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1. HaloTag display enables quantitative single-particle characterisation and functionalisation of engineered extracellular vesicles.

Author

Mitrut, Roxana, Stranford, Devin, DiBiase, Beth, Chan, Jonathan, Bailey, Matthew, Luo, Minrui, Harper, Clare, Meade, Thomas, Wang, Muzhou, and Leonard, Joshua

Subjects
HaloTag, extracellular vesicle, quantification, single vesicle, Extracellular Vesicles, Humans, Flow Cytometry, Protein Engineering, Microscopy, Fluorescence, Bioengineering
Abstract

Extracellular vesicles (EVs) play key roles in diverse biological processes, transport biomolecules between cells and have been engineered for therapeutic applications. A useful EV bioengineering strategy is to express engineered proteins on the EV surface to confer targeting, bioactivity and other properties. Measuring how incorporation varies across a population of EVs is important for characterising such materials and understanding their function, yet it remains challenging to quantitatively characterise the absolute number of engineered proteins incorporated at single-EV resolution. To address these needs, we developed a HaloTag-based characterisation platform in which dyes or other synthetic species can be covalently and stoichiometrically attached to engineered proteins on the EV surface. To evaluate this system, we employed several orthogonal quantification methods, including flow cytometry and fluorescence microscopy, and found that HaloTag-mediated quantification is generally robust across EV analysis methods. We compared HaloTag-labelling to antibody-labelling of EVs using single vesicle flow cytometry, enabling us to measure the substantial degree to which antibody labelling can underestimate proteins present on an EV. Finally, we demonstrate the use of HaloTag to compare between protein designs for EV bioengineering. Overall, the HaloTag system is a useful EV characterisation tool which complements and expands existing methods.

Published
2024

6. Defocus modelling for 3D reconstruction and rendering

Author

Bailey, Matthew James, Hilton, Adrian Douglas Mark, and Guillemaut, Jean-Yves

Subjects
Depth from Defocus, Thick Lens Model, Multi-View Reconstruction, Neural Rendering
Abstract

Defocus formation from a finite aperture is a well-known phenomenon, occurring in many forms of photographic media. Although defocus is often exploited for artistic reasons, a surprising amount of information about the scene structure is encoded in the camera's blurring function. The aim of this work is to explore how this can be leveraged to recover 3D geometry from scenes with complex reflectance. Depth from defocus (DFD) is a well-established field that aims to reconstruct scene geometry from analysis of the defocus appearance, usually by modelling the camera as a thin lens. While many existing methods achieve approximate depth maps suitable for some applications, the majority are limited to geometrically inconsistent single-view reconstructions. The first contribution generalises image formation to a thick lens, and proposes a novel calibration procedure for accurate defocus modelling. This approach is shown to significantly outperform traditional thin lens assumptions in macro-scale scene reconstruction. The second contribution generalises reconstruction to multiple views, and evaluates the com- plementary properties of defocus and stereo information in a novel reconstruction framework. Unlike conventional multi-view stereo (MVS), which depends on photometric consistency be- tween views, DFD requires only a single viewpoint for reconstruction. This makes defocus-based approaches naturally robust to view-dependent materials considered challenging for traditional MVS. Conversely, textures which are invariant to defocus can be suitable for correspondence. This complementary relationship is investigated to determine the benefits of combining defocus information with stereo cues; with performance evaluated on per-viewpoint depth maps as well as complete 3D reconstructions. The results demonstrate an improvement over DFD alone even in specular and reflective datasets, and outperform state-of-the-art MVS. The third contribution explores the novel application of neural rendering to defocus modelling. Specifically, the recent advances in deep learning are leveraged to solve for three latent variables encoded as pixel intensities in a focal stack: the scene depth and radiance, and the camera point spread function. This is in contrast to the majority of existing defocus-based literature, which assume at least one of these variables is known. These quantities are disentangled by modelling each as a multilayer perception network, and trained end-to-end on the appearance of each pixel under different camera settings. This approach allows novel refocused images to be rendered that accurately capture the bokeh produced by specular highlights with arbitrary aperture shapes. Since the networks are trained according to a convolutional defocus model, the synthesised images can generalise to unconstrained aperture diameters, and achieve depth of field effects that exceed what was observed during training.

Published
2023
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12. Computational models of assembly, structure and damage to collagen IV networks

Author

Bailey, Matthew and Wilson, Mark

Subjects
Collagen, Computational chemistry
Abstract

Collagen IV networks play a key structural role in the human ocular lens capsule. However, their structure is not well understood, and is hypothesised to undergo significant changes over a lifetime, resulting in a loss of ability to accommodate different focal depths. In this thesis, a range of computational models and methods are developed, which aim to help better understand the properties of 2D networks of biopolymers, especially inspired by collagen IV. The available experimental images of collagen-containing networks are assessed and an image analysis protocol is developed. A Monte Carlo method is designed, which introduces disorder into simplified graph-based networks by switching edges. In addition, Molecular Dynamics is used to simulate coarse-grained polymers which attract one another at their headgroups. These coarse-grained polymers are shown to self-assemble into a variety of interesting network structures. The coarse-grained polymer approach is combined with a Molecular Statics scheme to calculate mechanical properties of the network, and understand how the networks behave when stretched. A model that can mimic the ageing of the network over a lifetime is developed. To better understand how lens capsule motion may damage collagen IV networks, the rupturing behaviour of the polymer networks is examined by stretching ordered hexagonal networks linearly and sinusoidally until they break. This is compared to the rupturing behaviour of networks containing defects. The MD method is used to assess the surface roughness and dimensionality of polymer networks, which is quantified by a fractal dimension. Finally, a new type of persistence diagram is used to quantify and visualise damage to ring structures in a network over time.

Published
2022

13. PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery

Author

Koc, Soner, Lloyd, Michael W, Grover, Jeffrey W, Xiao, Nan, Seepo, Sara, Subramanian, Sai Lakshmi, Ray, Manisha, Frech, Christian, DiGiovanna, John, Webster, Phillip, Neuhauser, Steven, Srivastava, Anuj, Woo, Xing Yi, Sanderson, Brian J, White, Brian, Lott, Paul, Dobrolecki, Lacey E, Dowst, Heidi, Bailey, Matthew, Cortes-Sanchez, Emilio, Scherer, Sandra, Yang, Chieh-Hsiang, Fujita, Maihi, Chu, Zhengtao, Zhao, Ling, Butterfield, Andrew, Akcakanat, Argun, Boning, Gao, Evans, Kurt, Fang, Bingliang, Gibbons, Don, Jensen, Vanessa, Keener, Dara, Kim, Michael, Kopetz, Scott, Majidi, Mourad, Menter, David, Minna, John, Park, Hyunsil, Yang, Fei, Timmons, Brenda, Wang, Jing, Westin, Shannon, Yap, Timothy, Zhang, Jianhua, Zhang, Ran, Ha, Min Jin, Chen, Huiqin, Xi, Yuanxin, Girard, Luc, Yucan, Erkan, Kirby, Bryce P, Dai, Bingbing, Xu, Yi, Sorokin, Alexey, Gale, Kelly, Augustine, Jithesh, Scott, Stephen, Meraz, Ismail, Fingerman, Dylan, Kossenkov, Andrew, Liu, Qin, Xiao, Min, Wickramasinghe, Jayamanna, Lin, Haiyin, Ramirez-Salazar, Eric, Nathanson, Kate, Tetzlaff, Mike, Xu, George, Yennu-Nanda, Vashisht G, Aft, Rebecca, Andrews, Jessica, Asaro, Alicia, Cao, Song, Chen, Feng, Davies, Sherri, DiPersio, John, Fields, Ryan, Foltz, Steven, Fuh, Katherine, Lim, Kian, Held, Jason, Hoog, Jeremy, Jayasinghe, Reyka G, Li, Yize, Luo, Jinqin, Ma, Cynthia, Mashl, Jay, Mo, Chia-Kuei, Rodriguez, Fernanda, Sun, Hua, Terekhanova, Nadezhda V, Tipton, Rose, VanTine, Brian, Wang-Gillam, Andrea, Wendl, Mike, Wu, Yige, Wyczalkowski, Matt, Yao, Lijun, and Zhou, Daniel Cui

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Networking and Information Technology R&D (NITRD), Biotechnology, 2.6 Resources and infrastructure (aetiology), Aetiology, Good Health and Well Being, PDXNet Consortium
Abstract

We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.

Published
2022

15. Series List

Author

Bailey, Matthew

Published
2023

17. Works Cited

Author

Bailey, Matthew

Published
2023

18. Index

Author

Bailey, Matthew

Published
2023

19. Notes

Author

Bailey, Matthew

Published
2023

21. Conclusion

Author

Bailey, Matthew

Published
2023

30. Regional Practice Variation and Outcomes in the Standard Versus Accelerated Initiation of Renal Replacement Therapy in Acute Kidney Injury (STARRT-AKI) Trial: A Post Hoc Secondary Analysis

Author

Vaara, Suvi T., Serpa Neto, Ary, Bellomo, Rinaldo, Adhikari, Neill K. J., Dreyfuss, Didier, Gallagher, Martin, Gaudry, Stephane, Hoste, Eric, Joannidis, Michael, Pettilä, Ville, Wang, Amanda Y., Kashani, Kianoush, Wald, Ron, Bagshaw, Sean M., Ostermann, Marlies, Bagshaw, Sean M, Wald, Ron, Adhikari, Neill K.J., Bellomo, Rinaldo, Dreyfuss, Didier, Du, Bin, Gallagher, Martin P., Gaudry, Stéphane, Hoste, Eric A., Lamontagne, François, Joannidis, Michael, Liu, Kathleen D., McAuley, Daniel F., McGuinness, Shay P., Nichol, Alistair D., Ostermann, Marlies, Palevsky, Paul M., Qiu, Haibo, Pettilä, Ville, Schneider, Antoine G., Smith, Orla M., Vaara, Suvi T., Weir, Matthew, Bellomo, Rinaldo, Eastwood, Glenn M., Peck, Leah, Young, Helen, Kruger, Peter, Laurie, Gordon, Saylor, Emma, Meyer, Jason, Venz, Ellen, Wetzig, Krista, French, Craig, McGain, Forbes, Mulder, John, Fennessy, Gerard, Koottayi, Sathyajith, Bates, Samantha, Towns, Miriam, Morgan, Rebecca, Tippett, Anna, Udy, Andrew, Mason, Chris, Licari, Elisa, Gantner, Dashiell, McClure, Jason, Nichol, Alistair, McCracken, Phoebe, Board, Jasmin, Martin, Emma, Vallance, Shirley, Young, Meredith, Vladic, Chelsey, McGloughlin, Steve, Gattas, David, Buhr, Heidi, Coles, Jennifer, Hutch, Debra, Wun, James, Cole, Louise, Whitehead, Christina, Lowrey, Julie, Masters, Kristy, Gresham, Rebecca, Campbell, Victoria, Gutierrez, David, Brailsford, Jane, Forbes, Loretta, Murray, Lauren, Maguire, Teena, NiChonghaile, Martina, Orford, Neil, Bone, Allison, Elderkin, Tania, Salerno, Tania, Chimunda, Tim, Fletcher, Jason, Broadfield, Emma, Porwal, Sanjay, Knott, Cameron, Boschert, Catherine, Smith, Julie, Richardson, Angus, Hill, Dianne, Duke, Graeme, Oziemski, Peter, Cegarra, Santiago, Chan, Peter, Welsh, Deborah, Hunter, Stephanie, Roodenburg, Owen, Dyett, John, Kokotsis, Nicos, Moser, Max, Yang, Yang, Padayachee, Laven, Vetro, Joseph, Gangopadhyay, Himangsu, Kaufman, Melissa, Ghosh, Angaj, Said, Simone, Patel, Alpesh, Bihari, Shailesh, Matheson, Elisha, Jin, Xia, Shrestha, Tapaswi, Schwartz, Kate, Gallagher, Martin P., Cross, Rosalba, Cheung, Winston, Wong, Helen, Kol, Mark, Shah, Asim, Wang, Amanda Y., Endre, Zoltan, Bradford, Celia, Janin, Pierre, Finfer, Simon, Diel, Naomi, Gatward, Jonathan, Hammond, Naomi, Delaney, Anthony, Bass, Frances, Yarad, Elizabeth, Buscher, Hergen, Reynolds, Claire, Baker, Nerilee, Joannidis, Michael, Bellmann, Romuald, Peer, Andreas, Hasslacher, Julia, Koglberger, Paul, Klein, Sebastian, Zotter, Klemens, Brandtner, Anna, Finkenstedt, Armin, Ditlbacher, Adelheid, Hartig, Frank, Fries, Dietmar, Bachler, Mirjam, Schenk, Bettina, Wagner, Martin, Staudinger, Thomas, Tiller, Esther, Schellongowski, Peter, Bojic, Andja, Hoste, Eric A., Bracke, Stephanie, De Crop, Luc, Vermeiren, Daisy, Thome, Fernando, Chiella, Bianca, Fendt, Lucia, Antunes, Veronica, Maisonneuve-Rosemont, Lafrance, Jean-Philippe, Lamontagne, François, D’Aragon, Frédérick, St-Arnaud, Charles, Mayette, Michael, Carbonnaeu, Élaine, Marchand, Joannie, Masse, Marie-Hélène, Ladouceur, Marilène, Turgeon, Alexis F., Lauzier, François, Bellemare, David, Langis Francoeur, Charles, LeBlanc, Guillaume, Guilbault, Gabrielle, Grenier, Stéphanie, Cloutier, Eve, Boivin, Annick, Delisle-Thibault, Charles, Giannakouros, Panagiota, Costerousse, Olivier, Cailhier, Jean-François, Carrier, François-Martin, Ghamraoui, Ali, Lebrasseur, Martine, Benettaib, Fatna, Salamé, Maya, Boumahni, Dounia, Tung Sia, Ying, Naud, Jean-François, Roy, Isabelle, Stelfox, Henry T., Ruddell, Stacey, Manns, Braden J., Duggan, Shelley, Carney, Dominic, Barchard, Jennifer, Whitlock, Richard P., Belley-Cote, Emilie, Savija, Nevena, Sabev, Alexandra, Campbell, Troy, Creary, Thais, Devereaux, Kelson, Brodutch, Shira, Rigatto, Claudio, Paunovic, Bojan, Mooney, Owen, Glybina, Anna, Harasemiw, Oksana, Di Nella, Michelle, Harmon, John, Mehta, Navdeep, Lakatos, Louis, Haslam, Nicole, Lellouche, Francois, Simon, Mathieu, Tung, Ying, Lizotte, Patricia, Bourchard, Pierre-Alexandre, Rochwerg, Bram, Karachi, Tim, Millen, Tina, Muscedere, John, Maslove, David, Gordon Boyd, J., Sibley, Stephanie, Drover, John, Hunt, Miranda, Georgescu, Ilinca, Wax, Randy, Lenga, Ilan, Sridhar, Kavita, Steele, Andrew, Fusco, Kelly, Ghate, Taneera, Tolibas, Michael, Robinson, Holly, Weir, Matthew A., Taneja, Ravi, Ball, Ian M., Garg, Amit, Campbell, Eileen, Ovsenek, Athena, Bagshaw, Sean M., van Diepen, Sean, Baig, Nadia, Magder, Sheldon, Yao, Han, Alam, Ahsan, Campisi, Josie, MacIntyre, Erika, Rokosh, Ella, Scherr, Kimberly, Lapinsky, Stephen, Mehta, Sangeeta, Shah, Sumesh, Niven, Daniel J., Stelfox, Henry T., Ruddell, Stacey, Russell, Michael, Jim, Kym, Brown, Gillian, Oxtoby, Kerry, Hall, Adam, Benoit, Luc, Sokolowski, Colleen, Prasad, Bhanu, Rao, Jag, Giebel, Shelley, Kutsogiannis, Demetrios J., Thompson, Patricia, Thompson, Tayne, Cirone, Robert, Kavikondala, Kanthi, Soth, Mark, Clarke, France, Takaoka, Alyson, Wald, Ron, Mazer, David, Burns, Karen, Friedrich, Jan, Klein, David, Sandhu, Gyan, Santos, Marlene, Khalid, Imrana, Hodder, Jennifer, Dodek, Peter, Ayas, Najib, Alcuaz, Victoria, Suen, Gabriel, Rewa, Oleksa, Singh, Gurmeet, Norris, Sean, Gibson, Neil, Arias, Castro, Shami, Aysha, Pelletier, Celine, Adhikari, Neill K.J., Zahirieh, Alireza, Amaral, Andre, Marinoff, Nicole, Kaur, Navjot, Perez, Adic, Wang, Jane, Haljan, Gregory, Condin, Christopher, McIntyre, Lauralyn, Gomes, Brigette, Porteous, Rebecca, Watpool, Irene, Hiremath, Swapnil, Clark, Edward, Herridge, Margaret S., Backhouse, Felicity, Elizabeth Wilcox, M., Walczak, Karolina, Ki, Vincent, Sharman, Asheer, Romano, Martin, Bagshaw, Sean M., Noel Gibney, R.T., Romanovsky, Adam S., Rewa, Oleksa, McCoshen, Lorena, Baig, Nadia, Wood, Gordon, Ovakim, Daniel, Auld, Fiona, Carney, Gayle, Duan, Meili, Ji, Xiaojun, Guo, Dongchen, Qi, Zhili, Lin, Jin, Zhang, Meng, Dong, Lei, Liu, Jingfeng, Liu, Pei, Zhi, Deyuan, Bai, Guoqiang, Qiu, Yu, Yang, Ziqi, Bai, Jing, Liu, Zhuang, Zhuang, Haizhou, Wang, Haiman, Li, Jian, Zhao, Mengya, Zhou, Xiao, Shi, Xianqing, Ye, Baning, Liu, Manli, Wu, Jing, Fu, Yongjian, Long, Dali, Pan, Yu, Wang, Jinlong, Mei, Huaxian, Zhang, Songsong, Wen, Mingxiang, Yang, Enyu, Mu, Sijie, Li, Jianquan, Hu, Tingting, Qin, Bingyu, Li, Min, Wang, Cunzhen, Dong, Xin, Wang, Kaiwu, Wang, Haibo, Yang, Jianxu, Du, Bin, Wang, Chuanyao, Wang, Dongxin, Li, Nan, Yu, Zhui, Xu, Song, Yao, Lan, Hou, Guo, Liu, Zhou, Lu, Liping, Lian, Yingtao, Wang, Chunting, Zhang, Jichen, Ding, Ruiqi, Qi, Guoqing, Wang, Qizhi, Wang, Peng, Meng, Zhaoli, Chen, Man, Hu, Xiaobo, He, Xiandi, Zhao, Shibing, Hang, Lele, Li, Rui, Qin, Suhui, Lu, Kun, Dun, Shijuan, Liu, Cheng, Zhou, Qi, Chen, Zhenzhen, Mei, Jing, Zhang, Minwei, Xu, Hao, Lin, Jincan, Shi, Qindong, Fu, Lijuan, Zeng, Qinjing, Ma, Hongye, Yan, Jinqi, Gao, Lan, Liu, Hongjuan, Zhang, Lei, Li, Hao, He, Xiaona, Fan, Jingqun, Guo, Litao, Liu, Yu, Wang, Xue, Sun, Jingjing, Liu, Zhongmin, Yang, Juan, Ding, Lili, Sheng, Lulu, Liu, Xingang, Yan, Jie, Wang, Quihui, Wang, Yifeng, Zhao, Dan, Zhao, Shuangping, Hu, Chenghuan, Li, Jing, Deng, Fuxing, Qiu, Haibo, Yang, Yi, Mo, Min, Pan, Chun, Wu, Changde, Huang, Yingzi, Huang, Lili, Liu, Airan, Pettilä, Ville, Vaara, Suvi T., Korhonen, Anna-Maija, Törnblom, Sanna, Sutinen, Sari, Pettilä, Leena, Heinonen, Jonna, Lappi, Eliria, Suhonen, Taria, Karlsson, Sari, Hoppu, Sanna, Jalkanen, Ville, Kuitunen, Anne, Levoranta, Markus, Långsjö, Jaakko, Ristimäki, Sanna, Malila, Kaisa, Wootten, Anna, Varila, Simo, Järvisalo, Mikko J, Inkinen, Outi, Kentala, Satu, Leivo, Keijo, Haltia, Paivi, Dreyfuss, Didier, Ricard, Jean-Damien, Messika, Jonathan, Tiagarajah, Abirami, Emery, Malo, Dechanet, Aline, Gernez, Coralie, Roux, Damien, Martin-Lefevre, Laurent, Fiancette, Maud, Vinatier, Isabelle, Claude Lacherade, Jean, Colin, Gwenhaël, Lebert, Christine, Azais, Marie-Ange, Yehia, Aihem, Pouplet, Caroline, Henry- Lagarrigue, Matthieu, Seguin, Amélie, Crosby, Laura, Maizel, Julien, Titeca-Beauport, Dimitri, Combes, Alain, Nieszkowska, Ania, Masi, Paul, Demoule, Alexandre, Mayaux, Julien, Dres, Martin, Morawiec, Elise, Decalvele, Maxens, Demiri, Suela, Faure, Morgane, Marios, Clémence, Mallet, Maxime, Amélie Ordon, Marie, Morizot, Laura, Cantien, Marie, Pousset, François, Gaudry, Stéphane, Poirson, Florent, Cohen, Yves, Argaud, Laurent, Cour, Martin, Bitker, Laurent, Simon, Marie, Hernu, Romain, Baudry, Thomas, De La Salle, Sylvie, Robine, Adrien, Sedillot, Nicholas, Tchenio, Xavier, Bouisse, Camille, Roux, Sylvie, Barbar, Davide, Trusson, Rémi, Tamion, Fabienne, Grangé, Steven, Carpentier, Dorothée, Chevrel, Guillaume, Ensenyat-Martin, Luis, Marque, Sophie, Quenot, Jean-Pierre, Andreu, Pascal, Dargent, Auguste, Large, Audrey, Chudeau, Nicolas, Landais, Mickael, Derrien, Benoit, Christophe Callahan, Jean, Guitton, Christophe, Le Moal, Charlène, Robert, Alain, Asehnoune, Karim, Cinotti, Raphaël, Grillot, Nicolas, Demeure, Dominique, Vinsonneau, Christophe, Rahmani, Imen, Marzouk, Mehdi, Dekeyser, Thibault, Sejourne, Caroline, Verlay, Mélanie, Thevenin, Fabienne, Delecolle, Lucie, Didier Thevenin, Lens, Souweine, Bertrand, Coupez, Elisabeth, Adda, Mireille, Eraldi, Jean-Pierre, Marchalot, Antoine, De Prost, Nicolas, Mekontso Dessap, Armand, Razazi, Keyvan, Meziani, Ferhat, Boisrame-Helms, Julie, Clere-Jehl, Raphael, Delabranche, Xavier, Kummerlen, Christine, Merdji, Hamid, Monnier, Alexandra, Rabouel, Yannick, Rahmani, Hassene, Allam, Hayat, Chenaf, Samir, Franja, Vincenta, Pons, Bertrand, Carles, Michel, Martino, Frédéric, Richard, Régine, Zuber, Benjamin, Lacave, Guillaume, Lakhal, Karim, Rozec, Bertrand, Dang Van, Hoa, Boulet, Éric, Dubos, René, Fadel, Fouad, Cleophax, Cedric, Dufour, Nicolas, Grant, Caroline, Thuong, Marie, Reignier, Jean, Canet, Emmanuel, Nicolet, Laurent, Boulain, Thierry, Nay, Mai-Anh, Benzekri, Dalila, Barbier, François, Bretagnol, Anne, Kamel, Toufik, Mathonnet, Armelle, Muller, Grégoire, Skarzynski, Marie, Rossi, Julie, Pradet, Amandine, Dos Santos, Sandra, Guery, Aurore, Muller, Lucie, Felix, Luis, Bohé, Julien, Thiéry, Guillaume, Aissaoui, Nadia, Vimpere, Damien, Commeureuc, Morgane, Diehl, Jean-Luc, Guerot, Emmanuel, Liangos, Orfeas, Wittig, Monika, Zarbock, Alexander, Küllmar, Mira, van Waegeningh, Thomas, Rosenow, Nadine, Nichol, Alistair D., Brickell, Kathy, Doran, Peter, Murray, Patrick T., Landoni, Giovanni, Lembo, Rosalba, Zangrillo, Alberto, Monti, Giacomo, Tozzi, Margherita, Marzaroli, Matteo, Lombardi, Gaetano, Paternoster, Gianluca, Vitiello, Michelangelo, McGuinness, Shay, Parke, Rachael, Butler, Magdalena, Gilder, Eileen, Cowdrey, Keri-Anne, Wallace, Samantha, Hallion, Jane, Woolett, Melissa, Neal, Philippa, Duffy, Karina, Long, Stephanie, McArthur, Colin, Simmonds, Catherine, Chen, Yan, McConnochie, Rachael, Newby, Lynette, Knight, David, Henderson, Seton, Mehrtens, Jan, Morgan, Stacey, Morris, Anna, Vander Hayden, Kymbalee, Burke, Tara, Bailey, Matthew, Freebairn, Ross, Chadwick, Lesley, Park, Penelope, Rolls, Christine, Thomas, Liz, Buehner, Ulrike, Williams, Erin, Albrett, Jonathan, Kirkham, Simon, Jackson, Carolyn, Browne, Troy, Goodson, Jennifer, Jackson, David, Houghton, James, Callender, Owen, Higson, Vicki, Keet, Owen, Dominy, Clive, Young, Paul, Hunt, Anna, Judd, Harriet, Lawrence, Cassie, Olatunji, Shaanti, Robertson, Yvonne, Latimer-Bell, Charlotte, Hendry, Deborah, Mckay-Vucago, Agnes, Beehre, Nina, Lesona, Eden, Navarra, Leanlove, Robinson, Chelsea, Jang, Ryan, Junge, Andrea, Lambert, Bridget, Schneider, Antoine G., Thibault, Michel, Eckert, Philippe, Kissling, Sébastien, Polychronopoulos, Erietta, Poli, Elettra, Altarelli, Marco, Schnorf, Madeleine, Abed Mallaird, Samia, Heidegger, Claudia, Perret, Aurelie, Montillier, Philippe, Sangla, Frederic, Neils, Seigenthaller, De Watteville, Aude, Phull, Mandeep-Kaur, George, Aparna, Hussain, Nauman, Pogreban, Tatiana, Lobaz, Steve, Daniels, Alison, Cunningham, Mishell, Kerr, Deborah, Nicholson, Alice, Shanmugasundaram, Pradeep, Abrams, Judith, Manso, Katarina, Hambrook, Geraldine, McKerrow, Elizabeth, Salva, Juvy, Foulkes, Stephen, Wise, Matthew, Morgan, Matt, Brooks, Jenny, Cole, Jade, Michelle Davies, Tracy, Hill, Helen, Thomas, Emma, Vizcaychipi, Marcela, Baharlo, Behrad, Carungcong, Jaime, Costa, Patricia, Martins, Laura, Kapoor, Ritoo, Hazelton, Tracy, Moon, Angela, Musselwhite, Janine, Shelley, Ben, McCall, Philip, Ostermann, Marlies, Arbane, Gill, Bociek, Aneta, Marotti, Martina, Lim, Rosario, Campos, Sara, Grau Novellas, Neus, Cennamo, Armando, Slack, Andrew, Wyncoll, Duncan, Camporota, Luigi, Sparkes, Simon, Tilley, Rosalinde, Rattray, Austin, Moreland, Gayle, Duffy, Jane, McGonigal, Elizabeth, Hopkins, Philip, Finney, Clare, Smith, John, Noble, Harriet, Watson, Hayley, Harris, Claire-Louise, Clarey, Emma, Corcoran, Eleanor, Beck, James, Howcroft, Clare, Youngs, Nora, Wilby, Elizabeth, Ogg, Bethan, Wolverson, Adam, Lee, Sandra, Butler, Susie, Okubanjo, Maryanne, Hindle, Julia, Welters, Ingeborg, Williams, Karen, Johnson, Emily, Patrick-Heselton, Julie, Shaw, David, Waugh, Victoria, Stewart, Richard, Mwaura, Esther, Wren, Lynn, Mew, Louise, Sutherland, Sara-Beth, Adderley, Jane, Ruddy, Jim, Harkins, Margaret, Kaye, Callum, Scott, Teresa, Mitchell, Wendy, Anderson, Felicity, Willox, Fiona, Jagannathan, Vijay, Clark, Michele, Purv, Sarah, Sharman, Andrew, Meredith, Megan, Ryan, Lucy, Conner, Louise, Peters, Cecilia, Harvey, Dan, Roshdy, Ashraf, Collins, Amy, Sim, Malcolm, Henderson, Steven, Chee, Nigel, Pitts, Sally, Bowman, Katie, Dilawershah, Maria, Vamplew, Luke, Howe, Elizabeth, Rogers, Paula, Hernandez, Clara, Prendergast, Clara, Benton, Jane, Rosenberg, Alex, Forni, Lui G., Grant, Alice, Carvelli, Paula, Raithatha, Ajay, Bird, Sarah, Richardson, Max, Needham, Matthew, Hirst, Claire, Ball, Jonathan, Leaver, Susannah, Howlett, Luisa, Castro Delgado, Carlos, Farnell-Ward, Sarah, Farrah, Helen, Gray, Geraldine, Joseph, Gipsy, Robinson, Francesca, Tridente, Ascanio, Harrop, Clare, Shuker, Karen, McLaughlan, Derek, Ramsey, Judith, Meehan, Sharon, Oliver Rose, Bernd, Reece-Anthony, Rosie, Gurung, Babita, Whitehouse, Tony, Snelson, Catherine, Veenith, Tonny, Johnston, Andy, Cooper, Lauren, Carrera, Ron, Ellis, Karen, Fellows, Emma, Harkett, Samanth, Bergin, Colin, Spruce, Elaine, Despy, Liesl, Goundry, Stephanie, Dooley, Natalie, Mason, Tracy, Clark, Amy, Dignam, Gemma, Ward, Geraldine, Attwood, Ben, Parsons, Penny, Mason, Sophie, Margarson, Michael, Lord, Jenny, McGlone, Philip, Hodgson, Luke E., Chadbourn, Indra, Gomez, Raquel, Margalef, Jordi, Pretorius, Rinus, Hamshere, Alexandra, Carter, Joseph, Cahill, Hazel, Grainger, Lia, Howard, Kate, Forshaw, Greg, Guy, Zoe, Kashani, Kianoush B., Albright, Robert C., Amsbaugh, Amy, Stoltenberg, Anita, Niven, Alexander S., Lynch, Matthew, O’Mara, AnnMarie, Naeem, Syed, Sharif, Sairah, McKenney Goulart, Joyce, Lynch, Matthew, O’Mara, AnnMarie, Naeem, Syed, Sharif, Sairah, McKenney Goulart, Joyce, Tolwani, Ashita, Lyas, Claretha, Latta, Laura, Bihorac, Azra, Hashemighouchani, Haleh, Efron, Philip, Ruppert, Matthew, Cupka, Julie, Kiley, Sean, Carson, Joshua, White, Peggy, Omalay, George, Brown, Sherry, Velez, Laura, Marceron, Alina, Neyra, Javier A., Carlos Aycinena, Juan, Elias, Madona, Ortiz-Soriano, Victor M., Hauschild, Caroline, and Dorfman, Robert

Published
2024
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32. Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidates for targeted treatment

Author

Sun, Hua, Cao, Song, Mashl, R Jay, Mo, Chia-Kuei, Zaccaria, Simone, Wendl, Michael C, Davies, Sherri R, Bailey, Matthew H, Primeau, Tina M, Hoog, Jeremy, Mudd, Jacqueline L, Dean, Dennis A, Patidar, Rajesh, Chen, Li, Wyczalkowski, Matthew A, Jayasinghe, Reyka G, Rodrigues, Fernanda Martins, Terekhanova, Nadezhda V, Li, Yize, Lim, Kian-Huat, Wang-Gillam, Andrea, Van Tine, Brian A, Ma, Cynthia X, Aft, Rebecca, Fuh, Katherine C, Schwarz, Julie K, Zevallos, Jose P, Puram, Sidharth V, Dipersio, John F, Davis-Dusenbery, Brandi, Ellis, Matthew J, Lewis, Michael T, Davies, Michael A, Herlyn, Meenhard, Fang, Bingliang, Roth, Jack A, Welm, Alana L, Welm, Bryan E, Meric-Bernstam, Funda, Chen, Feng, Fields, Ryan C, Li, Shunqiang, Govindan, Ramaswamy, Doroshow, James H, Moscow, Jeffrey A, Evrard, Yvonne A, Chuang, Jeffrey H, Raphael, Benjamin J, and Ding, Li

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Oncology and Carcinogenesis, Cancer, Human Genome, Biotechnology, Good Health and Well Being, Animals, Disease Models, Animal, Female, Gene Expression Regulation, Neoplastic, Genome, Genomics, Heterografts, Humans, Male, Mice, Models, Biological, Mutation, Neoplasms, Transcriptome, Xenograft Model Antitumor Assays, NCI PDXNet Consortium
Abstract

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors.

Published
2021

33. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts.

Author

Woo, Xing, Giordano, Jessica, Srivastava, Anuj, Zhao, Zi-Ming, Lloyd, Michael, de Bruijn, Roebi, Suh, Yun-Suhk, Patidar, Rajesh, Chen, Li, Scherer, Sandra, Bailey, Matthew, Yang, Chieh-Hsiang, Cortes-Sanchez, Emilio, Xi, Yuanxin, Wang, Jing, Wickramasinghe, Jayamanna, Kossenkov, Andrew, Rebecca, Vito, Sun, Hua, Mashl, R, Davies, Sherri, Jeon, Ryan, Frech, Christian, Randjelovic, Jelena, Rosains, Jacqueline, Galimi, Francesco, Bertotti, Andrea, Lafferty, Adam, OFarrell, Alice, Modave, Elodie, Lambrechts, Diether, Ter Brugge, Petra, Serra, Violeta, Marangoni, Elisabetta, El Botty, Rania, Kim, Hyunsoo, Kim, Jong-Il, Yang, Han-Kwang, Lee, Charles, Dean, Dennis, Davis-Dusenbery, Brandi, Evrard, Yvonne, Doroshow, James, Welm, Alana, Welm, Bryan, Lewis, Michael, Fang, Bingliang, Roth, Jack, Meric-Bernstam, Funda, Herlyn, Meenhard, Davies, Michael, Ding, Li, Li, Shunqiang, Govindan, Ramaswamy, Isella, Claudio, Moscow, Jeffrey, Trusolino, Livio, Byrne, Annette, Jonkers, Jos, Bult, Carol, Medico, Enzo, and Chuang, Jeffrey

Subjects
Animals, DNA Copy Number Variations, Databases, Genetic, Gene Expression Regulation, Neoplastic, Humans, Mice, Neoplasm Metastasis, Polymorphism, Single Nucleotide, Exome Sequencing, Xenograft Model Antitumor Assays
Abstract

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Published
2021

34. Pan-cancer proteogenomics connects oncogenic drivers to functional states

Author

An, Eunkyung, Anurag, Meenakshi, Bavarva, Jasmin, Birrer, Michael J., Calinawan, Anna, Ceccarelli, Michele, Chan, Daniel W., Chinnaiyan, Arul M., Cho, Hanbyul, Chowdhury, Shrabanti, Cieslik, Marcin P., da Veiga Leprevost, Felipe, Day, Corbin, Domagalski, Marcin J., Dou, Yongchao, Druker, Brian J., Edwards, Nathan, Ellis, Matthew J., Selvan, Myvizhi Esai, Foltz, Steven M., Francis, Alicia, Gonzalez Robles, Tania J., Gosline, Sara J.C., Gümüş, Zeynep H., Hiltke, Tara, Hong, Runyu, Hostetter, Galen, Hu, Yingwei, Huang, Chen, Huntsman, Emily, Jaehnig, Eric J., Jewel, Scott D., Ji, Jiayi, Jiang, Wen, Katsnelson, Lizabeth, Ketchum, Karen A., Kolodziejczak, Iga, Lei, Jonathan T., Liao, Yuxing, Lindgren, Caleb M., Liu, Tao, Ma, Weiping, McKerrow, Wilson, Nesvizhskii, Alexey I., Newton, Chelsea, Oldroyd, Robert, Omenn, Gilbert S., Paulovich, Amanda G., Petralia, Francesca, Reva, Boris, Rodland, Karin D., Ruggles, Kelly V., Rykunov, Dmitry, Savage, Sara R., Schadt, Eric E., Schnaubelt, Michael, Schraink, Tobias, Shi, Zhiao, Smith, Richard D., Song, Xiaoyu, Tan, Jimin, Thangudu, Ratna R., Tignor, Nicole, Wang, Joshua M., Wang, Pei, Wang, Ying (Cindy), Wen, Bo, Wiznerowicz, Maciej, Yi, Xinpei, Zhang, Bing, Zhang, Hui, Zhang, Xu, Zhang, Zhen, Li, Yize, Porta-Pardo, Eduard, Tokheim, Collin, Bailey, Matthew H., Yaron, Tomer M., Stathias, Vasileios, Geffen, Yifat, Imbach, Kathleen J., Cao, Song, Anand, Shankara, Akiyama, Yo, Liu, Wenke, Wyczalkowski, Matthew A., Song, Yizhe, Storrs, Erik P., Wendl, Michael C., Zhang, Wubing, Sibai, Mustafa, Ruiz-Serra, Victoria, Liang, Wen-Wei, Terekhanova, Nadezhda V., Rodrigues, Fernanda Martins, Clauser, Karl R., Heiman, David I., Zhang, Qing, Aguet, Francois, Calinawan, Anna P., Dhanasekaran, Saravana M., Birger, Chet, Satpathy, Shankha, Zhou, Daniel Cui, Wang, Liang-Bo, Baral, Jessika, Johnson, Jared L., Huntsman, Emily M., Pugliese, Pietro, Colaprico, Antonio, Iavarone, Antonio, Chheda, Milan G., Ricketts, Christopher J., Fenyö, David, Payne, Samuel H., Rodriguez, Henry, Robles, Ana I., Gillette, Michael A., Kumar-Sinha, Chandan, Lazar, Alexander J., Cantley, Lewis C., Getz, Gad, and Ding, Li

Published
2023
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36. Author Correction: Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples.

Author

Bailey, Matthew H, Meyerson, William U, Dursi, Lewis Jonathan, Wang, Liang-Bo, Dong, Guanlan, Liang, Wen-Wei, Weerasinghe, Amila, Li, Shantao, Li, Yize, Kelso, Sean, MC3 Working Group, PCAWG novel somatic mutation calling methods working group, Saksena, Gordon, Ellrott, Kyle, Wendl, Michael C, Wheeler, David A, Getz, Gad, Simpson, Jared T, Gerstein, Mark B, Ding, Li, and PCAWG Consortium

Subjects
MC3 Working Group, PCAWG novel somatic mutation calling methods working group, PCAWG Consortium
Abstract

Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20128-w.

Published
2020

37. Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples.

Author

Bailey, Matthew H, Meyerson, William U, Dursi, Lewis Jonathan, Wang, Liang-Bo, Dong, Guanlan, Liang, Wen-Wei, Weerasinghe, Amila, Li, Shantao, Li, Yize, Kelso, Sean, MC3 Working Group, PCAWG novel somatic mutation calling methods working group, Saksena, Gordon, Ellrott, Kyle, Wendl, Michael C, Wheeler, David A, Getz, Gad, Simpson, Jared T, Gerstein, Mark B, Ding, Li, and PCAWG Consortium

Subjects
MC3 Working Group, PCAWG novel somatic mutation calling methods working group, PCAWG Consortium, Humans, Neoplasms, DNA, Intergenic, Retrospective Studies, Base Composition, Mutation, Genome, Human, Exons, Databases, Genetic, Exome, Whole Genome Sequencing, Whole Exome Sequencing, Cancer, Biotechnology, Genetics, Human Genome
Abstract

The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF

Published
2020

38. Pan-cancer analysis of whole genomes

Author

Campbell, Peter J, Getz, Gad, Korbel, Jan O, Stuart, Joshua M, Jennings, Jennifer L, Stein, Lincoln D, Perry, Marc D, Nahal-Bose, Hardeep K, Ouellette, BF Francis, Li, Constance H, Rheinbay, Esther, Nielsen, G Petur, Sgroi, Dennis C, Wu, Chin-Lee, Faquin, William C, Deshpande, Vikram, Boutros, Paul C, Lazar, Alexander J, Hoadley, Katherine A, Louis, David N, Dursi, L Jonathan, Yung, Christina K, Bailey, Matthew H, Saksena, Gordon, Raine, Keiran M, Buchhalter, Ivo, Kleinheinz, Kortine, Schlesner, Matthias, Zhang, Junjun, Wang, Wenyi, Wheeler, David A, Ding, Li, Simpson, Jared T, O'Connor, Brian D, Yakneen, Sergei, Ellrott, Kyle, Miyoshi, Naoki, Butler, Adam P, Royo, Romina, Shorser, Solomon I, Vazquez, Miguel, Rausch, Tobias, Tiao, Grace, Waszak, Sebastian M, Rodriguez-Martin, Bernardo, Shringarpure, Suyash, Wu, Dai-Ying, Demidov, German M, Delaneau, Olivier, Hayashi, Shuto, Imoto, Seiya, Habermann, Nina, Segre, Ayellet V, Garrison, Erik, Cafferkey, Andy, Alvarez, Eva G, Maria Heredia-Genestar, Jose, Muyas, Francesc, Drechsel, Oliver, Bruzos, Alicia L, Temes, Javier, Zamora, Jorge, Baez-Ortega, Adrian, Kim, Hyung-Lae, Mashl, R Jay, Ye, Kai, DiBiase, Anthony, Huang, Kuan-lin, Letunic, Ivica, McLellan, Michael D, Newhouse, Steven J, Shmaya, Tal, Kumar, Sushant, Wedge, David C, Wright, Mark H, Yellapantula, Venkata D, Gerstein, Mark, Khurana, Ekta, Marques-Bonet, Tomas, Navarro, Arcadi, Bustamante, Carlos D, Siebert, Reiner, Nakagawa, Hidewaki, Easton, Douglas F, Ossowski, Stephan, Tubio, Jose MC, De La Vega, Francisco M, Estivill, Xavier, Yuen, Denis, Mihaiescu, George L, Omberg, Larsson, Ferretti, Vincent, Sabarinathan, Radhakrishnan, Pich, Oriol, Gonzalez-Perez, Abel, Weiner, Amaro Taylor, Fittall, Matthew W, Demeulemeester, Jonas, Tarabichi, Maxime, and Roberts, Nicola D

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Bioinformatics and Computational Biology, Genetics, Oncology and Carcinogenesis, Cancer Genomics, Biotechnology, Human Genome, Cancer, Prevention, 2.1 Biological and endogenous factors, Cell Proliferation, Cellular Senescence, Chromothripsis, Cloud Computing, DNA Mutational Analysis, Evolution, Molecular, Female, Genome, Human, Genomics, Germ-Line Mutation, High-Throughput Nucleotide Sequencing, Humans, Information Dissemination, Male, Mutagenesis, Mutation, Neoplasms, Oncogenes, Promoter Regions, Genetic, RNA Splicing, Reproducibility of Results, Telomerase, Telomere, ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, General Science & Technology
Abstract

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Published
2020

39. Effects of dietary yeast cell wall supplementation on growth performance, intestinal Campylobacter jejuni colonization, innate immune response, villus height, crypt depth, and slaughter characteristics of broiler chickens inoculated with Campylobacter jejuni at d 21

Author

Munoz, Luis R., Bailey, Matthew A., Krehling, James T., Bourassa, Dianna V., Hauck, Ruediger, Pacheco, Wilmer J., Chaves-Cordoba, Bernardo, Chasteen, Kaicie S., Talorico, Aidan A., Escobar, Cesar, Pietruska, Andrea, and Macklin, Ken S.

Published
2023
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40. Study protocol: PreOperative Brain Irradiation in Glioblastoma (POBIG) – A phase I trial

Author

Waqar, Mueez, Roncaroli, Federico, Djoukhadar, Ibrahim, Akkari, Leila, O'Leary, Claire, Hewitt, Lauren, Forte, Gabriella, Jackson, Richard, Hessen, Eline, Withington, Lisa, Beasley, William, Richardson, Jenny, Golby, Christopher, Whitehurst, Philip, Colaco, Rovel, Bailey, Matthew, Karabatsou, Konstantina, D'Urso, Pietro I., McBain, Catherine, Coope, David J., and Borst, Gerben R.

Published
2023
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43. Teams for Education

Author

Hubbard, Melissa, Bailey, Matthew J., Hess, D’arce, Hellebro, Mårten, Hubbard, Melissa, Bailey, Matthew J., Hess, D'arce, and Hellebro, Mårten

Published
2021
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46. Governance

Author

Hubbard, Melissa, Bailey, Matthew J., Hess, D’arce, Hellebro, Mårten, Hubbard, Melissa, Bailey, Matthew J., Hess, D'arce, and Hellebro, Mårten

Published
2021
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47. User Adoption in Teams

Author

Hubbard, Melissa, Bailey, Matthew J., Hess, D’arce, Hellebro, Mårten, Hubbard, Melissa, Bailey, Matthew J., Hess, D'arce, and Hellebro, Mårten

Published
2021
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48. Communicating in Teams

Author

Hubbard, Melissa, Bailey, Matthew J., Hess, D’arce, Hellebro, Mårten, Hubbard, Melissa, Bailey, Matthew J., Hess, D'arce, and Hellebro, Mårten

Published
2021
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49. Meetings in Teams

Author

Hubbard, Melissa, Bailey, Matthew J., Hess, D’arce, Hellebro, Mårten, Hubbard, Melissa, Bailey, Matthew J., Hess, D'arce, and Hellebro, Mårten

Published
2021
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50. Working in Teams

Author

Hubbard, Melissa, Bailey, Matthew J., Hess, D’arce, Hellebro, Mårten, Hubbard, Melissa, Bailey, Matthew J., Hess, D'arce, and Hellebro, Mårten

Published
2021
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