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• W2147027178 abstract "It has become clear that growth and progression of breast tumor cells not only depend on their malignant potential but also on factors present in the tumor microenvironment. Of the cell types that constitute the mammary stroma, the adipocytes are perhaps the least well studied despite the fact that they represent one of the most prominent cell types surrounding the breast tumor cells. There is compelling evidence demonstrating a role for the mammary fat pad in mammary gland development, and some studies have revealed the ability of fat tissue to augment the growth and ability to metastasize of mammary carcinoma cells. Very little is known, however, about which factors adipocytes produce that may orchestrate these actions and how this may come about. In an effort to shed some light on these questions, we present here a detailed proteomic analysis, using two-dimensional gel-based technology, mass spectrometry, immunoblotting, and antibody arrays, of adipose cells and interstitial fluid of fresh fat tissue samples collected from sites topologically distant from the tumors of high risk breast cancer patients that underwent mastectomy and that were not treated prior to surgery. A total of 359 unique proteins were identified, including numerous signaling molecules, hormones, cytokines, and growth factors, involved in a variety of biological processes such as signal transduction and cell communication; energy metabolism; protein metabolism; cell growth and/or maintenance; immune response; transport; regulation of nucleobase, nucleoside, and nucleic acid metabolism; and apoptosis. Apart from providing a comprehensive overview of the mammary fat proteome and its interstitial fluid, the results offer some insight as to the role of adipocytes in the breast tumor microenvironment and provide a first glance of their molecular cellular circuitry. In addition, the results open new possibilities to the study of obesity, which has a strong association with type 2 diabetes, hypertension, and coronary heart disease. It has become clear that growth and progression of breast tumor cells not only depend on their malignant potential but also on factors present in the tumor microenvironment. Of the cell types that constitute the mammary stroma, the adipocytes are perhaps the least well studied despite the fact that they represent one of the most prominent cell types surrounding the breast tumor cells. There is compelling evidence demonstrating a role for the mammary fat pad in mammary gland development, and some studies have revealed the ability of fat tissue to augment the growth and ability to metastasize of mammary carcinoma cells. Very little is known, however, about which factors adipocytes produce that may orchestrate these actions and how this may come about. In an effort to shed some light on these questions, we present here a detailed proteomic analysis, using two-dimensional gel-based technology, mass spectrometry, immunoblotting, and antibody arrays, of adipose cells and interstitial fluid of fresh fat tissue samples collected from sites topologically distant from the tumors of high risk breast cancer patients that underwent mastectomy and that were not treated prior to surgery. A total of 359 unique proteins were identified, including numerous signaling molecules, hormones, cytokines, and growth factors, involved in a variety of biological processes such as signal transduction and cell communication; energy metabolism; protein metabolism; cell growth and/or maintenance; immune response; transport; regulation of nucleobase, nucleoside, and nucleic acid metabolism; and apoptosis. Apart from providing a comprehensive overview of the mammary fat proteome and its interstitial fluid, the results offer some insight as to the role of adipocytes in the breast tumor microenvironment and provide a first glance of their molecular cellular circuitry. In addition, the results open new possibilities to the study of obesity, which has a strong association with type 2 diabetes, hypertension, and coronary heart disease. During the last years there have been numerous reports indicating that growth and progression of breast as well as other tumor cells depend not only on their malignant potential but also on stromal factors present in the tumor microenvironment, the insoluble extracellular matrix as well as cell-cell interactions (Refs. 1.Wiseman B.S. Werb Z. Stromal effects on mammary gland development and breast cancer.Science. 2002; 296: 1046-1049Google Scholar, 2.Silberstein G.B. Tumour-stromal interactions. Role of the stroma in mammary development.Breast Cancer Res. 2001; 3: 218-223Google Scholar, 3.Coussens L.M. Werb Z. Matrix metalloproteinases and the development of cancer.Chem. Biol. 1996; 3: 895-904Google Scholar, 4.Coussens L.M. Werb Z. Inflammatory cells and cancer: think different!.J. Exp. Med. 2001; 193: F23-F26Google Scholar, 5.Fidler I.J. Regulation of neoplastic angiogenesis.J. Natl. Cancer Inst. Monogr. 2001; 28: 10-14Google Scholar, 6.Fidler I.J. Angiogenic heterogeneity: regulation of neoplastic angiogenesis by the organ microenvironment.J. Natl. Cancer Inst. 2001; 93: 1040-1041Google Scholar and references therein). Of all the cell types present in the microenvironment, which include endothelial cells and their supporting pericytes, inflammatory cells (neutrophils, macrophages, eosinophils, and mast cells), immune cells (lymphocytes and dendritic cells), smooth muscle cells, myofibroblasts, preadipocytes, and adipocytes, the last are perhaps the least well studied despite the fact that they correspond to one of the most prominent cell types surrounding the breast tumor cells (7.Iyengar P. Combs T.P. Shah S.J. Gouon-Evans V. Pollard J.W. Albanese C. Flanagan L. Tenniswood M.P. Guha C. Lisanti M.P. Pestell R.G. Scherer P.E. Adipocyte-secreted factors synergistically promote mammary tumorigenesis through induction of anti-apoptotic transcriptional programs and proto-oncogene stabilization.Oncogene. 2003; 22: 6408-6423Google Scholar). Until recently, adipocytes were mainly considered as an energy storage depot, but we now have clear evidence pointing to the fat tissue as an endocrine organ that produces hormones, growth factors, adipokines, and other molecules that may affect normal duct development as well as tumor growth and metastasis (Refs. 8.Howlett A.R. Bissell M.J. The influence of tissue microenvironment (stroma and extracellular matrix) on the development and function of mammary epithelium.Epithelial Cell Biol. 1993; 2: 79-89Google Scholar, 9.Zangani D. Darcy K.M. Shoemaker S. Ip M.M. Adipocyte-epithelial interactions regulate the in vitro development of normal mammary epithelial cells.Exp. Cell Res. 1999; 247: 399-409Google Scholar, 10.Huss F.R. Kratz G. Mammary epithelial cell and adipocyte co-culture in a 3-D matrix: the first step towards tissue-engineered human breast tissue.Cells Tissues Organs. 2001; 169: 361-367Google Scholar, 11.Scherer P.E. Williams S. Fogliano M. Baldini G. Lodish H.F. A novel serum protein similar to C1q, produced exclusively in adipocytes.J. Biol. Chem. 1995; 45: 26746-26749Google Scholar, 12.Scherer P.E. Bickel P.E. Kotler M. Lodish H.F. Cloning of cell-specific secreted and surface proteins by subtractive antibody screening.Nat. Biotechnol. 1998; 16: 581-586Google Scholar, 13.Bickel P.E. Lodish H.F. Scherer P.E. Use and applications of subtractive antibody screening.Biotechnol. Genet. Eng. Rev. 2000; 17: 417-430Google Scholar, 14.Engelman J.A. Berg A.H. Lewis R.Y. Lisanti M.P. Scherer P.E. Tumor necrosis factor α-mediated insulin resistance, but not dedifferentiation, is abrogated by MEK1/2 inhibitors in 3T3-L1 adipocytes.Mol. Endocrinol. 2000; 14: 1557-1569Google Scholar, 15.Berg A.H. Combs T.P. Du X. Brownlee M. Scherer P.E. The adipocyte-secreted protein Acrp30 enhances hepatic insulin action.Nat. Med. 2001; 7: 947-953Google Scholar, 16.Cancello R. Tounian A. Poitou Ch. Clement K. Adiposity signals, genetic and body weight regulation in humans.Diabetes Metab. 2004; 30: 215-227Google Scholar, 17.Mora S. Pessin J.E. An adipocentric view of signaling and intracellular trafficking.Diabetes Metab. Res. Rev. 2002; 18: 345-356Google Scholar, 18.Trayhurn P. Wood I.S. Adipokines: inflammation and the pleiotropic role of white adipose tissue.Br. J. Nutr. 2004; 92: 347-355Google Scholar and references therein). It has been shown that normal mouse mammary ducts do not form correctly if there is no proper interaction with the fat tissue, and a number of signaling pathways that may be involved in this process have been identified (8.Howlett A.R. Bissell M.J. The influence of tissue microenvironment (stroma and extracellular matrix) on the development and function of mammary epithelium.Epithelial Cell Biol. 1993; 2: 79-89Google Scholar, 9.Zangani D. Darcy K.M. Shoemaker S. Ip M.M. Adipocyte-epithelial interactions regulate the in vitro development of normal mammary epithelial cells.Exp. Cell Res. 1999; 247: 399-409Google Scholar, 10.Huss F.R. Kratz G. Mammary epithelial cell and adipocyte co-culture in a 3-D matrix: the first step towards tissue-engineered human breast tissue.Cells Tissues Organs. 2001; 169: 361-367Google Scholar). Elliot and colleagues (19.Elliott B.E. Tam S.P. Dexter D. Chen Z.Q. Capacity of adipose tissue to promote growth and metastasis of a murine mammary carcinoma: effect of estrogen and progesterone.Int. J. Cancer. 1992; 51: 416-424Google Scholar), on the other hand, showed that fat tissue is able to augment the growth and ability to metastasize of the murine mammary carcinoma cell line SP1 when injected subcutaneously or peritoneally far away from fat pads, and Iyengar and colleagues (7.Iyengar P. Combs T.P. Shah S.J. Gouon-Evans V. Pollard J.W. Albanese C. Flanagan L. Tenniswood M.P. Guha C. Lisanti M.P. Pestell R.G. Scherer P.E. Adipocyte-secreted factors synergistically promote mammary tumorigenesis through induction of anti-apoptotic transcriptional programs and proto-oncogene stabilization.Oncogene. 2003; 22: 6408-6423Google Scholar) reported that factors secreted by adipocytes promote mammary tumorigenesis through induction of antiapoptotic transcriptional programs and proto-oncogene stabilization. In addition, several reports have demonstrated an association between breast cancer growth and the presence of adipose tissue (20.Chamras H. Bagga D. Elstner E. Setoodeh K. Koeffler H.P. Heber D. Preadipocytes stimulate breast cancer cell growth.Nutr. Cancer. 1998; 32: 59-63Google Scholar, 21.Manabe Y. Toda S. Miyazaki K. Sugihara H. Mature adipocytes, but not preadipocytes, promote the growth of breast carcinoma cells in collagen gel matrix culture through cancer-stromal cell interactions.J. Pathol. 2003; 201: 221-228Google Scholar, 22.Johnston P.G. Rondinone C.M. Voeller D. Allegra C.J. Identification of a protein factor secreted by 3T3-L1 preadipocytes inhibitory for the human MCF-7 breast cancer cell line.Cancer Res. 1992; 52: 6860-6865Google Scholar), and a connection between obesity and increased incidence of cancer has been established for breast, colorectal, endometrial, renal (renal cell), and esophageal (adenocarcinoma) malignancies (Ref. 23.Calle E.E. Thun M.J. Obesity and cancer.Oncogene. 2004; 23: 6365-6378Google Scholar and references therein). Presently, however, there is only limited information as to the factors produced by adipocytes that may affect normal breast duct development and tumor progression (1.Wiseman B.S. Werb Z. Stromal effects on mammary gland development and breast cancer.Science. 2002; 296: 1046-1049Google Scholar, 7.Iyengar P. Combs T.P. Shah S.J. Gouon-Evans V. Pollard J.W. Albanese C. Flanagan L. Tenniswood M.P. Guha C. Lisanti M.P. Pestell R.G. Scherer P.E. Adipocyte-secreted factors synergistically promote mammary tumorigenesis through induction of anti-apoptotic transcriptional programs and proto-oncogene stabilization.Oncogene. 2003; 22: 6408-6423Google Scholar, 24.Kratchmarova I. Kalume D.E. Blagoev B. Scherer P.E. Podtelejnikov A.V. Molina H. Bickel P.E. Andersen J.S. Fernandez M.M. Bunkenborg J. Roepstorff P. Kristiansen K. Lodish H.F. Mann M. Pandey A. A proteomic approach for identification of secreted proteins during the differentiation of 3T3-L1 preadipocytes to adipocytes.Mol. Cell. Proteomics. 2002; 1: 213-222Google Scholar). Most studies of adipogenesis have made use of rodent cells or primary cultures of human mesenchymal stem cells that have been induced to differentiate into adipocytes using a variety of effectors. By using cDNA microarrays (25.Hung S.C. Chang C.F. Ma H.L. Chen T.H. Low-Tone Ho L. Gene expression profiles of early adipogenesis in human mesenchymal stem cells.Gene (Amst.). 2004; 340: 141-150Google Scholar, 26.Guo X. Liao K. Analysis of gene expression profile during 3T3-L1 preadipocyte differentiation.Gene (Amst.). 2000; 251: 45-53Google Scholar, 27.Burton G.R Guan Y. Nagarajan R. McGehee Jr, R.E. Microarray analysis of gene expression during early adipocyte differentiation.Gene (Amst.). 2002; 293: 21-31Google Scholar, 28.Urs S. Smith C. Campbell B. Saxton A.M. Taylor J. Zhang B. Snoddy J. Jones Voy B. Moustaid-Moussa N. Gene expression profiling in human preadipocytes and adipocytes by microarray analysis.J. Nutr. 2004; 134: 762-770Google Scholar, 29.Boeuf S. Klingenspor M. Van Hal N.L. Schneider T. Keijer J. Klaus S. Differential gene expression in white and brown preadipocytes.Physiol. Genomics. 2001; 7: 15-25Google Scholar, 30.Sottile V. Seuwen K. A high-capacity screen for adipogenic differentiation.Anal. Biochem. 2001; 293: 124-128Google Scholar, 31.Albrektsen T. Richter H.E. Clausen J.T. Fleckner J. Identification of a novel integral plasma membrane protein induced during adipocyte differentiation.Biochem. J. 2001; 359: 393-402Google Scholar, 32.Soukas A. Socci N.D. Saatkamp B.D. Novelli S. Friedman J.M. Distinct transcriptional profiles of adipogenesis in vivo and in vitro.J. Biol. Chem. 2001; 276: 34167-34174Google Scholar) and proteomic technologies (Refs. 24.Kratchmarova I. Kalume D.E. Blagoev B. Scherer P.E. Podtelejnikov A.V. Molina H. Bickel P.E. Andersen J.S. Fernandez M.M. Bunkenborg J. Roepstorff P. Kristiansen K. Lodish H.F. Mann M. Pandey A. A proteomic approach for identification of secreted proteins during the differentiation of 3T3-L1 preadipocytes to adipocytes.Mol. Cell. Proteomics. 2002; 1: 213-222Google Scholar and 33.Brasaemle D.L. Dolios G. Shapiro L. Wang R. Proteomic analysis of proteins associated with lipid droplets of basal and lipolytically stimulated 3T3-L1 adipocytes.J. Biol. Chem. 2004; 279: 46835-46842Google Scholar and references therein), it has been possible to identify several genes and proteins that are differentially regulated as a result of adipogenesis. These studies have been inspired by the facts that increased adiposity and a failure in adipocyte differentiation are associated with morbidity, mortality, and many disorders, including obesity, which has a strong association with type 2 diabetes (34.Danforth Jr, E. Failure of adipocyte differentiation causes type II diabetes mellitus?.Nat. Genet. 2000; 26: 13Google Scholar, 35.Cederberg A. Enerback S. Insulin resistance and type 2 diabetes—an adipocentric view.Curr. Mol. Med. 2003; 3: 107-125Google Scholar), hypertension, and coronary heart disease (36.Kopelman P.G. Obesity as a medical problem.Nature. 2000; 404: 635-643Google Scholar). The question remains, however, as to whether these experimental model systems are able to completely replicate the in vivo situation (Ref. 37.Klaus S. Adipose tissue as a regulator of energy balance.Curr. Drug. Targets. 2004; 5: 241-250Google Scholar and references therein) as it has been shown that gene expression changes associated with adipogenesis in vivo and in vitro, while sharing many features in common, are in some respects rather different (32.Soukas A. Socci N.D. Saatkamp B.D. Novelli S. Friedman J.M. Distinct transcriptional profiles of adipogenesis in vivo and in vitro.J. Biol. Chem. 2001; 276: 34167-34174Google Scholar). In vivo transcript profiling studies of human and murine fat tissue (28.Urs S. Smith C. Campbell B. Saxton A.M. Taylor J. Zhang B. Snoddy J. Jones Voy B. Moustaid-Moussa N. Gene expression profiling in human preadipocytes and adipocytes by microarray analysis.J. Nutr. 2004; 134: 762-770Google Scholar, 32.Soukas A. Socci N.D. Saatkamp B.D. Novelli S. Friedman J.M. Distinct transcriptional profiles of adipogenesis in vivo and in vitro.J. Biol. Chem. 2001; 276: 34167-34174Google Scholar, 38.Gabrielsson B.L. Carlsson B. Carlsson L.M. Partial genome scale analysis of gene expression in human adipose tissue using DNA array.Obes. Res. 2000; 8: 374-384Google Scholar) have shown the complexity of the adipocyte transcriptome and have implicitly established that the biology of these cells has a degree of intricacy that was not expected. To date, however, only two studies have investigated the proteome of human and mouse adipose tissue; one resolved about 100 human proteins using wide IPG strips and identified 16 polypeptides by means of mass spectrometry (39.Corton M. Villuendas G. Botella J.I. San Millan J.L. Escobar-Morreale H.F. Peral B. Improved resolution of the human adipose tissue proteome at alkaline and wide range pH by the addition of hydroxyethyl disulfide.Proteomics. 2004; 4: 438-441Google Scholar), while the other resolved a considerable number of murine white adipose tissue proteins and identified 80 unique polypeptides (40.Lanne B. Potthast F. Hoglund A. Brockenhuus von Lowenhielm H. Nystrom A.C. Nilsson F. Dahllof B. Thiourea enhances mapping of the proteome from murine white adipose tissue.Proteomics. 2001; 1: 819-828Google Scholar). In our translational breast cancer program, which involves high risk patients that have undergone mastectomy (41.Celis J.E. Gromov P. Gromova I. Moreira J.M. Cabezon T. Ambartsumian N. Grigorian M. Lukanidin E. Thor Straten P. Guldberg P. Bartkova J. Bartek J. Lukas J. Lukas C. Lykkesfeldt A. Jaattela M. Roepstorff P. Bolund L. Orntoft T. Brunner N. Overgaard J. Sandelin K. Blichert-Toft M. Mouridsen H. Rank F.E. Integrating proteomic and functional genomic technologies in discovery-driven translational breast cancer research.Mol. Cell. Proteomics. 2003; 2: 369-377Google Scholar, 42.Celis J.E. Gromov P. Cabezon T. Moreira J.M. Ambartsumian N. Sandelin K. Rank F. Gromova I. Proteomic characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery.Mol. Cell. Proteomics. 2004; 3: 327-344Google Scholar, 43.Celis J.E. Moreira J.M. Gromova I. Cabezon T. Ralfkiaer U. Guldberg P. Straten P.T. Mouridsen H. Friis E. Holm D. Rank F. Gromov P. Towards discovery-driven translational research in breast cancer.FEBS J. 2005; 272: 2-15Google Scholar), we have frequently detected tumor cells interdigitating with and spreading through the peripheral fat tissue suggesting a close association between these two cell types (Fig. 1) (7.Iyengar P. Combs T.P. Shah S.J. Gouon-Evans V. Pollard J.W. Albanese C. Flanagan L. Tenniswood M.P. Guha C. Lisanti M.P. Pestell R.G. Scherer P.E. Adipocyte-secreted factors synergistically promote mammary tumorigenesis through induction of anti-apoptotic transcriptional programs and proto-oncogene stabilization.Oncogene. 2003; 22: 6408-6423Google Scholar). This observation together with published data demonstrating a role for the fat tissue in mammary gland development (Refs. 1.Wiseman B.S. Werb Z. Stromal effects on mammary gland development and breast cancer.Science. 2002; 296: 1046-1049Google Scholar and 44.Schmeichel K.L. Weaver V.M. Bissell M.J. Structural cues from the tissue microenvironment are essential determinants of the human mammary epithelial cell phenotype.J. Mammary Gland Biol. Neoplasia. 1998; 3: 201-213Google Scholar and references therein) and in modulating tumor behavior (3.Coussens L.M. Werb Z. Matrix metalloproteinases and the development of cancer.Chem. Biol. 1996; 3: 895-904Google Scholar, 45.Hansen R.K. Bissell M.J. Tissue architecture and breast cancer: the role of extracellular matrix and steroid hormones.Endocr. Relat. Cancer. 2000; 7: 95-113Google Scholar, 46.Park C.C. Bissell M.J. Barcellos-Hoff M.H. The influence of the microenvironment on the malignant phenotype.Mol. Med. Today. 2000; 6: 324-329Google Scholar, 47.Matrisian L.M. Cunha G.R. Mohla S. Epithelial-stromal interactions and tumor progression: meeting summary and future directions.Cancer Res. 2001; 6: 3844-3846Google Scholar) prompted us to carry out a detailed proteomic analysis of fresh fat tissue and its interstitial fluid in an attempt to identify protein components and excreted factors that may shed some light on the close association between mammary epithelia and fat tissue. In the first instance and to simplify the study, we chose to analyze fat tissue located topologically distant from the tumor in high risk breast cancer patients registered at the Department of Breast and Endocrine Surgery, Copenhagen University Hospital. Fat tissue biopsies from sites topologically distant from the tumor (more than 4–5 cm away; Fig. 2A) of high risk patients 1The criteria for high risk cancer applied by Danish Cooperative Breast Cancer Group are age below 35 years old, and/or tumor diameter of more than 20 mm, and/or histological malignancy grade 2 or 3, and/or negative estrogen and progesterone receptor status, and/or positive axillary status. Patients received no treatment prior to surgery. that underwent mastectomy were collected from the Pathology Department at the Copenhagen University Hospital 30–45 min after surgery. Samples for gel analysis were placed in liquid nitrogen and were rapidly transported to the Institute of Cancer Biology where they were stored at −80 °C. Samples for fluid recovery were placed in PBS, transported on ice, and processed immediately upon arrival at the Institute. On average, a total of 45 min to 1 h elapsed between surgical sample acquisition and sample preparation. The project was approved by the Scientific and Ethical Committee of the Copenhagen and Frederiksberg Municipalities (KF 01-069/03). About 0.50 g of clean fresh fat tissue was cut to small pieces (3 mm3), dipped into 5 ml of PBS, and placed in a 10-ml conical plastic tube containing 1.0 ml of PBS. Samples were incubated for 1 h at 37 °C in a humidified CO2 incubator. Thereafter the samples were centrifuged at 1000 rpm for 2 min, and the supernatant was aspirated with the aid of an elongated Pasteur pipette. Samples were further centrifuged at 5000 rpm for 20 min in a refrigerated centrifuge (4 °C). A fraction of the fat interstitial fluid (FIF) 2The abbreviations used are: FIF, fat interstitial fluid; 2D, two-dimensional; A-FABP, adipocyte fatty acid-binding protein; TIF, tumor interstitial fluid; IL, interleukin; TGF, transforming growth factor; TNF, tumor necrosis factor; IGF, insulin-like growth factor; CSF, colony-stimulating factor; TIMP, tissue inhibitor of metalloproteinases; MAPK, mitogen-activated protein kinase; MDM2, mouse double minute 2; ER, estrogen receptor; ERK, extracellular signal-regulated kinase; CBP, cAMP-response element-binding protein (CREB)-binding protein; JNK, c-Jun NH2-terminal kinase; MEK, mitogen-activated protein kinase/extracellular signal-regulated kinase kinase. (0.8 ml) was kept at −20 °C for antibody array-based analysis, while the rest was freeze-dried and resuspended in 0.5 ml of O'Farrell lysis solution and kept at −20 °C until use (48.O’Farrell P.H. High resolution two-dimensional electrophoresis of proteins.J. Biol. Chem. 1975; 250: 4007-4021Google Scholar). Twenty to thirty 6-μm cryostat sections of frozen fat tissue were resuspended in 0.1 ml of CBL1 lysis solution (Zeptosens AG, Witterswil, Switzerland) and were kept at −20 °C until use. In a few cases the sections were resuspended in 0.1 ml of O'Farrell lysis solution (48.O’Farrell P.H. High resolution two-dimensional electrophoresis of proteins.J. Biol. Chem. 1975; 250: 4007-4021Google Scholar) with similar results. The advantages of the CBL1 lysis solution are that it yields better focused spots, and it does not dry so easily after prolonged storage. A detailed protocol of its use in the study of tumor tissue biopsies and cell lines will be the subject of a further publication. 3P. Gromov, I. Gromova, and J. E. Celis, unpublished data. Fat lysates and freeze-dried fluids resuspended in lysis solution were subjected to both IEF and NEPHGE two-dimensional (2D) PAGE as described previously (49.Celis J.E. Trentem⊘lle S. Gromov P. Celis J.E. Carter N. Hunter T. Shotton D. Simons K. Small J.V. Cell Biology. A Laboratory Handbook. 4. Academic Press, San Diego2005Google Scholar). Between 30 and 40 μl of sample were applied to the first dimension. Proteins were visualized using a silver staining procedure compatible with mass spectrometry analysis (50.Gromova I. Celis J.E. Celis J.E. Carter N. Hunter T. Shotton D. Simons K. Small J.V. Cell Biology. A Laboratory Handbook. 4. Academic Press, San Diego2005Google Scholar). Gels were dried between two pieces of cellophane. Western immunoblotting was performed as described previously (51.Celis J.E. Gromov P. High-resolution two-dimensional gel electrophoresis and protein identification using western blotting and ECL detection.EXS. 2000; 88: 55-67Google Scholar). Protein bands were excised from the dry gels followed by rehydration in water for 30 min at room temperature. The gel pieces were detached from the cellophane film, rinsed twice with water, and cut into about 1-mm2 pieces with subsequent additional washes. Proteins were “in-gel” digested with bovine trypsin (unmodified, sequencing grade; Roche Diagnostics) for 8 h as described by Shevchenko and colleagues (52.Shevchenko A. Wilm M. Vorm O. Mann M. Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels.Anal. Chem. 1996; 68: 850-858Google Scholar). The reaction was stopped by adding TFA (up to 0.4%) followed by shaking for 20 min at room temperature to increase peptide recovery. In most cases, peptides were analyzed using the supernatant. In the few cases where the amount of peptides was too low or when no conclusive identification was achieved by peptide fingerprinting using the supernatant, the remaining amount of supernatant (approximately 10 μl) as well as the peptides additionally extracted from the gel pieces with 1% TFA and 50% ACN were concentrated on micro-ZipTip μ-C18 columns in accordance with the manufacturer's protocol (Millipore). Peptides were eluted from the column with 50% ACN, 0.2% TFA directly on the target and co-crystallized with α-cyano matrix (2 mg/ml cyano-4-hydroxycinnamic acid in 0.5% TFA/ACN, 1:2, v/v). The extraction procedure strongly increased the amount of peptides, thus allowing direct sequence analysis of low intensity peptides. Samples were prepared for analysis by applying 0.8 μl of digested supernatant or microcolumn-eluted material on the surface of a 400/384 AnchorChip target (Bruker Daltonik, GmbH) followed by co-crystallization with 0.3 μl of α-cyano matrix. After drying, the droplets were washed twice with 0.5% TFA to remove contamination from the samples. Mass spectrometry was performed using a Reflex IV MALDI-TOF mass spectrometer equipped with a Scout 384 ion source. All spectra were obtained in positive reflector mode with delayed extraction using an accelerating voltage of 28 kV. Each spectrum represented an average of 100–200 laser shots, depending on the signal-to-noise ratio. The resulting mass spectra were internally calibrated by using the autodigested tryptic mass values (805.417/906.505/1153.574/1433.721/2163.057/2273.160) visible in all spectra. Calibrated spectra were processed by the Xmass 5.1.1 and BioTools 2.1 software packages (Bruker Daltonik, GmbH). All spectra were analyzed manually. Spectra originating from parallel protein digestions were compared pairwise to discard common peaks derived either from trypsin autodigestion or from contamination with keratins. Only unique peptides present in the spectra were used in the first search. Data base searching was performed against a comprehensive non-redundant data base using MASCOT 1.8 software (53.Perkins D.N. Pappin D.J. Creasy D.M. Cottrell J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data.Electrophoresis. 1999; 20: 3551-3567Google Scholar) without restriction on the protein molecular mass and taxonomy. Since proteins were recovered from gels, a number of fixed modifications (acrylamide-modified cysteine, i.e. propionamide/carbamidomethylation) as well as variable ones (methionine oxidation and protein NH2 terminus acetylation) were included in the search parameters. The peptide tolerance did not exceed 50 ppm, and as a maximum only one trypsin missed cleavage was allowed. The protein identifications were considered to be confident when the protein score of the hit exceeded the threshold significance score of 70 (p < 0.05) and not less than six peptides were recognized. The data base was checked for redundancy, and whenever it was possible the Swiss-Prot accession numbers were assigned. Additionally peptide mass fingerprinting analysis was performed using the MS-Fit program (Protein Prospector, University of California San Francisco Mass Spectrometry Facility, London, UK). We also used the Find-Mod software (Protein Prospector, University of California San Francisco Mass Spectrometry Facility, London, UK) to check any unmatched peptides for potential protein post-translational modifications. The second search was performed for all identifications as follows. 1) The predicted peptide digest was compared with the experimental one to reveal additional peptides present within the spectra; 2) the unmatched molecular weight values from the initial search" @default.
• W2147027178 created "2016-06-24" @default.
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• W2147027178 date "2005-04-01" @default.
• W2147027178 modified "2023-10-11" @default.
• W2147027178 title "Identification of Extracellular and Intracellular Signaling Components of the Mammary Adipose Tissue and Its Interstitial Fluid in High Risk Breast Cancer Patients" @default.
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