Modelling multiscale aspects of colorectal cancer

Colorectal cancer (CRC) is responsible for nearly half a million deaths annually world-wide [11]. We present a series of mathematical models describing the dynamics of the intestinal epithelium and the kinetics of the molecular pathway most commonly mutated in CRC, the Wnt signalling network. We also discuss how we are coupling such models to build a multiscale model of normal and aberrant guts. This will enable us to combine disparate experimental and clinical data, to investigate interactions between phenomena taking place at different levels of organisation and, eventually, to test the efficacy of new drugs on the system as a whole

Italia : las jóvenes de hoy

CDX1 is a transcription factor that plays a key role in intestinal development and differentiation. However, the downstream targets of CDX1 are less well defined than those of its close homologue, CDX2. We report here the identification of downstream targets of CDX1 using microarray gene-expression analysis and other approaches. Keratin 20 (KRT20), a member of the intermediate filament and a well-known marker of intestinal differentiation, was initially identified as one of the genes likely to be directly regulated by CDX1. CDX1 and KRT20 mRNA expression were significantly correlated in a panel of 38 colorectal cancer cell lines. Deletion and mutation analysis of the KRT20 promoter showed that the minimum regulatory region for the control of KRT20 expression by CDX1 is within 246 bp upstream of the KRT20 transcription start site. ChIP analysis confirmed that CDX1 binds to the predicted CDX elements in this region of the KRT20 promoter in vivo. In addition, immunohistochemistry showed expression of CDX1 parallels that of KRT20 in the normal crypt, which further supports their close relationship. In summary, our observations strongly imply that KRT20 is directly regulated by CDX1, and therefore suggest a role for CDX1 in maintaining differentiation in intestinal epithelial cells. Because a key feature of the development of a cancer is an unbalanced program of proliferation and differentiation, dysregulation of CDX1 may be an advantage for the development of a colorectal carcinoma. This could, therefore, explain the relatively frequent down regulation of CDX1 in colorectal carcinomas by hypermethylation

Single-molecule DNA-mapping and whole-genome sequencing of individual cells

To elucidate cellular diversity and clonal evolution in tissues and tumors, one must resolve genomic heterogeneity in single cells. To this end, we have developed low-cost, mass-producible micro-/nanofluidic chips for DNA extraction from individual cells. These chips have modules that collect genomic DNA for sequencing or map genomic structure directly, on-chip, with denaturation-renaturation (D-R) optical mapping [Marie R, et al. (2013) Proc Natl Acad Sci USA 110:4893-4898]. Processing of single cells from the LS174T colorectal cancer cell line showed that D-R mapping of single molecules can reveal structural variation (SV) in the genome of single cells. In one experiment, we processed 17 fragments covering 19.8 Mb of the cell's genome. One megabase-large fragment aligned well to chromosome 19 with half its length, while the other half showed variable alignment. Paired-end single-cell sequencing supported this finding, revealing a region of complexity and a 50-kb deletion. Sequencing struggled, however, to detect a 20-kb gap that D-R mapping showed clearly in a megabase fragment that otherwise mapped well to the reference at the pericentromeric region of chromosome 4. Pericentromeric regions are complex and show substantial sequence homology between different chromosomes, making mapping of sequence reads ambiguous. Thus, D-R mapping directly, from a single molecule, revealed characteristics of the single-cell genome that were challenging for short-read sequencing

Strange Quark Matter and Compact Stars

Astrophysicists distinguish between three different types of compact stars. These are white dwarfs, neutron stars, and black holes. The former contain matter in one of the densest forms found in the Universe which, together with the unprecedented progress in observational astronomy, make such stars superb astrophysical laboratories for a broad range of most striking physical phenomena. These range from nuclear processes on the stellar surface to processes in electron degenerate matter at subnuclear densities to boson condensates and the existence of new states of baryonic matter--like color superconducting quark matter--at supernuclear densities. More than that, according to the strange matter hypothesis strange quark matter could be more stable than nuclear matter, in which case neutron stars should be largely composed of pure quark matter possibly enveloped in thin nuclear crusts. Another remarkable implication of the hypothesis is the possible existence of a new class of white dwarfs. This article aims at giving an overview of all these striking physical possibilities, with an emphasis on the astrophysical phenomenology of strange quark matter. Possible observational signatures associated with the theoretically proposed states of matter inside compact stars are discussed as well. They will provide most valuable information about the phase diagram of superdense nuclear matter at high baryon number density but low temperature, which is not accessible to relativistic heavy ion collision experiments.Comment: 58 figures, to appear in "Progress in Particle and Nuclear Physics"; References added for sections 1,2,3,5; Equation (116) corrected; Figs. 1 and 58 update

Commercial Nucleic-Acid Amplification Tests for Diagnosis of Pulmonary Tuberculosis in Respiratory Specimens: Meta-Analysis and Meta-Regression

BACKGROUND: Hundreds of studies have evaluated the diagnostic accuracy of nucleic-acid amplification tests (NAATs) for tuberculosis (TB). Commercial tests have been shown to give more consistent results than in-house assays. Previous meta-analyses have found high specificity but low and highly variable estimates of sensitivity. However, reasons for variability in study results have not been adequately explored. We performed a meta-analysis on the accuracy of commercial NAATs to diagnose pulmonary TB and meta-regression to identify factors that are associated with higher accuracy. METHODOLOGY/PRINCIPAL FINDINGS: We identified 2948 citations from searching the literature. We found 402 articles that met our eligibility criteria. In the final analysis, 125 separate studies from 105 articles that reported NAAT results from respiratory specimens were included. The pooled sensitivity was 0.85 (range 0.36-1.00) and the pooled specificity was 0.97 (range 0.54-1.00). However, both measures were significantly heterogeneous (p<.001). We performed subgroup and meta-regression analyses to identify sources of heterogeneity. Even after stratifying by type of commercial test, we could not account for the variability. In the meta-regression, the threshold effect was significant (p = .01) and the use of other respiratory specimens besides sputum was associated with higher accuracy. CONCLUSIONS/SIGNIFICANCE: The sensitivity and specificity estimates for commercial NAATs in respiratory specimens were highly variable, with sensitivity lower and more inconsistent than specificity. Thus, summary measures of diagnostic accuracy are not clinically meaningful. The use of different cut-off values and the use of specimens other than sputum could explain some of the observed heterogeneity. Based on these observations, commercial NAATs alone cannot be recommended to replace conventional tests for diagnosing pulmonary TB. Improvements in diagnostic accuracy, particularly sensitivity, need to be made in order for this expensive technology to be worthwhile and beneficial in low-resource countries

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

A global reference for human genetic variation

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Däkel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche duQuébec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute