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

IF 3 3区医学 Q2 ONCOLOGY

Breast Cancer Research and Treatment Pub Date : 2025-06-01 Epub Date: 2025-03-07 DOI:10.1007/s10549-025-07647-0

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

{"title":"Development of a prediction model for ctDNA detection (Cir-Predict) in breast cancer.","authors":"Chiaki Nakauchi, Nanae Masunaga, Naofumi Kagara, Chiya Oshiro, Masafumi Shimoda, Kenzo Shimazu","doi":"10.1007/s10549-025-07647-0","DOIUrl":null,"url":null,"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.","PeriodicalId":9133,"journal":{"name":"Breast Cancer Research and Treatment","volume":" ","pages":"331-339"},"PeriodicalIF":3.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006266/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Breast Cancer Research and Treatment","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10549-025-07647-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/7 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

乳腺癌ctDNA检测预测模型（cirr - predict）的建立。

目的：循环肿瘤DNA （ctDNA）检测是预测肿瘤复发风险和实时检测肿瘤基因变化的重要手段。ctDNA的数量受许多因素的影响。此外，ctDNA的检出率因报告而异。方法：本研究采用DNA微阵列法评估ctDNA在乳腺肿瘤组织中表达差异基因，并构建ctDNA在乳腺肿瘤组织中可检测性的预测模型。该模型名为cirr - predict，由126个探针集（111个基因）组成，在乳腺癌患者的训练集（n = 35）中构建，并在验证集（n = 13）中进行验证。结果：训练集和验证集的准确性、敏感性和特异性均在90%以上，且cirr - predict与ctDNA检测的相关性显著，独立于训练集和验证集的其他常规临床病理参数(P)。结论：cirr - predict不仅为乳腺癌治疗提供了有用的信息，而且有助于了解ctDNA的检测机制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Breast Cancer Research and Treatment 医学-肿瘤学

CiteScore

6.80

自引率

2.60%

发文量

342

审稿时长

1 months

期刊介绍： Breast Cancer Research and Treatment provides the surgeon, radiotherapist, medical oncologist, endocrinologist, epidemiologist, immunologist or cell biologist investigating problems in breast cancer a single forum for communication. The journal creates a "market place" for breast cancer topics which cuts across all the usual lines of disciplines, providing a site for presenting pertinent investigations, and for discussing critical questions relevant to the entire field. It seeks to develop a new focus and new perspectives for all those concerned with breast cancer.