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Soluble MICA and a MICA variation as possible prognostic biomarkers for HBV-induced hepatocellular carcinoma.

ABSTRACT: MHC class I polypeptide-related chain A (MICA) molecule is induced in response to viral infection and various types of stress. We recently reported that a single nucleotide polymorphism (SNP) rs2596542 located in the MICA promoter region was significantly associated with the risk for hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) and also with serum levels of soluble MICA (sMICA). In this study, we focused on the possible involvement of MICA in liver carcinogenesis related to hepatitis B virus (HBV) infection and examined correlation between the MICA polymorphism and the serum sMICA levels in HBV-induced HCC patients. The genetic association analysis revealed a nominal association with an SNP rs2596542; a G allele was considered to increase the risk of HBV-induced HCC (P?=?0.029 with odds ratio of 1.19). We also found a significant elevation of sMICA in HBV-induced HCC cases. Moreover, a G allele of SNP rs2596542 was significantly associated with increased sMICA levels (P?=?0.009). Interestingly, HCC patients with the high serum level of sMICA (>5 pg/ml) exhibited poorer prognosis than those with the low serum level of sMICA (?5 pg/ml) (P?=?0.008). Thus, our results highlight the importance of MICA genetic variations and the significance of sMICA as a predictive biomarker for HBV-induced HCC.

SUBMITTER: Kumar V

PROVIDER: S-EPMC3443094 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Soluble MICA and a MICA variation as possible prognostic biomarkers for HBV-induced hepatocellular carcinoma.

Kumar Vinod V Yi Lo Paulisally Hau PH Sawai Hiromi H Kato Naoya N Takahashi Atsushi A Deng Zhenzhong Z Urabe Yuji Y Mbarek Hamdi H Tokunaga Katsushi K Tanaka Yasuhito Y Sugiyama Masaya M Mizokami Masashi M Muroyama Ryosuke R Tateishi Ryosuke R Omata Masao M Koike Kazuhiko K Tanikawa Chizu C Kamatani Naoyuki N Kubo Michiaki M Nakamura Yusuke Y Matsuda Koichi K

PloS one 20120914 9

MHC class I polypeptide-related chain A (MICA) molecule is induced in response to viral infection and various types of stress. We recently reported that a single nucleotide polymorphism (SNP) rs2596542 located in the MICA promoter region was significantly associated with the risk for hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) and also with serum levels of soluble MICA (sMICA). In this study, we focused on the possible involvement of MICA in liver carcinogenesis related to hep ...[more]

PMID: 23024757

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Project description:MicroRNAs (miRNAs) exhibit essential regulatory functions related to cell growth, apoptosis, development and differentiation. Dysregulated expression of miRNAs is associated with a wide variety of human diseases. As such miRNA signatures are valuable as biomarkers for disease and for making treatment decisions. Hepatitis B virus (HBV) is a major risk factor for hepatocellular carcinoma (HCC). Here we screened for miRNAs in chronic HBV associated HCC.To determine the miRNAs in HCC occurrence associated with HBV infection, we analyzed global miRNA expression profiles in 12 pairs of HCC and adjacent matched non-HCC tissues from HBV-positive and HBV-negative patients using microarray analyses. The microarray result was validated by real-time PCR in 32 HBV-positive and 24 HBV-negative patient HCC samples. The potential candidate target genes of the miRNAs were predicted by miRWalk software. Genes simultaneously predicted as targets by two or more miRNAs were subjected to GO and KEGG pathway analysis. The miRNA regulatory network analysis was performed using the Ingenuity Pathway Analysis (IPA) software.Eight miRNAs (miR-223, miR-98, miR-15b, miR-199a-5p, miR-19b, miR-22, miR-451, and miR-101) were involved in HBV-unrelated HCC, 5 miRNAs (miR-98, miR-375, miR-335, miR-199a-5p, and miR-22) were involved in HBV infection, and 7 miRNAs (miR-150, miR-342-3p, miR-663, miR-20b, miR-92a-3p, miR-376c-3p and miR-92b) were specifically altered in HBV-related HCC. Gene Ontology and KEGG analyses predict that these HBV-related HCC miRNAs are involved in the regulation of: transcription, RNA polymerase II promoter, phosphorylation of proteins through MAPK signaling pathway, focal adhesion, and actin cytoskeleton. IPA analysis also suggest that these miRNAs act on AGO2, TP53, CCND1, and 11 other genes that significantly influence HCC occurrence and HBV infection.Our data indicates that the unique 7 miRNAs expression signature could be involved in the development HBV- related HCC.

Project description:Background: Hepatocellular carcinoma (HCC) is a main cause of malignancy-related death all over the world with a poor prognosis. The current research is focused on developing novel prognostic and diagnostic models of Hepatocellular carcinoma from the perspective of hepatitis B virus (HBV)-related genes, and predicting its prognostic characteristics and potential reliable biomarkers for Hepatocellular carcinoma diagnosis. Methods: As per the information related to Hepatocellular carcinoma expression profile and the clinical data in multiple public databases, we utilized limma for assessing the differentially expressed genes (DEGs) in HBV vs non- hepatitis B virus groups, and the gene set was enriched, analyzed and annotated by WebGestaltR package. Then, STRING was employed to investigate the protein interactions. A risk model for evaluating Hepatocellular carcinoma prognosis was built with Lasso Cox regression analysis. The effect patients receiving immunotherapy was predicted using Tumor Immune Dysfunction and Exclusion (TIDE). Additionally, pRRophetic was used to investigate the drug sensitivity. Lastly, the Support Vector Machine (SVM) approach was utilized for building the diagnostic model. Results: The Hepatocellular Carcinoma Molecular Atlas 18 (HCCDB18) data set was utilized for the identification of 1344 HBV-related differentially expressed genes, mainly associated with cell division activities. Five functional modules were established and then we built a prognostic model in accordance with the protein-protein interaction (PPI) network. Five HBV-related genes affecting prognosis were identified for constructing a prognostic model. Then, the samples were assigned into RS-high and -low groups as per their relevant prognostic risk score (RS). High-risk group showed worse prognosis, higher mutation rate of TP53, lower sensitivity to immunotherapy but higher response to chemotherapeutic drugs than low-risk group. Finally, the hepatitis B virus diagnostic model of Hepatocellular carcinoma was established. Conclusion: In conclusion, the prognostic and diagnostic models of hepatitis B virus gene-related Hepatocellular carcinoma were constructed. ABCB6, IPO7, TIMM9, FZD7, and ACAT1, the five HBV-related genes that affect the prognosis, can work as reliable biomarkers for the diagnosis of Hepatocellular carcinoma, giving a new insight for improving the prognosis, diagnosis, and treatment outcomes of HBV-type Hepatocellular carcinoma.

Project description:BackgroundHepatocellular carcinoma (HCC) most commonly develops in patients who have a viral infection, especially in the case of hepatitis B virus (HBV), and in patients with a chronic liver disease. HCC patients with bone metastasis (BM) suffer from pain and other symptoms that significantly reduce their quality of life. Identification of patients who are at high risk for BM after undergoing potentially curative treatment for HCC remains challenging. Here, we aimed to identify HCC BM-related genes and proteins to establish prediction biomarkers.MethodsRNA was extracted from 48 pairs of intratumoral and peritumoral formalin-fixed, paraffin-embedded tissue from HCC patients with and without BM. A cDNA-mediated annealing, selection, extension and ligation assay containing 502 cancer-related genes was used to identify novel BM-associated genes. An additional independent study with 350 HCC patients who had undergone hepatectomy was conducted to evaluate the expression of candidate genes at the protein level using immunohistochemistry on tissue microarrays (TMAs). Of the 350 patients, 273 (78.0%) were infected with HBV.ResultsSeven intratumoral genes and 17 peritumoral genes were overexpressed in patients with BM, whereas 15 intratumoral genes and 28 peritumoral genes were underexpressed in patients with BM. We selected the following four genes for further analysis because they were differentially expressed in the cancer gene-specific microarray and were previously reported to be associated with BM: connective tissue growth factor (CTGF), matrix metalloproteinase-1 (MMP-1), transforming growth factor β1 (TGF-β1), and interleukin-11 (IL-11). We assessed the protein expression of these selected genes using immunohistochemistry on TMAs including 350 HCC patient specimens. We determined that expression of intratumoral CTGF, intratumoral IL-11, and peritumoral MMP-1 were independent prognostic factors for developing BM in HCC patients. Combining intratumoral CTGF and IL-11 expression was also an independent risk factor for BM development.ConclusionsSixty-seven genes were differentially expressed in HCC patients with and without BM. High intratumoral CTGF, positive IL-11, and high peritumoral MMP-1 expression were associated with BM after hepatectomy. Intratumoral CTGF expression combined with IL-11 expression may serve as a useful predictive biomarker for HCC BM.

Dataset Information

Soluble MICA and a MICA variation as possible prognostic biomarkers for HBV-induced hepatocellular carcinoma.

Publications

Soluble MICA and a MICA variation as possible prognostic biomarkers for HBV-induced hepatocellular carcinoma.

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