Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer

Nakauchi, Chiaki; Masunaga, Nanae; Kagara, Naofumi; Oshiro, Chiya; Shimoda, Masafumi; Shimazu, Kenzo

doi:https://doi.org/10.1007/s10549-025-07647-0

Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer

Nakauchi, Chiaki; Masunaga, Nanae; Kagara, Naofumi et al.

Breast Cancer Research and Treatment, 2025, e2026921

アクセス数:622件（2025-09-04 12:23 集計）

固定URL: https://hdl.handle.net/11094/101006

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タイトル	Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer
著者	著者名 Nakauchi, Chiaki
	NRID 1000060961620 1000060961620 Scopus Author ID 57195636812 57195636812 著者名 Masunaga, Nanae
	NRID 1000080641539 1000080641539 著者名 Kagara, Naofumi
	著者名 Oshiro, Chiya
	NRID 1000030644455 1000030644455 ORCID 0000-0002-0832-9877 0000-0002-0832-9877 researchmap permalink shimodam shimodam Scopus Author ID 55796822600 55796822600 著者名 Shimoda, Masafumi
	NRID 1000030448039 1000030448039 researchmap permalink _-23f _-23f Scopus Author ID 7005224756 7005224756 著者名 Shimazu, Kenzo
キーワード等	Breast cancer
	CtDNA
	DNA microarray
	Liquid biopsy
内容	The version of record of this article, first published in Breast Cancer Research and Treatment, is available online at Publisher’s website: https://doi.org/10.1007/s10549-025-07647-0
抄録	Purpose: The detection of circulating tumor DNA (ctDNA) is a valuable method to predict the risk of recurrence and to detect real-time gene changes. The amount of ctDNA is affected by many factors. Moreover, the detection rate of ctDNA varies from report to report. Methods: The present study evaluated differentially expressed genes using a DNA microarray assay for gene expression in tumors with and without detected ctDNA and constructed a prediction model for the detectability of ctDNA in breast tumor tissues. The model, named Cir-Predict, consisted of 126 probe sets (111 genes) and was constructed in a training set of breast cancer patients (n = 35) and validated in a validation set (n = 13). Results: The accuracy, sensitivity, and specificity in training and validation sets were over 90%, and Cir-Predict was significantly associated with ctDNA detection independently of the other conventional clinicopathological parameters in training and validation sets (P < 0.001, P = 0.014, respectively). Cir-Predict (+) was significantly associated with worse recurrence-free survival (P = 0.006). Pathway analysis revealed that nine pathways including tight junction and cell cycle tended to be related to ctDNA detectability. Conclusion: Cir-Predict not only provides information useful for breast cancer treatment, but also helps the understanding of the mechanism by which ctDNA is detected.
出版者	Springer
収録物名	Breast Cancer Research and Treatment
ページ	e2026921
刊行年月	2025-03-07
言語	英語
ハンドルURL	https://hdl.handle.net/11094/101006
PISSN	01676806
eISSN	15737217
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1007/s10549-025-07647-0
アクセス権	open access
権利情報	This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCTERMS.bibliographicCitation	Breast Cancer Research and Treatment. 2025, p. e2026921
DC.title	Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer
DC.creator	Nakauchi, Chiaki
	Masunaga, Nanae
	Kagara, Naofumi
	Oshiro, Chiya
	Shimoda, Masafumi
	Shimazu, Kenzo
DC.publisher	Springer
DC.language' scheme='DCTERMS.RFC1766	英語
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-03-07
DC.identifier	https://doi.org/10.1007/s10549-025-07647-0
DC.subject	Breast cancer
	CtDNA
	DNA microarray
	Liquid biopsy
DC.description	The version of record of this article, first published in Breast Cancer Research and Treatment, is available online at Publisher’s website: https://doi.org/10.1007/s10549-025-07647-0
DCTERMS.abstract	Purpose: The detection of circulating tumor DNA (ctDNA) is a valuable method to predict the risk of recurrence and to detect real-time gene changes. The amount of ctDNA is affected by many factors. Moreover, the detection rate of ctDNA varies from report to report. Methods: The present study evaluated differentially expressed genes using a DNA microarray assay for gene expression in tumors with and without detected ctDNA and constructed a prediction model for the detectability of ctDNA in breast tumor tissues. The model, named Cir-Predict, consisted of 126 probe sets (111 genes) and was constructed in a training set of breast cancer patients (n = 35) and validated in a validation set (n = 13). Results: The accuracy, sensitivity, and specificity in training and validation sets were over 90%, and Cir-Predict was significantly associated with ctDNA detection independently of the other conventional clinicopathological parameters in training and validation sets (P < 0.001, P = 0.014, respectively). Cir-Predict (+) was significantly associated with worse recurrence-free survival (P = 0.006). Pathway analysis revealed that nine pathways including tight junction and cell cycle tended to be related to ctDNA detectability. Conclusion: Cir-Predict not only provides information useful for breast cancer treatment, but also helps the understanding of the mechanism by which ctDNA is detected.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	101006
citation_title	Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer
citation_author	Nakauchi, Chiaki
	Masunaga, Nanae
	Kagara, Naofumi
	Oshiro, Chiya
	Shimoda, Masafumi
	Shimazu, Kenzo
citation_publisher	Springer
citation_language	英語
citation_date	2025-03-07
citation_journal_title	Breast Cancer Research and Treatment
citation_firstpage	e2026921
citation_doi	https://doi.org/10.1007/s10549-025-07647-0
citation_public_url	https://hdl.handle.net/11094/101006

Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer

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