Dataset Information

The Cytokinome Profile in Patients with Hepatocellular Carcinoma and Type 2 Diabetes.

ABSTRACT: Understanding the dynamics of the complex interaction network of cytokines, defined as ''cytokinome'', can be useful to follow progression and evolution of hepatocellular carcinoma (HCC) from its early stages as well as to define therapeutic strategies. Recently we have evaluated the cytokinome profile in patients with type 2 diabetes (T2D) and/or chronic hepatitis C (CHC) infection and/or cirrhosis suggesting specific markers for the different stages of the diseases. Since T2D has been identified as one of the contributory cause of HCC, in this paper we examined the serum levels of cytokines, growth factors, chemokines, as well as of other cancer and diabetes biomarkers in a discovery cohort of patients with T2D, chronic hepatitis C (CHC) and/or CHC-related HCC comparing them with a healthy control group to define a profile of proteins able to characterize these patients, and to recognize the association between diabetes and HCC. The results have evidenced that the serum levels of some proteins are significantly and differently up-regulated in all the patients but they increased still more when HCC develops on the background of T2D. Our results were verified also using a separate validation cohort. Furthermore, significant correlations between clinical and laboratory data characterizing the various stages of this complex disease, have been found. In overall, our results highlighted that a large and simple omics approach, such as that of the cytokinome analysis, supplemented by common biochemical and clinical data, can give a complete picture able to improve the prognosis of the various stages of the disease progression. We have also demonstrated by means of interactomic analysis that our experimental results correlate positively with the general metabolic picture that is emerging in the literature for this complex multifactorial disease.

SUBMITTER: Capone F

PROVIDER: S-EPMC4520685 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The Cytokinome Profile in Patients with Hepatocellular Carcinoma and Type 2 Diabetes.

Capone Francesca F Guerriero Eliana E Colonna Giovanni G Maio Patrizia P Mangia Alessandra A Marfella Raffaele R Paolisso Giuseppe G Izzo Francesco F Potenza Nicoletta N Tomeo Luigi L Castello Giuseppe G Costantini Susan S

PloS one 20150730 7

Understanding the dynamics of the complex interaction network of cytokines, defined as ''cytokinome'', can be useful to follow progression and evolution of hepatocellular carcinoma (HCC) from its early stages as well as to define therapeutic strategies. Recently we have evaluated the cytokinome profile in patients with type 2 diabetes (T2D) and/or chronic hepatitis C (CHC) infection and/or cirrhosis suggesting specific markers for the different stages of the diseases. Since T2D has been identifi ...[more]

PMID: 26226632

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Project description:Fibrolamellar hepatocellular carcinoma (FLC) is a rare primary hepatic cancer that develops in children and young adults without cirrhosis. Little is known about its pathogenesis, and it can be treated only with surgery. We performed an integrative genomic analysis of a large series of patients with FLC to identify associated genetic factors.By using 78 clinically annotated FLC samples, we performed whole-transcriptome (n = 58), single-nucleotide polymorphism array (n = 41), and next-generation sequencing (n = 48) analyses; we also assessed the prevalence of the DNAJB1-PRKACA fusion transcript associated with this cancer (n = 73). We performed class discovery using non-negative matrix factorization, and functional annotation using gene-set enrichment analyses, nearest template prediction, ingenuity pathway analyses, and immunohistochemistry. The genomic identification of significant targets in a cancer algorithm was used to identify chromosomal aberrations, MuTect and VarScan2 were used to identify somatic mutations, and the random survival forest was used to determine patient prognoses. Findings were validated in an independent cohort.Unsupervised gene expression clustering showed 3 robust molecular classes of tumors: the proliferation class (51% of samples) had altered expression of genes that regulate proliferation and mammalian target of rapamycin signaling activation; the inflammation class (26% of samples) had altered expression of genes that regulate inflammation and cytokine enriched production; and the unannotated class (23% of samples) had a gene expression signature that was not associated previously with liver tumors. Expression of genes that regulate neuroendocrine function, as well as histologic markers of cholangiocytes and hepatocytes, were detected in all 3 classes. FLCs had few copy number variations; the most frequent were focal amplification at 8q24.3 (in 12.5% of samples), and deletions at 19p13 (in 28% of samples) and 22q13.32 (in 25% of samples). The DNAJB1-PRKACA fusion transcript was detected in 79% of samples. FLC samples also contained mutations in cancer-related genes such as BRCA2 (in 4.2% of samples), which are uncommon in liver neoplasms. However, FLCs did not contain mutations most commonly detected in liver cancers. We identified an 8-gene signature that predicted survival of patients with FLC.In a genomic analysis of 78 FLC samples, we identified 3 classes based on gene expression profiles. FLCs contain mutations and chromosomal aberrations not previously associated with liver cancer, and almost 80% contain the DNAJB1-PRKACA fusion transcript. By using this information, we identified a gene signature that is associated with patient survival time.

Project description:BackgroundThe clinical pathologic stages (stage I, II, III-IV) of hepatocellular carcinoma (HCC) are closely linked to the clinical prognosis of patients. This study aims at investigating the gene expression and mutational profile in different clinical pathologic stages of HCC.MethodsBased on the TCGA-LIHC cohort, we utilized a series of analytical approaches, such as statistical analysis, random forest, decision tree, principal component analysis (PCA), to identify the differential gene expression and mutational profiles. The expression patterns of several targeting genes were also verified by analyzing the Chinese HLivH060PG02 HCC cohort, several GEO datasets, HPA database, and diethylnitrosamine-induced HCC mouse model.ResultsWe identified a series of targeting genes with copy number variation, which is statistically associated with gene expression. Non-synonymous mutations mainly existed in some genes (e.g.,TTN, TP53, CTNNB1). Nevertheless, no association between gene mutation frequency and pathologic stage distribution was detected. The random forest and decision tree modeling analysis data showed a group of genes related to different HCC pathologic stages, including GAS2L3 and SEMA3F. Additionally, our PCA data indicated several genes associated with different pathologic stages, including SNRPA and SNRPD2. Compared with adjacent normal tissues, we observed a highly expressed level of GAS2L3, SNRPA, and SNRPD2 (P = 0.002) genes in HCC tissues of our HLivH060PG02 cohort. We also detected the high expression pattern of GAS2L3, SEMA3F, SNRPA, and SNRPD2 in the datasets of GSE102079, GSE76427, GSE64041, GSE121248, GSE84005, and the qPCR assay using diethylnitrosamine-induced HCC mouse model. Moreover, SEMA3F and SNRPD2 protein were highly stained in the HCC tissues of the HPA database. The high expression level of these four genes was associated with the poor survival prognosis of HCC cases.ConclusionsOur study provides evidence regarding the gene expression and mutational profile in different clinical pathologic stages of TCGA HCC cases. Identifying four targeting genes, including GAS2L3, SNRPA, SNRPD2, and SEMA3F, offers insight into the molecular mechanisms associated with different prognoses of HCC.

Dataset Information

The Cytokinome Profile in Patients with Hepatocellular Carcinoma and Type 2 Diabetes.

Publications

The Cytokinome Profile in Patients with Hepatocellular Carcinoma and Type 2 Diabetes.

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