A novel four-serum marker model for early detection and therapeutic monitoring of breast cancer

Sep 30, 2026

Early diagnosis of breast cancer (BC) is essential for improving patient outcomes, yet current imaging methods have well-known constraints. This retrospective study analyzed serum biomarkers in 1366 BC patients and 1186 healthy controls from Shenzhen Nanshan People’s Hospital (2022–2025) to build and validate a tumor-marker predictive model. Eight markers (CEA, AFP, CA199, CA242, CA15-3, CA125, FER, NSE) were tested; AFP, CA242, CA15-3, and NSE formed a four-marker panel with diagnostic and treatment-monitoring value, including dynamic risk score associations with response and progression.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Abstract

Diagnostic model development

Biomarkers and statistical analysis

Diagnostic performance and stratification

Longitudinal monitoring and clinical implications

Keywords and abbreviations

[www. nature.com/scientificreports](www. nature.com/scientificreports) OPEN A novel four-serum marker model for early detection and therapeutic monitoring of breast cancer Shang Chen1,2, Jianling Zeng3, Ke Gong3, Yaru Liu2,4, Shoubin Long2, Li Han1􀀍 & Dixian Luo2,5􀀍 Early diagnosis of breast cancer (BC) remains pivotal for enhancing patient outcomes, yet current imaging modalities face inherent limitations. This retrospective study, encompassing 1366 BC patients and 1186 healthy controls (HC) from Shenzhen Nanshan People’s Hospital (2022–2025), developed and validated a serum tumor marker-based predictive model to address this gap. Eight markers—CEA, AFP, CA199, CA242, CA15-3, CA125, FER, and NSE—were analyzed, with multivariate logistic regression identifying AFP, CA242, CA15-3, and NSE as independent diagnostic predictors. The resulting fourmarker panel demonstrated robust performance, achieving anAUC of 0.90 (95% CI: 0.89–0.92) with 77.3% sensitivity and 89.7% specificity in the development cohort (n = 1535), and sustained efficacy invalidation (AUC = 0.82, 87.5% sensitivity, 72.8% specificity; n = 761). The model effectively stratified early-stage (T1/T2: 86.49% accuracy) versus advanced-stage (T3/T4: 92.00%) tumors, lymph node involvement (N0: 86.49%; N+: 88.00%), metastatic status (M0: 87.32%; M+: 85.71%), and molecular subtypes (LuminalA: 91.33%; Luminal B: 82.35%; HER2+: 84.61%; triple-negative: 87.75%) . Notably, longitudinal risk score trends correlated with therapeutic response, declining in remission and rising with progression. These findings collectively highlight the model’s dual utility as a high-accuracy diagnostic tool for early BC detection and a dynamic biomarker for monitoring treatment efficacy. This novel model may provide an auxiliary approach in current screening paradigms, underscoring its transformative potential in oncology practice. Keywords Breast cancer, Serum tumor marker, Predictive model, Efficacy assessment, Preoperative diagnosis Abbreviations BC Breast cancer HC Healthy controls N+ Lymph node-positive N0 Lymph node-negative CEA Carcinoembryonic antigen CA125 Carbohydrate antigen CA125 AFP Alpha-fetoprotein NSE Neuron-specific enolase FER Ferritin NED No evidence of disease S/PD Stable/persistent disease DP/R Disease progression/recurrence PPV Positive predictive value NPV Negative predictive value 1Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, The First Clinical College, Changsha Medical University, Changsha 410219, P. R. China. 2Laboratory Medicine Centre, Shenzhen Nanshan People’s Hospital, Shenzhen University, Shenzhen 518052, P. R. China. 3Translational Medicine Institute, The First People’s Hospital of Chenzhou, University of South China, Hengyang 423000, P. R. China. 4School of Basic Medical Sciences, Ningxia Medical University, Yinchuan 750004, P. R. China. 5Medical Laboratory Center, Shenzhen Luohu Hospital Group Luohu People’s Hospital, The third Affiliated Hospital of Shenzhen University, Shenzhen 518001, P. R. China. 􀀍 email: [524675905@qq.com](524675905@qq.com); luo_[dixian@email.szu.edu.cn](dixian@email.szu.edu.cn) [www. nature.com/scientificreports/](www. nature.com/scientificreports/) AUC Area under the curve OR Odds ratio In 2022, the global cancer patient population was estimated at approximately 20 million, with breast cancer (BC) accounting for 11.6% of cases, ranking it as one of the most prevalent malignancies worldwide, second only to lung cancer1. Recent years have witnessed an increasing incidence of BC, accompanied by a trend toward younger age at onset, posing a significant threat to women’s health. BC often presents insidiously, with nonspecific or absent symptoms in early stages; consequently, diagnosis frequently occurs at advanced stages, when therapeut

FAQs

Which serum markers were used to develop the four-marker panel?

The study analyzed CEA, AFP, CA199, CA242, CA15-3, CA125, FER, and NSE, and identified AFP, CA242, CA15-3, and NSE as independent diagnostic predictors forming the four-marker panel.

What diagnostic performance did the four-marker model achieve?

In the development cohort (n = 1535), the model achieved an AUC of 0.90 with 77.3% sensitivity and 89.7% specificity, and showed sustained performance in validation (AUC = 0.82, 87.5% sensitivity, 72.8% specificity).

How does the model relate to therapeutic response over time?

Longitudinal risk score trends tracked treatment dynamics, declining in remission and rising with progression, supporting its utility for monitoring efficacy and disease status.

Sep 30, 2026

Uploaded by Taylor Morgan