Literature DB >> 26925708

Annexin A2 and S100A10 are independent predictors of serous ovarian cancer outcome.

Noor A Lokman1, Carmen E Pyragius2, Andrew Ruszkiewicz3, Martin K Oehler4, Carmela Ricciardelli5.   

Abstract

Annexin A2, a calcium phospholipid binding protein, has been shown to play an important role in ovarian cancer metastasis. This study examined whether annexin A2 and S100A10 can be used as prognostic markers in serous ovarian cancer. ANXA2 and S100A10 gene expressions were assessed in publicly available ovarian cancer data sets and annexin A2 and S100A10 protein expressions were assessed by immunohistochemistry in a uniform cohort of stage III serous ovarian cancers (n = 109). Kaplan-Meier and Cox regression analyses were performed to assess the relationship between annexin A2 or S100A10 messenger RNA (mRNA) and protein expressions with clinical outcome. High ANXA2 mRNA levels in stage III serous ovarian cancers were associated with reduced progression-free survival (PFS; P = 0.023) and overall survival (OS; P = 0.0038), whereas high S100A10 mRNA levels predicted reduced OS (P = 0.0019). Using The Cancer Genome Atlas data sets, ANXA2 but not S100A10 expression was associated with higher clinical stage (P = 0.005), whereas both ANXA2 and S100A10 expressions were associated with the mesenchymal molecular subtype (P < 0.0001). Kaplan-Meier and Cox regression analyses showed that high stromal annexin A2 immunostaining was significantly associated with reduced PFS (P = 0.013) and OS (P = 0.044). Moreover, high cytoplasmic S100A10 staining was significantly associated with reduced OS (P = 0.027). Multivariate Cox regression analysis showed stromal annexin A2 (P = 0.009) and cytoplasmic S100A10 (P = 0.016) levels to be independent predictors of OS. Patients with high stromal annexin A2 and high cytoplasmic S100A10 expressions had a 3.4-fold increased risk of progression (P = 0.02) and 7.9-fold risk of ovarian cancer death (P = 0.04). Our findings indicate that together annexin A2 and S100A10 expressions are powerful predictors of serous ovarian cancer outcome.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 26925708     DOI: 10.1016/j.trsl.2016.02.002

Source DB:  PubMed          Journal:  Transl Res        ISSN: 1878-1810            Impact factor:   7.012


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