Serum CA125 is a predictive marker for breast cancer outcomes and correlates with molecular subtypes
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Cheng Fang1,2, Yue Cao2, Xiaoping Liu2, Xian-Tao Zeng2 and Yirong Li1
1Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
2Center for Evidence-Based and Translation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
Yirong Li, email: [email protected]
Keywords: serum tumor markers, CA125, breast cancer, clinicopathological features, molecular subtype
Received: March 09, 2017 Accepted: June 11, 2017 Published: July 12, 2017
Detection of serum tumor markers has been developed as a non-invasive tool to assess treatment efficiency in different types of cancer. This study aims to investigate the role of preoperative serum tumor markers (CEA, CA125 and CA15-3) in the management of breast cancer, and their relationships with patients’ clinicopathological parameters as well as different molecular subtypes. Altogether, 151 patients with invasive breast cancer and 180 control subjects with benign breast diseases were enrolled in this study. In the present study, preoperative serum levels of CEA, CA125 and CA15-3 were significantly higher in patients with breast cancer than controls subjects. Moreover, late-stage cancer patients exhibited significantly higher levels of CEA, CA125 and CA15-3 compared with early-stage ones. Statistical analysis indicated that elevated CA125 and CA15-3 levels were obviously related to patients with larger tumor diameter (>5cm) and lymph node metastasis. Furthermore, our results showed that the preoperative serum levels of CA125 exhibited statistical differences among various molecular subtypes, with the most frequent elevations occurring in the triple-negative tumors. In summary, our study indicated that the preoperative serum levels of CEA, CA125 and CA15-3 might be more efficient for monitoring advanced tumors than early diagnosis. High preoperative CA125 levels may reflect tumor burden and are associated with aggressive molecular subtype, suggesting that it can be used to predict poor outcome and prognosis of breast cancer patients.
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