BackgroundHundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diverse data sources, it is of fundamental importance to evaluate their consistency.ResultsFirst, we showed that the lists of cancer genes from some major data sources were highly inconsistent in terms of overlapping genes. In particular, most cancer genes accumulated in previous small-scale studies could not be rediscovered in current high-throughput genome screening studies. Then, based on a metric proposed in this study, we showed that most cancer gene lists from different data sources were highly functionally consistent. Finally, we extracted functionally consistent cancer genes from various data sources and collected them in our database F-Census.ConclusionsAlthough they have very low gene overlapping, most cancer gene data sources are highly consistent at the functional level, which indicates that they can separately capture partial genes in a few key pathways associated with cancer. Our results suggest that the sample sizes currently used for cancer studies might be inadequate for consistently capturing individual cancer genes, but could be sufficient for finding a number of cancer genes that could represent functionally most cancer genes. The F-Census database provides biologists with a useful tool for browsing and extracting functionally consistent cancer genes from various data sources.

BackgroundThe cyclic AMP (cAMP) signaling pathway has been reported to either promote or suppress cell death, in a cell context-dependent manner. Our previous study has shown that the induction of dynein light chain (DLC) by cAMP response element-binding protein (CREB) is required for cAMP-mediated inhibition of mitogen-activated protein kinase (MAPK) p38 activation in fibroblasts, which leads to suppression of NF-κB activity and promotion of tumor necrosis factor-α (TNF-α)-induced cell death. However, it remains unknown whether this regulation is also applicable to fibroblastoma cells.MethodsIntracellular cAMP was determined in L929 fibroblastoma cells after treatment of the cells with various cAMP elevation agents. Effects of cAMP in the presence or absence of the RNA synthesis inhibitor actinomycin D or small interfering RNAs (siRNAs) against CREB on TNF-α-induced cell death in L929 cells were measured by propidium iodide (PI) staining and subsequent flow cytomety. The activation of p38 and c-Jun N-terminal protein kinase (JNK), another member of MAPK superfamily, was analyzed by immunoblotting. JNK selective inhibitor D-JNKi1 and p38 selective inhibitor SB203580 were included to examine the roles of JNK and p38 in this process. The expression of DLC or other mediators of cAMP was analyzed by immunoblotting. After ectopic expression of DLC with a transfection marker GFP, effects of cAMP on TNF-α-induced cell death in GFP+ cells were measured by PI staining and subsequent flow cytomety.ResultsElevation of cAMP suppressed TNF-α-induced necrotic cell death in L929 fibroblastoma cells via CREB-mediated transcription. The pro-survival role of cAMP was associated with selective unresponsiveness of L929 cells to the inhibition of p38 activation by cAMP, even though cAMP significantly inhibited the activation of JNK under the same conditions. Further exploration revealed that the induction of DLC, the major mediator of p38 inhibition by cAMP, was impaired in L929 cells. Enforced inhibition of p38 activation by using p38 specific inhibitor or ectopic expression of DLC reversed the protection of L929 cells by cAMP from TNF-α-induced cell death.ConclusionThese data suggest that the lack of a pro-apoptotic pathway in tumor cells leads to a net survival effect of cAMP.

BackgroundDue to the high morbidity and mortality of fulminant hepatitis, early diagnosis followed by early effective treatment is the key for prognosis improvement. So far, little is known about the gene expression changes in the early stage of this serious illness. Identification of the genes related to the very early stage of fulminant hepatitis development may provide precise clues for early diagnosis.ResultsBalb/C mice were used for ConA injection to induce fulminant hepatitis that was confirmed by pathological and biochemical examination. After a gene chip-based screening, the data of gene expression in the liver, was further dissected by ANOVA analysis, gene expression profiles, gene network construction and real-time RT-PCR.At the very early stage of ConA-triggered fulminant hepatitis, totally 1,473 genes with different expression variations were identified. Among these, 26 genes were finally selected for further investigation. The data from gene network analysis demonstrate that two genes, MPDZ and Acsl1, localized in the core of the network.ConclusionsAt the early stages of fulminant hepatitis, expression of twenty-six genes involved in protein transport, transcription regulation and cell metabolism altered significantly. These genes form a network and have shown strong correlation with fulminant hepatitis development. Our study provides several potential targets for the early diagnosis of fulminant hepatitis.

BackgroundHundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diverse data sources, it is of fundamental importance to evaluate their consistency.ResultsFirst, we showed that the lists of cancer genes from some major data sources were highly inconsistent in terms of overlapping genes. In particular, most cancer genes accumulated in previous small-scale studies could not be rediscovered in current high-throughput genome screening studies. Then, based on a metric proposed in this study, we showed that most cancer gene lists from different data sources were highly functionally consistent. Finally, we extracted functionally consistent cancer genes from various data sources and collected them in our database F-Census.ConclusionsAlthough they have very low gene overlapping, most cancer gene data sources are highly consistent at the functional level, which indicates that they can separately capture partial genes in a few key pathways associated with cancer. Our results suggest that the sample sizes currently used for cancer studies might be inadequate for consistently capturing individual cancer genes, but could be sufficient for finding a number of cancer genes that could represent functionally most cancer genes. The F-Census database provides biologists with a useful tool for browsing and extracting functionally consistent cancer genes from various data sources.

BackgroundDue to the high morbidity and mortality of fulminant hepatitis, early diagnosis followed by early effective treatment is the key for prognosis improvement. So far, little is known about the gene expression changes in the early stage of this serious illness. Identification of the genes related to the very early stage of fulminant hepatitis development may provide precise clues for early diagnosis.ResultsBalb/C mice were used for ConA injection to induce fulminant hepatitis that was confirmed by pathological and biochemical examination. After a gene chip-based screening, the data of gene expression in the liver, was further dissected by ANOVA analysis, gene expression profiles, gene network construction and real-time RT-PCR.At the very early stage of ConA-triggered fulminant hepatitis, totally 1,473 genes with different expression variations were identified. Among these, 26 genes were finally selected for further investigation. The data from gene network analysis demonstrate that two genes, MPDZ and Acsl1, localized in the core of the network.ConclusionsAt the early stages of fulminant hepatitis, expression of twenty-six genes involved in protein transport, transcription regulation and cell metabolism altered significantly. These genes form a network and have shown strong correlation with fulminant hepatitis development. Our study provides several potential targets for the early diagnosis of fulminant hepatitis.

BackgroundSemantic similarity scores for protein pairs are widely applied in functional genomic researches for finding functional clusters of proteins, predicting protein functions and protein-protein interactions, and for identifying putative disease genes. However, because some proteins, such as those related to diseases, tend to be studied more intensively, annotations are likely to be biased, which may affect applications based on semantic similarity measures. Thus, it is necessary to evaluate the effects of the bias on semantic similarity scores between proteins and then find a method to avoid them.ResultsFirst, we evaluated 14 commonly used semantic similarity scores for protein pairs and demonstrated that they significantly correlated with the numbers of annotation terms for the proteins (also known as the protein annotation length). These results suggested that current applications of the semantic similarity scores between proteins might be unreliable. Then, to reduce this annotation bias effect, we proposed normalizing the semantic similarity scores between proteins using the power transformation of the scores. We provide evidence that this improves performance in some applications.ConclusionsCurrent semantic similarity measures for protein pairs are highly dependent on protein annotation lengths, which are subject to biological research bias. This affects applications that are based on these semantic similarity scores, especially in clustering studies that rely on score magnitudes. The normalized scores proposed in this paper can reduce the effects of this bias to some extent.