2 files

C-Terminal Tensin-Like Protein Is a Novel Prognostic Marker for Primary Melanoma Patients

posted on 07.11.2013, 03:30 by Cecilia Sjoestroem, Shahram Khosravi, Guohong Zhang, Magdalena Martinka, Gang Li


C-terminal tensin-like protein (Cten) is a focal adhesion protein originally identified as a tumor suppressor in prostate cancer. It has since been found to be overexpressed and function as an oncogene in numerous other cancers, but the expression status of Cten in melanoma is still unknown.


Using tissue microarrays containing 562 melanocytic lesions, we evaluated Cten protein expression by immunohistochemistry. The association between Cten expression and patient survival was examined using Kaplan-Meier survival analysis, and univariate and multivariate Cox regression analyses were used to estimate the crude and adjusted hazard ratios.


Strong Cten expression was detected in 7%, 24%, 41%, and 46% of normal nevi, dysplastic nevi, primary melanoma, and metastatic melanoma samples, respectively, and Cten expression was found to be significantly higher in dysplastic nevi compared to normal nevi (P = 0.046), and in primary melanoma compared to dysplastic nevi (P = 0.003), but no difference was observed between metastatic and primary melanoma. Cten staining also correlated with AJCC stages (P = 0.015) and primary tumor thickness (P = 0.002), with Cten expression being induced in the transition from thin (<1mm) to thick (≥1mm) melanomas. Strong Cten expression was significantly associated with a worse 5-year overall (P = 0.008) and disease-specific survival (P = 0.004) for primary melanoma patients, and multivariate Cox regression analysis revealed that Cten expression was an independent prognostic marker for these patients (P = 0.038 for overall survival; P = 0.021 for disease-specific survival).


Our findings indicate that induction of Cten protein expression is a relatively early event in melanoma progression, and that Cten has the potential to serve as a prognostic marker for primary melanoma patients.


Usage metrics