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Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) infection is one of the most life-threatening human cancers in China. However, the pathogenesis of HCC development is still unclear. Here, we systemically analyzed liver tissues from different stages of HCC patients through 8-plex Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) approach. A total of 4,620 proteins were identified and 3,781 proteins were quantified. When T1, T2 and T3 tumor tissues were compared with T1 non-tumor cells, 330, 365 and 387 differentially expressed proteins were identified respectively. IPA (Ingenuity Pathway Analysis) analysis revealed that these differentially expressed proteins were involved in endothelial cancer, cell spreading, cell adhesion and cell movement of tumor cell lines pathway and so on. Further study showed that the filamin C (FLNC) protein was significantly overexpressed with the development of HCC, which might play an important role in HCC invasion and metastasis. These results were also confirmed with western blot (WB). The mRNA levels were significantly increased in 50 pairs of tumor and adjacent non-tumor tissues from TCGA database. The higher expression of FLNC in HCC might be a common phenomenon, thereby shedding new light on molecular mechanism and biomarker for the diagnosis purpose of HCC development.

SUBMITTER: Qi Y

PROVIDER: S-EPMC5354476 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma.

Qi Yingzi Y Xu Feng F Chen Lingsheng L Li Yanchang Y Xu Zhongwei Z Zhang Yao Y Wei Wei W Su Na N Zhang Tao T Fan Fengxu F Wang Xing X Qin Xue X Zhang Lingqiang L Liu Yinkun Y Xu Ping P

Oncotarget 20161001 42

Hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) infection is one of the most life-threatening human cancers in China. However, the pathogenesis of HCC development is still unclear. Here, we systemically analyzed liver tissues from different stages of HCC patients through 8-plex Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) approach. A total of 4,620 proteins were identified and 3,781 proteins were quantified. When T1, T2 and T3 tumor tissues were compared with T1 ...[more]

PMID: 27626164

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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:Prostate cancer is the most common malignancy and the second leading cause of cancer-related deaths in men. One common treatment is androgen-deprivation therapy, which reduces symptoms in most patients. However, over time, patients develop tumors that are androgen-independent and ultimately fatal. The mechanisms that cause this transition remain largely unknown, and as a result, there are no effective treatments against androgen-independent prostate cancer. As a model platform, we used the LNCaP cell line and its androgen-independent derivative, LNCaP-SF. Utilizing stable isotope labeling with amino acids in cell culture coupled to mass spectrometry, we assessed the differential global protein expression of the two cell lines. Our proteomic analysis resulted in the quantification of 3355 proteins. Bioinformatic prioritization resulted in 42 up-regulated and 46 down-regulated proteins in LNCaP-SF cells relative to LNCaP cells. Our top candidate, HMGCS2, an enzyme involved in ketogenesis, was found to be 9-fold elevated in LNCaP-SF cells, based on peptide ratios. After analyzing the remaining enzymes of this pathway (ACAT1, BDH1, HMGCL, and OXCT1), we observed increased expression of these proteins in the LNCaP-SF cells, which was further verified using Western blotting. To determine whether these enzymes were up-regulated in clinical samples, we performed quantitative PCR and immunohistochemistry on human prostate cancer tissues, from which we observed significantly increased transcript and protein levels in high-grade cancer (Gleason grade ? 8). In addition, we observed significant elevation of these enzymes in the LuCaP 96AI castration-resistant xenograft. Further assessment of ACAT1 on human castration-resistant metastatic prostate cancer tissues revealed substantially elevated expression of ACAT1 in these specimens. Taken together, our results indicate that enzymes of the ketogenic pathway are up-regulated in high-grade prostate cancer and could serve as potential tissue biomarkers for the diagnosis or prognosis of high-grade disease.

Project description:BackgroundHint1 is a novel tumor suppressor gene, and inactivation of its expression is closely associated with the carcinogenesis of a variety of malignancies. The effects of Hint1 deficiency on the competing endogenous RNA (ceRNA) regulatory network in the context of HCC remains to be fully characterized. This study aims to explore Hint1-related hub lncRNAs in HCC and to establish a reliable prognostic model for HCC patients based on these hub lncRNAs.MethodslncRNA + mRNA microarray was used to identify differentially expressed (DE) lncRNAs and mRNAs in Huh7 cells before and after Hint1 knockdown. A Hint1-related ceRNA network was mapped by bioinformation technology. The DEmRNAs in the network were analyzed via GO and KEGG enrichment analyses. Hub DElncRNAs associated with HCC patient prognosis were then detected through univariate and multivariate Cox regression analyses and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, and nomograms. We also utilized Kaplan-Meier curves to validate the relationship between hub lncRNAs and the overall survival (OS) of HCC patients. Finally, A Hint1-related core ceRNA network based on the hub DElncRNAs and DEmRNAs was mapped.ResultsWe identified 417 differentially expressed DElncRNAs and 2096 DEmRNAs in Huh7 cells before and after Hint1 knockdown. Three hub DElncRNAs (LINC00324, SNHG3, and DIO3OS) in the Hint1-associated ceRNA network were screened out using univariate and multivariate Cox regression analyses. A hepatocellular carcinoma (HCC) prognostic risk-scoring model and nomogram were constructed using these three hub lncRNAs, and it was confirmed that the risk score of the model could be used as an independent predictor of HCC prognosis. A Hint1-related core ceRNA network based on the hub DElncRNAs and DEmRNAs was also mapped.ConclusionWe constructed a reliable prognostic model for HCC patients based on three Hint1-related hub lncRNAs, and we believe these three hub lncRNAs may play critical roles in hepatocarcinogenesis, and progression.

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Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma.

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Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma.

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