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NCBI: db=pubmed; Term=Delft[Affiliation] AND (Reinders M[Author] OR Abeel T[Author] OR Wessels L[Author] OR de Ridder J[Author] OR Lelieveldt B[Author] OR van Ham R[Author])
Updated: 14 hours 20 min ago

Automated Ischemic Lesion Segmentation in MRI Mouse Brain Data after Transient Middle Cerebral Artery Occlusion.

Thu, 02/16/2017 - 17:09

Automated Ischemic Lesion Segmentation in MRI Mouse Brain Data after Transient Middle Cerebral Artery Occlusion.

Front Neuroinform. 2017;11:3

Authors: Mulder IA, Khmelinskii A, Dzyubachyk O, de Jong S, Rieff N, Wermer MJ, Hoehn M, Lelieveldt BP, van den Maagdenberg AM

Abstract
Magnetic resonance imaging (MRI) has become increasingly important in ischemic stroke experiments in mice, especially because it enables longitudinal studies. Still, quantitative analysis of MRI data remains challenging mainly because segmentation of mouse brain lesions in MRI data heavily relies on time-consuming manual tracing and thresholding techniques. Therefore, in the present study, a fully automated approach was developed to analyze longitudinal MRI data for quantification of ischemic lesion volume progression in the mouse brain. We present a level-set-based lesion segmentation algorithm that is built using a minimal set of assumptions and requires only one MRI sequence (T2) as input. To validate our algorithm we used a heterogeneous data set consisting of 121 mouse brain scans of various age groups and time points after infarct induction and obtained using different MRI hardware and acquisition parameters. We evaluated the volumetric accuracy and regional overlap of ischemic lesions segmented by our automated method against the ground truth obtained in a semi-automated fashion that includes a highly time-consuming manual correction step. Our method shows good agreement with human observations and is accurate on heterogeneous data, whilst requiring much shorter average execution time. The algorithm developed here was compiled into a toolbox and made publically available, as well as all the data sets.

PMID: 28197090 [PubMed - in process]

Toward optical guidance during endoscopic ultrasound-guided fine needle aspirations of pancreatic masses using single fiber reflectance spectroscopy: a feasibility study.

Fri, 02/10/2017 - 09:51
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Toward optical guidance during endoscopic ultrasound-guided fine needle aspirations of pancreatic masses using single fiber reflectance spectroscopy: a feasibility study.

J Biomed Opt. 2017 Feb 01;22(2):24001

Authors: Stegehuis PL, Boogerd LS, Inderson A, Veenendaal RA, van Gerven P, Bonsing BA, Sven Mieog J, Amelink A, Veselic M, Morreau H, van de Velde CJ, Lelieveldt BP, Dijkstra J, Robinson DJ, Vahrmeijer AL

PMID: 28170030 [PubMed - in process]

Estrogen receptor α wields treatment-specific enhancers between morphologically similar endometrial tumors.

Fri, 02/10/2017 - 09:51
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Estrogen receptor α wields treatment-specific enhancers between morphologically similar endometrial tumors.

Proc Natl Acad Sci U S A. 2017 Feb 06;:

Authors: Droog M, Nevedomskaya E, Dackus GM, Fles R, Kim Y, Hollema H, Mourits M, Nederlof PM, van Boven HH, Linn SC, van Leeuwen FE, Wessels LF, Zwart W

Abstract
The DNA-binding sites of estrogen receptor α (ERα) show great plasticity under the control of hormones and endocrine therapy. Tamoxifen is a widely applied therapy in breast cancer that affects ERα interactions with coregulators and shifts the DNA-binding signature of ERα upon prolonged exposure in breast cancer. Although tamoxifen inhibits the progression of breast cancer, it increases the risk of endometrial cancer in postmenopausal women. We therefore asked whether the DNA-binding signature of ERα differs between endometrial tumors that arise in the presence or absence of tamoxifen, indicating divergent enhancer activity for tumors that develop in different endocrine milieus. Using ChIP sequencing (ChIP-seq), we compared the ERα profiles of 10 endometrial tumors from tamoxifen users with those of six endometrial tumors from nonusers and integrated these results with the transcriptomic data of 47 endometrial tumors from tamoxifen users and 64 endometrial tumors from nonusers. The ERα-binding sites in tamoxifen-associated endometrial tumors differed from those in the tumors from nonusers and had distinct underlying DNA sequences and divergent enhancer activity as marked by histone 3 containing the acetylated lysine 27 (H3K27ac). Because tamoxifen acts as an agonist in the postmenopausal endometrium, similar to estrogen in the breast, we compared ERα sites in tamoxifen-associated endometrial cancers with publicly available ERα ChIP-seq data in breast tumors and found a striking resemblance in the ERα patterns of the two tissue types. Our study highlights the divergence between endometrial tumors that arise in different hormonal conditions and shows that ERα enhancer use in human cancer differs in the presence of nonphysiological endocrine stimuli.

PMID: 28167798 [PubMed - as supplied by publisher]

BrainScope: interactive visual exploration of the spatial and temporal human brain transcriptome.

Tue, 01/31/2017 - 22:27
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BrainScope: interactive visual exploration of the spatial and temporal human brain transcriptome.

Nucleic Acids Res. 2017 Jan 27;:

Authors: Huisman SM, van Lew B, Mahfouz A, Pezzotti N, Höllt T, Michielsen L, Vilanova A, Reinders MJ, Lelieveldt BP

Abstract
Spatial and temporal brain transcriptomics has recently emerged as an invaluable data source for molecular neuroscience. The complexity of such data poses considerable challenges for analysis and visualization. We present BrainScope: a web portal for fast, interactive visual exploration of the Allen Atlases of the adult and developing human brain transcriptome. Through a novel methodology to explore high-dimensional data (dual t-SNE), BrainScope enables the linked, all-in-one visualization of genes and samples across the whole brain and genome, and across developmental stages. We show that densities in t-SNE scatter plots of the spatial samples coincide with anatomical regions, and that densities in t-SNE scatter plots of the genes represent gene co-expression modules that are significantly enriched for biological functions. We also show that the topography of the gene t-SNE maps reflect brain region-specific gene functions, enabling hypothesis and data driven research. We demonstrate the discovery potential of BrainScope through three examples: (i) analysis of cell type specific gene sets, (ii) analysis of a set of stable gene co-expression modules across the adult human donors and (iii) analysis of the evolution of co-expression of oligodendrocyte specific genes over developmental stages. BrainScope is publicly accessible at www.brainscope.nl.

PMID: 28132031 [PubMed - as supplied by publisher]

The transcriptional regulator c2h2 accelerates mushroom formation in Agaricus bisporus.

Tue, 01/31/2017 - 22:27
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The transcriptional regulator c2h2 accelerates mushroom formation in Agaricus bisporus.

Appl Microbiol Biotechnol. 2016 Aug;100(16):7151-9

Authors: Pelkmans JF, Vos AM, Scholtmeijer K, Hendrix E, Baars JJ, Gehrmann T, Reinders MJ, Lugones LG, Wösten HA

Abstract
The Cys2His2 zinc finger protein gene c2h2 of Schizophyllum commune is involved in mushroom formation. Its inactivation results in a strain that is arrested at the stage of aggregate formation. In this study, the c2h2 orthologue of Agaricus bisporus was over-expressed in this white button mushroom forming basidiomycete using Agrobacterium-mediated transformation. Morphology, cap expansion rate, and total number and biomass of mushrooms were not affected by over-expression of c2h2. However, yield per day of the c2h2 over-expression strains peaked 1 day earlier. These data and expression analysis indicate that C2H2 impacts timing of mushroom formation at an early stage of development, making its encoding gene a target for breeding of commercial mushroom strains.

PMID: 27207144 [PubMed - indexed for MEDLINE]

Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance.

Wed, 01/18/2017 - 10:59
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Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance.

Nat Genet. 2017 Jan 16;:

Authors: Manson AL, Cohen KA, Abeel T, Desjardins CA, Armstrong DT, Barry CE, Brand J, TBResist Global Genome Consortium, Chapman SB, Cho SN, Gabrielian A, Gomez J, Jodals AM, Joloba M, Jureen P, Lee JS, Malinga L, Maiga M, Nordenberg D, Noroc E, Romancenco E, Salazar A, Ssengooba W, Velayati AA, Winglee K, Zalutskaya A, Via LE, Cassell GH, Dorman SE, Ellner J, Farnia P, Galagan JE, Rosenthal A, Crudu V, Homorodean D, Hsueh PR, Narayanan S, Pym AS, Skrahina A, Swaminathan S, Van der Walt M, Alland D, Bishai WR, Cohen T, Hoffner S, Birren BW, Earl AM

Abstract
Multidrug-resistant tuberculosis (MDR-TB), caused by drug-resistant strains of Mycobacterium tuberculosis, is an increasingly serious problem worldwide. Here we examined a data set of whole-genome sequences from 5,310 M. tuberculosis isolates from five continents. Despite the great diversity of these isolates with respect to geographical point of isolation, genetic background and drug resistance, the patterns for the emergence of drug resistance were conserved globally. We have identified harbinger mutations that often precede multidrug resistance. In particular, the katG mutation encoding p.Ser315Thr, which confers resistance to isoniazid, overwhelmingly arose before mutations that conferred rifampicin resistance across all of the lineages, geographical regions and time periods. Therefore, molecular diagnostics that include markers for rifampicin resistance alone will be insufficient to identify pre-MDR strains. Incorporating knowledge of polymorphisms that occur before the emergence of multidrug resistance, particularly katG p.Ser315Thr, into molecular diagnostics should enable targeted treatment of patients with pre-MDR-TB to prevent further development of MDR-TB.

PMID: 28092681 [PubMed - as supplied by publisher]

A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence.

Mon, 12/19/2016 - 05:48
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A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence.

Genome Biol. 2016 Dec 16;17(1):261

Authors: Canisius S, Martens JW, Wessels LF

Abstract
In cancer, mutually exclusive or co-occurring somatic alterations across genes can suggest functional interactions. Existing tests for such patterns make the unrealistic assumption of identical gene alteration probabilities across tumors. We present Discrete Independence Statistic Controlling for Observations with Varying Event Rates (DISCOVER), a novel test that is more sensitive than other methods and controls its false positive rate. A pan-cancer analysis using DISCOVER finds no evidence for widespread co-occurrence, and most co-occurrences previously detected do not exceed expectation by chance. Many mutual exclusivities are identified involving well-known genes related to cell cycle and growth factor signaling, as well as lesser known regulators of Hedgehog signaling.

PMID: 27986087 [PubMed - in process]

A Landscape of Pharmacogenomic Interactions in Cancer.

Fri, 12/16/2016 - 02:40
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A Landscape of Pharmacogenomic Interactions in Cancer.

Cell. 2016 Jul 28;166(3):740-54

Authors: Iorio F, Knijnenburg TA, Vis DJ, Bignell GR, Menden MP, Schubert M, Aben N, Gonçalves E, Barthorpe S, Lightfoot H, Cokelaer T, Greninger P, van Dyk E, Chang H, de Silva H, Heyn H, Deng X, Egan RK, Liu Q, Mironenko T, Mitropoulos X, Richardson L, Wang J, Zhang T, Moran S, Sayols S, Soleimani M, Tamborero D, Lopez-Bigas N, Ross-Macdonald P, Esteller M, Gray NS, Haber DA, Stratton MR, Benes CH, Wessels LF, Saez-Rodriguez J, McDermott U, Garnett MJ

Abstract
Systematic studies of cancer genomes have provided unprecedented insights into the molecular nature of cancer. Using this information to guide the development and application of therapies in the clinic is challenging. Here, we report how cancer-driven alterations identified in 11,289 tumors from 29 tissues (integrating somatic mutations, copy number alterations, DNA methylation, and gene expression) can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs. We find that cell lines faithfully recapitulate oncogenic alterations identified in tumors, find that many of these associate with drug sensitivity/resistance, and highlight the importance of tissue lineage in mediating drug response. Logic-based modeling uncovers combinations of alterations that sensitize to drugs, while machine learning demonstrates the relative importance of different data types in predicting drug response. Our analysis and datasets are rich resources to link genotypes with cellular phenotypes and to identify therapeutic options for selected cancer sub-populations.

PMID: 27397505 [PubMed - indexed for MEDLINE]

Populations of latent Mycobacterium tuberculosis lack a cell wall: Isolation, visualization, and whole-genome characterization.

Fri, 12/16/2016 - 02:40
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Populations of latent Mycobacterium tuberculosis lack a cell wall: Isolation, visualization, and whole-genome characterization.

Int J Mycobacteriol. 2016 Mar;5(1):66-73

Authors: Velayati AA, Abeel T, Shea T, Konstantinovich Zhavnerko G, Birren B, Cassell GH, Earl AM, Hoffner S, Farnia P

Abstract
OBJECTIVE/BACKGROUND: Mycobacterium tuberculosis (MTB) causes active tuberculosis (TB) in only a small percentage of infected people. In most cases, the infection is clinically latent, where bacilli can persist in human hosts for years without causing disease. Surprisingly, the biology of such persister cells is largely unknown. This study describes the isolation, identification, and whole-genome sequencing (WGS) of latent TB bacilli after 782days (26months) of latency (the ability of MTB bacilli to lie persistent).
METHODS: The in vitro double-stress model of latency (oxygen and nutrition) was designed for MTB culture. After 26months of latency, MTB cells that persisted were isolated and investigated under light and atomic force microscopy. Spoligotyping and WGS were performed to verify the identity of the strain.
RESULTS: We established a culture medium in which MTB bacilli arrest their growth, reduce their size (0.3-0.1μm), lose their acid fastness (85-90%) and change their shape. Spoligopatterns of latent cells were identical to original H37Rv, with differences observed at spacers two and 14. WGS revealed only a few genetic changes relative to the already published H37Rv reference genome. Among these was a large 2064-bp insertion (RvD6), which was originally detected in both H37Ra and CDC1551, but not H37Rv.
CONCLUSION: Here, we show cell-wall free cells of MTB bacilli in their latent state, and the biological adaptation of these cells was more phenotypic in nature than genomic. These cell-wall free cells represent a good model for understanding the nature of TB latency.

PMID: 26927992 [PubMed - indexed for MEDLINE]

Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer.

Fri, 12/16/2016 - 02:40
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Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer.

Sci Rep. 2016 Jan 05;6:18517

Authors: Michaut M, Chin SF, Majewski I, Severson TM, Bismeijer T, de Koning L, Peeters JK, Schouten PC, Rueda OM, Bosma AJ, Tarrant F, Fan Y, He B, Xue Z, Mittempergher L, Kluin RJ, Heijmans J, Snel M, Pereira B, Schlicker A, Provenzano E, Ali HR, Gaber A, O'Hurley G, Lehn S, Muris JJ, Wesseling J, Kay E, Sammut SJ, Bardwell HA, Barbet AS, Bard F, Lecerf C, O'Connor DP, Vis DJ, Benes CH, McDermott U, Garnett MJ, Simon IM, Jirström K, Dubois T, Linn SC, Gallagher WM, Wessels LF, Caldas C, Bernards R

Abstract
Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies.

PMID: 26729235 [PubMed - indexed for MEDLINE]

Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography.

Thu, 12/08/2016 - 19:06
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Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography.

J Biomed Opt. 2016 Dec 01;21(12):126005

Authors: Liu S, Eggermont J, Wolterbeek R, Broersen A, Busk CA, Precht H, Lelieveldt BP, Dijkstra J

PMID: 27926746 [PubMed - in process]

Brain transcriptome atlases: a computational perspective.

Sat, 12/03/2016 - 14:20
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Brain transcriptome atlases: a computational perspective.

Brain Struct Funct. 2016 Dec 1;

Authors: Mahfouz A, Huisman SM, Lelieveldt BP, Reinders MJ

Abstract
The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

PMID: 27909802 [PubMed - as supplied by publisher]

Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy.

Fri, 11/25/2016 - 07:12

Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy.

Sci Rep. 2016 Nov 23;6:36812

Authors: Knijnenburg TA, Klau GW, Iorio F, Garnett MJ, McDermott U, Shmulevich I, Wessels LF

Abstract
Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present 'Logic Optimization for Binary Input to Continuous Output' (LOBICO), a computational approach that infers small and easily interpretable logic models of binary input features that explain a continuous output variable. Applying LOBICO to a large cancer cell line panel, we find that logic combinations of multiple mutations are more predictive of drug response than single gene predictors. Importantly, we show that the use of the continuous information leads to robust and more accurate logic models. LOBICO implements the ability to uncover logic models around predefined operating points in terms of sensitivity and specificity. As such, it represents an important step towards practical application of interpretable logic models.

PMID: 27876821 [PubMed - in process]

Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data.

Mon, 10/31/2016 - 09:42
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Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data.

Proc Natl Acad Sci U S A. 2016 Oct 25;113(43):12244-12249

Authors: Abdelmoula WM, Balluff B, Englert S, Dijkstra J, Reinders MJ, Walch A, McDonnell LA, Lelieveldt BP

Abstract
The identification of tumor subpopulations that adversely affect patient outcomes is essential for a more targeted investigation into how tumors develop detrimental phenotypes, as well as for personalized therapy. Mass spectrometry imaging has demonstrated the ability to uncover molecular intratumor heterogeneity. The challenge has been to conduct an objective analysis of the resulting data to identify those tumor subpopulations that affect patient outcome. Here we introduce spatially mapped t-distributed stochastic neighbor embedding (t-SNE), a nonlinear visualization of the data that is able to better resolve the biomolecular intratumor heterogeneity. In an unbiased manner, t-SNE can uncover tumor subpopulations that are statistically linked to patient survival in gastric cancer and metastasis status in primary tumors of breast cancer.

PMID: 27791011 [PubMed - in process]