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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])
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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.

Fri, 06/16/2017 - 06:00
Related Articles

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 - indexed for MEDLINE]

Deletion of Polycomb Repressive Complex 2 From Mouse Intestine Causes Loss of Stem Cells.

Tue, 06/06/2017 - 19:58
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Deletion of Polycomb Repressive Complex 2 From Mouse Intestine Causes Loss of Stem Cells.

Gastroenterology. 2016 Oct;151(4):684-697.e12

Authors: Koppens MA, Bounova G, Gargiulo G, Tanger E, Janssen H, Cornelissen-Steijger P, Blom M, Song JY, Wessels LF, van Lohuizen M

Abstract
BACKGROUND & AIMS: The polycomb repressive complex 2 (PRC2) regulates differentiation by contributing to repression of gene expression and thereby stabilizing the fate of stem cells and their progeny. PRC2 helps to maintain adult stem cell populations, but little is known about its functions in intestinal stem cells. We studied phenotypes of mice with intestine-specific deletion of the PRC2 proteins embryonic ectoderm development (EED) (a subunit required for PRC2 function) and enhancer of zeste homolog 2 (EZH2) (a histone methyltransferase).
METHODS: We performed studies of AhCre;EedLoxP/LoxP (EED knockout) mice and AhCre;Ezh2LoxP/LoxP (EZH2 knockout) mice, which have intestine-specific disruption in EED and EZH2, respectively. Small intestinal crypts were isolated and subsequently cultured to grow organoids. Intestines and organoids were analyzed by immunohistochemical, in situ hybridization, RNA sequence, and chromatin immunoprecipitation methods.
RESULTS: Intestines of EED knockout mice had massive crypt degeneration and lower numbers of proliferating cells compared with wild-type control mice. Cdkn2a became derepressed and we detected increased levels of P21. We did not observe any differences between EZH2 knockout and control mice. Intestinal crypts from EED knockout mice had signs of aberrant differentiation of uncommitted crypt cells-these differentiated toward the secretory cell lineage. Furthermore, crypts from EED-knockout mice had impaired Wnt signaling and concomitant loss of intestinal stem cells, this phenotype was not reversed upon ectopic stimulation of Wnt and Notch signaling in organoids. Analysis of gene expression patterns from intestinal tissues of EED knockout mice showed dysregulation of several genes involved in Wnt signaling. Wnt signaling was regulated directly by PRC2.
CONCLUSIONS: In intestinal tissues of mice, PRC2 maintains small intestinal stem cells by promoting proliferation and preventing differentiation in the intestinal stem cell compartment. PRC2 controls gene expression in multiple signaling pathways that regulate intestinal homeostasis. Sequencing data are available in the genomics data repository GEO under reference series GSE81578; RNA sequencing data are available under subseries GSE81576; and ChIP sequencing data are available under subseries GSE81577.

PMID: 27342214 [PubMed - indexed for MEDLINE]

Identifying transposon insertions and their effects from RNA-sequencing data.

Sat, 06/03/2017 - 16:39
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Identifying transposon insertions and their effects from RNA-sequencing data.

Nucleic Acids Res. 2017 Jun 01;:

Authors: de Ruiter JR, Kas SM, Schut E, Adams DJ, Koudijs MJ, Wessels LFA, Jonkers J

Abstract
Insertional mutagenesis using engineered transposons is a potent forward genetic screening technique used to identify cancer genes in mouse model systems. In the analysis of these screens, transposon insertion sites are typically identified by targeted DNA-sequencing and subsequently assigned to predicted target genes using heuristics. As such, these approaches provide no direct evidence that insertions actually affect their predicted targets or how transcripts of these genes are affected. To address this, we developed IM-Fusion, an approach that identifies insertion sites from gene-transposon fusions in standard single- and paired-end RNA-sequencing data. We demonstrate IM-Fusion on two separate transposon screens of 123 mammary tumors and 20 B-cell acute lymphoblastic leukemias, respectively. We show that IM-Fusion accurately identifies transposon insertions and their true target genes. Furthermore, by combining the identified insertion sites with expression quantification, we show that we can determine the effect of a transposon insertion on its target gene(s) and prioritize insertions that have a significant effect on expression. We expect that IM-Fusion will significantly enhance the accuracy of cancer gene discovery in forward genetic screens and provide initial insight into the biological effects of insertions on candidate cancer genes.

PMID: 28575524 [PubMed - as supplied by publisher]

Comparing methods for fetal fraction determination and quality control of NIPT samples.

Thu, 06/01/2017 - 15:03

Comparing methods for fetal fraction determination and quality control of NIPT samples.

Prenat Diagn. 2017 May 31;:

Authors: van Beek DM, Straver R, Weiss MM, Boon EMJ, Amsterdam KH, Oudejans CBM, Reinders MJT, Sistermans EA

Abstract
OBJECTIVE: To compare available analysis methods for determining fetal fraction on single read Next Generation Sequencing data. This is important as the performance of Non-invasive Prenatal Testing procedures depends on the fraction of fetal DNA.
METHODS: We tested six different methods for the detection of fetal fraction in NIPT samples. The same clinically obtained data were used for all methods, allowing us to assess the effect of fetal fraction on the test result, and to investigate the use of fetal fraction for quality control.
RESULTS: We show that non-NIPT methods based on Body Mass Index (BMI) and gestational age are unreliable predictors of fetal fraction, male pregnancy specific methods based on read counts on the Y chromosome perform consistently, the fetal sex-independent new methods SeqFF and SANEFALCON are less reliable but can be used to obtain a basic indication of fetal fraction in case of a female fetus.
CONCLUSION: We recommend the use of a combination of methods to prevent the issue of reports on samples with insufficient fetal DNA; SANEFALCON to check for presence of fetal DNA, SeqFF for estimating the fetal fraction for a female pregnancy, any Y-based method for estimating the fetal fraction for a male pregnancy.

PMID: 28561435 [PubMed - as supplied by publisher]

Genomic and functional analyses of Mycobacterium tuberculosis strains implicate ald in D-cycloserine resistance.

Wed, 05/31/2017 - 14:20
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Genomic and functional analyses of Mycobacterium tuberculosis strains implicate ald in D-cycloserine resistance.

Nat Genet. 2016 May;48(5):544-51

Authors: Desjardins CA, Cohen KA, Munsamy V, Abeel T, Maharaj K, Walker BJ, Shea TP, Almeida DV, Manson AL, Salazar A, Padayatchi N, O'Donnell MR, Mlisana KP, Wortman J, Birren BW, Grosset J, Earl AM, Pym AS

Abstract
A more complete understanding of the genetic basis of drug resistance in Mycobacterium tuberculosis is critical for prompt diagnosis and optimal treatment, particularly for toxic second-line drugs such as D-cycloserine. Here we used the whole-genome sequences from 498 strains of M. tuberculosis to identify new resistance-conferring genotypes. By combining association and correlated evolution tests with strategies for amplifying signal from rare variants, we found that loss-of-function mutations in ald (Rv2780), encoding L-alanine dehydrogenase, were associated with unexplained drug resistance. Convergent evolution of this loss of function was observed exclusively among multidrug-resistant strains. Drug susceptibility testing established that ald loss of function conferred resistance to D-cycloserine, and susceptibility to the drug was partially restored by complementation of ald. Clinical strains with mutations in ald and alr exhibited increased resistance to D-cycloserine when cultured in vitro. Incorporation of D-cycloserine resistance in novel molecular diagnostics could allow for targeted use of this toxic drug among patients with susceptible infections.

PMID: 27064254 [PubMed - indexed for MEDLINE]

Characterization of pathogenic SORL1 genetic variants for association with Alzheimer's disease: a clinical interpretation strategy.

Sat, 05/27/2017 - 09:55
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Characterization of pathogenic SORL1 genetic variants for association with Alzheimer's disease: a clinical interpretation strategy.

Eur J Hum Genet. 2017 May 24;:

Authors: Holstege H, van der Lee SJ, Hulsman M, Wong TH, van Rooij JG, Weiss M, Louwersheimer E, Wolters FJ, Amin N, Uitterlinden AG, Hofman A, Ikram MA, van Swieten JC, Meijers-Heijboer H, van der Flier WM, Reinders MJ, van Duijn CM, Scheltens P

Abstract
Accumulating evidence suggests that genetic variants in the SORL1 gene are associated with Alzheimer disease (AD), but a strategy to identify which variants are pathogenic is lacking. In a discovery sample of 115 SORL1 variants detected in 1908 Dutch AD cases and controls, we identified the variant characteristics associated with SORL1 variant pathogenicity. Findings were replicated in an independent sample of 103 SORL1 variants detected in 3193 AD cases and controls. In a combined sample of the discovery and replication samples, comprising 181 unique SORL1 variants, we developed a strategy to classify SORL1 variants into five subtypes ranging from pathogenic to benign. We tested this pathogenicity screen in SORL1 variants reported in two independent published studies. SORL1 variant pathogenicity is defined by the Combined Annotation Dependent Depletion (CADD) score and the minor allele frequency (MAF) reported by the Exome Aggregation Consortium (ExAC) database. Variants predicted strongly damaging (CADD score >30), which are extremely rare (ExAC-MAF <1 × 10(-5)) increased AD risk by 12-fold (95% CI 4.2-34.3; P=5 × 10(-9)). Protein-truncating SORL1 mutations were all unknown to ExAC and occurred exclusively in AD cases. More common SORL1 variants (ExAC-MAF≥1 × 10(-5)) were not associated with increased AD risk, even when predicted strongly damaging. Findings were independent of gender and the APOE-ɛ4 allele. High-risk SORL1 variants were observed in a substantial proportion of the AD cases analyzed (2%). Based on their effect size, we propose to consider high-risk SORL1 variants next to variants in APOE, PSEN1, PSEN2 and APP for personalized risk assessments in clinical practice.European Journal of Human Genetics advance online publication, 24 May 2017; doi:10.1038/ejhg.2017.87.

PMID: 28537274 [PubMed - as supplied by publisher]

Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration.

Thu, 05/25/2017 - 08:04
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Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration.

Biomaterials. 2017 May 12;137:49-60

Authors: Hulshof FFB, Papenburg B, Vasilevich A, Hulsman M, Zhao Y, Levers M, Fekete N, de Boer M, Yuan H, Singh S, Beijer N, Bray MA, Logan DJ, Reinders M, Carpenter AE, van Blitterswijk C, Stamatialis D, de Boer J

Abstract
Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated.

PMID: 28535442 [PubMed - as supplied by publisher]

Mycobacterium tuberculosis Whole Genome Sequences From Southern India Suggest Novel Resistance Mechanisms and the Need for Region-Specific Diagnostics.

Sat, 05/13/2017 - 21:46
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Mycobacterium tuberculosis Whole Genome Sequences From Southern India Suggest Novel Resistance Mechanisms and the Need for Region-Specific Diagnostics.

Clin Infect Dis. 2017 May 12;:

Authors: Manson AL, Abeel T, Galagan JE, Sundaramurthi JC, Salazar A, Gehrmann T, Shanmugam SK, Palaniyandi K, Narayanan S, Swaminathan S, Earl AM

Abstract
Background.: India is home to 25% of all tuberculosis cases and the second highest number of multidrug resistant cases worldwide. However, little is known about the genetic diversity and resistance determinants of Indian Mycobacterium tuberculosis, particularly for the primary lineages found in India, lineages 1 and 3.
Methods.: We whole genome sequenced 223 randomly selected M. tuberculosis strains from 196 patients within the Tiruvallur and Madurai districts of Tamil Nadu in Southern India. Using comparative genomics, we examined genetic diversity, transmission patterns, and evolution of resistance.
Results.: Genomic analyses revealed (11) prevalence of strains from lineages 1 and 3, (11) recent transmission of strains among patients from the same treatment centers, (11) emergence of drug resistance within patients over time, (11) resistance gained in an order typical of strains from different lineages and geographies, (11) underperformance of known resistance-conferring mutations to explain phenotypic resistance in Indian strains relative to studies focused on other geographies, and (11) the possibility that resistance arose through mutations not previously implicated in resistance, or through infections with multiple strains that confound genotype-based prediction of resistance.
Conclusions.: In addition to substantially expanding the genomic perspectives of lineages 1 and 3, sequencing and analysis of M. tuberculosis whole genomes from Southern India highlight challenges of infection control and rapid diagnosis of resistant tuberculosis using current technologies. Further studies are needed to fully explore the complement of diversity and resistance determinants within endemic M. tuberculosis populations.

PMID: 28498943 [PubMed - as supplied by publisher]

Automatic quantification of bone marrow edema on MRI of the wrist in patients with early arthritis: A feasibility study.

Wed, 05/10/2017 - 19:01
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Automatic quantification of bone marrow edema on MRI of the wrist in patients with early arthritis: A feasibility study.

Magn Reson Med. 2017 May 07;:

Authors: Aizenberg E, Roex EAH, Nieuwenhuis WP, Mangnus L, van der Helm-van Mil AHM, Reijnierse M, Bloem JL, Lelieveldt BPF, Stoel BC

Abstract
PURPOSE: To investigate the feasibility of automatic quantification of bone marrow edema (BME) on MRI of the wrist in patients with early arthritis.
METHODS: For 485 early arthritis patients (clinically confirmed arthritis of one or more joints, symptoms for less than 2 years), MR scans of the wrist were processed in three automatic stages. First, super-resolution reconstruction was applied to fuse coronal and axial scans into a single high-resolution 3D image. Next, the carpal bones were located and delineated using atlas-based segmentation. Finally, the extent of BME within each bone was quantified by identifying image intensity values characteristic of BME by fuzzy clustering and measuring the fraction of voxels with these characteristic intensities within each bone. Correlation with visual BME scores was assessed through Pearson correlation coefficient.
RESULTS: Pearson correlation between quantitative and visual BME scores across 485 patients was r=0.83, P<0.001.
CONCLUSIONS: Quantitative measurement of BME on MRI of the wrist has the potential to provide a feasible alternative to visual scoring. Complete automation requires automatic detection and compensation of acquisition artifacts. Magn Reson Med, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

PMID: 28480581 [PubMed - as supplied by publisher]

Towards a global cancer knowledge network: dissecting the current international cancer genomic sequencing landscape.

Mon, 05/01/2017 - 12:47
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Towards a global cancer knowledge network: dissecting the current international cancer genomic sequencing landscape.

Ann Oncol. 2017 May 01;28(5):1145-1151

Authors: Vis DJ, Lewin J, Liao RG, Mao M, Andre F, Ward RL, Calvo F, Teh BT, Camargo AA, Knoppers BM, Sawyers CL, Wessels LFA, Lawler M, Siu LL, Voest E, 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 harmonization 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 harmonization 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: 28453708 [PubMed - in process]

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]