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PATRIZIA CANCEMI

MULTIOMICS ANALYSIS OF S100 PROTEINS IN BREAST CANCER

  • Autori: Cancemi, P; Albanese, NN; Di Cara, G; Musso, R; Lupo,C; Roz, E; Feo,S; Pucci-Minafra,I.
  • Anno di pubblicazione: 2015
  • Tipologia: Abstract in atti di convegno pubblicato in rivista
  • OA Link: http://hdl.handle.net/10447/155735

Abstract

The S100 gene family is the largest subfamily of calcium binding proteins of EF-hand type, expressed in tissue and cell-specific manner. S100 proteins act as intracellular regulators and as extracellular signaling. Within cells, S100 have been involved in the regulation of proliferation, differentiation, apoptosis, energy metabolism, inflammation, migration and invasion via interactions with a variety of target proteins. Extracellular S100 proteins act in an autocrine and paracrine manner through the activation of surface receptors that regulate cell proliferation, differentiation, survival and migration. More recently, there is growing interest in the S100 proteins and their relationship with different cancers because of their involvement in a variety of biological events closely related to tumorigenesis and cancer progression1. However, the occurrence, the role and the possible coordination of this group of proteins in breast cancer is still poorly known. We previously describe a large-scale proteomic investigation performed on breast cancer patients for the screening of multiple forms of S100 proteins2,3. Our results have shown that the majority of S100 proteins are preferentially expressed in the tumor mass compared with the normal adjacent tissue and that some S100 protein members were ubiquitously expressed in almost all patients, while others appeared more sporadic among the same group of patients. More interestingly, patients which developed distant metastases showed a general tendency of higher S100 protein expression, compared to the disease-free group. Present study was aimed to assess the gene expression levels of the S100 protein family members utilizing a breast cancer dataset generated on Affymetrix microarrays technologies4. GOBO (Gene expression-based Outcome for Breast cancer Online) is a user-friendly online tool that allows, also, the identification of co-expressed genes and association with outcome in an 1881 breast cancer samples. Other important association with breast cancer outome was carried out by Kaplan Meir-plotter database5. Integrating results obtained by proteomic and trascriptomic analysis of S100 proteins highlight their important involvement in breast cancer progression, and support the idea that S100 proteins are important prognostic factors, related to survival period of tumor patients. However, the specific mechanisms by which S100 proteins affect progression of breast require further study.