Molecular subtyping of metastatic melanoma based on cell ganglioside metabolism profiles
- Equal contributors
1 Department of Medical Biotechnology and Translational Medicine, University of Milan, Segrate, Milan, Italy
2 Human Tumors Immunobiology Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
3 Laboratory of Stem Cells for Tissue Engineering, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
4 Department of Biomedical Sciences for Health, University of Milan, Segrate, Milan, Italy
5 Immunobiology Department, Center of Molecular Immunology, Havana, Cuba
BMC Cancer 2014, 14:560 doi:10.1186/1471-2407-14-560Published: 1 August 2014
In addition to alterations concerning the expression of oncogenes and onco-suppressors, melanoma is characterized by the presence of distinctive gangliosides (sialic acid carrying glycosphingolipids). Gangliosides strongly control cell surface dynamics and signaling; therefore, it could be assumed that these alterations are linked to modifications of cell behavior acquired by the tumor. On these bases, this work investigated the correlations between melanoma cell ganglioside metabolism profiles and the biological features of the tumor and the survival of patients.
Melanoma cell lines were established from surgical specimens of AJCC stage III and IV melanoma patients. Sphingolipid analysis was carried out on melanoma cell lines and melanocytes through cell metabolic labeling employing [3-3H]sphingosine and by FACS. N-glycolyl GM3 was identified employing the 14 F7 antibody. Gene expression was assayed by Real Time PCR. Cell invasiveness was assayed through a Matrigel invasion assay; cell proliferation was determined through the soft agar assay, MTT, and [3H] thymidine incorporation. Statistical analysis was performed using XLSTAT software for melanoma hierarchical clustering based on ganglioside profile, the Kaplan-Meier method, the log-rank (Mantel-Cox) test, and the Mantel-Haenszel test for survival analysis.
Based on the ganglioside profiles, through a hierarchical clustering, we classified melanoma cells isolated from patients into three clusters: 1) cluster 1, characterized by high content of GM3, mainly in the form of N-glycolyl GM3, and GD3; 2) cluster 2, characterized by the appearance of complex gangliosides and by a low content of GM3; 3) cluster 3, which showed an intermediate phenotype between cluster 1 and cluster 3. Moreover, our data demonstrated that: a) a correlation could be traced between patients’ survival and clusters based on ganglioside profiles, with cluster 1 showing the worst survival; b) the expression of several enzymes (sialidase NEU3, GM2 and GM1 synthases) involved in ganglioside metabolism was associated with patients’ survival; c) melanoma clusters showed different malignant features such as growth in soft agar, invasiveness, expression of anti-apoptotic proteins.
Ganglioside profile and metabolism is strictly interconnected with melanoma aggressiveness. Therefore, the profiling of melanoma gangliosides and enzymes involved in their metabolism could represent a useful prognostic and diagnostic tool.