Dataset Information

Dataset for the quantitative proteomics analysis of the primary hepatocellular carcinoma with single and multiple lesions.

ABSTRACT: Hepatocellular Carcinoma (HCC) is one of the most common malignant tumor, which is causing the second leading cancer-related death worldwide. The tumor tissues and the adjacent noncancerous tissues obtained from HCC patients with single and multiple lesions were quantified using iTRAQ. A total of 5513 proteins (FDR of 1%) were 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.

SUBMITTER: Xing X

PROVIDER: S-EPMC4589833 | biostudies-other | 2015 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Dataset for the quantitative proteomics analysis of the primary hepatocellular carcinoma with single and multiple lesions.

Xing Xiaohua X Huang Yao Y Wang Sen S Chi Minhui M Zeng Yongyi Y Chen Lihong L Li Ling L Zeng Jinhua J Lin Minjie M Han Xiao X Liu Jingfeng J Liu Xiaolong X

Data in brief 20150908

Hepatocellular Carcinoma (HCC) is one of the most common malignant tumor, which is causing the second leading cancer-related death worldwide. The tumor tissues and the adjacent noncancerous tissues obtained from HCC patients with single and multiple lesions were quantified using iTRAQ. A total of 5513 proteins (FDR of 1%) were 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 t ...[more]

PMID: 26543886

Similar Datasets

Project description:Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC.Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis.Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages.The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance.

Project description:Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide with poor prognosis due to resistance to conventional chemotherapy and limited efficacy of radiotherapy. There is an urgent need to develop novel biomarkers for early diagnosis, as well as to identify new drug targets for therapeutic interventions.54 paired HCC samples and 21 normal liver tissues were obtained from West China Hospital of Sichuan University. Informed consent was obtained from all the patients or their relatives prior to analysis, and the project was approved by the Institutional Ethics Committee of Sichuan University. Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC)-based proteomics was employed to profile the differentially expressed proteins between a HepG2 human hepatoma cell line and an immortal hepatic cell line L02. Validation of PGAM1 expression was performed by semi-quantitative RT-PCR, immunoblot and immunohistochemistry using clinical samples. shRNA expressing plasmids specifically targeting PGAM1 were designed and constructed by GenePharma Corporation (Shanghai, China), and were utilized to silence expression of PGAM1 in vitro and in vivo. Cell proliferation was measured by a combination of colony formation assay and Ki67 staining. Apoptosis was examined by flow cytometry and TUNEL assay.A total of 63 dysregulated proteins were identified, including 51 up-regulated proteins, and 12 down-regulated proteins (over 2-fold, p < 0.01). Phosphoglycerate mutase 1 (PGAM1) was found markedly upregulated. Clinico-pathological analysis indicated that overexpression of PGAM1 was associated with 66.7% HCC, and strongly correlated with poor differentiation and decreased survival rates (p < 0.01). shRNAs-mediated repression of PGAM1 expression resulted in significant inhibition in liver cancer cell growth both in vitro and in vivo.Our studies suggested that PGAM1 plays an important role in hepatocarcinogenesis, and should be a potential diagnostic biomarker, as well as an attractive therapeutic target for hepatocellular carcinoma.

Dataset Information

Dataset for the quantitative proteomics analysis of the primary hepatocellular carcinoma with single and multiple lesions.

Publications

Dataset for the quantitative proteomics analysis of the primary hepatocellular carcinoma with single and multiple lesions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets