T-Cell Densities in Brain Metastases Are Associated with Patient Survival Times and Diffusion Tensor MRI Changes

Brain metastases are common and are usually detected by MRI. Diffusion tensor imaging (DTI) is a derivative MRI technique that can detect disruption of white matter tracts in the brain. We have matched preoperative DTI with image-guided sampling of the brain–tumor interface in 26 patients during resection of a brain metastasis and assessed mean diffusivity and fractional anisotropy (FA). The tissue samples were analyzed for vascularity, inflammatory cell infiltration, growth pattern, and tumor expression of proteins associated with growth or local invasion such as Ki67, S100A4, and MMP2, 9, and 13. A lower FA in the peritumoral region indicated more white matter tract disruption and independently predicted longer overall survival times (HR for death = 0.21; 95% confidence interval, 0.06–0.82; P = 0.024). Of all the biological markers studied, only increased density of CD3+ lymphocytes in the same region correlated with decreased FA (Mann–Whitney U, P = 0.037) as well as confounding completely the effect of FA on multivariate survival analyses. We conclude that the T-cell response to brain metastases is not a surrogate of local tumor invasion, primary cancer type, or aggressive phenotype and is associated with patient survival time regardless of these biological factors. Furthermore, it can be assayed by DTI, potentially offering a quick, noninvasive, clinically available method to detect an active immune microenvironment and, in principle, to measure susceptibility to immunotherapy. Significance: These findings show that white matter tract integrity is degraded in areas where T-cell infiltration is highest, providing a noninvasive method to identify immunologically active microenvironments in secondary brain tumors. Cancer Res; 78(3); 610–6. ©2017 AACR

Genomic profiling using the UltraSEEK panel identifies discordancy between paired primary and breast cancer brain metastases and an association with brain metastasis-free survival

PurposeBrain metastases (BM) are an increasing clinical problem. This study aimed to assess paired primary breast cancers (BC) and BM for aberrations within TP53, PIK3CA, ESR1, ERBB2 and AKT utilising the MassARRAY® UltraSEEK® technology (Agena Bioscience, San Diego, USA).MethodsDNA isolated from 32 paired primary BCs and BMs was screened using the custom UltraSEEK® Breast Cancer Panel. Data acquisition and analysis was performed by the Agena Bioscience Typer software v4.0.26.74.ResultsMutations were identified in 91% primary BCs and 88% BM cases. TP53, AKT1, ESR1, PIK3CA and ERBB2 genes were mutated in 68.8%, 37.5%, 31.3%, 28.1% and 3.1% respectively of primary BCs and in 59.4%, 37.5%, 28.1%, 28.1% and 3.1% respectively of BMs. Differences in the mutations within the 5 genes between BC and paired BM were identified in 62.5% of paired cases. In primary BCs, ER-positive/HER2-negative cases harboured the most mutations (70%), followed by ER-positive/HER2-positive (15%) and triple-negatives (13.4%), whereas in BMs, the highest number of mutations was observed in triple-negative (52.5%), followed by ER-positive/HER2-negative (35.6%) and ER-negative/HER2-positive (12%). There was a significant association between the number of mutations in the primary BC and breast-to-brain metastasis-free survival (p = 0.0001) but not with overall survival (p = 0.056).ConclusionThese data demonstrate the discordancy between primary BC and BM, as well as the presence of clinically important, actionable mutations in BCBM. The UltraSEEK® Breast Cancer Panel provides a tool for BCBM that can be utilised to direct more tailored treatment decisions and for clinical studies investigating targeted agents

A novel panel of differentially-expressed microRNAs in breast cancer brain metastasis may predict patient survival

Breast cancer brain metastasis (BCBM) is an area of unmet clinical need. MicroRNAs (miRNAs) have been linked to the metastatic process in breast cancer (BC). In this study, we aim to determine differentially-expressed miRNAs utilising primary BCs that did not relapse (BCNR, n = 12), primaries that relapsed (BCR) and their paired (n = 40 pairs) brain metastases (BM) using the NanoString™ nCounter™ miRNA Expression Assays. Significance analysis of microarrays identified 58 and 11 differentially-expressed miRNAs between BCNR vs BCR and BCR vs BM respectively and pathway analysis revealed enrichment for genes involved in invasion and metastasis. Four miRNAs, miR-132-3p, miR-199a-5p, miR-150-5p and miR-155-5p, were differentially-expressed within both cohorts (BCNR-BCR, BCR-BM) and receiver-operating characteristic curve analysis (p = 0.00137) and Kaplan-Meier survival method (p = 0.0029, brain metastasis-free survival; p = 0.0007, overall survival) demonstrated their potential use as prognostic markers. Ingenuity pathway enrichment linked them to the MET oncogene, and the cMET protein was overexpressed in the BCR (p < 0.0001) and BM (p = 0.0008) cases, compared to the BCNRs. The 4-miRNAs panel identified in this study could be potentially used to distinguish BC patients with an increased risk of developing BCBM and provide potential novel therapeutic targets, whereas cMET-targeting warrants further investigation in the treatment of BCBM

Matrix metalloproteinase 2 is a target of the RAN-GTP pathway and mediates migration, invasion and metastasis in human breast cancer

RAS-related nuclear protein(RAN) is a nuclear shuttle and normally regulates events in the cell cycle. When overexpressed in cultured cells, it causes increases in cell migration/invasion in vitro and its overexpression is associated with early breast cancer patient deaths in vivo. However, the underlying mechanism is unknown. The effect of RAN overexpression on potential targets MMP2, ATF3, CXCR3 was investigated by Real-Time PCR/Western blots in the triple receptor negative breast cancer(TRNBC) cell line MDA-MB231 and consequent biological effects were measured by cell adhesion, cell migration and cell invasion assays. Results showed that knockdown of RAN lead to a reduction of MMP2 and its potential regulators ATF3 and CXCR3. Moreover, knockdown of ATF3 or CXCR3 downregulated MMP2 without affecting RAN, indicating that RAN regulates MMP2 through ATF3 and CXCR3. Knockdown of RAN and MMP2 reduced cell adhesion, cell migration and cell growth in agar, whilst overexpression of MMP2 reversed the knockdown of RAN. Furthermore, immunohistochemical staining for RAN and MMP2 are positively associated with each other in the same tumour and separately with patient survival times in breast cancer specimens, suggesting that a high level of RAN may be a pre-requisite for MMP2 overexpression and metastasis. Moreover, positive immunohistochemical staining for both RAN and MMP-2 reduces further patient survival times over that for either protein separately. Our results suggest that MMP2 expression can stratify progression of breast cancers with a high and low incidence of RAN, both RAN and MMP2 in combination can be used for a more accurate patient prognosis. SIMPLE SUMMARY: Ran is an important regulator of normal cell growth and behaviour. We have established in cell line models of breast cancer (BC) a molecular pathway between RAN and its protein-degrading effector MMP-2 and properties related to metastasis in culture. Using immunohistochemistry (IHC) staining of primary BCs, we have shown that RAN and MMP-2 are on their own significantly associated with patient demise from metastatic BC. Moreover, when staining for MMP-2 is added to that for RAN in the primary tumours, there is a significant decrease in patient survival time over that for either protein alone. Thus a combination of staining for RAN and MMP2 is an excellent marker for poor prognosis in breast cancer

Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening

Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space

fMRI Evidence for a Dual Process Account of the Speed-Accuracy Tradeoff in Decision-Making

Background: The speed and accuracy of decision-making have a well-known trading relationship: hasty decisions are more prone to errors while careful, accurate judgments take more time. Despite the pervasiveness of this speed-accuracy tradeoff (SAT) in decision-making, its neural basis is still unknown. Methodology/Principal Findings: Using functional magnetic resonance imaging (fMRI) we show that emphasizing the speed of a perceptual decision at the expense of its accuracy lowers the amount of evidence-related activity in lateral prefrontal cortex. Moreover, this speed-accuracy difference in lateral prefrontal cortex activity correlates with the speedaccuracy difference in the decision criterion metric of signal detection theory. We also show that the same instructions increase baseline activity in a dorso-medial cortical area involved in the internal generation of actions. Conclusions/Significance: These findings suggest that the SAT is neurally implemented by modulating not only the amount of externally-derived sensory evidence used to make a decision, but also the internal urge to make a response. We propose that these processes combine to control the temporal dynamics of the speed-accuracy trade-off in decisionmaking

Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

: O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s disease Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types C. A. Semple O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu O16 Modeling genetic interactions associated with molecular subtypes of breast cancer B. Ji, A. Tyler, G. Ananda, G. Carter O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski O18 Predictive biomarkers to metastatic pancreatic cancer treatment J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman O19 DDIT4 gene expression as a prognostic marker in several malignant tumors L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto O20 Spatial organization of the genome and genomic alterations in human cancers K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group O21 Landscape of targeted therapies in solid tumors S. Patterson, C. Statz, S. Mockus O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis S. Likhitrattanapisal O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4 C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13 K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle O32 Legal interoperability: a sine qua non for international data sharing A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes R. Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker O40 A general statistic framework for genome-based disease risk prediction M. Xiong, L. Ma, N. Lin, C. Amos O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong O42 Big data and NGS data analysis: the cloud to the rescue O. Dobretsberger, M. Egger, F. Leimgruber O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data V. A. A. Antonio, N. Ono, Clark Kendrick C. Go O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans C. Zeng, J. Shao O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes? I. Campbell, M.-A. Young, P. James, Lifepool O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS C. Schumacher, S. Sandhu, T. Harkins, V. Makarov O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs O55 Rapid capture methods for clinical sequencing J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs O56 A diploid personal human genome model for better genomes from diverse sequence data K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs O57 Development of PacBio long range capture for detection of pathogenic structural variants Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers O59 Assessing RNA structure disruption induced by single-nucleotide variation J. Lin, Y. Zhang, Z. Ouyang P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility E. S. Chen P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients H. Bahrami, A. Khoshzaban, S. Heidari Keshal P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population K. K. R. Alharbi P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population M. Matar P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization N. Mili, R. Molinari, Y. Ma, S. Guerrier P9 Vulnerability of genetic variants to the risk of autism among Saudi children N. Elhawary, M. Tayeb, N. Bogari, N. Qotb P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7 mice Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome D. Graur P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns B. S. Soibam P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes J. J. Gruber, N. Jaeger, M. Snyder P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson P23 RNA sequencing identifies gene mutations for neuroblastoma K. Zhang P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales P25 Targeted Methylation Sequencing of Prostate Cancer N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía P28 Genetic modifiers of Alström syndrome J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess P34 Molecular regulation of chondrogenic human induced pluripotent stem cells M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid P36 Accessing genomic evidence for clinical variants at NCBI S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA C. Xiao, E. Yaschenko, S. Sherry P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling C. Rangel-Escareño, H. Rueda-Zarate P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium P43 Rapid and scalable typing of structural variants for disease cohorts W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits L. 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Andreesen, E. Holler P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Atha

The multi-peak adaptive landscape of crocodylomorph body size evolution

Background: Little is known about the long-term patterns of body size evolution in Crocodylomorpha, the > 200-million-year-old group that includes living crocodylians and their extinct relatives. Extant crocodylians are mostly large-bodied (3–7 m) predators. However, extinct crocodylomorphs exhibit a wider range of phenotypes, and many of the earliest taxa were much smaller ( Results: Crocodylomorphs reached an early peak in body size disparity during the Late Jurassic, and underwent an essentially continual decline since then. A multi-peak Ornstein-Uhlenbeck model outperforms all other evolutionary models fitted to our data (including both uniform and non-uniform), indicating that the macroevolutionary dynamics of crocodylomorph body size are better described within the concept of an adaptive landscape, with most body size variation emerging after shifts to new macroevolutionary regimes (analogous to adaptive zones). We did not find support for a consistent evolutionary trend towards larger sizes among lineages (i.e., Cope’s rule), or strong correlations of body size with climate. Instead, the intermediate to large body sizes of some crocodylomorphs are better explained by group-specific adaptations. In particular, the evolution of a more aquatic lifestyle (especially marine) correlates with increases in average body size, though not without exceptions. Conclusions: Shifts between macroevolutionary regimes provide a better explanation of crocodylomorph body size evolution on large phylogenetic and temporal scales, suggesting a central role for lineage-specific adaptations rather than climatic forcing. Shifts leading to larger body sizes occurred in most aquatic and semi-aquatic groups. This, combined with extinctions of groups occupying smaller body size regimes (particularly during the Late Cretaceous and Cenozoic), gave rise to the upward-shifted body size distribution of extant crocodylomorphs compared to their smaller-bodied terrestrial ancestors.</p

Rheumatoid arthritis - clinical aspects: 134. Predictors of Joint Damage in South Africans with Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) causes progressive joint damage and functional disability. Studies on factors affecting joint damage as clinical outcome are lacking in Africa. The aim of the present study was to identify predictors of joint damage in adult South Africans with established RA. Methods: A cross-sectional study of 100 black patients with RA of >5 years were assessed for joint damage using a validated clinical method, the RA articular damage (RAAD) score. Potential predictors of joint damage that were documented included socio-demographics, smoking, body mass index (BMI), disease duration, delay in disease modifying antirheumatic drug (DMARD) initiation, global disease activity as measured by the disease activity score (DAS28), erythrocyte sedimentation rate (ESR), C reactive protein (CRP), and autoantibody status. The predictive value of variables was assessed by univariate and stepwise multivariate regression analyses. A p value <0.05 was considered significant. Results: The mean (SD) age was 56 (9.8) years, disease duration 17.5 (8.5) years, educational level 7.5 (3.5) years and DMARD lag was 9 (8.8) years. Female to male ratio was 10:1. The mean (SD) DAS28 was 4.9 (1.5) and total RAAD score was 28.3 (12.8). The mean (SD) BMI was 27.2 kg/m2 (6.2) and 93% of patients were rheumatoid factor (RF) positive. More than 90% of patients received between 2 to 3 DMARDs. Significant univariate predictors of a poor RAAD score were increasing age (p = 0.001), lower education level (p = 0.019), longer disease duration (p < 0.001), longer DMARD lag (p = 0.014), lower BMI (p = 0.025), high RF titre (p < 0.001) and high ESR (p = 0.008). The multivariate regression analysis showed that the only independent significant predictors of a higher mean RAAD score were older age at disease onset (p = 0.04), disease duration (p < 0.001) and RF titre (p < 0.001). There was also a negative association between BMI and the mean total RAAD score (p = 0.049). Conclusions: Patients with longstanding established RA have more severe irreversible joint damage as measured by the clinical RAAD score, contrary to other studies in Africa. This is largely reflected by a delay in the initiation of early effective treatment. Independent of disease duration, older age at disease onset and a higher RF titre are strongly associated with more joint damage. The inverse association between BMI and articular damage in RA has been observed in several studies using radiographic damage scores. The mechanisms underlying this paradoxical association are still widely unknown but adipokines have recently been suggested to play a role. Disclosure statement: C.I. has received a research grant from the Connective Tissue Diseases Research Fund, University of the Witwatersrand. All other authors have declared no conflicts of interes