Clinicopathologic significance of S100A4 expression in osteosarcoma

C.-m. Cao, F.-x. Yang, P.-l. Wang, Q.-x. Yang, X.-r. Sun

Medical Laboratory Diagnosis Center, Jinan Central Hospital, Jinan, Shangdong, China. sxrrtyy@126.com

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• Oncology

OBJECTIVE: Osteosarcoma is the most common primary malignancy, mainly arising from the metaphysis of the long bones of adolescents and young adults. Its poor prognosis is strongly associated with invasion and distant metastasis. The calcium-binding protein S100A4 promotes metastasis in several experimental animal models, including osteosarcoma (OS), and S100A4 protein expression is associated with patient outcome in a number of tumor types. In the present study, we investigated the expression of S100A4 and its clinicopathologic significance in OSs.

PATIENTS AND METHODS: S100A4 were examined immunohistochemically in resected OSs from 120 patients with OS to clarify their clinicopathologic significance. Multivariate survival analyses were carried out on all investigated parameters.

RESULTS: The immunohistochemical assays revealed that S1004A expression in osteosarcoma tissues was significantly higher than that in corresponding noncancerous bone tissues (p < 0.001). In addition, positive S100A4 expression more frequently occurred in osteosarcoma tissues with advanced clinical stage (p = 0.003), positive distant metastasis (p = 0.001) and poor response to chemotherapy (p = 0.04). In Kaplan-Meier analysis, only S100A4 positively stained cases showed a significantly decreased overall survival time and disease-free survival compared with negatively stained cases (both p < 0.001). On Cox multivariate analysis, positive S100A4 expression was an independent and significant prognostic factor to predict poor overall survival and disease-free survival (both p = 0.001).

CONCLUSIONS: Expression of S100A4 protein in OS may be related to the prediction of metastasis potency, response to chemotherapy and poor prognosis for osteosarcoma patients, suggesting that S100A4 may serve as a prognostic marker for the optimization of clinical treatments.

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