Medical Oncology

, 31:764

Tissue microarray analysis of X-linked inhibitor of apoptosis (XIAP) expression in breast cancer patients

Original Paper

DOI: 10.1007/s12032-013-0764-8

Cite this article as:
Xu, YC., Liu, Q., Dai, JQ. et al. Med Oncol (2014) 31: 764. doi:10.1007/s12032-013-0764-8

Abstract

The goal of this study was to determine the diagnostic and prognostic potential of X-linked inhibitor of apoptosis (XIAP) expression in breast cancer. We analyzed a tissue microarray comprised of 100 breast cancer cases and 70 matched normal samples. Analysis of an online database, which included 2,977 patients, was also performed. There was a significant difference in cytoplasmic expression of XIAP (XIAP-C) between breast cancer tissue and matched normal (p < 0.001). Staining of XIAP-C was defined as negative (breast cancer 8.42 % vs. normal 30.91 %), slight (40.0 vs. 45.45 %), moderate (43.16 vs. 23.64 %), or high (8.42 vs. 0 %). High XIAP-C protein expression correlated with human epidermal growth factor receptor 2 (HER-2) status (p = 0.010) and with human p53 mutant-type (P53) status (p = 0.039). We found that XIAP expression did not correlate with disease-free survival (p = 0.706) and overall survival (p = 0.496) of breast cancer patients. An Internet-based system analysis confirmed our results. In the subgroup analysis, basal-like breast cancer patients with high XIAP levels in the tumor had a significantly increased risk of relapse; thus, the up-regulation of XIAP appeared to be predictive of poor relapse-free survival (p = 0.013). Kaplan–Meier curves also identified a significant correlation between distant metastasis-free survival and XIAP expression in patients with lymph-node-negative disease (p = 0.030). In summary, expression of XIAP-C was significantly higher in breast cancer compared to normal tissue. XIAP-C expression correlated with HER-2 status and may be considered a prognostic biomarker for basal-like breast cancer patients.

Keywords

X-linked inhibitor of apoptosis Prognosis Breast cancer Tissue microarray 

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Ying-Chun Xu
    • 1
  • Qiang Liu
    • 3
  • Jia-Qi Dai
    • 2
  • Zhi-Qiang Yin
    • 2
  • Lei Tang
    • 1
  • Yue Ma
    • 1
  • Xiao-Lin Lin
    • 1
  • Hong-Xia Wang
    • 1
  1. 1.Department of Oncology, Ren Ji Hospital, School of MedicineShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of Surgery, Ren Ji Hospital, School of MedicineShanghai Jiao Tong UniversityShanghaiChina
  3. 3.Department of Pathology, Ren Ji Hospital, School of MedicineShanghai Jiao Tong UniversityShanghaiChina

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