Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer

Sex-Related Differences in Gene Expression by Porcine Aortic Valvular Interstitial Cells

<div><p>While many large-scale risk factors for calcific aortic valve disease (CAVD) have been identified, the molecular etiology and subsequent pathogenesis of CAVD have yet to be fully understood. Specifically, it is unclear what biological phenomena underlie the significantly higher occurrence of CAVD in the male population. We hypothesized the existence of intrinsic, cellular-scale differences between male and female valvular interstitial cells (VICs) that contribute to male sex being a risk factor for CAVD. Differences in gene expression profiles between healthy male and female porcine VICs were investigated via microarray analysis. Mean expression values of each probe set in the male samples were compared to the female samples, and biological processes were analyzed for overrepresentation using Gene Ontology term enrichment analysis. There were 183 genes identified as significantly (fold change>2; P<0.05) different in male versus female aortic valve leaflets. Within this significant gene list there were 298 overrepresented biological processes, several of which are relevant to pathways identified in CAVD pathogenesis. In particular, pathway analysis indicated that cellular proliferation, apoptosis, migration, ossification, angiogenesis, inflammation, and extracellular matrix reorganization were all significantly represented in the data set. These gene expression findings also translated into functional differences in VIC behavior in the <em>in vitro</em> environment, as sex-related differences in proliferation and apoptosis were confirmed in VIC populations cultured <em>in vitro</em>. These data suggest that a sex-related propensity for CAVD exists on the cellular level in healthy subjects, a phenomenon that could have significant clinical implications. These findings also strongly support discontinuing the use of mixed-sex VIC cultures, thereby changing the current standard in the field.</p> </div

Ingenuity pathway analysis Network #1.

<p>Ingenuity pathway analysis was used to assemble a network based upon 22 differentially expressed focus genes that were upregulated in male VICs compared to female VICs. Genes are represented as nodes, with node shape representing the functional class of the gene product (seen in legend). Node color depicts degree of overrepresentation in male samples; uncolored nodes are depicted based upon evidence in the IPA Knowledge Base indicating a strong biological relevance to the network. *indicates multiple identifiers in the dataset file map to a single gene in the IPA Global Molecular Network. Corresponding fold change values are listed beneath each gene label. Focus gene names are defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039980#pone.0039980.s005" target="_blank">Table S1</a>.</p

Functional categorization analysis of most significant pathways and diseases represented by microarray data.

<p>A functional categorization analysis of the most significant pathways and diseases represented in the microarray-generated list of significantly different genes was generated using Ingenuity software. The p-value was calculated using the right-tailed Fisher’s exact test. Each bar represents the highest level of function for each category, each of which includes many sub-level functions and is represented by the number of genes in the male and female samples (denoted in parentheses, respectively). The bar was determined by the lowest p-value among sub-level functions for each category. Threshold indicates p-value cutoff of 0.05.</p

Ingenuity pathway analysis Network #3.

<p>Ingenuity pathway analysis was used to assemble a network based upon 14 differentially expressed focus genes that were upregulated in male VICs compared to female VICs. Corresponding fold change values are listed beneath each gene label. Focus gene names are defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039980#pone.0039980.s005" target="_blank">Table S1</a>.</p

Significant biological processes determined by GO enrichment analysis and categorized according to disease-related pathway grouping (expanded table available in Table S4).

<p>Significant biological processes determined by GO enrichment analysis and categorized according to disease-related pathway grouping (expanded table available in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039980#pone.0039980.s008" target="_blank">Table S4</a>).</p

IPA-generated molecular networks assembled from differentially expressed genes (bold) in males versus females in the significant genes list.

‡<p>The score is a numerical rank of the degree of relevance of the network to the molecules in the significant genes list and is based on the hypergeometric distribution calculated as –log(Fisher’s exact test result).</p>*<p>indicates multiple identifiers in the significant genes dataset map to a single gene in the IPA Global Molecular Network.</p

Translation of findings to <i>in vitro</i> VIC function.

<p>Male and female VICs were cultured for 5 days in serum-free media and evaluated for (A) proliferation, using the Click-iT EdU Alexa Fluor 488 Imaging Assay, and (B) apoptosis, using the Promega Caspase-Glo 3/7 Assay System. Values are means plus standard deviation, n = 4 per condition. *P<0.05 compared to male VICs.</p

Ingenuity pathway analysis Network #2.

<p>Ingenuity pathway analysis was used to assemble a network based upon 20 differentially expressed focus genes that were upregulated in male VICs compared to female VICs. * indicates multiple identifiers in the dataset file map to a single gene in the IPA Global Molecular Network. Corresponding fold change values are listed beneath each gene label. Focus gene names are defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039980#pone.0039980.s005" target="_blank">Table S1</a>.</p

qRT-PCR validation of microarray data.

<p>Data are displayed as mean log2(fold-change) in gene expression in male versus female samples. Gene abbreviations: aggrecan (<i>ACAN</i>), dipeptidyl-peptidase 4 (<i>DPP4</i>), stanniocalcin 1 precursor (<i>STC1</i>), natriuretic peptide precursor C (<i>NPPC</i>), kinase insert domain receptor (<i>KDR</i>), angiopoietin-like 4 (<i>ANGPTL4</i>), apolipoprotein E (<i>APOE</i>), calcitonin receptor-like (<i>CALCRL</i>), and insulin-like growth factor binding protein 5 (<i>IGFBP5</i>). *P<0.05 compared to female VIC RT-PCR results, ^#P<0.05 compared to female VIC microarray results.</p