S have identified different prognostic and predictor genes which can distinguish early from late relapse or disease progression. However, transcription of a target gene in the tumor may not be a good predictor of drug resistance and prognosis for ovarian cancer. For example, mRNA abundance may not correlate with the corresponding protein expression and function. Furthermore, for some primary or recurrent ovarian cancer patients, tissue samples are not always available for gene profiling. Unlike with other pelvic/abdominal malignant metastasis, massive ascites are a Hical representation of the model for assessment of gene differential behaviour distinctive clinical manifestation in advanced EOC, with more than 80 of these patients having widespread metastasis to the serosal surfaces and 23727046 associated peritoneal and/or pleural effusions [5]. Body fluids have been shown to be excellent media for biomarker discovery in cancer, and ascites fluid contains malignant epithelial cells and activated mesothelial cells, which can produce cytokines, growth factors and invasion-promoting components associated with invasion and metastasis [6]. This fluid therefore contains the secretome of ovarian cancer cells and reflects other microenvironmental factors of the malignancy. Thus, applying the ever advancing technique of proteomics to the analysis of ascites may facilitate discovery of novel biomarkers that are more Title Loaded From File sensitive and specific than those currently available. The aim of our study was to screen and identify distinctive biomarkers in ascites of ovarian cancer associated with intrinsic chemoresistance by two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE) technology, which would help identify these patients with poor prognosis and improve their clinical outcome with alternative therapies.three times in ice-cold Tris-buffered sucrose solution (10 mM Tris, 250 mM sucrose, pH 7.0) and then scraped and lysed in ice-cold lysis buffer (30 mM Tris-HCl, 7 M urea, 2 M thiourea, 4 w/v CHAPS, pH 8.5). Ascites samples were processed using the ProteoPrep Blue Albumin Depletion Kit (Sigma, St. Louis, MO, USA) that selectively removes albumin and IgG according to the manufacturer’s instructions. To purify the protein extraction and determine the final protein concentration, the 2-D Clean-up Kit (GE Healthcare, Buckinghamshire, UK) and 2-D Quant Kit 1317923 (GE Healthcare) were used sequentially.Study Design and Protein Sample Labeling with CyDyeTwelve chemosensitve samples were divided equally into two subgroups with six samples each, and seven chemoresistance samples were likewise allocated into two subgroups with four or three samples each. Equal amounts of the protein samples in the same subgroup were mixed and separated into four equal aliquots (50 mg each). Two of the chemosensitive protein sample aliquots were labeled with Cy3, and two of the chemoresistant sample aliquots were labeled with Cy5. The remaining two chemosensitive samples were then labeled with Cy5 and the other two chemoresistant samples with Cy3. A sample consisting of equal amounts of all samples was used as the pooled internal standard (50 mg) and labeled with 200 pmol of Cy2. Therefore, one chemosensitive patient pool (Cy3 or Cy5), one chemoresistant patient pool (Cy5 or Cy3) and one internal standard (Cy2) were run in each gel, with four gels in total based on our design. This dye swapping strategy was adopted to avoid dye bias and allowed for equal distribution of Cy dyes in both patient groups. Protein labeling was conducted with CyDye DIGE Fluors.S have identified different prognostic and predictor genes which can distinguish early from late relapse or disease progression. However, transcription of a target gene in the tumor may not be a good predictor of drug resistance and prognosis for ovarian cancer. For example, mRNA abundance may not correlate with the corresponding protein expression and function. Furthermore, for some primary or recurrent ovarian cancer patients, tissue samples are not always available for gene profiling. Unlike with other pelvic/abdominal malignant metastasis, massive ascites are a distinctive clinical manifestation in advanced EOC, with more than 80 of these patients having widespread metastasis to the serosal surfaces and 23727046 associated peritoneal and/or pleural effusions [5]. Body fluids have been shown to be excellent media for biomarker discovery in cancer, and ascites fluid contains malignant epithelial cells and activated mesothelial cells, which can produce cytokines, growth factors and invasion-promoting components associated with invasion and metastasis [6]. This fluid therefore contains the secretome of ovarian cancer cells and reflects other microenvironmental factors of the malignancy. Thus, applying the ever advancing technique of proteomics to the analysis of ascites may facilitate discovery of novel biomarkers that are more sensitive and specific than those currently available. The aim of our study was to screen and identify distinctive biomarkers in ascites of ovarian cancer associated with intrinsic chemoresistance by two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE) technology, which would help identify these patients with poor prognosis and improve their clinical outcome with alternative therapies.three times in ice-cold Tris-buffered sucrose solution (10 mM Tris, 250 mM sucrose, pH 7.0) and then scraped and lysed in ice-cold lysis buffer (30 mM Tris-HCl, 7 M urea, 2 M thiourea, 4 w/v CHAPS, pH 8.5). Ascites samples were processed using the ProteoPrep Blue Albumin Depletion Kit (Sigma, St. Louis, MO, USA) that selectively removes albumin and IgG according to the manufacturer’s instructions. To purify the protein extraction and determine the final protein concentration, the 2-D Clean-up Kit (GE Healthcare, Buckinghamshire, UK) and 2-D Quant Kit 1317923 (GE Healthcare) were used sequentially.Study Design and Protein Sample Labeling with CyDyeTwelve chemosensitve samples were divided equally into two subgroups with six samples each, and seven chemoresistance samples were likewise allocated into two subgroups with four or three samples each. Equal amounts of the protein samples in the same subgroup were mixed and separated into four equal aliquots (50 mg each). Two of the chemosensitive protein sample aliquots were labeled with Cy3, and two of the chemoresistant sample aliquots were labeled with Cy5. The remaining two chemosensitive samples were then labeled with Cy5 and the other two chemoresistant samples with Cy3. A sample consisting of equal amounts of all samples was used as the pooled internal standard (50 mg) and labeled with 200 pmol of Cy2. Therefore, one chemosensitive patient pool (Cy3 or Cy5), one chemoresistant patient pool (Cy5 or Cy3) and one internal standard (Cy2) were run in each gel, with four gels in total based on our design. This dye swapping strategy was adopted to avoid dye bias and allowed for equal distribution of Cy dyes in both patient groups. Protein labeling was conducted with CyDye DIGE Fluors.