Timp1 interacts with beta-1 integrin and CD63 along melanoma genesis and confers anoikis resistance by activating PI3-K signaling pathway independently of Akt phosphorylation

Background: Anoikis resistance is one of the abilities acquired along tumor progression. This characteristic is associated with metastasis development, since tumorigenic cells must survive independently of cell-matrix interactions in this process. in our laboratory, it was developed a murine melanocyte malignant transformation model associated with a sustained stressful condition. After subjecting melan-a melanocytes to 1, 2, 3 and 4 cycles of anchorage impediment, anoikis resistant cells were established and named 1C, 2C, 3C and 4C, respectively. These cells showed altered morphology and PMA independent cell growth, but were not tumorigenic, corresponding to pre-malignant cells. After limiting dilution of 4C pre-malignant cells, melanoma cell lines with different characteristics were obtained. Previous data from our group showed that increased Timp1 expression correlated with anoikis-resistant phenotype. Timp1 was shown to confer anchorage-independent growth capability to melan-a melanocytes and render melanoma cells more aggressive when injected into mice. However, the mechanisms involved in anoikis regulation by Timp1 in tumorigenic cells are not clear yet.Methods: the beta 1-integrin and Timp1 expression were evaluated by Western blotting and CD63 protein expression by flow cytometry using specific antibodies. To analyze the interaction among Timp1, CD63 and beta 1-integrin, immunoprecipitation assays were performed, anoikis resistance capability was evaluated in the presence or not of the PI3-K inhibitors, Wortmannin and LY294002. Relative expression of TIMP1 and CD63 in human metastatic melanoma cells was analyzed by real time PCR.Results: Differential association among Timp1, CD63 and beta 1-integrins was observed in melan-a melanocytes, 4C pre-malignant melanocytes and 4C11- and 4C11+ melanoma cells. Timp1 present in conditioned medium of melanoma cells rendered melan-a melanocytes anoikis-resistant through PI3-K signaling pathway independently of Akt activation. in human melanoma cell lines, in which TIMP1 and beta-1 integrin were also found to be interacting, TIMP1 and CD63 levels together was shown to correlate significantly with colony formation capacity.Conclusions: Our results show that Timp1 is assembled in a supramolecular complex containing CD63 and beta 1-integrins along melanoma genesis and confers anoikis resistance by activating PI3-K signaling pathway, independently of Akt phosphorylation. in addition, our data point TIMP1, mainly together with CD63, as a potential biomarker of melanoma.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Federal de São Paulo, Dept Pharmacol, São Paulo, BrazilUniversidade Federal de São Paulo, Microbiol Immunol & Parasitol Dept, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biochem, São Paulo, BrazilLudwig Inst Canc Res, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Pharmacol, São Paulo, BrazilUniversidade Federal de São Paulo, Microbiol Immunol & Parasitol Dept, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biochem, São Paulo, BrazilFAPESP: 2011/12306-1FAPESP: 2010/18715-8CAPES: 2867/10Web of Scienc

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors