Development of Serum Biomarker Panels for The Early Detection of Breast Cancer

¹Laboratory of Translational Medicine, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China

²Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

³Department of Respiratory Medicine, Chinese PLA General Hospital, Beijing, China

⁴Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospital & Institute, Beijing, China

⁵Department of Radiology, Chinese PLA General Hospital, Beijing, China

⁶National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, China

⁷Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China

ǂ Authors contributed equally

^*Corresponding Author

Yaping Tian

Tel:+86-10-66939374

Fax: +86-10 -88217385

E-mail: tianyp61@gmail.com.

F-Yong Wang

Tel: 86-10-62616659

E-mail: ywang@amss.ac.cn.

Luonan Chen

Tel: 86-21-64365937

Fax: 86-21-54972551

Email: lnchen@sibs.ac.cn.   

Abstract

Purpose: We aimed to develop noninvasive and early detection breast cancer biomarkers panel that may serve as assistant diagnostic method.

Methods: 61 biomarkers were detected in sea of 101 healthy controls, 46 benign breast diseases and 77 breast cancer patients in the training group. A metropolis algorithm with Monte Carlo simulation was used for choosing the model. 444 individuals were used for validation. Serum from 245 female cancer patients including 5 kinds of cancers were also collected to evaluate cancer selectivity.

Results: Panel consisting of Apolipoprotein AІ (ApoAІ), ApopB, C-reactive protein (CRP) and interleukin (IL)-8 had the highest value for discriminating between breast cancer and healthy control. The sensitivity (SN) was 98.70% for all-stage, 100.00% for early-stage and 97.92% for advanced-stage with 90% specificity (SP). In the validation group, the sensitivities were 96.43%, 100.00% and 94.21% at 90% SP. This panel identified 14.29% cervical cancer, 0% lung cancer, 20.29% pancreatic cancer, 25.00% gastric cancer, and 17.50% colorectal cancer as non-breast cancer. Panel consisting of Pepsinogen (PG) І /II, CRP, Superoxide dismutase, Tumor necrosis factor α had the highest value for discriminating between breast cancer and benign breast diseases. The SN was 88.31% for all-stage, 72.41% for early-stage and 97.92% for advanced-stage with 90% SP. In the validation group, the sensitivities were 81.25%, 69.77% and 88.41% at 90% SP.

Conclusions: The biomarker panels showed an improved performance when compared to CA153. It may serve as assistant tools for breast cancer screening and early detection to improve the clinical outcome.

Keywords: Serum; Breast Cancer; Metropolis Algorithm, Monte Carlo Simulation; Early Detection

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