Quantitative analysis of the secretome of TGF‐β signaling‐deficient mammary fibroblasts

Abstract

Transforming growth factor β (TGF-β) is a master regulator of autocrine and paracrine signaling pathways between a tumor and its microenvironment. Decreased expression of TGF-β type II receptor (TβRII) in stromal cells is associated with increased tumor metastasis and shorter patient survival. In this study, SILAC quantitative proteomics was used to identify differentially externalized proteins in the conditioned media from the mammary fibroblasts with or without intact TβRII. Over 1000 proteins were identified and their relative differential levels were quantified. Immunoassays were used to further validate identification and quantification of the proteomic results. Differential expression was detected for various extracellular proteins, including proteases and their inhibitors, growth factors, cytokines, and extracellular matrix proteins. CXCL10, a cytokine found to be up-regulated in the TβRII knockout mammary fibroblasts, is shown to directly stimulate breast tumor cell proliferation and migration. Overall, this study revealed hundreds of specific extracellular protein changes modulated by deletion of TβRII in mammary fibroblasts, which may play important roles in the tumor microenvironment. These results warrant further investigation into the effects of inhibiting the TGF-β signaling pathway in fibroblasts because systemic inhibition of TGF-β signaling pathways is being considered as a potential cancer therapy.

Global secretome analysis identifies novel mediators of bone metastasis

“…Analyses of the complete set of secreted proteins -otherwise known as the "secretome" -have been reported in various organisms, cell types, and pathologies, and are quickly gaining popularity [6,7]. Not surprisingly, several studies have focused on analyses of cancer-or metastasis-specific changes in secretome profiles [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. However, none of the studies to date has focused on secretomes relevant to the bone metastasis phenotype.…”

Conditioned media from cell lines: A complementary model to clinical specimens for the discovery of disease‐specific biomarkers

“…Zwickl et al demonstrated a method involving culturing HepG2 cells using standard conditions using methionine and cysteine-free William's E medium (ICN) in the presence of 35 S-labelled methionine and cysteine. Metabolic labelling of cells allows the detection of proteins by autoradiography, when only proteins synthesized by living cells during the metabolic labelling period will be visualized [23].…”

“…Metabolic labelling of cells allows the detection of proteins by autoradiography, when only proteins synthesized by living cells during the metabolic labelling period will be visualized [23]. More recently, Gundacker et al also used 35 S-labelled methionine and cysteine to identify the secreted proteins in the supernatant of cultured dendritic cells [24].…”

“…The light (natural isotope) and heavy amino acids are chemically identical and thus co-elute upon LC-based separation. But, since the peptides are isotopically distinct, the light-and heavy-labelled peptides are clearly distinguishable by MS, allowing for comparable abundance levels to be established [7,35].…”

Progress in Mining the Human Proteome for Disease Applications

“…Quantitative comparison of the proteome of single islets, containing 2,000-4,000 cells, treated with high or low glucose levels, allowed analysis of a repertoire of proteins involved in diabetes, including novel components. At the subcellular level, the secretome, the cell surface proteome, and the phosphoproteome can be analyzed with exquisite detail using proteomics technologies to identify potential novel diagnostic and therapeutic targets (Chenau et al, 2009;Daub et al, 2008;Faca et al, 2009;Greco et al, 2010;Gundry et al, 2008;Kohnke et al, 2009;Kosako et al, 2009;May, 2009;Piersma et al, 2010;Rinschen et al, 2010;Xu et al, 2010;Xue et al, 2010). Likewise, proteome profiling of tissues has allowed searches for disease alterations in great depths (Beretta, 2009;de la Cuesta et al, 2009;Voshol et al, 2009;Parikh et al, 2010;Sanchez-Carbayo, 2010).…”