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Dataset for the Quantitative Proteomics Analysis of the Primary Hepatocellular Carcinoma with Single and Multiple Lesions

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Dataset for the Quantitative Proteomics Analysis of the Primary Hepatocellular Carcinoma with Single and Multiple Lesions Data in Brief 5 (2015) 226–240 Contents lists available at ScienceDirect Data in Brief journal homepage: www.elsevier.com/locate/dib Data Article Dataset for the quantitative proteomics analysis of the primary hepatocellular carcinoma with single and multiple lesions Xiaohua Xing a,b, Yao Huang c, Sen Wang a,b, Minhui Chi a,b,c, Yongyi Zeng a,b,c, Lihong Chen a,b,c, Ling Li a,b,c, Jinhua Zeng a,b,c, Minjie Lin a,b, Xiao Han d, Jingfeng Liu a,b,c, Xiaolong Liu a,b,n a The Liver Center of Fujian Province, Fujian Medical University, Fuzhou 350025, People’s Republic of China b The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, People’s Republic of China c Liver Disease Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350007, People’s Republic of China d Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, People’s Republic of China article info abstract Article history: Hepatocellular Carcinoma (HCC) is one of the most common malig- Received 18 August 2015 nant tumor, which is causing the second leading cancer-related death Received in revised form worldwide. The tumor tissues and the adjacent noncancerous tissues 27 August 2015 obtained from HCC patients with single and multiple lesions were Accepted 28 August 2015 quantified using iTRAQ. A total of 5513 proteins (FDR of 1%) were Available online 8 September 2015 identified which correspond to roughly 27% of the total liver proteome. And 107 and 330 proteins were dysregulated in HCC tissue with multiple lesions (MC group) and HCC tissue with a single lesion (SC group), compared with their noncancerous tissue (MN and SN group) respectively. Bioinformatics analysis (GO, KEGG and IPA) allowed these data to be organized into distinct categories. The data accompanying the manuscript on this approach (Xing et al., J. Proteomics (2015), http://dx.doi.org/10.1016/j.jprot.2015.08.007 [1]) have been deposited to the iProX with identifier IPX00037601. & 2015 The Authors. Published by Elsevier Inc. This is an open access articleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/). DOI of original article: http://dx.doi.org/10.1016/j.jprot.2015.08.007 n Correspondence to: The Liver Center of Fujian Province, Fujian Medical University, Fuzhou 350025, People’s Republic of China. E-mail address: [email protected] (X. Liu). http://dx.doi.org/10.1016/j.dib.2015.08.036 2352-3409/& 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). X. Xing et al. / Data in Brief 5 (2015) 226–240 227 Specifications table Subject area Biology More specific sub- Proteomics on the Hepatocellular Carcinoma ject area Type of data List of identified proteins as tables (.xls), raw data in website How data was The data was acquired by Liquid chromatography mass spectrometry in acquired tandem (LC–MS/MS).The samples were separated by a Acquity UPLC system (Waters Corporation, Milford, MA) and detected by a Nano-Aquity UPLC system (Waters Corporation, Milford, MA) connected to a quadrupole- Orbitrap mass spectrometer (Q-Exactive) (Thermo Fisher Scientific, Bremen, Germany). Data format Filtered and analyzed Experimental Non-applied factors Experimental Proteins were extracted from tumor tissues of HCC patients with single and features multiple lesions, iTRAQ labeled and then prepared for liquid chromatography-mass spectrometry (LC–MS/MS) analysis. Data source Fuzhou, China, Mengchao Hepatobiliary Hospital of Fujian Medical location University Data accessibility Filtered and analyzed data are supplied here and raw data have also been deposited to the integrated Proteome resources (iProX) with identifier IPX00037601 (http://www.iprox.org/index). Fig. 1. The qualities of the proteome dataset. (A) Frequency distribution of the identified proteins with Z1 unique peptides. (B) Molecular weight distribution of identified proteins proved that there is no bias in the protein extraction process. (C) Isoelectric point distribution of the identified proteins to show the unbias of the protein extraction. (D) Protein hydro- phobicity distribution of the identified proteins. 228 X. Xing et al. / Data in Brief 5 (2015) 226–240 Value of the data The proteome of hepatocellular carcinoma with single and multiple lesions analyzed using iTRAQ technology. A total of 5513 proteins (FDR of 1%) were identified which correspond to roughly 27% of the total liver proteome. The in-depth proteomics analysis of the HCC tumor tissues with a single and multiple lesions might be useful for further study of the mechanisms. Fig. 2. The iTRAQ ratio distribution and involved biological processes of the differentially expressed proteins in the HCC with single and multiple lesions. (A) Volcano plot represented the protein abundance changes in the HCC cancerous tissue with multiple lesions comparing to their adjacent noncancerous tissues. A total of 107 dysregulated proteins with fold change Z1.5 and p values o0.05 were identified. (B) Volcano plot represented the protein abundance changes in the HCC cancerous tissues with a single lesion comparing to their adjacent noncancerous tissue. A total of 330 dysregulated proteins with fold change Z1.5 and p values o0.05 were identified. (C) Venn diagrams showed the overlaps and number of differentially expressed proteins in the HCC with single and multiple lesions. (D) GO analysis of the involved biological processes of the common dysregulated proteins in both types of the HCC. All of the biological processes were ranked in term of enrichment of the differentially expressed proteins, and the top 10 are presented here. X. Xing et al. / Data in Brief 5 (2015) 226–240 229 Table 1 Basic information and characteristics of the HCC patients with a single or multiple observed lesions, who were enrolled in this dataset. HCC with multiple HCC with a single lesions lesion Gender Male 30 30 Female 0 0 Age (years) r55 17 17 455 13 13 AFP (ng/ml) r400 12 20 4400 18 10 Tumor size (cm) r596 5–10 21 24 Progression of cirrhosis None 3 5 Mild 13 12 Moderate 13 12 Severe 1 1 Tumor boundaries Distinct 18 22 Indistinct 12 8 Differentiation degree I–II 8 4 II–III 17 22 III–IV 5 4 Vascular tumor thrombosis No 26 25 Yes 4 5 Tumor encapsulation No 2 6 Incomplete 14 10 Complete 14 14 1. Data, experimental design, materials and methods 1.1. Data and experimental design The data show the lists of proteins identified and quantified in the HCC tumor tissues with single and multiple lesions. The tissues were divided into 4 groups: cancerous tissues from HCC patients with multiple observed lesions (MC group, n¼30); surrounding noncancerous tissues from HCC patients with multiple observed lesions (MN group, n¼30); cancerous tissues from primary HCC patients with a single observed lesion (SC group, n¼30); surrounding noncancerous tissues from primary HCC patients with a single observed lesion (SN group, n¼30). The detailed characteristics of the selected HCC patients were listed in Table 1. For each group, every 5 individual samples with equal tissue weight were mixed, and then the proteins were extracted from the mixed samples. And then the samples were labeled with the iTRAQ 230 X. Xing et al. / Data in Brief 5 (2015) 226–240 Fig. 3. The hierarchical clustering and involved biological processes analysis of differentially expressed proteins in the primary HCC with single and multiple lesions. (A) Hierarchical clustering of the 107 dysregulated proteins in the HCC with multiple lesions (MC vs. MN). (B) Hierarchical clustering of the 330 dysregulated proteins in the HCC with a single lesion (SC vs. SN). (C, D) GO analysis of the dysregulated proteins involved biological processes in the HCC with multiple lesions (C) and in the HCC with a single lesion (D). 8-plex reagent as follows: four groups (MC group, MN group, SC group and SN group) were labeled with 113, 114, 115 and 116 isobaric tag, respectively; and the peptides from the biological repetitions of the above 4 groups were labeled with 117, 118, 119 and 121, respectively. The iTRAQ 8-plex labeling was independently repeated 3 times, defining as A, B and C. So we have 6 repeated protein extracts for each group to minimize the individual differences of the patients. 1.2. Materials and methods Tissue samples, including the cancerous and surrounding noncancerous tissues, were obtained from 30 primary HCC patients with multiple observed lesions and 30 primary HCC patients with a single observed lesion, respectively. All patients have undergone radical surgery at Mengchao Hepatobiliary Hospital of Fujian Medical University from August 2010 to January 2013. The protein from these two type HCC tissues was determined by BCA assay (TransGen Biotech, Beijing, China) following the manufacture’sprotocol. Afterwards, 100 μg proteins per condition were treated with DTT (8 mM) and iodoacetamide (50 mM) for reduction and alkylation. Afterwards, the proteins were typically digested by sequence-grade modified trypsin (Promega, Madison, WI), and then the resultant peptides mixture was further labeled using che- micals from the iTRAQ reagent kit (AB SCIEX, USA). The peptide mixture was fractionated by high pH separation using a Acquity UPLC system (Waters Corporation, Milford, MA) connected to a reverse phase column (BEH C18, 1.7 mm, 2.1 Â 50 mm2,Waters Corporation, Milford, MA). High pH separation was performed using a linear gradient starting from 5% B to 35% B in 20 min (solution B: 20 mM ammonium formate in 90% ACN, the pH was adjusted to 10.0 with ammonium hydroxide). The column flow rate was maintained at 600 μl/min and column temperature was X.
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