Prognostic value of biomarkers EpCAM and αB-crystallin associated with lymphatic metastasis in breast cancer by iTRAQ analysis

BMC Cancer 19, Article number: 831 (2019) | Download Citation

Abstract

Background

Metastasis is responsible for the majority of deaths in a variety of cancer types, including breast cancer. Although several factors or biomarkers have been identified to predict the outcome of patients with breast cancer, few studies have been conducted to identify metastasis-associated biomarkers.

Methods

Quantitative iTRAQ proteomics analysis was used to detect differentially expressed proteins between lymph node metastases and their paired primary tumor tissues from 23 patients with metastatic breast cancer. Immunohistochemistry was performed to validate the expression of two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins in 190 paraffin-embedded tissue samples. These four proteins were further analyzed for their correlation with clinicopathological features in 190 breast cancer patients.

Results

We identified 637 differentially regulated proteins (397 upregulated and 240 downregulated) in lymph node metastases compared with their paired primary tumor tissues. Data are available via ProteomeXchange with identifier PXD013931. Furthermore, bioinformatics analysis using GEO profiling confirmed the difference in the expression of EpCAM between metastases and primary tumors tissues. Two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins were associated with the progression of breast cancer. Obviously, EpCAM plays a role in the metastasis of breast cancer cells to the lymph node. We further identified αB-crystallin as an independent biomarker to predict lymph node metastasis and the outcome of breast cancer patients.

Conclusion

We have identified that EpCAM plays a role in the metastasis of breast cancer cells to the lymph node. αB-crystallin, a stress-related protein that has recently been shown to be important for cell invasion and survival, was identified as a potential prognostic biomarker to predict the outcome of breast cancer patients.