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Global proteomic profiling in multistep hepatocarcinogenesis and identification of PARP1 as a novel molecular marker in hepatocellular carcinoma.

ABSTRACT: The more accurate biomarkers have long been desired for hepatocellular carcinoma (HCC). Here, we characterized global large-scale proteomics of multistep hepatocarcinogenesis in an attempt to identify novel biomarkers for HCC. Quantitative data of 37874 sequences and 3017 proteins during hepatocarcinogenesis were obtained in cohort 1 of 75 samples (5 pooled groups: normal livers, hepatitis livers, cirrhotic livers, peritumoral livers, and HCC tissues) by iTRAQ 2D LC-MS/MS. The diagnostic performance of the top six most upregulated proteins in HCC group and HSP70 as reference were subsequently validated in cohort 2 of 114 samples (hepatocarcinogenesis from normal livers to HCC) using immunohistochemistry. Of seven candidate protein markers, PARP1, GS and NDRG1 showed the optimal diagnostic performance for HCC. PARP1, as a novel marker, showed comparable diagnostic performance to that of classic markers GS and NDRG1 in HCC (AUCs = 0.872, 0.856 and 0.792, respectively). A significant higher AUC of 0.945 was achieved when three markers combined. For diagnosis of HCC, the sensitivity and specificity were 88.2% and 81.0% when at least two of the markers were positive. Similar diagnostic values of PARP1, GS and NDRG1 were confirmed by immunohistochemistry in cohort 3 of 180 HCC patients. Further analysis indicated that PARP1 and NDRG1 were associated with some clinicopathological features, and the independent prognostic factors for HCC patients. Overall, global large-scale proteomics on spectrum of multistep hepatocarcinogenesis are obtained. PARP1 is a novel promising diagnostic/prognostic marker for HCC, and the three-marker panel (PARP1, GS and NDRG1) with excellent diagnostic performance for HCC was established.

SUBMITTER: Xu X

PROVIDER: S-EPMC4924674 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Global proteomic profiling in multistep hepatocarcinogenesis and identification of PARP1 as a novel molecular marker in hepatocellular carcinoma.

Xu Xiao X Liu Zhikun Z Wang Jianguo J Xie Haiyang H Li Jie J Cao Jili J Zhou Lin L Zheng Shusen S

Oncotarget 20160301 12

The more accurate biomarkers have long been desired for hepatocellular carcinoma (HCC). Here, we characterized global large-scale proteomics of multistep hepatocarcinogenesis in an attempt to identify novel biomarkers for HCC. Quantitative data of 37874 sequences and 3017 proteins during hepatocarcinogenesis were obtained in cohort 1 of 75 samples (5 pooled groups: normal livers, hepatitis livers, cirrhotic livers, peritumoral livers, and HCC tissues) by iTRAQ 2D LC-MS/MS. The diagnostic perform ...[more]

PMID: 26883192

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Project description:BACKGROUND:Liver cirrhosis is the most important risk factor for hepatocellular carcinoma (HCC) but the role of liver disease aetiology in cancer development remains under-explored. We investigated global gene expression profiles from HCC arising in different liver diseases to test whether HCC development is driven by expression of common or different genes, which could provide new diagnostic markers or therapeutic targets. METHODOLOGY AND PRINCIPAL FINDINGS:Global gene expression profiling was performed for 4 normal (control) livers as well as 8 background liver and 7 HCC from 3 patients with hereditary haemochromatosis (HH) undergoing surgery. In order to investigate different disease phenotypes causing HCC, the data were compared with public microarray repositories for gene expression in normal liver, hepatitis C virus (HCV) cirrhosis, HCV-related HCC (HCV-HCC), hepatitis B virus (HBV) cirrhosis and HBV-related HCC (HBV-HCC). Principal component analysis and differential gene expression analysis were carried out using R Bioconductor. Liver disease-specific and shared gene lists were created and genes identified as highly expressed in hereditary haemochromatosis HCC (HH-HCC) were validated using quantitative RT-PCR. Selected genes were investigated further using immunohistochemistry in 86 HCC arising in liver disorders with varied aetiology. Using a 2-fold cut-off, 9 genes were highly expressed in all HCC, 11 in HH-HCC, 270 in HBV-HCC and 9 in HCV-HCC. Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. Serine peptidase inhibitor, Kazal type 1 (SPINK1) mRNA was very highly expressed in HH-HCC (median fold change 2291, p?=?0.0072) and was detected by immunohistochemistry in 91% of HH-HCC, 0% of HH-related cirrhotic or dysplastic nodules and 79% of mixed-aetiology HCC. CONCLUSION:HCC, arising from diverse backgrounds, uniformly over-express a small set of genes. SPINK1, a secretory trypsin inhibitor, demonstrated potential as a diagnostic HCC marker and should be evaluated in future studies.

Project description:Objective Hepatocellular carcinoma (HCC) is one of the most common and malignant tumors with an insidious onset, difficult early diagnosis, and limited therapy options, resulting in a poor prognosis. Cell division cycle associated 2 (CDCA2), also known as Repo-Man, plays an important role in regulating mitosis and DNA repair, but the involvement of CDCA2 in HCC remains unclear. Methods The differentially expressed genes that were significantly upregulated in multiple RNA sequencing datasets of HCC were screened. Receiver operating characteristic (ROC) curve analysis was performed to identify diagnostic markers for HCC. Least absolute shrinkage and selection operator Cox regression analysis was performed to screen the prognosis-related genes. The screening and analyses identified CDCA2 as the target gene in this study. The expression of CDCA2 was analyzed in public databases and clinical specimens, and CDCA2 involvement in HCC was explored by both bioinformatic analysis and in vitro experiments. Results The level of CDCA2 was enhanced in HCC compared with healthy livers. Overexpression of CDCA2 positively correlated with the pathological grade and TNM stage of the diseases. Furthermore, CDCA2 was found to be an independent prognostic predictor. An excellent prognostic model of HCC was successfully constructed with CDCA2 in combination with TNM stage. Bioinformatic analysis revealed that CDCA2 was closely associated with the cell cycle, apoptosis, and p53 signaling pathway. Silencing CDCA2 in Huh7 cells resulted in significant upregulation of p53 and the downstream PUMA and NOXA and a subsequently increased apoptosis. Inhibition of p53 signaling and apoptosis was found after overexpression of CDCA2 in L02 cells. Strikingly, the proliferation of cells was not affected by CDCA2. Conclusions CDCA2 was a novel diagnostic marker for HCC, and overexpression of this gene reflected poor pathological grade, stage, and clinical prognosis. CDCA2 promoted the pathogenesis of HCC by suppressing the p53-PUMA/NOXA signaling and the subsequent apoptosis.

Project description:Tumor-associated (TA) autoantibodies, which are generated by the immune system upon the recognition of abnormal TA antigens, are promising biomarkers for the early detection of tumors. In order to detect autoantibody biomarkers effectively, antibody-specific epitopes in the diagnostic test should maintain the specific conformations that are as close as possible to those presenting in the body. However, when using patients' serum as a source of TA autoantibodies the characterization of the autoantibody-specific epitope is not easy due to the limited amount of patient-derived serum.To overcome these limits, we constructed a B cell hybridoma pool derived from a hepatocellular carcinoma (HCC) model HBx-transgenic mouse and characterized autoantibodies derived from them as tumor biomarkers. Their target antigens were identified by mass spectrometry and the correlations with HCC were examined. With the assumption that TA autoantibodies generated in the tumor mouse model are induced in human cancer patients, the enzyme-linked immunosorbent assays (ELISA) based on the characteristics of mouse TA autoantibodies were developed for the detection of autoantibody biomarkers in human serum. To mimic natural antigenic structures, the specific epitopes against autoantibodies were screened from the phage display cyclic random heptapeptide library, and the streptavidin antigens fused with the specific epitopes were used as coating antigens.In this study, one of HCC-associated autoantibodies derived from HBx-transgenic mouse, XC24, was characterized. Its target antigen was identified as splicing factor 3b subunit 1 (SF3B1) and the high expression of SF3B1 was confirmed in HCC tissues. The specific peptide epitopes against XC24 were selected and, among them, XC24p11 cyclic peptide (-CDATPPRLC-) was used as an epitope of anti-SF3B1 autoantibody ELISA. With this epitope, we could effectively distinguish between serum samples from HCC patients (n?=?102) and healthy subjects (n?=?85) with 73.53% sensitivity and 91.76% specificity (AUC?=?0.8731). Moreover, the simultaneous detection of anti-XC24p11 epitope autoantibody and AFP enhanced the efficiency of HCC diagnosis with 87.25% sensitivity and 90.59% specificity (AUC?=?0.9081).ELISA using XC24p11 peptide epitope that reacts against anti-SF3B1 autoantibody can be used as a novel test to enhance the diagnostic efficiency of HCC.

Dataset Information

Global proteomic profiling in multistep hepatocarcinogenesis and identification of PARP1 as a novel molecular marker in hepatocellular carcinoma.

Publications

Global proteomic profiling in multistep hepatocarcinogenesis and identification of PARP1 as a novel molecular marker in hepatocellular carcinoma.

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