Prediction of lncRNA-mRNA association network.

<p>The co-expression network was composed of 252 network nodes and 420 connections between 120 lncRNAs and 132 coding genes. Within this co-expression network, 369 pairs presented as positive, and 51 pairs presented as negative. This co-expression network indicated that one lncRNA could target 11 coding genes at most and that one coding gene could correlate with 128 lncRNAs at most.</p

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

<div><p>Background</p><p>Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored.</p><p>Principal Findings</p><p>In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features.</p><p>Conclusions</p><p>Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.</p></div

Differentially expressed lncRNAs and mRNAs in 4 hepatoblastoma vs. paired distant noncancerous tissues.

<p>The box plot is a convenient way to quickly visualize the distributions of a dataset of lncRNA (A) and mRNA (B) profiles. After normalization, the distributions of log₂ ratios among nine samples were nearly the same. The scatter plot is a visualization method used to assess the lncRNA (C) and mRNA (D) expression variations between hepatoblastoma and the paired distant noncancerous tissues. The values of the X- and Y-axes in the scatter plot are the averaged normalized signal values of the group (log₂ scaled). The green lines represent fold change lines (the default fold change given is 2.0).</p

Overlap of four sets of significant pathways obtained using the pathway coverage method.

<p>Note: The diagonal is the number of significant pathways. The percentages above (or below) the diagonal represent the number of the overlapping pathways divided by the number of the longer (or shorter) set of pathways. The values in bold font are the comparison result between the larger and smaller sample sizes.</p

The difference in A, the percentage of known cancer genes or damaging genes and B, the conservative score between five groups of mutated genes and control genes.

<p>Five groups of mutated genes were ranked in the top 50, 100, 150, 200 and 250 by betweenness coefficient of the network. Control genes are mutated genes with a betweenness coefficient of zero. The horizontal line parallel to the x axis represents the longitudinal coordinates of the control genes. * represents a significant difference (p<0.05).</p

Significantly mutated pathways.

<p><b>A,</b> Top 30 of 113 significantly mutated pathways and the difference in <b>B,</b> the percentage of known cancer genes or damaging genes and <b>C,</b> the conservative score between mutated genes in significantly mutated pathways (In SMP) and those not in significantly mutated pathways (Not In SMP). Coverage represents the fraction of tumors with at least one mutated gene in the specified pathway. Known cancer genes were obtained from the F-census database, and damaging genes were predicted using PolyPhen.</p

qRT-PCR validation of some differentially expressed lncRNAs and ESM1 mRNA in these 4 hepatoblasoma tissue samples.

<p>The data showed that expressions of lncRNAs TCONS-00090092-MEG3, TCONS-l2-00000179, TCONS-l2-00014091, TCONS-l2-00004424, TCONS-l2-00021262, and TCONS-00014978 and ESM1 mRNA were upregulated and that TCONS-l2-00018070, TCONS-l2-00018071, TCONS-l2-00006843, TCONS-l2-00030560, TCONS-l2-00020565, TCONS-00024647, and TCONS-00014512 were downregulated in hepatoblastoma tissues relative to the paired distant noncancerous tissues, consistent with the microarray data.</p

Distribution of study subjects and serum AFP levels.

<p>*at serum sample day.</p

Overview of genes with mutations in at least 10 of 207 patient samples.

<p>The heatmap shows genes (rows) and tumors (columns) with mutations (blue). The number of events per gene is indicated to the left.</p

Primers used for qRT-PCR analysis of lncRNA and mRNA levels.

<p>Primers used for qRT-PCR analysis of lncRNA and mRNA levels.</p