dbHCCvar: A comprehensive database of human genetic variations in hepatocellular carcinoma

Yu, Xiaoming; Fang, Fang; Tang, Chun-Lei; Yao, Lei; Yu, Li-Fang; Liu, Yu

doi:10.1002/humu.21595

Cited by 13 publications

(13 citation statements)

References 34 publications

(31 reference statements)

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“…HCC.Net, which has compiled a network with thousands of HCC-related genes identified in different types and stages of HCC, contains 2,131 HCC-related genes [14]. dbHCCvar is an online database which contains 636 human genetic variations and 195 human genes which have been statistically tested to be associated with HCC [15]. EHCO is derived from thirteen gene sets related to HCC and gives 3833 HCC-significant genes [16].…”

Section: Methodsmentioning

confidence: 99%

“…Our study group has recently developed two systems biology-based classifiers for early diagnosis of HCC and prostate cancer (PCa), respectively, by combining differential gene and protein expression and topological characteristics of human protein interaction networks, and also demonstrated that these classifiers may efficiently enhance the diagnostic performance for HCC and PCa [11,12]. On this basis, in the current study, we intend to collect full-scale HCC related data including HCC significant genes and proteins which were differentially expressed or had genetic variations in HCC tissues relative to their corresponding normal tissues from five existing HCC related databases (OncoDB.HCC [13], HCC.net [14], dbHCCvar [15], EHCO [16] and Liverome [17]). In order to investigate the functional relationships between these significant molecules, we constructed the protein-protein interaction network and analyzed the topological features of nodes to screen novel markers for HCC.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

Zhang

Yang

et al. 2013

PLoS ONE

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AimTo screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation.MethodsHCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated.ResultsIn total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC.ConclusionThis study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

Zhang

Yang

et al. 2013

PLoS ONE

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“…HCC.Net, which has compiled a network with thousands of HCC-related genes identified in different types and stages of HCC, contains 2,131 HCC-related genes25. dbHCCvar is an online database which contains 636 human genetic variations and 195 human genes which have been statistically tested to be associated with HCC26. EHCO is derived from thirteen gene sets related to HCC and gives 3833 HCC-significant genes27.…”

Section: Methodsmentioning

confidence: 99%

A systems biology-based investigation into the therapeutic effects of Gansui Banxia Tang on reversing the imbalanced network of hepatocellular carcinoma

Zhang

Guo

Wang

et al. 2014

Sci Rep

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Several complex molecular events are involved in tumorigenesis of hepatocellular carcinoma (HCC). The interactions of these molecules may constitute the HCC imbalanced network. Gansui Banxia Tang (GSBXT), as a classic Chinese herbal formula, is a popular complementary and alternative medicine modality for treating HCC. In order to investigate the therapeutic effects and the pharmacological mechanisms of GSBXT on reversing HCC imbalanced network, we in the current study developed a comprehensive systems approach of integrating disease-specific and drug-specific networks, and successfully revealed the relationships of the ingredients in GSBXT with their putative targets, and with HCC significant molecules and HCC related pathway systems for the first time. Meanwhile, further experimental validation also demonstrated the preventive effects of GSBXT on tumor growth in mice and its regulatory effects on potential targets.

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“…The present review will summarize the influence of this inherited background on the risk of HCC with the constant will to illustrate both the limitations and the progress made in this field. For a more exhaustive overview, free online databases providing comprehensively and systematically compiled genetic associations have been recently established [58].…”

Section: Genetic Predisposition and Hccmentioning

confidence: 99%

Single nucleotide polymorphisms and risk of hepatocellular carcinoma in cirrhosis

Nahon

Zucman‐Rossi

2012

Journal of Hepatology

149

110

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Liver carcinogenesis is a complex and multi-factorial process, in which both environmental and genetic features interfere and contribute to malignant transformation. Patients with cirrhosis are particularly exposed and justify periodical screenings in order to detect the early development of hepatocellular carcinoma (HCC). The risk of HCC is, however, not identical from one patient to another. The identification of host factors that may also play an important role in HCC development may improve our understanding of the implications of the various biological pathways involved in liver carcinogenesis; such progress may as well help refine the selection of patients who could benefit from specific preventative measures or could be given adapted screening policies. Numerous candidate-gene studies have reported associations between single nucleotide polymorphisms (SNPs) and the presence of HCC. Some of these publications unfortunately suffer from major methodological drawbacks because of their case-control, retrospective and monocentric aspect. Prospective cohort studies conducted in large homogeneous populations and comprising a sufficient number of events during follow-up may overcome these pitfalls, but require a long time to be conducted and are still scarce. More recently, the first Genome Wide Association studies (GWAs) have enabled the identification of unsuspected loci that may be involved in various steps implicated in liver tumourigenesis. Taken together, these studies highlight variants that modulate oxidative stress, iron metabolism, inflammatory and immune responses, DNA repair mechanisms or systems involved in cell-cycle regulation as genetic traits susceptible to modify the natural history of cirrhotic patients and partly explain the observed differences in the risk of HCC occurrence. However, large genetic epidemiology studies in the field of cancer diseases have suggested the limited ability of polymorphic traits, alone, to refine individual prognosis. The integration of various panels of genes into clinical scores may in the near future define a "genomic risk prediction" specific to liver cancer developed in cirrhotic patients.

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dbHCCvar: A comprehensive database of human genetic variations in hepatocellular carcinoma

Cited by 13 publications

References 34 publications

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

A systems biology-based investigation into the therapeutic effects of Gansui Banxia Tang on reversing the imbalanced network of hepatocellular carcinoma

Single nucleotide polymorphisms and risk of hepatocellular carcinoma in cirrhosis

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