Sex matters during adolescence: Testosterone-related cortical thickness maturation differs between boys and girls

Age-related changes in cortical thickness have been observed during adolescence, including thinning in frontal and parietal cortices, and thickening in the lateral temporal lobes. Studies have shown sex differences in hormone-related brain maturation when boys and girls are age-matched, however, because girls mature 1-2 years earlier than boys, these sex differences could be confounded by pubertal maturation. To address puberty effects directly, this study assessed sex differences in testosterone-related cortical maturation by studying 85 boys and girls in a narrow age range and matched on sexual maturity. We expected that testosterone-by-sex interactions on cortical thickness would be observed in brain regions known from the animal literature to be high in androgen receptors. We found sex differences in associations between circulating testosterone and thickness in left inferior parietal lobule, middle temporal gyrus, calcarine sulcus, and right lingual gyrus, all regions known to be high in androgen receptors. Visual areas increased with testosterone in boys, but decreased in girls. All other regions were more impacted by testosterone levels in girls than boys. The regional pattern of sex-by-testosterone interactions may have implications for understanding sex differences in behavior and adolescent-onset neuropsychiatric disorders. © 2012 Bramen et al

Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

Anticipatory nausea in cyclical vomiting

BACKGROUND: Cyclical Vomiting Syndrome (CVS) is characterised by discrete, unexplained episodes of intense nausea and vomiting, and mainly affects children and adolescents. Comprehending Cyclical Vomiting Syndrome requires awareness of the severity of nausea experienced by patients. As a subjective symptom, nausea is easily overlooked, yet is the most distressing symptom for patients and causes many behavioural changes during attacks. CASE PRESENTATION: This first-hand account of one patient's experience of Cyclical Vomiting Syndrome shows how severe nausea contributed to the development of anticipatory nausea and vomiting (ANV), a conditioned response frequently observed in chemotherapy patients. This conditioning apparently worsened the course of the patient's disease. Anticipatory nausea and vomiting has not previously been recognised in Cyclical Vomiting Syndrome, however predictors of its occurrence in oncology patients indicate that it could complicate many cases. CONCLUSION: We suggest a model whereby untreated severe and prolonged nausea provokes anxiety about further cyclical vomiting attacks. This anxiety facilitates conditioning, thus increasing the range of triggers in a self-perpetuating manner. Effective management of the nausea-anxiety feedback loop can reduce the likelihood of anticipatory nausea and vomiting developing in other patients

Copy Number and Loss of Heterozygosity Detected by SNP Array of Formalin-Fixed Tissues Using Whole-Genome Amplification

The requirement for large amounts of good quality DNA for whole-genome applications prohibits their use for small, laser capture micro-dissected (LCM), and/or rare clinical samples, which are also often formalin-fixed and paraffin-embedded (FFPE). Whole-genome amplification of DNA from these samples could, potentially, overcome these limitations. However, little is known about the artefacts introduced by amplification of FFPE-derived DNA with regard to genotyping, and subsequent copy number and loss of heterozygosity (LOH) analyses. Using a ligation adaptor amplification method, we present data from a total of 22 Affymetrix SNP 6.0 experiments, using matched paired amplified and non-amplified DNA from 10 LCM FFPE normal and dysplastic oral epithelial tissues, and an internal method control. An average of 76.5% of SNPs were called in both matched amplified and non-amplified DNA samples, and concordance was a promising 82.4%. Paired analysis for copy number, LOH, and both combined, showed that copy number changes were reduced in amplified DNA, but were 99.5% concordant when detected, amplifications were the changes most likely to be ‘missed’, only 30% of non-amplified LOH changes were identified in amplified pairs, and when copy number and LOH are combined ∼50% of gene changes detected in the unamplified DNA were also detected in the amplified DNA and within these changes, 86.5% were concordant for both copy number and LOH status. However, there are also changes introduced as ∼20% of changes in the amplified DNA are not detected in the non-amplified DNA. An integrative network biology approach revealed that changes in amplified DNA of dysplastic oral epithelium localize to topologically critical regions of the human protein-protein interaction network, suggesting their functional implication in the pathobiology of this disease. Taken together, our results support the use of amplification of FFPE-derived DNA, provided sufficient samples are used to increase power and compensate for increased error rates

Multiplicity: an organizing principle for cancers and somatic mutations

<p>Abstract</p> <p>Background</p> <p>With the advent of whole-genome analysis for profiling tumor tissue, a pressing need has emerged for principled methods of organizing the large amounts of resulting genomic information. We propose the concept of multiplicity measures on cancer and gene networks to organize the information in a clinically meaningful manner. Multiplicity applied in this context extends Fearon and Vogelstein's multi-hit genetic model of colorectal carcinoma across multiple cancers.</p> <p>Methods</p> <p>Using the Catalogue of Somatic Mutations in Cancer (COSMIC), we construct networks of interacting cancers and genes. Multiplicity is calculated by evaluating the number of cancers and genes linked by the measurement of a somatic mutation. The Kamada-Kawai algorithm is used to find a two-dimensional minimum energy solution with multiplicity as an input similarity measure. Cancers and genes are positioned in two dimensions according to this similarity. A third dimension is added to the network by assigning a maximal multiplicity to each cancer or gene. Hierarchical clustering within this three-dimensional network is used to identify similar clusters in somatic mutation patterns across cancer types.</p> <p>Results</p> <p>The clustering of genes in a three-dimensional network reveals a similarity in acquired mutations across different cancer types. Surprisingly, the clusters separate known causal mutations. The multiplicity clustering technique identifies a set of causal genes with an area under the ROC curve of 0.84 versus 0.57 when clustering on gene mutation rate alone. The cluster multiplicity value and number of causal genes are positively correlated via Spearman's Rank Order correlation (<it>r_s</it>(8) = 0.894, Spearman's <it>t </it>= 17.48, <it>p </it>< 0.05). A clustering analysis of cancer types segregates different types of cancer. All blood tumors cluster together, and the cluster multiplicity values differ significantly (Kruskal-Wallis, <it>H </it>= 16.98, <it>df </it>= 2, <it>p </it>< 0.05).</p> <p>Conclusion</p> <p>We demonstrate the principle of multiplicity for organizing somatic mutations and cancers in clinically relevant clusters. These clusters of cancers and mutations provide representations that identify segregations of cancer and genes driving cancer progression.</p

Intratumor genetic heterogeneity in squamous cell carcinoma of the oral cavity

BackgroundWe sought to evaluate intratumor heterogeneity in squamous cell carcinoma of the oral cavity (OCC) and specifically determine the effect of physical separation and histologic differentiation within the same tumor.MethodsWe performed whole exome sequencing on five biopsy sites—two from well‐differentiated, two from poorly differentiated regions, and one from normal parenchyma—from five primary OCC specimens.ResultsWe found high levels of intratumor heterogeneity and, in four primary tumors, identified only 0 to 2 identical mutations in all subsites. We found that the heterogeneity inversely correlated with physical separation and that pairs of well‐differentiated samples were more similar to each other than analogous poorly differentiated specimens. Only TP53 mutations, but not other purported “driver mutations” in head and neck squamous cell carcinoma, were found in multiple biopsy sites.ConclusionThese data highlight the challenges to characterization of the mutational landscape of OCC with single site biopsy and have implications for personalized medicine.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150549/1/hed25719.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150549/2/hed25719_am.pd