyzing tumor-associated gene mutations in primary breast cancer based on ctDNA could serve as a biomarker for prognosis and optimal treatment selection. Ninety-five primary breast cancer patients treated at our department from January 2017 to October 2020 were included. Pretreatment plasma samples were subjected to NGS analysis of ctDNA, and correlations with patients’ clinicopathological characteristics were evaluated. Fifty-nine (62.1%) patients were positive for ctDNA. ctDNA tended to be positive in hormone receptor-negative, and TP53 (34%), BRCA1 (20%), and BRCA2 (17%) gene mutations were more frequent. Regarding recurrence-free survival, the prognosis was poor in the TP53 and/or BRCA1 mutation-positive groups, especially in triple-negative breast cancer (TNBC) patients. In conclusion, the results of this study indicate that ctDNA with liquid biopsy could identify the poor prognosis group before treatment among TNBC patients and for those for whom optimal treatment selection is desirable; additionally, optimal treatment could be selected according to the ctDNA analysis results.

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Collaborators (8)

Makoto Matsushita

Osaka University

JAPAN
View details

Takayoshi Suzuki

Section Chief

National Institute of Health Sciences

JAPAN
View details

Reiko Sugiura

Kindai University

JAPAN
View details

Koji Hatano

Osaka University Graduate School of Medicine

JAPAN
View details

Toshitaka Nagao

Professor

Tokyo Medical and Dental University

JAPAN
View details

Kazuhiro Yoshimura

Professor

Kindai University

JAPAN
View details

Makoto Kubo

Kyushu University

JAPAN
View details

Yasuhiro Tsutani

Kindai University Faculty of Medicine

JAPAN
View details
ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.