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The expression and biological functions of oncofetal markers GD2 and GD3 were extensively studied in neuroectoderm-derived cancers in order to characterize their potential as therapeutic targets. Using immunological approaches, we previously identified GD3, GD2, and OAcGD2 expression in breast cancer (BC) cell lines. However, antibodies specific for O-acetylated gangliosides are not exempt of limitations, as they only provide information on the expression of a limited set of O-acetylated ganglioside species. Consequently, the aim of the present study was to use structural approaches in order to apprehend ganglioside diversity in melanoma, neuroblastoma, and breast cancer cells, focusing on O-acetylated species that are usually lost under alkaline conditions and require specific analytical procedures. We used purification and extraction methods that preserve the O-acetyl modification for the analysis of native gangliosides by MALDI-TOF. We identified the expression of GM1, GM2, GM3, GD2, GD3, GT2, and GT3 in SK-Mel28 (melanoma), LAN-1 (neuroblastoma), Hs 578T, SUM 159PT, MDA-MB-231, MCF-7 (BC), and BC cell lines over-expressing GD3 synthase. Among O-acetylated gangliosides, we characterized the expression of OAcGM1, OAcGD3, OAcGD2, OAcGT2, and OAcGT3. Furthermore, the experimental procedure allowed us to clearly identify the position of the sialic acid residue that carries the O-acetyl group on b- and c-series gangliosides by MS/MS fragmentation. These results show that ganglioside O-acetylation occurs on both inner and terminal sialic acid residue in a cell type-dependent manner, suggesting different O-acetylation pathways for gangliosides. They also highlight the limitation of immuno-detection for the complete identification of O-acetylated ganglioside profiles in cancer cells.

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3 ABSTRACTPurpose. Prognosis of early beast cancer is heterogeneous. Today, no histo-clinical or biological factor predictive for clinical outcome after adjuvant anthracycline-based chemotherapy (CT) has been validated and introduced in routine use. Using DNA microarrays, we searched for a gene expression signature associated with metastatic relapse after adjuvant anthracycline-based CT without taxane. Methods.We profiled a multicentric series of 595 breast cancers including 498 treated with such adjuvant CT. The identification of the prognostic signature was done using a metagene-based supervised approach in a learning set of 323 patients. The signature was then tested on an independent validation set comprised of 175 similarly treated patients, 128 of them from the PACS01 prospective clinical trial.Results. We identified a 3-metagene predictor of metastatic relapse in the learning set, and confirmed its independent prognostic impact in the validation set. In multivariate analysis, the predictor outperformed the individual current prognostic factors, as well as the Nottingham Prognostic Index-based classifier, both in the learning and the validation sets, and added independent prognostic information. Among the patients treated with adjuvant anthracycline-based CT, with a median follow-up of 68 months, the 5-year metastasis-free survival was 82% in the "good-prognosis" group and 56% in the "poorprognosis" group. Conclusion.Our predictor refines the prediction of metastasis-free survival after adjuvant anthracycline-based CT and might help tailoring adjuvant CT regimens. 4 KEY WORDSAdjuvant chemotherapy, breast cancer, DNA microarray, genomics, prognosis.

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