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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 32 min ago

Fully-automatic left ventricular segmentation from long-axis cardiac cine MR scans.

Mon, 04/24/2017 - 05:59
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Fully-automatic left ventricular segmentation from long-axis cardiac cine MR scans.

Med Image Anal. 2017 Apr 13;39:44-55

Authors: Shahzad R, Tao Q, Dzyubachyk O, Staring M, Lelieveldt BPF, van der Geest RJ

Abstract
With an increasing number of large-scale population-based cardiac magnetic resonance (CMR) imaging studies being conducted nowadays, there comes the mammoth task of image annotation and image analysis. Such population-based studies would greatly benefit from automated pipelines, with an efficient CMR image analysis workflow. The purpose of this work is to investigate the feasibility of using a fully-automatic pipeline to segment the left ventricular endocardium and epicardium simultaneously on two orthogonal (vertical and horizontal) long-axis cardiac cine MRI scans. The pipeline is based on a multi-atlas-based segmentation approach and a spatio-temporal registration approach. The performance of the method was assessed by: (i) comparing the automatic segmentations to those obtained manually at both the end-diastolic and end-systolic phase, (ii) comparing the automatically obtained clinical parameters, including end-diastolic volume, end-systolic volume, stroke volume and ejection fraction, with those defined manually and (iii) by the accuracy of classifying subjects to the appropriate risk category based on the estimated ejection fraction. Automatic segmentation of the left ventricular endocardium was achieved with a Dice similarity coefficient (DSC) of 0.93 on the end-diastolic phase for both the vertical and horizontal long-axis scan; on the end-systolic phase the DSC was 0.88 and 0.85, respectively. For the epicardium, a DSC of 0.94 and 0.95 was obtained on the end-diastolic vertical and horizontal long-axis scans; on the end-systolic phase the DSC was 0.90 and 0.88, respectively. With respect to the clinical volumetric parameters, Pearson correlation coefficient (R) of 0.97 was obtained for the end-diastolic volume, 0.95 for end-systolic volume, 0.87 for stroke volume and 0.84 for ejection fraction. Risk category classification based on ejection fraction showed that 80% of the subjects were assigned to the correct risk category and only one subject (< 1%) was more than one risk category off. We conclude that the proposed automatic pipeline presents a viable and cost-effective alternative for manual annotation.

PMID: 28432954 [PubMed - as supplied by publisher]

Predicting clinical benefit from everolimus in patients with advanced solid tumors, the CPCT-03 study.

Sat, 04/22/2017 - 02:18
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Predicting clinical benefit from everolimus in patients with advanced solid tumors, the CPCT-03 study.

Oncotarget. 2017 Mar 08;:

Authors: Weeber F, Cirkel GA, Hoogstraat M, Bins S, Gadellaa-van Hooijdonk CGM, Ooft S, van Werkhoven E, Willems SM, van Stralen M, Veldhuis WB, Besselink NJM, Horlings HM, Steeghs N, de Jonge MJ, Langenberg MHG, Wessels LFA, Cuppen EPJG, Schellens JH, Sleijfer S, Lolkema MP, Voest EE

Abstract
BACKGROUND: In this study, our aim was to identify molecular aberrations predictive for response to everolimus, an mTOR inhibitor, regardless of tumor type.
METHODS: To generate hypotheses about potential markers for sensitivity to mTOR inhibition, drug sensitivity and genomic profiles of 835 cell lines were analyzed. Subsequently, a multicenter study was conducted. Patients with advanced solid tumors lacking standard of care treatment options were included and underwent a pre-treatment tumor biopsy to enable DNA sequencing of 1,977 genes, derive copy number profiles and determine activation status of pS6 and pERK. Treatment benefit was determined according to TTP ratio and RECIST. We tested for associations between treatment benefit and single molecular aberrations, clusters of aberrations and pathway perturbation.
RESULTS: Cell line screens indicated several genes, such as PTEN (P = 0.016; Wald test), to be associated with sensitivity to mTOR inhibition. Subsequently 73 patients were included, of which 59 started treatment with everolimus. Response and molecular data were available from 43 patients. PTEN aberrations, i.e. copy number loss or mutation, were associated with treatment benefit (P = 0.046; Fisher's exact test).
CONCLUSION: Loss-of-function aberrations in PTEN potentially represent a tumor type agnostic biomarker for benefit from everolimus and warrants further confirmation in subsequent studies.

PMID: 28423691 [PubMed - as supplied by publisher]

Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer.

Sun, 04/16/2017 - 21:53
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Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer.

Oncotarget. 2017 Mar 15;8(13):20572-20587

Authors: Gallenne T, Ross KN, Visser NL, Salony, Desmet CJ, Wittner BS, Wessels LFA, Ramaswamy S, Peeper DS

Abstract
Prognostic classifiers conceivably comprise biomarker genes that functionally contribute to the oncogenic and metastatic properties of cancer, but this has not been investigated systematically. The transcription factor Fra-1 not only has an essential role in breast cancer, but also drives the expression of a highly prognostic gene set. Here, we systematically perturbed the function of 31 individual Fra-1-dependent poor-prognosis genes and examined their impact on breast cancer growth in vivo. We find that stable shRNA depletion of each of nine individual signature genes strongly inhibits breast cancer growth and aggressiveness. Several factors within this nine-gene set regulate each other's expression, suggesting that together they form a network. The nine-gene set is regulated by estrogen, ERBB2 and EGF signaling, all established breast cancer factors. We also uncover three transcription factors, MYC, E2F1 and TP53, which act alongside Fra-1 at the core of this network. ChIP-Seq analysis reveals that a substantial number of genes are bound, and regulated, by all four transcription factors. The nine-gene set retains significant prognostic power and includes several potential therapeutic targets, including the bifunctional enzyme PAICS, which catalyzes purine biosynthesis. Depletion of PAICS largely cancelled breast cancer expansion, exemplifying a prognostic gene with breast cancer activity. Our data uncover a core genetic and prognostic network driving human breast cancer. We propose that pharmacological inhibition of components within this network, such as PAICS, may be used in conjunction with the Fra-1 prognostic classifier towards personalized management of poor prognosis breast cancer.

PMID: 28411283 [PubMed - in process]

Multilevel models improve precision and speed of IC50 estimates.

Wed, 03/29/2017 - 06:36
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Multilevel models improve precision and speed of IC50 estimates.

Pharmacogenomics. 2016 05;17(7):691-700

Authors: Vis DJ, Bombardelli L, Lightfoot H, Iorio F, Garnett MJ, Wessels LF

Abstract
AIM: Experimental variation in dose-response data of drugs tested on cell lines result in inaccuracies in the estimate of a key drug sensitivity characteristic: the IC50. We aim to improve the precision of the half-limiting dose (IC50) estimates by simultaneously employing all dose-responses across all cell lines and drugs, rather than using a single drug-cell line response.
MATERIALS & METHODS: We propose a multilevel mixed effects model that takes advantage of all available dose-response data.
RESULTS: The new estimates are highly concordant with the currently used Bayesian model when the data are well behaved. Otherwise, the multilevel model is clearly superior.
CONCLUSION: The multilevel model yields a significant reduction of extreme IC50 estimates, an increase in precision and it runs orders of magnitude faster.

PMID: 27180993 [PubMed - indexed for MEDLINE]

Transcription factors of Schizophyllum commune involved in mushroom formation and modulation of vegetative growth.

Sat, 03/25/2017 - 02:36
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Transcription factors of Schizophyllum commune involved in mushroom formation and modulation of vegetative growth.

Sci Rep. 2017 Mar 22;7(1):310

Authors: Pelkmans JF, Patil MB, Gehrmann T, Reinders MJ, Wösten HA, Lugones LG

Abstract
Mushrooms are the most conspicuous fungal structures. Transcription factors (TFs) Bri1 and Hom1 of the model fungus Schizophyllum commune are involved in late stages of mushroom development, while Wc-2, Hom2, and Fst4 function early in development. Here, it is shown that Bri1 and Hom1 also stimulate vegetative growth, while biomass formation is repressed by Wc-2, Hom2, and Fst4. The Δbri1Δbri1 and the Δhom1Δhom1 strains formed up to 0.6 fold less biomass when compared to wild-type, while Δwc-2Δwc-2, Δhom2Δhom2, and Δfst4Δfst4 strains formed up to 2.8 fold more biomass. Inactivation of TF gene tea1, which was downregulated in the Δwc-2Δwc-2, Δhom2Δhom2, and Δfst4Δfst4 strains, resulted in a strain that was severely affected in mushroom development and that produced 1.3 fold more biomass than the wild-type. In contrast, introducing a constitutive active version of hom2 that had 4 predicted phosphorylation motifs eliminated resulted in radial growth inhibition and prompt fructification in both Δhom2 and wild-type strains, even in sterile monokaryons. Together, it is concluded that TFs involved in mushroom formation also modulate vegetative growth. Among these TFs is the homeodomain protein Hom2, being the first time that this class of regulatory proteins is implicated in repression of vegetative growth in a eukaryote.

PMID: 28331193 [PubMed - in process]

Towards a Global Cancer Knowledge Network: Dissecting the current international cancer genomic sequencing landscape.

Fri, 03/24/2017 - 01:56
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Towards a Global Cancer Knowledge Network: Dissecting the current international cancer genomic sequencing landscape.

Ann Oncol. 2017 Feb 03;:

Authors: Vis DJ, Lewin J, Liao RG, Mao M, Andre F, Ward RL, Calvo F, Teh BT, Camargo AA, Knoppers BM, Sawyers C, Wessels LF, Lawler M, Siu LL, Voest E, behalf of the Clinical Working Group of the Global Alliance for Genomics and Health

Abstract
Background: While next generation sequencing has enhanced our understanding of the biological basis of malignancy, current knowledge on global practices for sequencing cancer samples is limited. To address this deficiency, we developed a survey to provide a snapshot of current sequencing activities globally, identify barriers to data sharing and use this information to develop sustainable solutions for the cancer research community.
Methods: A multi-item survey was conducted assessing demographics, clinical data collection, genomic platforms, privacy/ethics concerns, funding sources and data sharing barriers for sequencing initiatives globally. Additionally, respondents were asked as to provide the primary intent of their initiative (Clinical Diagnostic, Research or Combination).
Results: Of 107 initiatives invited to participate, 59 responded (response rate=55%). Whole Exome Sequencing ( p =0.03) and Whole Genome Sequencing ( p =  0.01), were utilized less frequently in Clinical Diagnostic than in Research initiatives. Procedures to identify cancer-specific variants were heterogeneous, with bioinformatics pipelines employing different mutation calling/variant annotation algorithms. Measurement of treatment efficacy varied amongst initiatives, with time on treatment (57%) and RECIST (53%) being the most common however; other parameters were also employed. Whilst 72% of initiatives indicated data sharing, its scope varied, with a number of restrictions in place (e.g. transfer of raw data). The largest perceived barriers to data harmonisation were the lack of financial support ( p <  0.01) and bioinformatics concerns (e.g. lack of interoperability)( p =  0.02). Capturing clinical data was more likely to be perceived as a barrier to data sharing by larger initiatives than by smaller initiatives ( p =  0.01).
Conclusions: These results identify the main barriers, as perceived by the cancer sequencing community, to effective sharing of cancer genomic and clinical data. They highlight the need for greater harmonisation of technical, ethical and data capture processes in cancer sample sequencing worldwide, in order to support effective and responsible data sharing for the benefit of patients.

PMID: 28327897 [PubMed - as supplied by publisher]

Detection of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Longitudinal Brain MRI.

Tue, 03/14/2017 - 19:07
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Detection of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Longitudinal Brain MRI.

Front Neuroinform. 2017;11:16

Authors: Sun Z, van de Giessen M, Lelieveldt BP, Staring M

Abstract
Mild Cognitive Impairment (MCI) is an intermediate stage between healthy and Alzheimer's disease (AD). To enable early intervention it is important to identify the MCI subjects that will convert to AD in an early stage. In this paper, we provide a new method to distinguish between MCI patients that either convert to Alzheimer's Disease (MCIc) or remain stable (MCIs), using only longitudinal T1-weighted MRI. Currently, most longitudinal studies focus on volumetric comparison of a few anatomical structures, thereby ignoring more detailed development inside and outside those structures. In this study we propose to exploit the anatomical development within the entire brain, as found by a non-rigid registration approach. Specifically, this anatomical development is represented by the Stationary Velocity Field (SVF) from registration between the baseline and follow-up images. To make the SVFs comparable among subjects, we use the parallel transport method to align them in a common space. The normalized SVF together with derived features are then used to distinguish between MCIc and MCIs subjects. This novel feature space is reduced using a Kernel Principal Component Analysis method, and a linear support vector machine is used as a classifier. Extensive comparative experiments are performed to inspect the influence of several aspects of our method on classification performance, specifically the feature choice, the smoothing parameter in the registration and the use of dimensionality reduction. The optimal result from a 10-fold cross-validation using 36 month follow-up data shows competitive results: accuracy 92%, sensitivity 95%, specificity 90%, and AUC 94%. Based on the same dataset, the proposed approach outperforms two alternative ones that either depends on the baseline image only, or uses longitudinal information from larger brain areas. Good results were also obtained when scans at 6, 12, or 24 months were used for training the classifier. Besides the classification power, the proposed method can quantitatively compare brain regions that have a significant difference in development between the MCIc and MCIs groups.

PMID: 28286479 [PubMed - in process]

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]