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8. VEDLIoT: Very Efficient Deep Learning in IoT

Author

Kaiser, Martin, Griessl, René, Kucza, Nils, Haumann, Carola, Tigges, Lennart, Mika, Kevin, Hagemeyer, Jens, Porrmann, Florian, Rückert, Ulrich, vor dem Berge, M., Krupop, S., Porrmann, M., Tassemeier, M., Trancoso, P., Qararyah, F., Zouzoula, S., Casimiro, A., Bessani, A., Cecilio, J., Andersson, S., Brunnegard, O., Eriksson, O., Weiss, R., Mcierhofer, F., Salomonsson, H., Malekzadeh, E., Odman, D., Khurshid, A., Felber, P., Pasin, M., Schiavoni, V., Menetrey, J., Gugala, K., Zierhoffer, P., Knauss, E., Heyn, H., and ARRAY(0xab8ee90)

Subjects
Performance (cs.PF), FOS: Computer and information sciences, Computer Science - Cryptography and Security, Computer Science - Performance, Computer Science - Distributed, Parallel, and Cluster Computing, Hardware Architecture (cs.AR), Distributed, Parallel, and Cluster Computing (cs.DC), Computer Science - Hardware Architecture, Cryptography and Security (cs.CR)
Abstract

The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also dealing with safety and security challenges. The approach is based on a modular and scalable cognitive IoT hardware platform. Using modular microserver technology enables the user to configure the hardware to satisfy a wide range of applications. VEDLIoT offers a complete design flow for Next-Generation IoT devices required for collaboratively solving complex Deep Learning applications across distributed systems. The methods are tested on various use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage with the first results available., Comment: This publication incorporates results from the VEDLIoT project, which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 957197

Published
2022

9. VEDLIoT: Very Efficient Deep Learning in IoT

Author

Kaiser, M., primary, Griessl, R., additional, Kucza, N., additional, Haumann, C., additional, Tigges, L., additional, Mika, K., additional, Hagemeyer, J., additional, Porrmann, F., additional, Ruckert, U., additional, vor dem Berge, M., additional, Krupop, S., additional, Porrmann, M., additional, Tassemeier, M., additional, Trancoso, P., additional, Qararyah, F., additional, Zouzoula, S., additional, Casimiro, A., additional, Bessani, A., additional, Cecilio, J., additional, Andersson, S., additional, Brunnegard, O., additional, Eriksson, O., additional, Weiss, R., additional, Mcierhofer, F., additional, Salomonsson, H., additional, Malekzadeh, E., additional, Odman, D., additional, Khurshid, A., additional, Felber, P., additional, Pasin, M., additional, Schiavoni, V., additional, Menetrey, J., additional, Gugala, K., additional, Zierhoffer, P., additional, Knauss, E., additional, and Heyn, H., additional

Published
2022
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11. LifeTime and improving European healthcare through cell-based interceptive medicine

Author

Rajewsky, N., Almouzni, G., Gorski, S., Aerts, S., Amit, I., Bertero, M., Bock, C., Bredenoord, A., Cavalli, G., Chiocca, S., Clevers, H., Strooper, B., Eggert, A., Ellenberg, J., Fernández, X., Figlerowicz, M., Gasser, S., Hubner, N., Kjems, J., Knoblich, J., Krabbe, G., Lichter, P., Linnarsson, S., Marine, J., Marioni, J., Marti-Renom, M., Netea, M., Nickel, D., Nollmann, M., Novak, H., Parkinson, H., Piccolo, S., Pinheiro, I., Pombo, A., Popp, C., Reik, W., Roman-Roman, S., Rosenstiel, P., Schultze, J., Stegle, O., Tanay, A., Testa, G., Thanos, D., Theis, F., Torres-Padilla, M., Valencia, A., Vallot, C., van Oudenaarden, A., Vidal, M., Voet, T., Alberi, L., Alexander, S., Alexandrov, T., Arenas, E., Bagni, C., Balderas, R., Bandelli, A., Becher, B., Becker, M., Beerenwinkel, N., Benkirame, M., Beyer, M., Bickmore, W., Biessen, E., Blomberg, N., Blumcke, I., Bodenmiller, B., Borroni, B., Boumpas, D., Bourgeron, T., Bowers, S., Braeken, D., Brooksbank, C., Brose, N., Bruining, H., Bury, J., Caporale, N., Cattoretti, G., Chabane, N., Chneiweiss, H., Cook, S., Curatolo, P., de Jonge, M., Deplancke, B., de Witte, P., Dimmeler, S., Draganski, B., Drews, A., Dumbrava, C., Engelhardt, S., Gasser, T., Giamarellos-Bourboulis, E., Graff, C., Grün, D., Gut, I., Hansson, O., Henshall, D., Herland, A., Heutink, P., Heymans, S., Heyn, H., Huch, M., Huitinga, I., Jackowiak, P., Jongsma, K., Journot, L., Junker, J., Katz, S., Kehren, J., Kempa, S., Kirchhof, P., Klein, C., Koralewska, N., Korbel, J., Kühnemund, M., Lamond, A., Lauwers, E., Le Ber, I., Leinonen, V., Tobon, A., Lundberg, E., Lunkes, A., Maatz, H., Mann, M., Marelli, L., Matser, V., Matthews, P., Mechta-Grigoriou, F., Menon, R., Nielsen, A., Pagani, M., Pasterkamp, R., Pitkänen, A., Popescu, V., Pottier, C., Puisieux, A., Rademakers, R., Reiling, D., Reiner, O., Remondini, D., Ritchie, C., Rohrer, J., Saliba, A., Sanchez-Valle, R., Santosuosso, A., Sauter, A., Scheltema, R., Scheltens, P., Schiller, H., Schneider, A., Seibler, P., Sheehan-Rooney, K., Shields, D., Sleegers, K., Smit, A., Smith, K., Smolders, I., Synofzik, M., Tam, W., Teichmann, S., Thom, M., Turco, M., van Beusekom, H., Vandenberghe, R., den Hoecke, S., de Poel, I., van der Ven, A., van der Zee, J., van Lunzen, J., van Minnebruggen, G., Paesschen, W., van Swieten, J., van Vught, R., Verhage, M., Verstreken, P., Villa, C., Vogel, J., von Kalle, C., Walter, J., Weckhuysen, S., Weichert, W., Wood, L., Ziegler, A., Zipp, F., HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany., Medical Research Council (MRC), UK DRI Ltd, TWINCORE, Zentrum für experimentelle und klinische Infektionsforschung GmbH,Feodor-Lynen Str. 7, 30625 Hannover, Germany., Barcelona Supercomputing Center, LifeTime Community Working Groups, Cardiology, Neurology, Institut de génétique humaine (IGH), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Human genetics, Rajewsky N., Almouzni G., Gorski S.A., Aerts S., Amit I., Bertero M.G., Bock C., Bredenoord A.L., Cavalli G., Chiocca S., Clevers H., De Strooper B., Eggert A., Ellenberg J., Fernandez X.M., Figlerowicz M., Gasser S.M., Hubner N., Kjems J., Knoblich J.A., Krabbe G., Lichter P., Linnarsson S., Marine J.-C., Marioni J.C., Marti-Renom M.A., Netea M.G., Nickel D., Nollmann M., Novak H.R., Parkinson H., Piccolo S., Pinheiro I., Pombo A., Popp C., Reik W., Roman-Roman S., Rosenstiel P., Schultze J.L., Stegle O., Tanay A., Testa G., Thanos D., Theis F.J., Torres-Padilla M.-E., Valencia A., Vallot C., van Oudenaarden A., Vidal M., Voet T., Alberi L., Alexander S., Alexandrov T., Arenas E., Bagni C., Balderas R., Bandelli A., Becher B., Becker M., Beerenwinkel N., Benkirame M., Beyer M., Bickmore W., Biessen E.E.A.L., Blomberg N., Blumcke I., Bodenmiller B., Borroni B., Boumpas D.T., Bourgeron T., Bowers S., Braeken D., Brooksbank C., Brose N., Bruining H., Bury J., Caporale N., Cattoretti G., Chabane N., Chneiweiss H., Cook S.A., Curatolo P., de Jonge M.I., Deplancke B., de Witte P., Dimmeler S., Draganski B., Drews A., Dumbrava C., Engelhardt S., Gasser T., Giamarellos-Bourboulis E.J., Graff C., Grun D., Gut I., Hansson O., Henshall D.C., Herland A., Heutink P., Heymans S.R.B., Heyn H., Huch M., Huitinga I., Jackowiak P., Jongsma K.R., Journot L., Junker J.P., Katz S., Kehren J., Kempa S., Kirchhof P., Klein C., Koralewska N., Korbel J.O., Kuhnemund M., Lamond A.I., Lauwers E., Le Ber I., Leinonen V., Tobon A.L., Lundberg E., Lunkes A., Maatz H., Mann M., Marelli L., Matser V., Matthews P.M., Mechta-Grigoriou F., Menon R., Nielsen A.F., Pagani M., Pasterkamp R.J., Pitkanen A., Popescu V., Pottier C., Puisieux A., Rademakers R., Reiling D., Reiner O., Remondini D., Ritchie C., Rohrer J.D., Saliba A.-E., Sanchez-Valle R., Santosuosso A., Sauter A., Scheltema R.A., Scheltens P., Schiller H.B., Schneider A., Seibler P., Sheehan-Rooney K., Shields D., Sleegers K., Smit A.B., Smith K.G.C., Smolders I., Synofzik M., Tam W.L., Teichmann S., Thom M., Turco M.Y., van Beusekom H.M.M., Vandenberghe R., Van den Hoecke S., Van de Poel I., van der Ven A., van der Zee J., van Lunzen J., van Minnebruggen G., Van Paesschen W., van Swieten J., van Vught R., Verhage M., Verstreken P., Villa C.E., Vogel J., von Kalle C., Walter J., Weckhuysen S., Weichert W., Wood L., Ziegler A.-G., Zipp F., Center for Neurogenomics and Cognitive Research, Functional Genomics, Rajewsky, N, Almouzni, G, Gorski, S, Aerts, S, Amit, I, Bertero, M, Bock, C, Bredenoord, A, Cavalli, G, Chiocca, S, Clevers, H, De Strooper, B, Eggert, A, Ellenberg, J, Fernández, X, Figlerowicz, M, Gasser, S, Hubner, N, Kjems, J, Knoblich, J, Krabbe, G, Lichter, P, Linnarsson, S, Marine, J, Marioni, J, Marti-Renom, M, Netea, M, Nickel, D, Nollmann, M, Novak, H, Parkinson, H, Piccolo, S, Pinheiro, I, Pombo, A, Popp, C, Reik, W, Roman-Roman, S, Rosenstiel, P, Schultze, J, Stegle, O, Tanay, A, Testa, G, Thanos, D, Theis, F, Torres-Padilla, M, Valencia, A, Vallot, C, van Oudenaarden, A, Vidal, M, Voet, T, Cattoretti, G, Alliance for Modulation in Epilepsy, Pharmaceutical and Pharmacological Sciences, Experimental Pharmacology, RS: Carim - H02 Cardiomyopathy, MUMC+: MA Med Staf Spec Cardiologie (9), and Cardiologie

Subjects
0301 basic medicine, Male, Artificial intelligence, Legislation, Medical, [SDV]Life Sciences [q-bio], Molecular datasets, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Cell- and Tissue-Based Therapy, Diseases, LifeTime Community Working Groups, Disease, Biomarkers, Systems biology, Health data, Pharmacology, Toxicology and Pharmaceutics(all), 0302 clinical medicine, Conjunts de dades, ethics [Delivery of Health Care], Health care, Pathology, Medicine, European healthcare, BRAIN, Single-cell multi-omics, GENE-EXPRESSION, Multidisciplinary, methods [Medicine], Education, Medical, Settore BIO/13, Intel.ligència artificial, 3. Good health, ALZHEIMERS-DISEASE, Europe, Health, Management system, Perspective, Female, ddc:500, Single-Cell Analysis, Biomarkers, Diseases, Systems biology, Complex diseases, Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC], medicine.medical_specialty, General Science & Technology, Cells, MEDLINE, cell-based interceptive medicine, LifeTime Initiative, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Clinical datasets, Artificial Intelligence, REVEALS, LifeTime Community, standards [Medicine], Humans, OMICS, RECONSTRUCTION, Intensive care medicine, trends [Medicine], trends [Delivery of Health Care], business.industry, Disease progression, standards [Delivery of Health Care], methods [Delivery of Health Care], 030104 developmental biology, lnfectious Diseases and Global Health Radboud Institute for Health Sciences [Radboudumc 4], single cell, personalized therapy, machine learning, bioinformatics, systems biology, disease, cell-based interceptive medicine, Early Diagnosis, Cardiovascular and Metabolic Diseases, Human medicine, business, Delivery of Health Care, 030217 neurology & neurosurgery, Cell based
Abstract

Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade., The LifeTime initiative is an ambitious, multidisciplinary programme that aims to improve healthcare by tracking individual human cells during disease processes and responses to treatment in order to develop and implement cell-based interceptive medicine in Europe.

Published
2020

13. Publisher Correction: LifeTime and improving European healthcare through cell-based interceptive medicine (Nature, (2020), 587, 7834, (377-386), 10.1038/s41586-020-2715-9)

Author

Rajewsky, N. Almouzni, G. Gorski, S.A. Aerts, S. Amit, I. Bertero, M.G. Bock, C. Bredenoord, A.L. Cavalli, G. Chiocca, S. Clevers, H. De Strooper, B. Eggert, A. Ellenberg, J. Fernández, X.M. Figlerowicz, M. Gasser, S.M. Hubner, N. Kjems, J. Knoblich, J.A. Krabbe, G. Lichter, P. Linnarsson, S. Marine, J.-C. Marioni, J.C. Marti-Renom, M.A. Netea, M.G. Nickel, D. Nollmann, M. Novak, H.R. Parkinson, H. Piccolo, S. Pinheiro, I. Pombo, A. Popp, C. Reik, W. Roman-Roman, S. Rosenstiel, P. Schultze, J.L. Stegle, O. Tanay, A. Testa, G. Thanos, D. Theis, F.J. Torres-Padilla, M.-E. Valencia, A. Vallot, C. van Oudenaarden, A. Vidal, M. Voet, T. Alberi, L. Alexander, S. Alexandrov, T. Arenas, E. Bagni, C. Balderas, R. Bandelli, A. Becher, B. Becker, M. Beerenwinkel, N. Benkirane, M. Beyer, M. Bickmore, W.A. Biessen, E.E.A.L. Blomberg, N. Blumcke, I. Bodenmiller, B. Borroni, B. Boumpas, D.T. Bourgeron, T. Bowers, S. Braeken, D. Brooksbank, C. Brose, N. Bruining, H. Bury, J. Caporale, N. Cattoretti, G. Chabane, N. Chneiweiss, H. Cook, S.A. Curatolo, P. de Jonge, M.I. Deplancke, B. de Witte, P. Dimmeler, S. Draganski, B. Drews, A. Dumbrava, C. Engelhardt, S. Gasser, T. Giamarellos-Bourboulis, E.J. Graff, C. Grün, D. Gut, I.G. Hansson, O. Henshall, D.C. Herland, A. Heutink, P. Heymans, S.R.B. Heyn, H. Huch, M. Huitinga, I. Jackowiak, P. Jongsma, K.R. Journot, L. Junker, J.P. Katz, S. Kehren, J. Kempa, S. Kirchhof, P. Klein, C. Koralewska, N. Korbel, J.O. Kühnemund, M. Lamond, A.I. Lauwers, E. Le Ber, I. Leinonen, V. López-Tobón, A. Lundberg, E. Lunkes, A. Maatz, H. Mann, M. Marelli, L. Matser, V. Matthews, P.M. Mechta-Grigoriou, F. Menon, R. Nielsen, A.F. Pagani, M. Pasterkamp, R.J. Pitkänen, A. Popescu, V. Pottier, C. Puisieux, A. Rademakers, R. Reiling, D. Reiner, O. Remondini, D. Ritchie, C. Rohrer, J.D. Saliba, A.-E. Sanchez-Valle, R. Santosuosso, A. Sauter, A. Scheltema, R.A. Scheltens, P. Schiller, H.B. Schneider, A. Seibler, P. Sheehan-Rooney, K. Shields, D.J. Sleegers, K. Smit, A.B. Smith, K.G.C. Smolders, I. Synofzik, M. Tam, W.L. Teichmann, S.A. Thom, M. Turco, M.Y. van Beusekom, H.M.M. Vandenberghe, R. Van den Hoecke, S. van de Poel, I. van der Ven, A. van der Zee, J. van Lunzen, J. van Minnebruggen, G. van Oudenaarden, A. Van Paesschen, W. van Swieten, J.C. van Vught, R. Verhage, M. Verstreken, P. Villa, C.E. Vogel, J. von Kalle, C. Walter, J. Weckhuysen, S. Weichert, W. Wood, L. Ziegler, A.-G. Zipp, F. LifeTime Community Working Groups

Subjects
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING
Abstract

In this Perspective, owing to an error in the HTML, the surname of author Alejandro López-Tobón of the LifeTime Community Working Groups consortium was indexed as ‘Tobon’ rather than ‘López-Tobón’ and the accents were missing. The HTML version of the original Perspective has been corrected; the PDF and print versions were always correct. © 2021, The Author(s).

Published
2021

17. Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

Author

Stuart, J.M., Huelsken, J., Czerwi��ska, P., Kami��ska, B., Mishra, L., Godwin, A.K., Mazurek, S., Noushmehr, H., Wiznerowicz, M., Lazar, A.J., Sokolov, A., The Cancer Genome Atlas Research Network, Krasnitz, A., Laird, P.W., Gentles, A.J., Hoadley, K.A., Burzykowski, T., Omberg, L., Gevaert, O., Malta, T.M., Weinstein, J.N., Heyn, H., Colaprico, A., and Poisson, L.

Subjects
cancer stem cells, Carcinogenesis, pan-cancer, The Cancer Genome Atlas, Cancer Genome Atlas Research Network, epigenomic, Medical and Health Sciences, Machine Learning, genomic, Databases, stemness, Genetic, Stem Cell Research - Nonembryonic - Human, Neoplasms, Tumor Microenvironment, Humans, Neoplasm Metastasis, Cancer, Stem Cells, dedifferentiation, DNA Methylation, Cell Dedifferentiation, Biological Sciences, Stem Cell Research, MicroRNAs, Good Health and Well Being, Stem Cell Research - Nonembryonic - Non-Human, Transcriptome, Epigenesis, Developmental Biology
Abstract

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation. Stemness features extracted from transcriptomic and epigenetic data from TCGA tumors reveal novel biological and clinical insight, as well as potential drug targets for anti-cancer therapies.

Published
2018

18. PM20D1 is a quantitative trait locus associated with Alzheimer's disease

Author

Sanchez-Mut JV, Heyn H, Silva BA, Dixsaut L, Garcia-Esparcia P, Vidal E, Sayols S, Glauser L, Monteagudo-Sánchez A, Perez-Tur J, Ferrer I, Monk D, Schneider B, Esteller M, and Gräff J

Abstract

The chances to develop Alzheimer's disease (AD) result from a combination of genetic and non-genetic risk factors 1 , the latter likely being mediated by epigenetic mechanisms 2 . In the past, genome-wide association studies (GWAS) have identified an important number of risk loci associated with AD pathology 3 , but a causal relationship remains difficult to establish. In contrast, locus-specific or epigenome-wide association studies (EWAS) have revealed site-specific epigenetic alterations, which provide mechanistic insights for a particular risk gene but often lack the statistical power of GWAS 4 . Here, combining both approaches, we report a previously unidentified association of the peptidase M20-domain-containing protein 1 (PM20D1) with AD. We find that PM20D1 is a methylation and expression quantitative trait locus coupled to an AD-risk associated haplotype, which displays enhancer-like characteristics and contacts the PM20D1 promoter via a haplotype-dependent, CCCTC-binding-factor-mediated chromatin loop. Furthermore, PM20D1 is increased following AD-related neurotoxic insults at symptomatic stages in the APP/PS1 mouse model of AD and in human patients with AD who are carriers of the non-risk haplotype. In line, genetically increasing or decreasing the expression of PM20D1 reduces and aggravates AD-related pathologies, respectively. These findings suggest that in a particular genetic background, PM20D1 contributes to neuroprotection against AD.

Published
2018

20. Epigenetic loss of the RNA decapping enzyme NUDT16 mediates C-MYC activation in T-cell acute lymphoblastic leukemia

Author

Anadón, C, primary, van Tetering, G, additional, Ferreira, H J, additional, Moutinho, C, additional, Martínez-Cardús, A, additional, Villanueva, A, additional, Soler, M, additional, Heyn, H, additional, Moran, S, additional, Castro de Moura, M, additional, Setien, F, additional, Vidal, A, additional, Genescà, E, additional, Ribera, J M, additional, Nomdedeu, J F, additional, Guil, S, additional, and Esteller, M, additional

Published
2017
Full Text
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21. Assessing Associations between the AURKA-HMMR-TPX2-TUBG1 Functional Module and Breast Cancer Risk in BRCA1/2 Mutation Carriers

Author

Blanco, I., Kuchenbaecker, K., Cuadras, D., Wang, X.S., Barrowdale, D., Garibay, G.R., Librado, P., Sanchez-Gracia, A., Rozas, J., Bonifaci, N., McGuffog, L., Pankratz, V.S., Islam, A., Mateo, F., Berenguer, A., Petit, A., Catala, I., Brunet, J., Feliubadalo, L., Tornero, E., Benitez, J., Osorio, A., Cajal, T.R.Y., Nevanlinna, H., Aittomaki, K., Arun, B.K., Toland, A.E., Karlan, B.Y., Walsh, C., Lester, J., Greene, M.H., Mai, P.L., Nussbaum, R.L., Andrulis, I.L., Domchek, S.M., Nathanson, K.L., Rebbeck, T.R., Barkardottir, R.B., Jakubowska, A., Lubinski, J., Durda, K., Jaworska-Bieniek, K., Claes, K., Maerken, T. van, Diez, O., Hansen, T.V., Jonson, L., Gerdes, A.M., Ejlertsen, B., Hoya, M. de la, Caldees, T., Dunning, A.M., Oliver, C., Fineberg, E., Cook, M., Peock, S., McCann, E., Murray, A., Jacobs, C., Pichert, G., Lalloo, F., Chu, C., Dorkins, H., Paterson, J., Ong, K.R., Teixeira, M.R., Teixeira, Hogervorst, F.B.L., Hout, A.H. van der, Seynaeve, C., Luijt, R.B. van der, Ligtenberg, M.J.L., Devilee, P., Wijnen, J.T., Rookus, M.A., Meijers-Heijboer, H.E.J., Blok, M.J., Ouweland, A.M.W. van den, Aalfs, C.M., Rodriguez, G.C., Phillips, K.A.A., Piedmonte, M., Nerenstone, S.R., Bae-Jump, V.L., O'Malley, D.M., Ratner, E.S., Schmutzler, R.K., Wappenschmidt, B., Rhiem, K., Engel, C., Meindl, A., Ditsch, N., Arnold, N., Plendl, H.J., Niederacher, D., Sutter, C., Wang-Gohrke, S., Steinemann, D., Preisler-Adams, S., Kast, K., Varon-Mateeva, R., Gehrig, A., Bojesen, A., Pedersen, I.S., Sunde, L., Jensen, U.B., Thomassen, M., Kruse, T.A., Foretova, L., Peterlongo, P., Bernard, L., Peissel, B., Scuvera, G., Manoukian, S., Radice, P., Ottini, L., Montagna, M., Agata, S., Maugard, C., Simard, J., Soucy, P., Berger, A., Fink-Retter, A., Singer, C.F., Rappaport, C., Geschwantler-Kaulich, D., Tea, M.K., Pfeiler, G., John, E.M., Miron, A., Neuhausen, S.L., Terry, M.B., Chung, W.K., Daly, M.B., Goldgar, D.E., Janavicius, R., Dorfling, C.M., Rensburg, E.J. van, Fostira, F., Konstantopoulou, I., Garber, J., Godwin, A.K., Olah, E., Narod, S.A., Rennert, G., Paluch, S.S., Laitman, Y., Friedman, E., Liljegren, A., Rantala, J., Stenmark-Askmalm, M., Loman, N., Imyanitov, E.N., Hamann, U., Spurdle, A.B., Healey, S., Weitzel, J.N., Herzog, J., Margileth, D., Gorrini, C., Esteller, M., Gomez, A., Sayols, S., Vidal, E., Heyn, H., Stoppa-Lyonnet, Leone, M., Barjhoux, L., Fassy-Colcombet, M., Pauw, A. de, Lasset, C., Ferrer, S.F., Castera, L., Berthet, P., Cornelis, F., Bignon, Y.J., Damiola, F., Mazoyer, S., Sinilnikova, O.M., Maxwell, C.A., Vijai, J., Robson, M., Kauff, N., Corines, M.J., Villano, D., Cunningham, J., Lee, A., Lindor, N., Lazaro, C., Easton, D.F., Offit, K., Chenevix-Trench, G., Couch, F.J., Antoniou, A.C., Pujana, M.A., BCFR, SWE-BRCA, KConFab Investigators, GEMO, Human genetics, CCA - Oncogenesis, Medical Oncology, Clinical Genetics, Suzuki, Hiromu, MUMC+: DA KG Lab Centraal Lab (9), RS: GROW - Oncology, RS: GROW - R4 - Reproductive and Perinatal Medicine, CCA -Cancer Center Amsterdam, ARD - Amsterdam Reproduction and Development, Human Genetics, Department of Obstetrics and Gynecology, Clinicum, Medicum, Haartman Institute (-2014), and Department of Medical and Clinical Genetics

Subjects
single nucleotide, Oncology, Carcinogenesis, TUBG1, Genes, BRCA2, Genes, BRCA1, Càncer d'ovari, MODIFIERS, Genome-wide association study, Cell Cycle Proteins, Breast cancer, mammary glands, Aetiology, genes, skin and connective tissue diseases, Cancer, Extracellular Matrix Proteins, Hazard ratio, CHIP-SEQ, 3. Good health, ddc, Hyaluronan Receptors, Medicine, Teixeira, Human, medicine.medical_specialty, Evolution, Science, Non-P.H.S, Single-nucleotide polymorphism, Evolution, Molecular, SDG 3 - Good Health and Well-being, Ovarian cancer, Genetics, biochemistry, Humans, human, CELL, Polymorphism, GENOME-WIDE ASSOCIATION, medicine (all), Retrospective Studies, Cancer och onkologi, Prevention, Mutació (Biologia), Biology and Life Sciences, Molecular, SWE-BRCA, BRCA1, medicine.disease, BRCA2, POLYMORPHISM, Genes, Genetic Loci, Cancer and Oncology, Mutation, U.S. Gov't, Bioinformatics, medicine.disease_cause, 3123 Gynaecology and paediatrics, Tubulin, Tumours of the digestive tract Radboud Institute for Molecular Life Sciences [Radboudumc 14], ELEMENTS, 2.1 Biological and endogenous factors, CD44, Non-U.S. Gov't, Aurora Kinase A, Likelihood Functions, Multidisciplinary, Research Support, Non-U.S. Gov't, agricultural and biological sciences (all), genetics and molecular biology (all), BCFR, Nuclear Proteins, Single Nucleotide, Mammary Glands, SURVIVAL, kConFab Investigators, Female, Microtubule-Associated Proteins, Research Article, Antigens, CD44, aurora kinase A, breast neoplasms, carcinogenesis, cell cycle proteins, estrogen receptor alpha, evolution, molecular, extracellular matrix proteins, female, genetic loci, genetic predisposition to disease, humans, likelihood functions, mammary glands, human, microtubule-associated proteins, nuclear proteins, polymorphism, retrospective studies, tubulin, genes, BRCA1, genes, BRCA2, mutation, biochemistry, genetics and molecular biology (all), SUSCEPTIBILITY LOCI, General Science & Technology, 3122 Cancers, Breast Neoplasms, Biology, Research Support, Polymorphism, Single Nucleotide, N.I.H, GENETIC INTERACTION NETWORKS, Càncer de mama, EXPRESSION SIGNATURE, Amino acid sequence, Research Support, N.I.H., Extramural, Internal medicine, Seqüència d'aminoàcids, evolution, Genetic variation, Journal Article, medicine, Genetic Predisposition to Disease, ddc:610, molecular, Antigens, Mammary Glands, Human, ddc:611, Intramural, Estrogen Receptor alpha, Extramural, Mutation (Biology), Research Support, N.I.H., Intramural, 3111 Biomedicine, GEMO, Research Support, U.S. Gov't, Non-P.H.S
Abstract

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04 - 1.15, p = 1.9 x 10(-4) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03 - 1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted p(interaction) values greater than 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers. Funding Agencies|National Cancer Institute [UM1 CA164920]; Lithuania (BFBOCC-LT): Research Council of Lithuania grant [LIG-07/2012]; Hereditary Cancer Association (Paveldimo vezio asociacija); LSC grant [10.0010.08]; ESF [2009/0220/1DP/1.1.1.2.0/09/APIA/VIAA/016]; Liepajas municipal council; Cancer Association of South Africa (CANSA); Morris and Horowitz Familes Endowed Professorship; NEYE Foundation; Spanish Association against Cancer [AECC08, RTICC 06/0020/1060, FISPI08/1120]; Mutua Madrilena Foundation (FMMA); COH-CCGCRN: City of Hope Clinical Cancer Genetics Community Network from the National Cancer Institute and the Office of the Director, National Institutes of Health; Hereditary Cancer Research Registry from the National Cancer Institute and the Office of the Director, National Institutes of Health [RC4CA153828]; Fondazione IRCCS Istituto Nazionale Tumori; Cancer Research-United Kingdom grant [C12292/A11174, C1287/ A10118]; NHMRC Program Grant; DKFZ; European Union (European Social Fund-ESF); Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF)-Research Funding Program of the General Secretariat for Research and Technology: ARISTEIA; European Social Fund; Cancer Research United Kingdom Grants [C1287/A10118, C1287/A11990]; National Institute of Health Research (NIHR) grant; NIHR grant; Royal Marsden NHS Foundation Trust; Cancer Research United Kingdom Grant [C5047/A8385]; University of Kansas Cancer Center [P30 CA168524]; Kansas Bioscience Authority Eminent Scholar Program; Chancellors Distinguished Chair in Biomedical Sciences Professorship; AKG [5U01CA113916, R01CA140323]; German Cancer Aid [109076]; Center for Molecular Medicine Cologne (CMMC); Ligue National Contre le Cancer; Association "Le cancer du sein, parlonsen!" Award; Canadian Institutes of Health Research; Fund for Scientific Research Flanders (FWO); National Cancer Institute grant [CA 27469]; GOG Statistical and Data Center [CA 37517]; GOGs Cancer Prevention and Control Committee [CA 101165]; Intramural Research Program, NCI; ISCIII (Spain) [RD12/00369/0006, 12/00539]; European Regional Development FEDER funds; Helsinki University Central Hospital Research Fund; Academy of Finland [132473]; Finnish Cancer Society; Sigrid Juselius Foundation; Dutch Cancer Society grant [NKI1998-1854, NKI2004-3088, NKI2007-3756]; Netherlands Organization of Scientific Research [NWO 91109024]; Pink Ribbon grant [110005]; BBMRI grant [NWO 184.021.007/CP46]; Hungarian Research Grant [KTIA-OTKA CK-80745]; Norwegian EEA Financial Mechanism [HU0115/NA/2008-3/OP-9]; Spanish Ministry of Health ISCIII FIS [PI10/01422, PI12/01528, PI13/00285]; RTICC [RD12/0036/0008]; Ramon Areces (XV) Foundation; Eugenio Rodriguez Pascual Foundation; Roses Contra el Cancer Foundation; Spanish Association Against Cancer (AECC); AGAUR Generalitat de Catalunya [2009-SGR290, 2009-SGR293]; Polish Foundation of Science; Icelandic Association "Walking for Breast Cancer Research"; Nordic Cancer Union; Landspitali University Hospital Research Fund; Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" program; Canadian Breast Cancer Research Alliance-grant [019511]; Ministry of Economic Development, Innovation and Export Trade-grant [PSR-SIIRI-701]; Ministero dellIstruzione, dellUniversita e della Ricerca and Ministero della Salute; Liga Portuguesa Contra o Cancro; National Breast Cancer Foundation; National Health and Medical Research Council (NHMRC); Queensland Cancer Fund; Cancer Council of New South Wales; Cancer Council of Victoria; Cancer Foundation of Western Australia; Cancer Councils of Tasmania; National Institutes of Health grant [CA128978]; NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201]; United States Department of Defence Ovarian Cancer Idea award [W81XWH-10-1-0341]; Breast Cancer Research Foundation; Jewish General Hospital Weekend; Quebec Ministry of Economic Development, Innovation and Export Trade; Cancer Councils of South Australia; European Regional Development Fund; State Budget of the Czech Republic (RECAMO) [CZ.1.05/2.1.00/03.0101]; MH CZ-DRO (MMCI) [00209805]; Niehaus Family Genetics Research Fund; STARR Cancer Consortium Grant; NAROD [1R01 CA149429-01]; NCI Intramural Research Program, National Institutes of Health [NO2-CP-11019-50, N02-CP-65504]; Westat, Inc, Rockville, Maryland; Clalit Health Services in Israel; Israel Cancer Association; Breast Cancer Research Foundation (BCRF), New York; Russian Federation for Basic Research [11-04-00227, 12-04-00928, 12-04-01490]; Federal Agency for Science and Innovations, Russia [02.740.11.0780]; Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" program and grant from the National Cancer Institute [UM1 CA164920]; Breast Cancer Family Registry (BCFR); United States Government or the BCFR; Ohio State University Comprehensive Cancer Center; Isreal cancer association; Israeli Inherited breast cancer consortium; Swedish Cancer Society; Ralph and Marion Falk Medical Research Trust; Entertainment Industry Fund National Womens Cancer Research Alliance; National Institutes of Health (NIH) [R01-CA102776, R01-CA083855]; Rooney Family Foundation; Susan G. Komen Foundation for the cure, Basser Research Center; American Cancer Society Early Detection Professorship [SIOP-06-258-01-COUN]; SAF2010-20493; [PBZ_KBN_122/P05/2004]

Published
2015

22. Collaborative Knowledge Acquisition and Explorationin Technology Search

Author

Stange, D., Andreas Nürnberger, and Heyn, H.

Subjects
gemeinsamer Wissenserwerb, collaborative knowledge acquisition, ddc:330
Abstract

This article is about technology search as an example of a knowledge acquisition task in industry. Technology search is about finding technology related information in structured as well as unstructured sources. This information is needed to support optimal decision making in business processes. There are new opptortunities for technology search and challenges that need to be addressed. This article outlines some of these challenges and presents two concepts to address them in a search system.

Published
2015

25. DNA methylation profiling in breast cancer discordant identical twins identifies DOK7 as novel epigenetic biomarker

Author

Heyn H, Carmona FJ, Gomez A, Ferreira HJ, Bell JT, Sayols S, Ward K, Stefansson OA, Moran S, Sandoval J, Eyfjord JE, Spector TD, and Esteller M

Abstract

Using whole blood from 15 twin pairs discordant for breast cancer and high-resolution (450K) DNA methylation analysis, we identified 403 differentially methylated CpG sites including known and novel potential breast cancer genes. Confirming the results in an independent validation cohort of 21 twin pairs determined the docking protein DOK7 as a candidate for blood-based cancer diagnosis. DNA hypermethylation of the promoter region was also seen in primary breast cancer tissues and cancer cell lines. Hypermethylation of DOK7 occurs years before tumor diagnosis, suggesting a role as a powerful epigenetic blood-based biomarker as well as providing insights into breast cancer pathogenesis.

Published
2013

26. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome

Author

Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA, Bibikova M, and Esteller M

Abstract

DNA methylation is the most studied epigenetic mark and CpG methylation is central to many biological processes and human diseases. Since cancer has highlighted the contribution to disease of aberrant DNA methylation patterns, such as the presence of promoter CpG island hypermethylation-associated silencing of tumor suppressor genes and global DNA hypomethylation defects, their importance will surely become apparent in other pathologies. However, advances in obtaining comprehensive DNA methylomes are hampered by the high cost and time-consuming aspects of the single nucleotide methods currently available for whole genome DNA methylation analyses. Following the success of the standard CpG methylation microarrays for 1,505 CpG sites and 27,000 CpG sites, we have validated in vivo the newly developed 450,000 (450K) cytosine microarray (Illumina). The 450K microarray includes CpG and CNG sites, CpG islands/shores/shelves/open sea, non-coding RNA (microRNAs and long non-coding RNAs) and sites surrounding the transcription start sites (-200 bp to -1,500 bp, 5'-UTRs and exons 1) for coding genes, but also for the corresponding gene bodies and 3'-UTRs, in addition to intergenic regions derived from GWAS studies. Herein, we demonstrate that the 450K DNA methylation array can consistently and significantly detect CpG methylation changes in the HCT-116 colorectal cancer cell line in comparison with normal colon mucosa or HCT-116 cells with defective DNA methyltransferases (DKO). The provided validation highlights the potential use of the 450K DNA methylation microarray as a useful tool for ongoing and newly designed epigenome projects.

Published
2011

28. DNA methylation profiling in breast cancer discordant identical twins identifies DOK7 as novel epigenetic biomarker

Author

Heyn, H., primary, Carmona, F. J., additional, Gomez, A., additional, Ferreira, H. J., additional, Bell, J. T., additional, Sayols, S., additional, Ward, K., additional, Stefansson, O. A., additional, Moran, S., additional, Sandoval, J., additional, Eyfjord, J. E., additional, Spector, T. D., additional, and Esteller, M., additional

Published
2012
Full Text
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31. Cetacean Relaxin

Author

Schwabe, C, Böllesbach, E E, Heyn, H, and Yoshioka, M

Abstract

The tendency toward extremely high variability among relaxing derived from purportedly closely related species has come to an abrupt end with the discovery of quasi-porcine relaxin in the minke whale (Balaenoptera acutorostrata) and the Bryde's whale (Balaenoptera edeni). An aqueous abstract of the corpora lutea of the two baleen whales contained significant amounts of relaxin-like activity as determined by a mouse bioassay and by cross-reactivity with anti-pig relaxin antibodies. The activity could be isolated and purified to homogeneity. Sequence analysis revealed that both whale relaxins differed from each other by about 3 residues, whereas the relaxin of B. edenidiffered at only one position from that of pig relaxin. The similarity appears to include even the chain length heterogeneity observed at the C-terminal end of the B chain in porcine relaxin which is produced by a peculiar mode of connecting peptide removal from the prohormone. This finding may well represent one of the better documented challenges to the current paradigm of molecular evolution.

Published
1989
Full Text
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32. Computer aided cytometry in high grade malignant non-Hodgkin's lymphomas and tonsils

Author

Hans Konrad Müller-Hermelink, Heyn H, Harms H, and Bergmann M

Subjects
Pathology, medicine.medical_specialty, Hodgkin s, Cell type, Multivariate analysis, business.industry, Chronic tonsillitis, Lymphoma, Non-Hodgkin, Palatine Tonsil, High resolution, Color, Lymphatic tissues, Feature (computer vision), hemic and lymphatic diseases, Multivariate Analysis, medicine, Image Processing, Computer-Assisted, Humans, Lymphocytes, business, Cytometry
Abstract

The aim of the study is to establish quantitative cytological criteria for reliable diagnoses in high grade malignant non-Hodgkin's lymphomas (NHL). For this purpose Pappenheim-stained cytologic imprints from 15 cases of high grade malignant NHL and ten cases of chronic tonsillitis have been analysed using a TV-microscope system, high resolution color scanning (13.3 pixel/microns), and image processing on a computer. The highly reliable computer-extracted cell features can be used to discriminate the different cell types of malignant NHL. Because of a considerable overlap, no feature on its own is sufficient to discriminate all the different cells. Only multivariate analysis of a suitable combination of features allows reliable discrimination. The results show that the different cells defined by subjective morphological criteria in the Kiel-classification of malignant NHL also form distinctive subpopulations with regard to their objective mathematical cell features and show distinctive differences when compared with their benign counterparts derived from reactive lymphatic tissue.

Published
1989

34. A Landscape of Pharmacogenomic Interactions in Cancer

Author

Francesco Iorio, Ta, Knijnenburg, Dj, Vis, Gr, Bignell, Mp, Menden, 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, Rk, Egan, Liu Q, and Mironenko T

37. Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

Author

Tathiane M. Malta, Artem Sokolov, Andrew J. Gentles, Tomasz Burzykowski, Laila Poisson, John N. Weinstein, Bożena Kamińska, Joerg Huelsken, Larsson Omberg, Olivier Gevaert, Antonio Colaprico, Patrycja Czerwińska, Sylwia Mazurek, Lopa Mishra, Holger Heyn, Alex Krasnitz, Andrew K. Godwin, Alexander J. Lazar, Joshua M. Stuart, Katherine A. Hoadley, Peter W. Laird, Houtan Noushmehr, Maciej Wiznerowicz, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Melpomeni Kasapi, Martin L. Ferguson, Carolyn M. Hutter, Heidi J. Sofia, Roy Tarnuzzer, Zhining Wang, Liming Yang, Jean C. Zenklusen, Jiashan (Julia) Zhang, Sudha Chudamani, Jia Liu, Laxmi Lolla, Rashi Naresh, Todd Pihl, Qiang Sun, Yunhu Wan, Ye Wu, Juok Cho, Timothy DeFreitas, Scott Frazer, Nils Gehlenborg, Gad Getz, David I. Heiman, Jaegil Kim, Michael S. Lawrence, Pei Lin, Sam Meier, Michael S. Noble, Gordon Saksena, Doug Voet, Hailei Zhang, Brady Bernard, Nyasha Chambwe, Varsha Dhankani, Theo Knijnenburg, Roger Kramer, Kalle Leinonen, Yuexin Liu, Michael Miller, Sheila Reynolds, Ilya Shmulevich, Vesteinn Thorsson, Wei Zhang, Rehan Akbani, Bradley M. Broom, Apurva M. Hegde, Zhenlin Ju, Rupa S. Kanchi, Anil Korkut, Jun Li, Han Liang, Shiyun Ling, Wenbin Liu, Yiling Lu, Gordon B. Mills, Kwok-Shing Ng, Arvind Rao, Michael Ryan, Jing Wang, Jiexin Zhang, Adam Abeshouse, Joshua Armenia, Debyani Chakravarty, Walid K. Chatila, Ino de Bruijn, Jianjiong Gao, Benjamin E. Gross, Zachary J. Heins, Ritika Kundra, Konnor La, Marc Ladanyi, Augustin Luna, Moriah G. Nissan, Angelica Ochoa, Sarah M. Phillips, Ed Reznik, Francisco Sanchez-Vega, Chris Sander, Nikolaus Schultz, Robert Sheridan, S. Onur Sumer, Yichao Sun, Barry S. Taylor, Jioajiao Wang, Hongxin Zhang, Pavana Anur, Myron Peto, Paul Spellman, Christopher Benz, Christopher K. Wong, Christina Yau, D. Neil Hayes, Joel S. Parker, Matthew D. Wilkerson, Adrian Ally, Miruna Balasundaram, Reanne Bowlby, Denise Brooks, Rebecca Carlsen, Eric Chuah, Noreen Dhalla, Robert Holt, Steven J.M. Jones, Katayoon Kasaian, Darlene Lee, Yussanne Ma, Marco A. Marra, Michael Mayo, Richard A. Moore, Andrew J. Mungall, Karen Mungall, A. Gordon Robertson, Sara Sadeghi, Jacqueline E. Schein, Payal Sipahimalani, Angela Tam, Nina Thiessen, Kane Tse, Tina Wong, Ashton C. Berger, Rameen Beroukhim, Andrew D. Cherniack, Carrie Cibulskis, Stacey B. Gabriel, Galen F. Gao, Gavin Ha, Matthew Meyerson, Steven E. Schumacher, Juliann Shih, Melanie H. Kucherlapati, Raju S. Kucherlapati, Stephen Baylin, Leslie Cope, Ludmila Danilova, Moiz S. Bootwalla, Phillip H. Lai, Dennis T. Maglinte, David J. Van Den Berg, Daniel J. Weisenberger, J. Todd Auman, Saianand Balu, Tom Bodenheimer, Cheng Fan, Alan P. Hoyle, Stuart R. Jefferys, Corbin D. Jones, Shaowu Meng, Piotr A. Mieczkowski, Lisle E. Mose, Amy H. Perou, Charles M. Perou, Jeffrey Roach, Yan Shi, Janae V. Simons, Tara Skelly, Matthew G. Soloway, Donghui Tan, Umadevi Veluvolu, Huihui Fan, Toshinori Hinoue, Hui Shen, Wanding Zhou, Michelle Bellair, Kyle Chang, Kyle Covington, Chad J. Creighton, Huyen Dinh, HarshaVardhan Doddapaneni, Lawrence A. Donehower, Jennifer Drummond, Richard A. Gibbs, Robert Glenn, Walker Hale, Yi Han, Jianhong Hu, Viktoriya Korchina, Sandra Lee, Lora Lewis, Wei Li, Xiuping Liu, Margaret Morgan, Donna Morton, Donna Muzny, Jireh Santibanez, Margi Sheth, Eve Shinbrot, Linghua Wang, Min Wang, David A. Wheeler, Liu Xi, Fengmei Zhao, Julian Hess, Elizabeth L. Appelbaum, Matthew Bailey, Matthew G. Cordes, Li Ding, Catrina C. Fronick, Lucinda A. Fulton, Robert S. Fulton, Cyriac Kandoth, Elaine R. Mardis, Michael D. McLellan, Christopher A. Miller, Heather K. Schmidt, Richard K. Wilson, Daniel Crain, Erin Curley, Johanna Gardner, Kevin Lau, David Mallery, Scott Morris, Joseph Paulauskis, Robert Penny, Candace Shelton, Troy Shelton, Mark Sherman, Eric Thompson, Peggy Yena, Jay Bowen, Julie M. Gastier-Foster, Mark Gerken, Kristen M. Leraas, Tara M. Lichtenberg, Nilsa C. Ramirez, Lisa Wise, Erik Zmuda, Niall Corcoran, Tony Costello, Christopher Hovens, Andre L. Carvalho, Ana C. de Carvalho, José H. Fregnani, Adhemar Longatto-Filho, Rui M. Reis, Cristovam Scapulatempo-Neto, Henrique C.S. Silveira, Daniel O. Vidal, Andrew Burnette, Jennifer Eschbacher, Beth Hermes, Ardene Noss, Rosy Singh, Matthew L. Anderson, Patricia D. Castro, Michael Ittmann, David Huntsman, Bernard Kohl, Xuan Le, Richard Thorp, Chris Andry, Elizabeth R. Duffy, Vladimir Lyadov, Oxana Paklina, Galiya Setdikova, Alexey Shabunin, Mikhail Tavobilov, Christopher McPherson, Ronald Warnick, Ross Berkowitz, Daniel Cramer, Colleen Feltmate, Neil Horowitz, Adam Kibel, Michael Muto, Chandrajit P. Raut, Andrei Malykh, Jill S. Barnholtz-Sloan, Wendi Barrett, Karen Devine, Jordonna Fulop, Quinn T. Ostrom, Kristen Shimmel, Yingli Wolinsky, Andrew E. Sloan, Agostino De Rose, Felice Giuliante, Marc Goodman, Beth Y. Karlan, Curt H. Hagedorn, John Eckman, Jodi Harr, Jerome Myers, Kelinda Tucker, Leigh Anne Zach, Brenda Deyarmin, Hai Hu, Leonid Kvecher, Caroline Larson, Richard J. Mural, Stella Somiari, Ales Vicha, Tomas Zelinka, Joseph Bennett, Mary Iacocca, Brenda Rabeno, Patricia Swanson, Mathieu Latour, Louis Lacombe, Bernard Têtu, Alain Bergeron, Mary McGraw, Susan M. Staugaitis, John Chabot, Hanina Hibshoosh, Antonia Sepulveda, Tao Su, Timothy Wang, Olga Potapova, Olga Voronina, Laurence Desjardins, Odette Mariani, Sergio Roman-Roman, Xavier Sastre, Marc-Henri Stern, Feixiong Cheng, Sabina Signoretti, Andrew Berchuck, Darell Bigner, Eric Lipp, Jeffrey Marks, Shannon McCall, Roger McLendon, Angeles Secord, Alexis Sharp, Madhusmita Behera, Daniel J. Brat, Amy Chen, Keith Delman, Seth Force, Fadlo Khuri, Kelly Magliocca, Shishir Maithel, Jeffrey J. Olson, Taofeek Owonikoko, Alan Pickens, Suresh Ramalingam, Dong M. Shin, Gabriel Sica, Erwin G. Van Meir, Hongzheng Zhang, Wil Eijckenboom, Ad Gillis, Esther Korpershoek, Leendert Looijenga, Wolter Oosterhuis, Hans Stoop, Kim E. van Kessel, Ellen C. Zwarthoff, Chiara Calatozzolo, Lucia Cuppini, Stefania Cuzzubbo, Francesco DiMeco, Gaetano Finocchiaro, Luca Mattei, Alessandro Perin, Bianca Pollo, Chu Chen, John Houck, Pawadee Lohavanichbutr, Arndt Hartmann, Christine Stoehr, Robert Stoehr, Helge Taubert, Sven Wach, Bernd Wullich, Witold Kycler, Dawid Murawa, Ki Chung, W. Jeffrey Edenfield, Julie Martin, Eric Baudin, Glenn Bubley, Raphael Bueno, Assunta De Rienzo, William G. Richards, Steven Kalkanis, Tom Mikkelsen, Lisa Scarpace, Nicolas Girard, Marta Aymerich, Elias Campo, Eva Giné, Armando López Guillermo, Nguyen Van Bang, Phan Thi Hanh, Bui Duc Phu, Yufang Tang, Howard Colman, Kimberley Evason, Peter R. Dottino, John A. Martignetti, Hani Gabra, Hartmut Juhl, Teniola Akeredolu, Serghei Stepa, Dave Hoon, Keunsoo Ahn, Koo Jeong Kang, Felix Beuschlein, Anne Breggia, Michael Birrer, Debra Bell, Mitesh Borad, Alan H. Bryce, Erik Castle, Vishal Chandan, John Cheville, John A. Copland, Michael Farnell, Thomas Flotte, Nasra Giama, Thai Ho, Michael Kendrick, Jean-Pierre Kocher, Karla Kopp, Catherine Moser, David Nagorney, Daniel O’Brien, Brian Patrick O’Neill, Tushar Patel, Gloria Petersen, Florencia Que, Michael Rivera, Lewis Roberts, Robert Smallridge, Thomas Smyrk, Melissa Stanton, R. Houston Thompson, Michael Torbenson, Ju Dong Yang, Lizhi Zhang, Fadi Brimo, Jaffer A. Ajani, Ana Maria Angulo Gonzalez, Carmen Behrens, Jolanta Bondaruk, Russell Broaddus, Bogdan Czerniak, Bita Esmaeli, Junya Fujimoto, Jeffrey Gershenwald, Charles Guo, Christopher Logothetis, Funda Meric-Bernstam, Cesar Moran, Lois Ramondetta, David Rice, Anil Sood, Pheroze Tamboli, Timothy Thompson, Patricia Troncoso, Anne Tsao, Ignacio Wistuba, Candace Carter, Lauren Haydu, Peter Hersey, Valerie Jakrot, Hojabr Kakavand, Richard Kefford, Kenneth Lee, Georgina Long, Graham Mann, Michael Quinn, Robyn Saw, Richard Scolyer, Kerwin Shannon, Andrew Spillane, Jonathan Stretch, Maria Synott, John Thompson, James Wilmott, Hikmat Al-Ahmadie, Timothy A. Chan, Ronald Ghossein, Anuradha Gopalan, Douglas A. Levine, Victor Reuter, Samuel Singer, Bhuvanesh Singh, Nguyen Viet Tien, Thomas Broudy, Cyrus Mirsaidi, Praveen Nair, Paul Drwiega, Judy Miller, Jennifer Smith, Howard Zaren, Joong-Won Park, Nguyen Phi Hung, Electron Kebebew, W. Marston Linehan, Adam R. Metwalli, Karel Pacak, Peter A. Pinto, Mark Schiffman, Laura S. Schmidt, Cathy D. Vocke, Nicolas Wentzensen, Robert Worrell, Hannah Yang, Marc Moncrieff, Chandra Goparaju, Jonathan Melamed, Harvey Pass, Natalia Botnariuc, Irina Caraman, Mircea Cernat, Inga Chemencedji, Adrian Clipca, Serghei Doruc, Ghenadie Gorincioi, Sergiu Mura, Maria Pirtac, Irina Stancul, Diana Tcaciuc, Monique Albert, Iakovina Alexopoulou, Angel Arnaout, John Bartlett, Jay Engel, Sebastien Gilbert, Jeremy Parfitt, Harman Sekhon, George Thomas, Doris M. Rassl, Robert C. Rintoul, Carlo Bifulco, Raina Tamakawa, Walter Urba, Nicholas Hayward, Henri Timmers, Anna Antenucci, Francesco Facciolo, Gianluca Grazi, Mirella Marino, Roberta Merola, Ronald de Krijger, Anne-Paule Gimenez-Roqueplo, Alain Piché, Simone Chevalier, Ginette McKercher, Kivanc Birsoy, Gene Barnett, Cathy Brewer, Carol Farver, Theresa Naska, Nathan A. Pennell, Daniel Raymond, Cathy Schilero, Kathy Smolenski, Felicia Williams, Carl Morrison, Jeffrey A. Borgia, Michael J. Liptay, Mark Pool, Christopher W. Seder, Kerstin Junker, Mikhail Dinkin, George Manikhas, Domenico Alvaro, Maria Consiglia Bragazzi, Vincenzo Cardinale, Guido Carpino, Eugenio Gaudio, David Chesla, Sandra Cottingham, Michael Dubina, Fedor Moiseenko, Renumathy Dhanasekaran, Karl-Friedrich Becker, Klaus-Peter Janssen, Julia Slotta-Huspenina, Mohamed H. Abdel-Rahman, Dina Aziz, Sue Bell, Colleen M. Cebulla, Amy Davis, Rebecca Duell, J. Bradley Elder, Joe Hilty, Bahavna Kumar, James Lang, Norman L. Lehman, Randy Mandt, Phuong Nguyen, Robert Pilarski, Karan Rai, Lynn Schoenfield, Kelly Senecal, Paul Wakely, Paul Hansen, Ronald Lechan, James Powers, Arthur Tischler, William E. Grizzle, Katherine C. Sexton, Alison Kastl, Joel Henderson, Sima Porten, Jens Waldmann, Martin Fassnacht, Sylvia L. Asa, Dirk Schadendorf, Marta Couce, Markus Graefen, Hartwig Huland, Guido Sauter, Thorsten Schlomm, Ronald Simon, Pierre Tennstedt, Oluwole Olabode, Mark Nelson, Oliver Bathe, Peter R. Carroll, June M. Chan, Philip Disaia, Pat Glenn, Robin K. Kelley, Charles N. Landen, Joanna Phillips, Michael Prados, Jeffry Simko, Karen Smith-McCune, Scott VandenBerg, Kevin Roggin, Ashley Fehrenbach, Ady Kendler, Suzanne Sifri, Ruth Steele, Antonio Jimeno, Francis Carey, Ian Forgie, Massimo Mannelli, Michael Carney, Brenda Hernandez, Benito Campos, Christel Herold-Mende, Christin Jungk, Andreas Unterberg, Andreas von Deimling, Aaron Bossler, Joseph Galbraith, Laura Jacobus, Michael Knudson, Tina Knutson, Deqin Ma, Mohammed Milhem, Rita Sigmund, Rashna Madan, Howard G. Rosenthal, Clement Adebamowo, Sally N. Adebamowo, Alex Boussioutas, David Beer, Thomas Giordano, Anne-Marie Mes-Masson, Fred Saad, Therese Bocklage, Lisa Landrum, Robert Mannel, Kathleen Moore, Katherine Moxley, Russel Postier, Joan Walker, Rosemary Zuna, Michael Feldman, Federico Valdivieso, Rajiv Dhir, James Luketich, Edna M. Mora Pinero, Mario Quintero-Aguilo, Carlos Gilberto Carlotti, Jose Sebastião Dos Santos, Rafael Kemp, Ajith Sankarankuty, Daniela Tirapelli, James Catto, Kathy Agnew, Elizabeth Swisher, Jenette Creaney, Bruce Robinson, Carl Simon Shelley, Eryn M. Godwin, Sara Kendall, Cassaundra Shipman, Carol Bradford, Thomas Carey, Andrea Haddad, Jeffey Moyer, Lisa Peterson, Mark Prince, Laura Rozek, Gregory Wolf, Rayleen Bowman, Kwun M. Fong, Ian Yang, Robert Korst, W. Kimryn Rathmell, J. Leigh Fantacone-Campbell, Jeffrey A. Hooke, Albert J. Kovatich, Craig D. Shriver, John DiPersio, Bettina Drake, Ramaswamy Govindan, Sharon Heath, Timothy Ley, Brian Van Tine, Peter Westervelt, Mark A. Rubin, Jung Il Lee, Natália D. Aredes, Armaz Mariamidze, Malta T.M., Sokolov A., Gentles A.J., Burzykowski T., Poisson L., Weinstein J.N., Kaminska B., Huelsken J., Omberg L., Gevaert O., Colaprico A., Czerwinska P., Mazurek S., Mishra L., Heyn H., Krasnitz A., Godwin A.K., Lazar A.J., Caesar-Johnson S.J., Demchok J.A., Felau I., Kasapi M., Ferguson M.L., Hutter C.M., Sofia H.J., Tarnuzzer R., Wang Z., Yang L., Zenklusen J.C., Zhang J.J., Chudamani S., Liu J., Lolla L., Naresh R., Pihl T., Sun Q., Wan Y., Wu Y., Cho J., DeFreitas T., Frazer S., Gehlenborg N., Getz G., Heiman D.I., Kim J., Lawrence M.S., Lin P., Meier S., Noble M.S., Saksena G., Voet D., Zhang H., Bernard B., Chambwe N., Dhankani V., Knijnenburg T., Kramer R., Leinonen K., Liu Y., Miller M., Reynolds S., Shmulevich I., Thorsson V., Zhang W., Akbani R., Broom B.M., Hegde A.M., Ju Z., Kanchi R.S., Korkut A., Li J., Liang H., Ling S., Liu W., Lu Y., Mills G.B., Ng K.-S., Rao A., Ryan M., Wang J., Zhang J., Abeshouse A., Armenia J., Chakravarty D., Chatila W.K., de Bruijn I., Gao J., Gross B.E., Heins Z.J., Kundra R., La K., Ladanyi M., Luna A., Nissan M.G., Ochoa A., Phillips S.M., Reznik E., Sanchez-Vega F., Sander C., Schultz N., Sheridan R., Sumer S.O., Sun Y., Taylor B.S., Anur P., Peto M., Spellman P., Benz C., Stuart J.M., Wong C.K., Yau C., Hayes D.N., Parker J.S., Wilkerson M.D., Ally A., Balasundaram M., Bowlby R., Brooks D., Carlsen R., Chuah E., Dhalla N., Holt R., Jones S.J.M., Kasaian K., Lee D., Ma Y., Marra M.A., Mayo M., Moore R.A., Mungall A.J., Mungall K., Robertson A.G., Sadeghi S., Schein J.E., Sipahimalani P., Tam A., Thiessen N., Tse K., Wong T., Berger A.C., Beroukhim R., Cherniack A.D., Cibulskis C., Gabriel S.B., Gao G.F., Ha G., Meyerson M., Schumacher S.E., Shih J., Kucherlapati M.H., Kucherlapati R.S., Baylin S., Cope L., Danilova L., Bootwalla M.S., Lai P.H., Maglinte D.T., Van Den Berg D.J., Weisenberger D.J., Auman J.T., Balu S., Bodenheimer T., Fan C., Hoadley K.A., Hoyle A.P., Jefferys S.R., Jones C.D., Meng S., Mieczkowski P.A., Mose L.E., Perou A.H., Perou C.M., Roach J., Shi Y., Simons J.V., Skelly T., Soloway M.G., Tan D., Veluvolu U., Fan H., Hinoue T., Laird P.W., Shen H., Zhou W., Bellair M., Chang K., Covington K., Creighton C.J., Dinh H., Doddapaneni H., Donehower L.A., Drummond J., Gibbs R.A., Glenn R., Hale W., Han Y., Hu J., Korchina V., Lee S., Lewis L., Li W., Liu X., Morgan M., Morton D., Muzny D., Santibanez J., Sheth M., Shinbrot E., Wang L., Wang M., Wheeler D.A., Xi L., Zhao F., Hess J., Appelbaum E.L., Bailey M., Cordes M.G., Ding L., Fronick C.C., Fulton L.A., Fulton R.S., Kandoth C., Mardis E.R., McLellan M.D., Miller C.A., Schmidt H.K., Wilson R.K., Crain D., Curley E., Gardner J., Lau K., Mallery D., Morris S., Paulauskis J., Penny R., Shelton C., Shelton T., Sherman M., Thompson E., Yena P., Bowen J., Gastier-Foster J.M., Gerken M., Leraas K.M., Lichtenberg T.M., Ramirez N.C., Wise L., Zmuda E., Corcoran N., Costello T., Hovens C., Carvalho A.L., de Carvalho A.C., Fregnani J.H., Longatto-Filho A., Reis R.M., Scapulatempo-Neto C., Silveira H.C.S., Vidal D.O., Burnette A., Eschbacher J., Hermes B., Noss A., Singh R., Anderson M.L., Castro P.D., Ittmann M., Huntsman D., Kohl B., Le X., Thorp R., Andry C., Duffy E.R., Lyadov V., Paklina O., Setdikova G., Shabunin A., Tavobilov M., McPherson C., Warnick R., Berkowitz R., Cramer D., Feltmate C., Horowitz N., Kibel A., Muto M., Raut C.P., Malykh A., Barnholtz-Sloan J.S., Barrett W., Devine K., Fulop J., Ostrom Q.T., Shimmel K., Wolinsky Y., Sloan A.E., De Rose A., Giuliante F., Goodman M., Karlan B.Y., Hagedorn C.H., Eckman J., Harr J., Myers J., Tucker K., Zach L.A., Deyarmin B., Hu H., Kvecher L., Larson C., Mural R.J., Somiari S., Vicha A., Zelinka T., Bennett J., Iacocca M., Rabeno B., Swanson P., Latour M., Lacombe L., Tetu B., Bergeron A., McGraw M., Staugaitis S.M., Chabot J., Hibshoosh H., Sepulveda A., Su T., Wang T., Potapova O., Voronina O., Desjardins L., Mariani O., Roman-Roman S., Sastre X., Stern M.-H., Cheng F., Signoretti S., Berchuck A., Bigner D., Lipp E., Marks J., McCall S., McLendon R., Secord A., Sharp A., Behera M., Brat D.J., Chen A., Delman K., Force S., Khuri F., Magliocca K., Maithel S., Olson J.J., Owonikoko T., Pickens A., Ramalingam S., Shin D.M., Sica G., Van Meir E.G., Eijckenboom W., Gillis A., Korpershoek E., Looijenga L., Oosterhuis W., Stoop H., van Kessel K.E., Zwarthoff E.C., Calatozzolo C., Cuppini L., Cuzzubbo S., DiMeco F., Finocchiaro G., Mattei L., Perin A., Pollo B., Chen C., Houck J., Lohavanichbutr P., Hartmann A., Stoehr C., Stoehr R., Taubert H., Wach S., Wullich B., Kycler W., Murawa D., Wiznerowicz M., Chung K., Edenfield W.J., Martin J., Baudin E., Bubley G., Bueno R., De Rienzo A., Richards W.G., Kalkanis S., Mikkelsen T., Noushmehr H., Scarpace L., Girard N., Aymerich M., Campo E., Gine E., Guillermo A.L., Van Bang N., Hanh P.T., Phu B.D., Tang Y., Colman H., Evason K., Dottino P.R., Martignetti J.A., Gabra H., Juhl H., Akeredolu T., Stepa S., Hoon D., Ahn K., Kang K.J., Beuschlein F., Breggia A., Birrer M., Bell D., Borad M., Bryce A.H., Castle E., Chandan V., Cheville J., Copland J.A., Farnell M., Flotte T., Giama N., Ho T., Kendrick M., Kocher J.-P., Kopp K., Moser C., Nagorney D., O'Brien D., O'Neill B.P., Patel T., Petersen G., Que F., Rivera M., Roberts L., Smallridge R., Smyrk T., Stanton M., Thompson R.H., Torbenson M., Yang J.D., Zhang L., Brimo F., Ajani J.A., Gonzalez A.M.A., Behrens C., Bondaruk J., Broaddus R., Czerniak B., Esmaeli B., Fujimoto J., Gershenwald J., Guo C., Logothetis C., Meric-Bernstam F., Moran C., Ramondetta L., Rice D., Sood A., Tamboli P., Thompson T., Troncoso P., Tsao A., Wistuba I., Carter C., Haydu L., Hersey P., Jakrot V., Kakavand H., Kefford R., Lee K., Long G., Mann G., Quinn M., Saw R., Scolyer R., Shannon K., Spillane A., Stretch J., Synott M., Thompson J., Wilmott J., Al-Ahmadie H., Chan T.A., Ghossein R., Gopalan A., Levine D.A., Reuter V., Singer S., Singh B., Tien N.V., Broudy T., Mirsaidi C., Nair P., Drwiega P., Miller J., Smith J., Zaren H., Park J.-W., Hung N.P., Kebebew E., Linehan W.M., Metwalli A.R., Pacak K., Pinto P.A., Schiffman M., Schmidt L.S., Vocke C.D., Wentzensen N., Worrell R., Yang H., Moncrieff M., Goparaju C., Melamed J., Pass H., Botnariuc N., Caraman I., Cernat M., Chemencedji I., Clipca A., Doruc S., Gorincioi G., Mura S., Pirtac M., Stancul I., Tcaciuc D., Albert M., Alexopoulou I., Arnaout A., Bartlett J., Engel J., Gilbert S., Parfitt J., Sekhon H., Thomas G., Rassl D.M., Rintoul R.C., Bifulco C., Tamakawa R., Urba W., Hayward N., Timmers H., Antenucci A., Facciolo F., Grazi G., Marino M., Merola R., de Krijger R., Gimenez-Roqueplo A.-P., Piche A., Chevalier S., McKercher G., Birsoy K., Barnett G., Brewer C., Farver C., Naska T., Pennell N.A., Raymond D., Schilero C., Smolenski K., Williams F., Morrison C., Borgia J.A., Liptay M.J., Pool M., Seder C.W., Junker K., Dinkin M., Manikhas G., Alvaro D., Bragazzi M.C., Cardinale V., Carpino G., Gaudio E., Chesla D., Cottingham S., Dubina M., Moiseenko F., Dhanasekaran R., Becker K.-F., Janssen K.-P., Slotta-Huspenina J., Abdel-Rahman M.H., Aziz D., Bell S., Cebulla C.M., Davis A., Duell R., Elder J.B., Hilty J., Kumar B., Lang J., Lehman N.L., Mandt R., Nguyen P., Pilarski R., Rai K., Schoenfield L., Senecal K., Wakely P., Hansen P., Lechan R., Powers J., Tischler A., Grizzle W.E., Sexton K.C., Kastl A., Henderson J., Porten S., Waldmann J., Fassnacht M., Asa S.L., Schadendorf D., Couce M., Graefen M., Huland H., Sauter G., Schlomm T., Simon R., Tennstedt P., Olabode O., Nelson M., Bathe O., Carroll P.R., Chan J.M., Disaia P., Glenn P., Kelley R.K., Landen C.N., Phillips J., Prados M., Simko J., Smith-McCune K., VandenBerg S., Roggin K., Fehrenbach A., Kendler A., Sifri S., Steele R., Jimeno A., Carey F., Forgie I., Mannelli M., Carney M., Hernandez B., Campos B., Herold-Mende C., Jungk C., Unterberg A., von Deimling A., Bossler A., Galbraith J., Jacobus L., Knudson M., Knutson T., Ma D., Milhem M., Sigmund R., Madan R., Rosenthal H.G., Adebamowo C., Adebamowo S.N., Boussioutas A., Beer D., Giordano T., Mes-Masson A.-M., Saad F., Bocklage T., Landrum L., Mannel R., Moore K., Moxley K., Postier R., Walker J., Zuna R., Feldman M., Valdivieso F., Dhir R., Luketich J., Pinero E.M.M., Quintero-Aguilo M., Carlotti C.G., Dos Santos J.S., Kemp R., Sankarankuty A., Tirapelli D., Catto J., Agnew K., Swisher E., Creaney J., Robinson B., Shelley C.S., Godwin E.M., Kendall S., Shipman C., Bradford C., Carey T., Haddad A., Moyer J., Peterson L., Prince M., Rozek L., Wolf G., Bowman R., Fong K.M., Yang I., Korst R., Rathmell W.K., Fantacone-Campbell J.L., Hooke J.A., Kovatich A.J., Shriver C.D., DiPersio J., Drake B., Govindan R., Heath S., Ley T., Van Tine B., Westervelt P., Rubin M.A., Lee J.I., Aredes N.D., Mariamidze A., SAIC-F-Frederick, Inc, and Leidos Biomedical Research, Inc.

Subjects
0301 basic medicine, Carcinogenesis, pan-cancer, Cancer Genome Atlas Research Network, medicine.disease_cause, Biochemistry, epigenomic, Epigenesis, Genetic, genomic, Machine Learning, GENE-EXPRESSION SIGNATURE, TUMOR, Neoplasms, Databases, Genetic, Tumor Microenvironment, LS4_6, Stemness, Neoplasm Metastasis, 610 Medicine & health, Induced pluripotent stem cell, 11 Medical and Health Sciences, Carcinogenesi, Epigenomics, Cancer stem cells, Stem Cells, PROLIFERATION, MicroRNA, Sciences bio-médicales et agricoles, CANCER, stemne, Neoplasm Metastasi, CONNECTIVITY MAP, ALGORITMOS, Stem cell, Life Sciences & Biomedicine, Human, Biochemistry & Molecular Biology, cancer stem cell, The Cancer Genome Atlas, Biology, Article, General Biochemistry, Genetics and Molecular Biology, NO, ANNEXIN 1, 03 medical and health sciences, Stem Cell, Cancer stem cell, medicine, Humans, Epigenetics, EMBRYONIC STEM, Tumor microenvironment, Science & Technology, Biochemistry, Genetics and Molecular Biology(all), dedifferentiation, Cell Biology, 06 Biological Sciences, Cell Dedifferentiation, DNA Methylation, Immune checkpoint, SELF-RENEWAL, MicroRNAs, 030104 developmental biology, CELLS, Cancer research, Neoplasm, OVEREXPRESSION, The Cancer Genome Atla, Transcriptome, cancer stem cells, machine learning, stemness, Genetics and Molecular Biology(all), Developmental Biology
Abstract

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation. Stemness features extracted from transcriptomic and epigenetic data from TCGA tumors reveal novel biological and clinical insight, as well as potential drug targets for anti-cancer therapies., 0, info:eu-repo/semantics/published

Published
2018

39. Spatiotemporal omics for biology and medicine.

Author

Liu L, Chen A, Li Y, Mulder J, Heyn H, and Xu X

Subjects
Humans, Animals, Proteomics, Genomics
Abstract

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases., Competing Interests: Declaration of interests X.X., L.L., A.C., and Y.L. are the co-inventors of Stereo-seq technology. The chip, procedure, and applications of Stereo-seq are covered in pending patents., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Published
2024
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40. Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony.

Author

Eder M, Martin OMF, Oswal N, Sedlackova L, Moutinho C, Del Carmen-Fabregat A, Menendez Bravo S, Sebé-Pedrós A, Heyn H, and Stroustrup N

Subjects
Animals, Caenorhabditis elegans Proteins metabolism, Caenorhabditis elegans Proteins genetics, RNA, Messenger metabolism, RNA, Messenger genetics, Caenorhabditis elegans genetics, Caenorhabditis elegans physiology, Aging genetics, Gene Regulatory Networks, Transcriptome genetics, Longevity genetics
Abstract

In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans "pan-transcriptome"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging., Competing Interests: Declaration of interests H.H. is co-founder of Omniscope and scientific advisory board member of MiRXES. C.M. is scientific consultant member of GLG., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Published
2024
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41. Decoding the muscle transcriptome of patients with late onset Pompe disease reveals markers of disease progression.

Author

Monceau A, Gokul Nath R, Suárez-Calvet X, Musumeci O, Toscano A, Kierdaszuk B, Kostera-Pruszczyk A, Domínguez-González C, Hernández-Lain A, Paradas C, Rivas E, Papadimas G, Papadopoulos C, Chrysanthou-Piterou M, Gallardo E, Olivé M, Lilleker J, Roberts ME, Marchese D, Lunazzi G, Heyn H, Fernández-Simón E, Villalobos E, Clark J, Katsikis P, Collins C, Mehra P, Laidler Z, Vincent A, Tasca G, Marini-Bettolo C, Guglieri M, Straub V, Raben N, and Díaz-Manera J

Abstract

Late-onset Pompe Disease (LOPD) is a rare genetic disorder caused by the deficiency of acid alpha-glucosidase leading to progressive cellular dysfunction due to the accumulation of glycogen in the lysosome. The mechanism of relentless muscle damage - a classic manifestation of the disease - has been extensively studied by analysing the whole muscle tissue; however, little, if any, is known about transcriptional heterogeneity among nuclei within the multinucleated skeletal muscle cells. This is the first report of application of single nuclei RNA sequencing to uncover changes in the gene expression profile in muscle biopsies from eight patients with LOPD and four muscle samples from age and gender matched healthy controls. We matched these changes with histology findings using GeoMx Spatial Transcriptomics to compare the transcriptome of control myofibers from healthy individuals with non-vacuolated (histologically unaffected) and vacuolated (histologically affected) myofibers of LODP patients. We observed an increase in the proportion of slow and regenerative muscle fibers and macrophages in LOPD muscles. The expression of the genes involved in glycolysis was reduced, whereas the expression of the genes involved in the metabolism of lipids and amino acids was increased in non-vacuolated fibers, indicating early metabolic abnormalities. Additionally, we detected upregulation of autophagy genes, and downregulation of the genes involved in ribosomal and mitochondrial function leading to defective oxidative phosphorylation. The upregulation of the genes associated with inflammation, apoptosis and muscle regeneration was observed only in vacuolated fibers. Notably, enzyme replacement therapy - the only available therapy for the disease - showed a tendency to restore metabolism dysregulation, particularly within slow fibers. A combination of single nuclei RNA sequencing and spatial transcriptomics revealed the landscape of normal and the diseased muscle, and highlighted the early abnormalities associated with the disease progression. Thus, the application of these two new cutting-edge technologies provided insight into the molecular pathophysiology of muscle damage in LOPD and identified potential avenues for therapeutic intervention., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Published
2024
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42. Unraveling the molecular architecture of autoimmune thyroid diseases at spatial resolution.

Author

Martínez-Hernández R, Sánchez de la Blanca N, Sacristán-Gómez P, Serrano-Somavilla A, Muñoz De Nova JL, Sánchez Cabo F, Heyn H, Sampedro-Núñez M, and Marazuela M

Subjects
Humans, Fibroblasts metabolism, Fibroblasts pathology, Histocompatibility Antigens Class II metabolism, Histocompatibility Antigens Class II genetics, Thyroid Epithelial Cells metabolism, Thyroid Epithelial Cells pathology, Endothelial Cells metabolism, Endothelial Cells pathology, Transcriptome, Myofibroblasts metabolism, Myofibroblasts pathology, Stromal Cells metabolism, Stromal Cells pathology, Female, Macrophage Migration-Inhibitory Factors, Intramolecular Oxidoreductases, Graves Disease pathology, Graves Disease immunology, Graves Disease genetics, Graves Disease metabolism, Thyroid Gland pathology, Thyroid Gland metabolism, Hashimoto Disease pathology, Hashimoto Disease immunology, Hashimoto Disease metabolism, Hashimoto Disease genetics, Antigens, Differentiation, B-Lymphocyte metabolism, Antigens, Differentiation, B-Lymphocyte genetics
Abstract

Autoimmune thyroid diseases (AITD) such as Graves' disease (GD) or Hashimoto's thyroiditis (HT) are organ-specific diseases that involve complex interactions between distinct components of thyroid tissue. Here, we use spatial transcriptomics to explore the molecular architecture, heterogeneity and location of different cells present in the thyroid tissue, including thyroid follicular cells (TFCs), stromal cells such as fibroblasts, endothelial cells, and thyroid infiltrating lymphocytes. We identify damaged antigen-presenting TFCs with upregulated CD74 and MIF expression in thyroid samples from AITD patients. Furthermore, we discern two main fibroblast subpopulations in the connective tissue including ADIRF + myofibroblasts, mainly enriched in GD, and inflammatory fibroblasts, enriched in HT patients. We also demonstrate an increase of fenestrated PLVAP + vessels in AITD, especially in GD. Our data unveil stromal and thyroid epithelial cell subpopulations that could play a role in the pathogenesis of AITD., (© 2024. The Author(s).)

Published
2024
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43. Systematic benchmarking of single-cell ATAC-sequencing protocols.

Author

De Rop FV, Hulselmans G, Flerin C, Soler-Vila P, Rafels A, Christiaens V, González-Blas CB, Marchese D, Caratù G, Poovathingal S, Rozenblatt-Rosen O, Slyper M, Luo W, Muus C, Duarte F, Shrestha R, Bagdatli ST, Corces MR, Mamanova L, Knights A, Meyer KB, Mulqueen R, Taherinasab A, Maschmeyer P, Pezoldt J, Lambert CLG, Iglesias M, Najle SR, Dossani ZY, Martelotto LG, Burkett Z, Lebofsky R, Martin-Subero JI, Pillai S, Sebé-Pedrós A, Deplancke B, Teichmann SA, Ludwig LS, Braun TP, Adey AC, Greenleaf WJ, Buenrostro JD, Regev A, Aerts S, and Heyn H

Subjects
Humans, Chromatin Immunoprecipitation Sequencing methods, Chromatin genetics, Transposases genetics, Sequence Analysis, DNA methods, High-Throughput Nucleotide Sequencing methods, Single-Cell Analysis methods, Benchmarking, Leukocytes, Mononuclear
Abstract

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols., (© 2023. The Author(s).)

Published
2024
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44. FixNCut: single-cell genomics through reversible tissue fixation and dissociation.

Author

Jiménez-Gracia L, Marchese D, Nieto JC, Caratù G, Melón-Ardanaz E, Gudiño V, Roth S, Wise K, Ryan NK, Jensen KB, Hernando-Momblona X, Bernardes JP, Tran F, Sievers LK, Schreiber S, van den Berge M, Kole T, van der Velde PL, Nawijn MC, Rosenstiel P, Batlle E, Butler LM, Parish IA, Plummer J, Gut I, Salas A, Heyn H, and Martelotto LG

Subjects
Humans, Animals, Mice, Tissue Fixation methods, Reproducibility of Results, Sequence Analysis, RNA methods, Single-Cell Analysis methods, RNA genetics, Genomics methods
Abstract

The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs., (© 2024. Crown.)

Published
2024
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45. scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

Author

Schäfer S, Smelik M, Sysoev O, Zhao Y, Eklund D, Lilja S, Gustafsson M, Heyn H, Julia A, Kovács IA, Loscalzo J, Marsal S, Zhang H, Li X, Gawel D, Wang H, and Benson M

Subjects
Humans, Precision Medicine, Tumor Necrosis Factor Inhibitors, Gene Expression Profiling, Immunomodulating Agents, Single-Cell Analysis, Sequence Analysis, RNA, Crohn Disease, Arthritis
Abstract

Background: Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs., Methods: Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs., Results: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment., Conclusions: We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio )., (© 2024. The Author(s).)

Published
2024
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46. Integrative single-cell expression and functional studies unravels a sensitization to cytarabine-based chemotherapy through HIF pathway inhibition in AML leukemia stem cells.

Author

Velasco-Hernandez T, Trincado JL, Vinyoles M, Closa A, Martínez-Moreno A, Gutiérrez-Agüera F, Molina O, Rodríguez-Cortez VC, Ximeno-Parpal P, Fernández-Fuentes N, Petazzi P, Beneyto-Calabuig S, Velten L, Romecin P, Casquero R, Abollo-Jiménez F, de la Guardia RD, Lorden P, Bataller A, Lapillonne H, Stam RW, Vives S, Torrebadell M, Fuster JL, Bueno C, Sarry JE, Eyras E, Heyn H, and Menéndez P

Abstract

Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML) and is driven by rare therapy-resistant leukemia stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling maintains cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to the chemoresistance of AML-LSCs and may represent a therapeutic target to sensitize AML-LSCs to chemotherapy. Here, we identify HIF high and HIF low specific AML subgroups (inv(16)/ t (8;21) and MLLr, respectively) and provide a comprehensive single-cell expression atlas of 119,000 AML cells and AML-LSCs in paired diagnostic-relapse samples from these molecular subgroups. The HIF/hypoxia pathway signature is attenuated in AML-LSCs compared with more differentiated AML cells but is more expressed than in healthy hematopoietic cells. Importantly, chemical inhibition of HIF cooperates with standard-of-care chemotherapy to impair AML growth and to substantially eliminate AML-LSCs in vitro and in vivo. These findings support the HIF pathway in the stem cell-driven drug resistance of AML and unravel avenues for combinatorial targeted and chemotherapy-based approaches to specifically eliminate AML-LSCs., Competing Interests: Pablo Menéndez is the founder of the spin‐off OneChain Immunotherapeutics, which has no connection with the present research. The other authors declare no conflict of interest., (© 2024 The Authors. HemaSphere published by John Wiley & Sons Ltd. on behalf of European Hematology Association.)

Published
2024
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47. Converging and evolving immuno-genomic routes toward immune escape in breast cancer.

Author

Blanco-Heredia J, Souza CA, Trincado JL, Gonzalez-Cao M, Gonçalves-Ribeiro S, Gil SR, Pravdyvets D, Cedeño S, Callari M, Marra A, Gazzo AM, Weigelt B, Pareja F, Vougiouklakis T, Jungbluth AA, Rosell R, Brander C, Tresserra F, Reis-Filho JS, Tiezzi DG, de la Iglesia N, Heyn H, and De Mattos-Arruda L

Subjects
Humans, Female, Genomics methods, Tumor Microenvironment, Breast Neoplasms genetics, Triple Negative Breast Neoplasms genetics, Triple Negative Breast Neoplasms pathology
Abstract

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions., (© 2024. The Author(s).)

Published
2024
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48. An atlas of cells in the human tonsil.

Author

Massoni-Badosa R, Aguilar-Fernández S, Nieto JC, Soler-Vila P, Elosua-Bayes M, Marchese D, Kulis M, Vilas-Zornoza A, Bühler MM, Rashmi S, Alsinet C, Caratù G, Moutinho C, Ruiz S, Lorden P, Lunazzi G, Colomer D, Frigola G, Blevins W, Romero-Rivero L, Jiménez-Martínez V, Vidal A, Mateos-Jaimez J, Maiques-Diaz A, Ovejero S, Moreaux J, Palomino S, Gomez-Cabrero D, Agirre X, Weniger MA, King HW, Garner LC, Marini F, Cervera-Paz FJ, Baptista PM, Vilaseca I, Rosales C, Ruiz-Gaspà S, Talks B, Sidhpura K, Pascual-Reguant A, Hauser AE, Haniffa M, Prosper F, Küppers R, Gut IG, Campo E, Martin-Subero JI, and Heyn H

Subjects
Humans, Adult, Palatine Tonsil, B-Lymphocytes metabolism
Abstract

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil., Competing Interests: Declaration of interests H.H. is co-founder of Omniscope, SAB member of Nanostring and MiRXES, and consultant to Moderna and Singularity. J.C.N. is consultant to Omniscope., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2024
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49. The cellular landscape of the endochondral bone during the transition to extrauterine life.

Author

Rueda AD, Salvador-Martínez I, Sospedra-Arrufat I, Alcaina-Caro A, Fernández-Miñán A, Burgos-Ruiz AM, Cases I, Mohedano A, Tena JJ, Heyn H, Lopez-Rios J, and Nusspaumer G

Subjects
Mice, Animals, Bone and Bones, Bone Marrow, Hematopoiesis, Osteogenesis genetics, Mesenchymal Stem Cells
Abstract

The cellular complexity of the endochondral bone underlies its essential and pleiotropic roles during organismal life. While the adult bone has received significant attention, we still lack a deep understanding of the perinatal bone cellulome. Here, we have profiled the full composition of the murine endochondral bone at the single-cell level during the transition from fetal to newborn life and in comparison with the adult tissue, with particular emphasis on the mesenchymal compartment. The perinatal bone contains different fibroblastic clusters with blastema-like characteristics in organizing and supporting skeletogenesis, angiogenesis and hematopoiesis. Our data also suggest dynamic inter- and intra-compartment interactions, as well as a bone marrow milieu that seems prone to anti-inflammation, which we hypothesize is necessary to ensure the proper program of lymphopoiesis and the establishment of central and peripheral tolerance in early life. Our study provides an integrative roadmap for the future design of genetic and cellular functional assays to validate cellular interactions and lineage relationships within the perinatal bone., (© 2024 The Authors. Immunology & Cell Biology published by John Wiley & Sons Australia, Ltd on behalf of the Australian and New Zealand Society for Immunology, Inc.)

Published
2024
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50. Author Correction: Macrophage and neutrophil heterogeneity at single-cell spatial resolution in human inflammatory bowel disease.

Author

Garrido-Trigo A, Corraliza AM, Veny M, Dotti I, Melón-Ardanaz E, Rill A, Crowell HL, Corbí Á, Gudiño V, Esteller M, Álvarez-Teubel I, Aguilar D, Masamunt MC, Killingbeck E, Kim Y, Leon M, Visvanathan S, Marchese D, Caratù G, Martin-Cardona A, Esteve M, Ordás I, Panés J, Ricart E, Mereu E, Heyn H, and Salas A

Published
2024
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