Líffræðifélag Íslands - biologia.is
Líffræðiráðstefnan 2017

Erindi/veggspjald / Talk/poster E29

Defining the breast cancer EMT model via a proteomic approach

Höfundar / Authors: Qiong Wang (1) Sigurður Trausti Karvelsson (2)

Starfsvettvangur / Affiliations: 1 2 University of Iceland

Kynnir / Presenter: Qiong Wang

Breast cancer is one of the highest occurring cancers in Iceland among females with a mortality rate of 18.6% (according to 2008-2012 statistics) (http://www.cancerregistry.is/). Around 90% of breast cancer deaths are caused by local invasion and distant metastasis of tumor cells. Epithelial to mesenchymal transition (EMT) is fundamental to cell development and a key feature in the progression of many cancers. EMT, however, remains a poorly understood cellular event primarily on account of biological complexity represented by biochemical alterations spanning the genomic, regulatory and metabolic levels. The genomic changes that take place during EMT are well defined; however, their impact on protein function and metabolism of EMT remains unclear. We proposed to explore a proteomic strategy to define changes that occur in proteome during EMT in breast epithelium through exploration of the EMT cell model, D492/D492M. D492 is a basal-like epithelial cell line with stem cell properties. D492M is the mesenchymal counterpart of D492 after induced EMT in D492 cells (Sigurdsson et al., 2011). The proteomic data obtained from this EMT model was thoroughly analyzed. There were 3093 proteins identified in total, with 2779 found in D492 and 2841 found in D492M. Moreover, 124 proteins were found unregulated at least 2 fold in D492M while 125 proteins were found at least 2 fold down regulated in D492M comparing to D492 (student’s t test, p < 0,05). Based on the GO term enrichment analysis, the down regulated proteins in D492M were mainly related to epithelium development, cell adhesion, hemidesmosome assembly, and the molecular functions of these down regulated proteins were including binding, phospholipase A2 inhibitor activity and EGFR activity. Besides, proteins in basement membrane and apical junction complex were down regulated. On the other side, proteins unregulated in D492M were mainly responsible for muscle contraction, extracellular matrix organization, heterophilic cell-cell adhesion and regulation of muscle system process. The molecular functions of these proteins were mainly for binding, namely, calmodulin binding, insulin-like growth factor binding and heparin binding. These proteins were mainly from extracellular matrix, extracellular region and extracellular space, and also from myofibril and actin cytoskeleton. The Reactome pathway enrichment analysis showed a list of metabolic pathways enriched in D492M including, but not limited to, the metabolism of amino acids and derivatives, polyamines, regulation of ornithine decarboxylase (ODC), metabolism of nucleotides and glucose, glycosis, pentose phosphoate pathway. At last, the differently expressed metabolic enzymes with at least 2-fold difference (student‘s t test, p < 0,05) were fished out, including downregulated enzymes in D492M: CNDP2, ACSS2, HSD17B12, TALDO1, CKMT1A, MGST1, GALE, LDHA, NQO1, PYGB, SULT1E1, GLUL, ACAA2, POLR1A, CA2, XDH, DGKA, SQRDL; and up regualted enzymes in D492M: UGDH, DHCR7, NNMT, PGM3, PGP, PKM, GSTM3, EPHX1, IDH2, PRPS1, PLOD2, ACSL1, ASS1, PGM2L1, CYP1B1. All enzymes listed above were thoroughly analyzed individually to find out the most important enzymes for functional assays in the future studies. The proteomic data were also used for Genome scale metabolic models (GEMs) to improve the EMT model in silica and identify the essential genes for EMT.