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1. The genomic and evolutionary landscapes of anaplastic thyroid carcinoma

Author

Peter Y.F. Zeng, Stephenie D. Prokopec, Stephen Y. Lai, Nicole Pinto, Michelle A. Chan-Seng-Yue, Roderick Clifton-Bligh, Michelle D. Williams, Christopher J. Howlett, Paul Plantinga, Matthew J. Cecchini, Alfred K. Lam, Iram Siddiqui, Jianxin Wang, Ren X. Sun, John D. Watson, Reju Korah, Tobias Carling, Nishant Agrawal, Nicole Cipriani, Douglas Ball, Barry Nelkin, Lisa M. Rooper, Justin A. Bishop, Cathie Garnis, Ken Berean, Norman G. Nicolson, Paul Weinberger, Ying C. Henderson, Christopher M. Lalansingh, Mao Tian, Takafumi N. Yamaguchi, Julie Livingstone, Adriana Salcedo, Krupal Patel, Frederick Vizeacoumar, Alessandro Datti, Liu Xi, Yuri E. Nikiforov, Robert Smallridge, John A. Copland, Laura A. Marlow, Martin D. Hyrcza, Leigh Delbridge, Stan Sidhu, Mark Sywak, Bruce Robinson, Kevin Fung, Farhad Ghasemi, Keith Kwan, S. Danielle MacNeil, Adrian Mendez, David A. Palma, Mohammed I. Khan, Mushfiq Shaikh, Kara M. Ruicci, Bret Wehrli, Eric Winquist, John Yoo, Joe S. Mymryk, James W. Rocco, David Wheeler, Steve Scherer, Thomas J. Giordano, John W. Barrett, William C. Faquin, Anthony J. Gill, Gary Clayman, Paul C. Boutros, and Anthony C. Nichols

Subjects
CP: Cancer, CP: Genomics, Biology (General), QH301-705.5
Abstract

Summary: Anaplastic thyroid carcinoma is arguably the most lethal human malignancy. It often co-occurs with differentiated thyroid cancers, yet the molecular origins of its aggressivity are unknown. We sequenced tumor DNA from 329 regions of thyroid cancer, including 213 from patients with primary anaplastic thyroid carcinomas. We also whole genome sequenced 9 patients using multi-region sequencing of both differentiated and anaplastic thyroid cancer components. Using these data, we demonstrate thatanaplastic thyroid carcinomas have a higher burden of mutations than other thyroid cancers, with distinct mutational signatures and molecular subtypes. Further, different cancer driver genes are mutated in anaplastic and differentiated thyroid carcinomas, even those arising in a single patient. Finally, we unambiguously demonstrate that anaplastic thyroid carcinomas share a genomic origin with co-occurring differentiated carcinomas and emerge from a common malignant field through acquisition of characteristic clonal driver mutations.

Published
2024
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2. Sex differences in oncogenic mutational processes

Author

Constance H. Li, Stephenie D. Prokopec, Ren X. Sun, Fouad Yousif, Nathaniel Schmitz, PCAWG Tumour Subtypes and Clinical Translation, Paul C. Boutros, and PCAWG Consortium

Subjects
Science
Abstract

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Published
2020
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3. BPG: Seamless, automated and interactive visualization of scientific data

Author

Christine P’ng, Jeffrey Green, Lauren C. Chong, Daryl Waggott, Stephenie D. Prokopec, Mehrdad Shamsi, Francis Nguyen, Denise Y. F. Mak, Felix Lam, Marco A. Albuquerque, Ying Wu, Esther H. Jung, Maud H. W. Starmans, Michelle A. Chan-Seng-Yue, Cindy Q. Yao, Bianca Liang, Emilie Lalonde, Syed Haider, Nicole A. Simone, Dorota Sendorek, Kenneth C. Chu, Nathalie C. Moon, Natalie S. Fox, Michal R. Grzadkowski, Nicholas J. Harding, Clement Fung, Amanda R. Murdoch, Kathleen E. Houlahan, Jianxin Wang, David R. Garcia, Richard de Borja, Ren X. Sun, Xihui Lin, Gregory M. Chen, Aileen Lu, Yu-Jia Shiah, Amin Zia, Ryan Kearns, and Paul C. Boutros

Subjects
Data-visualization, Interactive plotting, Software, Web-resources, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. Conclusion BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general

Published
2019
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4. Serological abnormalities that predict progression to systemic autoimmune rheumatic diseases in antinuclear antibody–positive individuals

Author

Carolina Muñoz-Grajales, Dennisse Bonilla, Linda T. Hiraki, Arthur Bookman, Andrzej Chruscinski, Joan E. Wither, Sindhu R. Johnson, Zareen Ahmad, Paul C. Boutros, Stephenie D. Prokopec, and Zahi Touma

Subjects
Adult, Male, Screening techniques, Anti-nuclear antibody, Clinical Sciences, Immunology, SLE, antinuclear antibodies, Asymptomatic, Autoimmune Disease, Antibodies, Serology, Autoimmune Diseases, Young Adult, Rheumatology, Antigen, Clinical Research, Predictive Value of Tests, Antinuclear, Rheumatic Diseases, medicine, 2.1 Biological and endogenous factors, Humans, Pharmacology (medical), Antinuclear antibody positive, Aetiology, screening and diagnosis, business.industry, Prevention, Inflammatory and immune system, Undifferentiated connective tissue disease, Clinical Science, Middle Aged, medicine.disease, 4.1 Discovery and preclinical testing of markers and technologies, Arthritis & Rheumatology, Ro52 antigen, Detection, Increased risk, Antibodies, Antinuclear, Public Health and Health Services, Disease Progression, Female, microarray analysis, medicine.symptom, business, 4.2 Evaluation of markers and technologies
Abstract

Objective We investigated the autoantibody (autoAb) profiles in ANA+ individuals lacking systemic autoimmune rheumatic disease (SARD) and early SARD patients to determine the key differences between these groups and identify factors that are associated with an increased risk of symptomatic progression within the next 2 years in ANA+ individuals. Methods Using custom antigen (Ag) microarrays, 144 IgM and IgG autoAbs were surveyed in 84 asymptomatic and 123 symptomatic (48 UCTD and 75 SARD patients) ANA+ individuals. AutoAbs were compared in ANA+ individuals lacking a SARD diagnosis with ≥2 years follow-up (n = 52), including all those who demonstrated progression (n = 14) during this period, with changes over time assessed in a representative subset. Results We show that ANA+ individuals have autoAb to many self-Ags that are not being captured by current screening techniques and very high levels of these autoAbs are predominantly restricted to early SARD patients, with SLE patients displaying reactivity to many more autoAgs than the other groups. In general, the symptoms that developed in progressors mirrored those seen in SARD patients with similar patterns of autoAbs. Only anti-Ro52 Abs were found to predict progression (positive predictive value 46%, negative predictive value 89%). Surprisingly, over 2 years of follow-up the levels of autoAbs remained remarkably stable regardless of whether individuals progressed or not. Conclusion Our findings strongly argue that development of assays with an expanded set of auto-Ags and enhanced dynamic range would improve the diagnostic and prognostic ability of autoAb testing.

Published
2021

5. Transgenerational epigenetic and transcriptomic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin exposure in rat

Author

Stephenie D. Prokopec, Paul C. Boutros, Hanna M. Miettinen, Raimo Pohjanvirta, Matti Viluksela, Food Hygiene and Environmental Health, Helsinki One Health (HOH), and Raimo Pohjanvirta / Principal Investigator

Subjects
0301 basic medicine, Male, DOWN-REGULATION, TCDD, Polychlorinated Dibenzodioxins, Health, Toxicology and Mutagenesis, 010501 environmental sciences, Toxicology, 01 natural sciences, Epigenesis, Genetic, Rats, Sprague-Dawley, Sprague-Dawley rat, AGENT-ORANGE, Testis, MESSENGER-RNA EXPRESSION, Differential methylation, Receptor, Carboxypeptidase A4, Genome, General Medicine, TOXICOGENOMIC ANALYSIS, Spermatozoa, 3. Good health, MELANOCORTIN RECEPTORS, Toxicity, DNA methylation, Environmental Pollutants, Female, Kidney Diseases, Transgenerational inheritance, ARYL-HYDROCARBON RECEPTOR, medicine.medical_specialty, Biology, 2,3,7,8-Tetrachlorodibenzo-p-dixoin (TCDD), 03 medical and health sciences, Immune system, Internal medicine, DIOXIN, medicine, Animals, Epigenetics, SPRAGUE-DAWLEY RATS, 0105 earth and related environmental sciences, Body Weight, Epigenome, DNA Methylation, Sperm, Rats, 030104 developmental biology, Endocrinology, 1182 Biochemistry, cell and molecular biology, Transcriptome, CARBOXYPEPTIDASE A4
Abstract

In rats, direct exposure to TCDD causes myriad toxicities. Exposed rats experience hepatotoxicity, wasting syndrome and immune suppression, amongst others. "Inherited exposure", as occurs in the F3 generation of directly exposed F0 animals, has also been shown to cause toxicity: both male and female F3 rats demonstrate an increased incidence of adult onset disease, females also display reproductive abnormalities and increased incidence of ovarian diseases while males show increased incidence of kidney disease and an altered sperm epigenome. Here, we explore the hepatic transcriptomic profile of male and female F3 Sprague-Dawley rats bred through the paternal germ line from F0 dams exposed to a single dose of TCDD (0, 30, 100, 300 or 1000 ng/kg body weight) by oral gavage. We hypothesize that RNA transcripts with altered abundance in livers of unexposed F3 progeny of treated F0 Sprague-Dawley rats may result from epigenetic modifications to the genome. We further survey patterns of differential methylation within male F3 rat testis. Female F3 rats demonstrated more TCDD-mediated hepatic transcriptomic changes than males, with differences primarily in the lowest dose group. In testis from male F3 rats, multiple olfactory receptors displayed patterns of differential methylation. Hypermethylation of Egfr and Mc5r among testes from TCDD lineage rats was observed, but without corresponding changes in hepatic mRNA abundance. Further studies examining these differences in other tissue types are warranted.

Published
2020

7. Flavopiridol causes cell cycle inhibition and demonstrates anti-cancer activity in anaplastic thyroid cancer models

Author

Jalna Meens, Paul C. Boutros, Danielle MacNeil, Kevin Fung, Laurie Ailles, Alessandro Datti, Nicole Pinto, John Yoo, Stephenie D. Prokopec, Anthony C. Nichols, John W. Barrett, Myung Woul Han, Joe S. Mymryk, Krupal B. Patel, Kara M. Ruicci, Neil Mundi, Farhad Ghasemi, Imran Khan, and Lebedeva, Irina V

Subjects
0301 basic medicine, Male, Cell cycle checkpoint, Cancer therapy, Cell Lines, Cancer Treatment, Anaplastic thyroid cancer, Apoptosis, Mice, SCID, Thyroid Carcinoma, Anaplastic, Biochemistry, Lung and Intrathoracic Tumors, Flavopiridol, Cell models, Cell cycle inhibition, Mice, 0302 clinical medicine, Piperidines, Thymic Tumors, Mice, Inbred NOD, Cell Movement, Medicine and Health Sciences, Anaplastic, Cell Cycle and Cell Division, RNA, Small Interfering, Endocrine Tumors, Cancer, Heterologous, Multidisciplinary, Tumor, Pharmaceutics, Cell migration, Cell cycle, Small interfering RNA, 3. Good health, Nucleic acids, Cell Motility, Oncology, Cell Processes, 5.1 Pharmaceuticals, 030220 oncology & carcinogenesis, Medicine, RNA Interference, Biological Cultures, Research Article, General Science & Technology, Science, Transplantation, Heterologous, Cell Migration, Research and Analysis Methods, SCID, Small Interfering, Cell Line, 03 medical and health sciences, Rare Diseases, Drug Therapy, In vivo, Cell Line, Tumor, medicine, Genetics, Animals, Humans, Thyroid Neoplasms, Non-coding RNA, Protein Kinase Inhibitors, Cell Proliferation, Flavonoids, Transplantation, business.industry, Carcinoma, Thyroid Carcinoma, Cancers and Neoplasms, Biology and Life Sciences, Cell Biology, Cell Cycle Checkpoints, medicine.disease, Cyclin-Dependent Kinase 9, Gene regulation, 030104 developmental biology, Cancer research, Inbred NOD, RNA, Cultured Fibroblasts, Gene expression, business, CDK inhibitor, Developmental Biology
Abstract

Anaplastic thyroid cancer (ATC) is a rare, but nearly uniformly fatal disease that is typically resistant to chemotherapy and radiation. Alternative strategies to target this cancer at a molecular level are necessary in order to improve dismal outcomes for ATC patients. We examined the effects of flavopiridol, a CDK inhibitor, in a panel of ATC cell lines. When cell lines were treated over a ten-point concentration range, CAL62, KMH2 and BHT-101 cell lines had a sub micromolar half-maximal inhibitory concentration, while no effect was seen in the non-cancerous cell line IMR-90. Flavopiridol treatment resulted in decreased levels of the cell cycle proteins CDK9 and MCL1, and induced cell cycle arrest. Flavopiridol also decreased the in vitro ability of ATC cells to form colonies and impeded migration using a transwell migration assay. In vivo, flavopiridol decreased tumor weight and tumor volume over time in a patient-derived xenograft model of ATC. Given the observed in vitro and in vivo activity, flavopiridol warrants further investigation for treatment of ATC.

Published
2020

8. 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, Shantao, Li, Kelso, Sean, Saksena, Gordon, Ellrott, Kyle, Wendl, Michael C, Wheeler, David A, Getz, Gad, Simpson, Jared T, Gerstein, Mark B, Ding, Lirehan, Akbani, Pavana, Anur, Matthew, H Bailey, Alex, Buchanan, Kami, Chiotti, Kyle, Covington, Allison, Creason, Ding, Li, Kyle, Ellrott, Fan, Yu, Steven, Foltz, Gad, Getz, Walker, Hale, David, Haussler, Julian, M Hess, Carolyn, M Hutter, Cyriac, Kandoth, Katayoon, Kasaian, Melpomeni, Kasapi, Dave, Larson, Ignaty, Leshchiner, John, Letaw, Singer, Ma, Michael, D McLellan, Yifei, Men, Gordon, B Mills, Beifang, Niu, Myron, Peto, Amie, Radenbaugh, Sheila, M Reynolds, Gordon, Saksena, Heidi, Sofia, Chip, Stewart, Adam, J Struck, Joshua, M Stuart, Wenyi, Wang, John, N Weinstein, David, A Wheeler, Christopher, K Wong, Liu, Xi, Kai, Ye, Matthias, Bieg, Paul, C Boutros, Ivo, Buchhalter, Adam, P Butler, Ken, Chen, Zechen, Chong, Oliver, Drechsel, Lewis Jonathan Dursi, Roland, Eils, Shadrielle M, G Espiritu, Robert, S Fulton, Shengjie, Gao, Josep L, L Gelpi, Mark, B Gerstein, Santiago, Gonzalez, Ivo, G Gut, Faraz, Hach, Michael, C Heinold, Jonathan, Hinton, Taobo, Hu, Vincent, Huang, Huang, Yi, Barbara, Hutter, David, R Jones, Jongsun, Jung, Natalie, Jäger, Hyung-Lae, Kim, Kortine, Kleinheinz, Sushant, Kumar, Yogesh, Kumar, Christopher, M Lalansingh, Ivica, Letunic, Dimitri, Livitz, Eric, Z Ma, Yosef, E Maruvka, R Jay Mashl, Andrew, Menzies, Ana, Milovanovic, Morten Muhlig Nielsen, Stephan, Ossowski, Nagarajan, Paramasivam, Jakob Skou Pedersen, Marc, D Perry, Montserrat, Puiggròs, Keiran, M Raine, Esther, Rheinbay, Romina, Royo, S Cenk Sahinalp, Iman, Sarrafi, Matthias, Schlesner, Jared, T Simpson, Lucy, Stebbings, Miranda, D Stobbe, Jon, W Teague, Grace, Tiao, David, Torrents, Jeremiah, A Wala, Jiayin, Wang, Sebastian, M Waszak, Joachim, Weischenfeldt, Michael, C Wendl, Johannes, Werner, Zhenggang, Wu, Hong, Xue, Sergei, Yakneen, Takafumi, N Yamaguchi, Venkata, D Yellapantula, Christina, K Yung, Junjun, Zhang, Lauri, A Aaltonen, Federico, Abascal, Adam, Abeshouse, Hiroyuki, Aburatani, David, J Adams, Nishant, Agrawal, Keun Soo Ahn, Sung-Min, Ahn, Hiroshi, Aikata, Rehan, Akbani, Kadir, C Akdemir, Hikmat, Al-Ahmadie, Sultan, T Al-Sedairy, Fatima, Al-Shahrour, Malik, Alawi, Monique, Albert, Kenneth, Aldape, Ludmil, B Alexandrov, Adrian, Ally, Kathryn, Alsop, Eva, G Alvarez, Fernanda, Amary, Samirkumar, B Amin, Brice, Aminou, Ole, Ammerpohl, Matthew, J Anderson, Yeng, Ang, Davide, Antonello, Samuel, Aparicio, Elizabeth, L Appelbaum, Yasuhito, Arai, Axel, Aretz, Koji, Arihiro, Shun-Ichi, Ariizumi, Joshua, Armenia, Laurent, Arnould, Sylvia, Asa, Yassen, Assenov, Gurnit, Atwal, Sietse, Aukema, J Todd Auman, Miriam, R Aure, Philip, Awadalla, Marta, Aymerich, Gary, D Bader, Adrian, Baez-Ortega, Peter, J Bailey, Miruna, Balasundaram, Saianand, Balu, Pratiti, Bandopadhayay, Rosamonde, E Banks, Stefano, Barbi, Andrew, P Barbour, Jonathan, Barenboim, Jill, Barnholtz-Sloan, Hugh, Barr, Elisabet, Barrera, John, Bartlett, Javier, Bartolome, Bassi, Claudio, Oliver, F Bathe, Daniel, Baumhoer, Prashant, Bavi, Stephen, B Baylin, Wojciech, Bazant, Duncan, Beardsmore, Timothy, A Beck, Sam, Behjati, Andreas, Behren, Cindy, Bell, Sergi, Beltran, Christopher, Benz, Andrew, Berchuck, Anke, K Bergmann, Erik, N Bergstrom, Benjamin, P Berman, Daniel, M Berney, Stephan, H Bernhart, Rameen, Beroukhim, Mario, Berrios, Samantha, Bersani, Johanna, Bertl, Miguel, Betancourt, Vinayak, Bhandari, Shriram, G Bhosle, Andrew, V Biankin, Darell, Bigner, Hans, Binder, Ewan, Birney, Michael, Birrer, Nidhan, K Biswas, Bodil, Bjerkehagen, Tom, Bodenheimer, Lori, Boice, Giada, Bonizzato, Johann, S De Bono, Arnoud, Boot, Moiz, S Bootwalla, Ake, Borg, Arndt, Borkhardt, Keith, A Boroevich, Ivan, Borozan, Christoph, Borst, Marcus, Bosenberg, Mattia, Bosio, Jacqueline, Boultwood, Guillaume, Bourque, G Steven Bova, David, T Bowen, Reanne, Bowlby, David D, L Bowtell, Sandrine, Boyault, Rich, Boyce, Jeffrey, Boyd, Alvis, Brazma, Paul, Brennan, Daniel, S Brewer, Arie, B Brinkman, Robert, G Bristow, Russell, R Broaddus, Jane, E Brock, Malcolm, Brock, Annegien, Broeks, Angela, N Brooks, Denise, Brooks, Benedikt, Brors, Søren, Brunak, Timothy J, C Bruxner, Alicia, L Bruzos, Christiane, Buchholz, Susan, Bullman, Hazel, Burke, Birgit, Burkhardt, Kathleen, H Burns, John, Busanovich, Carlos, D Bustamante, Atul, J Butte, Niall, J Byrne, Anne-Lise, Børresen-Dale, Samantha, J Caesar-Johnson, Andy, Cafferkey, Declan, Cahill, Claudia, Calabrese, Carlos, Caldas, Fabien, Calvo, Niedzica, Camacho, Peter, J Campbell, Elias, Campo, Cinzia, Cantù, Shaolong, Cao, Thomas, E Carey, Joana, Carlevaro-Fita, Rebecca, Carlsen, Ivana, Cataldo, Mario, Cazzola, Jonathan, Cebon, Robert, Cerfolio, Dianne, E Chadwick, Dimple, Chakravarty, Don, Chalmers, Calvin Wing Yiu Chan, Kin, Chan, Michelle, Chan-Seng-Yue, Vishal, S Chandan, David, K Chang, Stephen, J Chanock, Lorraine, A Chantrill, Aurélien, Chateigner, Nilanjan, Chatterjee, Kazuaki, Chayama, Hsiao-Wei, Chen, Jieming, Chen, Yiwen, Chen, Zhaohong, Chen, Andrew, D Cherniack, Jeremy, Chien, Yoke-Eng, Chiew, Suet-Feung, Chin, Juok, Cho, Sunghoon, Cho, Jung Kyoon Choi, Wan, Choi, Christine, Chomienne, Su Pin Choo, Angela, Chou, Angelika, N Christ, Elizabeth, L Christie, Eric, Chuah, Carrie, Cibulskis, Kristian, Cibulskis, Sara, Cingarlini, Peter, Clapham, Alexander, Claviez, Sean, Cleary, Nicole, Cloonan, Marek, Cmero, Colin, C Collins, Ashton, A Connor, Susanna, L Cooke, Colin, S Cooper, Leslie, Cope, Corbo, Vincenzo, Matthew, G Cordes, Stephen, M Cordner, Isidro, Cortés-Ciriano, Prue, A Cowin, Brian, Craft, David, Craft, Chad, J Creighton, Yupeng, Cun, Erin, Curley, Ioana, Cutcutache, Karolina, Czajka, Bogdan, Czerniak, Rebecca, A Dagg, Ludmila, Danilova, Maria Vittoria Davi, Natalie, R Davidson, Helen, Davies, Ian, J Davis, Brandi, N Davis-Dusenbery, Kevin, J Dawson, Francisco, M De La Vega, Ricardo De Paoli-Iseppi, Timothy, Defreitas, Angelo, P Dei Tos, Olivier, Delaneau, John, A Demchok, Jonas, Demeulemeester, German, M Demidov, Deniz, Demircioğlu, Nening, M Dennis, Robert, E Denroche, Stefan, C Dentro, Nikita, Desai, Vikram, Deshpande, Amit, G Deshwar, Christine, Desmedt, Jordi, Deu-Pons, Noreen, Dhalla, Neesha, C Dhani, Priyanka, Dhingra, Rajiv, Dhir, Anthony, Dibiase, Klev, Diamanti, Shuai, Ding, Huy, Q Dinh, Luc, Dirix, Harshavardhan, Doddapaneni, Nilgun, Donmez, Michelle, T Dow, Ronny, Drapkin, Ruben, M Drews, Serge, Serge, Tim, Dudderidge, Ana, Dueso-Barroso, Andrew, J Dunford, Michael, Dunn, Fraser, R Duthie, Ken, Dutton-Regester, Jenna, Eagles, Douglas, F Easton, Stuart, Edmonds, Paul, A Edwards, Sandra, E Edwards, Rosalind, A Eeles, Anna, Ehinger, Juergen, Eils, Adel, El-Naggar, Matthew, Eldridge, Serap, Erkek, Georgia, Escaramis, Xavier, Estivill, Dariush, Etemadmoghadam, Jorunn, E Eyfjord, Bishoy, M Faltas, Daiming, Fan, William, C Faquin, Claudiu, Farcas, Matteo, Fassan, Aquila, Fatima, Francesco, Favero, Nodirjon, Fayzullaev, Ina, Felau, Sian, Fereday, Martin, L Ferguson, Vincent, Ferretti, Lars, Feuerbach, Matthew, A Field, J Lynn Fink, Gaetano, Finocchiaro, Cyril, Fisher, Matthew, W Fittall, Anna, Fitzgerald, Rebecca, C Fitzgerald, Adrienne, M Flanagan, Neil, E Fleshner, Paul, Flicek, John, A Foekens, Kwun, M Fong, Nuno, A Fonseca, Christopher, S Foster, Natalie, S Fox, Michael, Fraser, Scott, Frazer, Milana, Frenkel-Morgenstern, William, Friedman, Joan, Frigola, Catrina, C Fronick, Akihiro, Fujimoto, Masashi, Fujita, Masashi, Fukayama, Lucinda, A Fulton, Mayuko, Furuta, P Andrew Futreal, Anja, Füllgrabe, Stacey, B Gabriel, Steven, Gallinger, Carlo, Gambacorti-Passerini, Jianjiong, Gao, Levi, Garraway, Øystein, Garred, Erik, Garrison, Dale, W Garsed, Nils, Gehlenborg, Joshy, George, Daniela, S Gerhard, Clarissa, Gerhauser, Jeffrey, E Gershenwald, Moritz, Gerstung, Mohammed, Ghori, Ronald, Ghossein, Nasra, H Giama, Richard, A Gibbs, Anthony, J Gill, Pelvender, Gill, Dilip, D Giri, Dominik, Glodzik, Vincent, J Gnanapragasam, Maria Elisabeth Goebler, Mary, J Goldman, Carmen, Gomez, Abel, Gonzalez-Perez, Dmitry, A Gordenin, James, Gossage, Kunihito, Gotoh, Ramaswamy, Govindan, Dorthe, Grabau, Janet, S Graham, Robert, C Grant, Anthony, R Green, Eric, Green, Liliana, Greger, Nicola, Grehan, Sonia, Grimaldi, Sean, M Grimmond, Robert, L Grossman, Adam, Grundhoff, Gunes, Gundem, Qianyun, Guo, Manaswi, Gupta, Shailja, Gupta, Marta, Gut, Jonathan, Göke, Gavin, Ha, Andrea, Haake, David, Haan, Siegfried, Haas, Kerstin, Haase, James, E Haber, Nina, Habermann, Syed, Haider, Natsuko, Hama, Freddie, C Hamdy, Anne, Hamilton, Mark, P Hamilton, Leng, Han, George, B Hanna, Martin, Hansmann, Nicholas, J Haradhvala, Olivier, Harismendy, Ivon, Harliwong, Arif, O Harmanci, Eoghan, Harrington, Takanori, Hasegawa, Steve, Hawkins, Shinya, Hayami, Shuto, Hayashi, D Neil Hayes, Stephen, J Hayes, Nicholas, K Hayward, Steven, Hazell, Yao, He, Allison, P Heath, Simon, C Heath, David, Hedley, Apurva, M Hegde, David, I Heiman, Zachary, Heins, Lawrence, E Heisler, Eva, Hellstrom-Lindberg, Mohamed, Helmy, Seong Gu Heo, Austin, J Hepperla, José María Heredia-Genestar, Carl, Herrmann, Peter, Hersey, Holmfridur, Hilmarsdottir, Satoshi, Hirano, Nobuyoshi, Hiraoka, Katherine, A Hoadley, Asger, Hobolth, Ermin, Hodzic, Jessica, I Hoell, Steve, Hoffmann, Oliver, Hofmann, Andrea, Holbrook, Aliaksei, Z Holik, Michael, A Hollingsworth, Oliver, Holmes, Robert, A Holt, Chen, Hong, Eun Pyo Hong, Jongwhi, H Hong, Gerrit, K Hooijer, Henrik, Hornshøj, Fumie, Hosoda, Yong, Hou, Volker, Hovestadt, William, Howat, Alan, P Hoyle, Ralph, H Hruban, Jianhong, Hu, Xing, Hua, Kuan-Lin, Huang, Mei, Huang, Mi Ni Huang, Wolfgang, Huber, Thomas, J Hudson, Michael, Hummel, Jillian, A Hung, David, Huntsman, Ted, R Hupp, Jason, Huse, Matthew, R Huska, Daniel, Hübschmann, Christine, A Iacobuzio-Donahue, Charles David Imbusch, Marcin, Imielinski, Seiya, Imoto, William, B Isaacs, Keren, Isaev, Shumpei, Ishikawa, Murat, Iskar, M Ashiqul Islam, S, Michael, Ittmann, Sinisa, Ivkovic, Jose M, G Izarzugaza, Jocelyne, Jacquemier, Valerie, Jakrot, Nigel, B Jamieson, Gun Ho Jang, Se Jin Jang, Joy, C Jayaseelan, Reyka, Jayasinghe, Stuart, R Jefferys, Karine, Jegalian, Jennifer, L Jennings, Seung-Hyup, Jeon, Lara, Jerman, Yuan, Ji, Wei, Jiao, Peter, A Johansson, Amber, L Johns, Jeremy, Johns, Rory, Johnson, Todd, A Johnson, Clemency, Jolly, Yann, Joly, Jon, G Jonasson, Corbin, D Jones, David T, W Jones, Nic, Jones, Steven J, M Jones, Jos, Jonkers, Young Seok Ju, Hartmut, Juhl, Malene, Juul, Randi Istrup Juul, Sissel, Juul, Rolf, Kabbe, Andre, Kahles, Abdullah, Kahraman, Vera, B Kaiser, Hojabr, Kakavand, Sangeetha, Kalimuthu, Christof von Kalle, Koo Jeong Kang, Katalin, Karaszi, Beth, Karlan, Rosa, Karlić, Dennis, Karsch, Karin, S Kassahn, Hitoshi, Katai, Mamoru, Kato, Hiroto, Katoh, Yoshiiku, Kawakami, Jonathan, D Kay, Stephen, H Kazakoff, Marat, D Kazanov, Maria, Keays, Electron, Kebebew, Richard, F Kefford, Manolis, Kellis, James, G Kench, Catherine, J Kennedy, Jules N, A Kerssemakers, David, Khoo, Vincent, Khoo, Narong, Khuntikeo, Ekta, Khurana, Helena, Kilpinen, Hark Kyun Kim, Hyung-Yong, Kim, Hyunghwan, Kim, Jaegil, Kim, Jihoon, Kim, Jong, K Kim, Youngwook, Kim, Tari, A King, Wolfram, Klapper, Leszek, J Klimczak, Stian, Knappskog, Michael, Kneba, Bartha, M Knoppers, Youngil, Koh, Jan, Komorowski, Daisuke, Komura, Mitsuhiro, Komura, Kong, Gu, Marcel, Kool, Jan, O Korbel, Viktoriya, Korchina, Andrey, Korshunov, Michael, Koscher, Roelof, Koster, Zsofia, Kote-Jarai, Antonios, Koures, Milena, Kovacevic, Barbara, Kremeyer, Helene, Kretzmer, Markus, Kreuz, Savitri, Krishnamurthy, Dieter, Kube, Kiran, Kumar, Pardeep, Kumar, Ritika, Kundra, Kirsten, Kübler, Ralf, Küppers, Jesper, Lagergren, Phillip, H Lai, Peter, W Laird, Sunil, R Lakhani, Emilie, Lalonde, 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Yamamoto, S, Yamaue, H, Yang, F, Yang, H, Yang, J, Yang, L, Yang, S, Yang, T, Yang, Y, Yao, X, Yaspo, M, Yates, L, Yau, C, Ye, C, Yoon, C, Yoon, S, Yousif, F, Yu, J, Yu, K, Yu, W, Yu, Y, Yuan, K, Yuan, Y, Yuen, D, Zaikova, O, Zamora, J, Zapatka, M, Zenklusen, J, Zenz, T, Zeps, N, Zhang, C, Zhang, F, Zhang, H, Zhang, X, Zhang, Y, Zhang, Z, Zhao, Z, Zheng, L, Zheng, X, Zhou, W, Zhou, Y, Bin, Z, Zhu, H, Zhu, J, Zhu, S, Zou, L, Zou, X, Defazio, A, van As, N, van Deurzen, C, van de Vijver, M, van't Veer, L, von Mering, C, Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Tampere University, BioMediTech, TAYS Cancer Centre, University of St Andrews. Sir James Mackenzie Institute for Early Diagnosis, University of St Andrews. Cellular Medicine Division, University of St Andrews. Statistics, University of St Andrews. School of Medicine, University of Zurich, Gerstein, Mark B, Ding, Li, Bailey, Matthew H [0000-0003-4526-9727], Wheeler, David A [0000-0002-9056-6299], Gerstein, Mark B [0000-0002-9746-3719], Faculty of Economic and Social Sciences and Solvay Business School, Lauri Antti Aaltonen / Principal Investigator, Genome-Scale Biology (GSB) Research Program, Department of Medical and Clinical Genetics, Organismal and Evolutionary Biology Research Programme, Helsinki Institute for Information Technology, Institute of Biotechnology, Bioinformatics, Department of Computer Science, Faculty of Medicine, and HUS Helsinki and Uusimaa Hospital District

Subjects
VARIANTS, 0302 clinical medicine, 706/648/697/129/2043, Databases, Genetic, Cancer genomics, SOMATIC POINT MUTATIONS, Càncer, lcsh:Science, Exome, Exome sequencing, Cancer, Base Composition, Neoplasms -- genetics, 1184 Genetics, developmental biology, physiology, 3100 General Physics and Astronomy, 3. Good health, 030220 oncology & carcinogenesis, Science & Technology - Other Topics, Transformació genètica, Genetic databases, Erfðarannsóknir, Human, GENES, Science, 1600 General Chemistry, General Biochemistry, Genetics and Molecular Biology, RC0254, 03 medical and health sciences, Genetic, SDG 3 - Good Health and Well-being, 1300 General Biochemistry, Genetics and Molecular Biology, Exome Sequencing, Genetics, Humans, Author Correction, Retrospective Studies, Whole genome sequencing, Comparative genomics, Science & Technology, RC0254 Neoplasms. Tumors. Oncology (including Cancer), INSERTIONS, DNA, PERFORMANCE, Human genetics, Communication and replication, Cancérologie, 692/4028/67/69, Genòmica, 030104 developmental biology, Mutation, Genome mutation, Human genome, lcsh:Q, COMPREHENSIVE CHARACTERIZATION, Genètica, 0301 basic medicine, Medizin, General Physics and Astronomy, Genome, Whole Exome Sequencing, Genetic transformation, International Cancer Genome Consortium, Neoplasms, 631/114/2399, Genamengi, Medicine and Health Sciences, Medicine(all), Women's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17], Multidisciplinary, 318 Medical biotechnology, Exome -- genetics, article, Exons, Women's cancers Radboud Institute for Health Sciences [Radboudumc 17], Multidisciplinary Sciences, CAPTURE, 1181 Ecology, evolutionary biology, oncology, DNA, Intergenic, 139, Medical Genetics, Biotechnology, ICGC/TCGA Pan-Cancer Analysis, 3122 Cancers, 610 Medicine & health, 45/23, QH426 Genetics, Biology, MC3 Working Group, Databases, Germline mutation, PCAWG novel somatic mutation calling methods working group, Krabbameinsrannsóknir, Cancer Genome Atlas, Genome, Human -- genetics, ddc:610, QH426, Medicinsk genetik, Krabbamein, Intergenic, Whole Genome Sequencing, Genome, Human, Human Genome, PCAWG Consortium, DAS, General Chemistry, DELETIONS, Good Health and Well Being, 10032 Clinic for Oncology and Hematology, 3111 Biomedicine, 631/1647/2217/748
Abstract

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, 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 < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

Published
2020
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9. Genomic and human papillomavirus profiling of an oral cancer cohort identifies TP53 as a predictor of overall survival

Author

Joe S. Mymryk, Eric Winquist, Farhad Ghasemi, Kara M. Ruicci, William Stecho, Kevin Fung, Andrew Warner, Stephenie D. Prokopec, Nicole Pinto, Christopher J. Howlett, John W. Barrett, Danielle MacNeil, David A. Palma, Axel Sahovaler, Paul Plantinga, Mohammed Imran Khan, Krupal B. Patel, Myung Woul Han, Neil Mundi, John Yoo, Paul C. Boutros, and Anthony C. Nichols

Subjects
0301 basic medicine, Oncology, medicine.medical_specialty, Survival, medicine.medical_treatment, Genomics, Cervical Cancer, lcsh:RC254-282, 2.2 Factors relating to physical environment, Sexually Transmitted Diseases/Herpes, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Overall survival, Genetics, Mutational status, 2.1 Biological and endogenous factors, Pharmacology (medical), Genetic Testing, Human papillomavirus, Dental/Oral and Craniofacial Disease, Gene, Cancer, business.industry, Prevention, Research, Oral cancer, Head and neck cancer, Human Genome, tp53, medicine.disease, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, 3. Good health, Radiation therapy, 030104 developmental biology, Infectious Diseases, 030220 oncology & carcinogenesis, Cohort, Sexually Transmitted Infections, business, Biotechnology
Abstract

Abtract Background The genomic landscape of head and neck cancer has been reported through The Cancer Genome Atlas project. We attempt to determine if high-risk human papillomavirus (HPV) or frequently mutated genes are correlated with survival in an oral cancer cohort. Methods Patient demographic data along with data from final pathology was collected. Tumor DNA was analyzed using a custom Illumina targeted sequencing panel. Five high-risk HPV types were tested by qPCR. Statistical analyses were used to identify associations between patient outcome and mutational status. Results High-risk HPV types were identified in 7% of cases; HPV status was not associated with survival. Mutations were identified in TP53, TERT promoter, & PIK3CA. Mutations in TP53 were significantly associated with poorer overall survival on multi-variate analysis (p = 0.03). Conclusions Mutations in TP53 were associated with poor patient survival. Expanding our sample size may identify further predictors of outcome to direct customized cancer care.

Published
2019

10. Comparative toxicoproteogenomics of mouse and rat liver identifies TCDD-resistance genes

Author

Stephenie D. Prokopec, Sandy Che Eun S. Lee, Amy X. Lu, Allan B. Okey, Rabah Soliymani, Cindy Q. Yao, John Douglas Mcpherson, Philip C. Zuzarte, John D. Watson, Michelle Sam, Raimo Pohjanvirta, Richard de Borja, Paul C. Boutros, Ren X. Sun, Ada Wong, Department of Biochemistry and Developmental Biology, Medicum, University of Helsinki, Helsinki One Health (HOH), Raimo Pohjanvirta / Principal Investigator, and Food Hygiene and Environmental Health

Subjects
0301 basic medicine, Male, Proteomics, TCDD, Polychlorinated Dibenzodioxins, Health, Toxicology and Mutagenesis, Developmental toxicity, 010501 environmental sciences, Toxicology, 01 natural sciences, Transcriptome, Mice, BINDING, Basic Helix-Loop-Helix Transcription Factors, heterocyclic compounds, GENECHIP DATA, NONGENOMIC PATHWAY, AH RECEPTOR, biology, 1184 Genetics, developmental biology, physiology, General Medicine, Genomics, Phenotype, DEVELOPMENTAL TOXICITY, DIOXIN-RESPONSIVE ENHANCER, Liver, Mice, Inbred DBA, Toxicity, Environmental Pollutants, 2,3,7,8-TETRACHLORODIBENZO-P-DIOXIN TCDD, Genetically modified mouse, Gene isoform, Model organisms, ARYL-HYDROCARBON RECEPTOR, EXPRESSION, Mice, Transgenic, 03 medical and health sciences, Species Specificity, Animals, Rats, Long-Evans, RNA, Messenger, Rats, Wistar, Transcriptomics, Gene, 0105 earth and related environmental sciences, Whole-genome sequencing, Dose-Response Relationship, Drug, AhR, PROTEIN-DNA INTERACTIONS, Aryl hydrocarbon receptor, Molecular biology, Rats, Mice, Inbred C57BL, stomatognathic diseases, 030104 developmental biology, Receptors, Aryl Hydrocarbon, biology.protein, 3111 Biomedicine
Abstract

The aryl hydrocarbon receptor (AHR) mediates many toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). However, the AHR alone does not explain the widely different outcomes among organisms. To identify the other factors involved, we evaluated three transgenic mouse lines, each expressing a different rat AHR isoform (rWT, DEL, and INS) providing widely different resistance to TCDD toxicity, as well as C57BL/6 and DBA/2 mice which exhibit a similar to tenfold divergence in TCDD sensitivity (exposures of 5-1000 mu g/kg TCDD). We supplement these with whole-genome sequencing, together with transcriptomic and proteomic analyses of the corresponding rat models, Long-Evans (L-E) and Han/Wistar (H/W) rats (having a similar to 1000-fold difference in their TCDD sensitivities; 100 mu g/kg TCDD), to identify genes associated with TCDD-response phenotypes. Overall, we identified up to 50% of genes with altered mRNA abundance following TCDD exposure are associated with a single AHR isoform (33.8%, 11.7%, 5.2% and 0.3% of 3076 genes altered unique to rWT, DEL, C57BL/6 and INS respectively following 1000 mu g/kg TCDD). Hepatic Pxdc1 was significantly repressed in all three TCDD-sensitive animal models (C57BL/6 and rWT mice, and L-E rat) after TCDD exposure. Three genes, including Cxxc5, Sugp1 and Hgfac, demonstrated different AHRE-1 (full) motif occurrences within their promoter regions between rat strains, as well as different patterns of mRNA abundance. Several hepatic proteins showed parallel up- or downward alterations with their RNAs, with three genes (SNRK, IGTP and IMPA2) showing consistent, strain-dependent changes. These data show the value of integrating genomic, transcriptomic and proteomic evidence across multi-species models in toxicologic studies.

Published
2019

11. Identifying TCDD-resistance genes via murine and rat comparative genomics and transcriptomics

Author

Amy X. Lu, Sandy Che Eun S. Lee, Allan B. Okey, Ada Wong, Stephenie D. Prokopec, Ren X. Sun, John Douglas Mcpherson, Philip C. Zuzarte, Richard de Borja, John D. Watson, Michelle Sam, Cindy Q. Yao, Raimo Pohjanvirta, and Paul C. Boutros

Subjects
Comparative genomics, Genetics, Genetically modified mouse, Gene isoform, 0303 health sciences, Biology, Aryl hydrocarbon receptor, Phenotype, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Gene expression, biology.protein, Gene, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

The aryl hydrocarbon receptor (AHR) mediates many of the toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). However, the AHR alone is insufficient to explain the widely different outcomes among organisms. Attempts to identify unknown factor(s) have been confounded by genetic variability of model organisms. Here, we evaluated three transgenic mouse lines, each expressing a different rat AHR isoform (rWT, DEL, and INS), as well as C57BL/6 and DBA/2 mice. We supplement these with whole-genome sequencing and transcriptomic analyses of the corresponding rat models: Long-Evans (L-E) and Han/Wistar (H/W) rats. These integrated multi-species genomic and transcriptomic data were used to identify genes associated with TCDD-response phenotypes.We identified several genes that show consistent transcriptional changes in both transgenic mice and rats. HepaticPxdc1was significantly repressed by TCDD in C57BL/6, rWT mice, and in L-E rat. Three genes demonstrated different AHRE-1 (full) motif occurrences within their promoter regions:Cxxc5had fewer occurrences in H/W, as compared with L-E;Sugp1andHgfac(in either L-E or H/W respectively). These genes also showed different patterns of mRNA abundance across strains.The AHR isoform explains much of the transcriptional variability: up to 50% of genes with altered mRNA abundance following TCDD exposure are associated with a single AHR isoform (30% and 10% unique to DEL and rWT respectively following 500 μg/kg TCDD). Genomic and transcriptomic evidence allowed identification of genes potentially involved in phenotypic outcomes:Pxdc1had differential mRNA abundance by phenotype;Cxxc5had altered AHR binding sites and differential mRNA abundance.Author SummaryEnvironmental contaminants such as dioxins cause many toxic responses, anything from chloracne (common in humans) to death. These toxic responses are mostly regulated by theAhr, a ligand-activated transcription factor with roles in drug metabolism and immune responses, however other contributing factors remain unclear. Studies are complicated by the underlying genetic heterogeneity of model organisms. Our team evaluated a number of mouse and rat models, including two strains of mouse, two strains of rat and three transgenic mouse lines which differ only at theAhrlocus, that present widely different sensitivities to the most potent dioxin: 2,3,7,8 tetrachlorodibenzo-p-dioxin (TCDD). We identified a number of changes to gene expression that were associated with different toxic responses. We then contrasted these findings with results from whole-genome sequencing of the H/W and L-E rats and found some key genes, such asCxxc5andMafb, which might contribute to TCDD toxicity. These transcriptomic and genomic datasets will provide a valuable resource for future studies into the mechanisms of dioxin toxicities.

Published
2019
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12. Transcriptomic Impact of IMA-08401, a Novel AHR Agonist Resembling Laquinimod, on Rat Liver

Author

Paul C. Boutros, Selma Mahiout, Lars Pettersson, Stephenie D. Prokopec, Raimo Pohjanvirta, Helsinki One Health (HOH), Raimo Pohjanvirta / Principal Investigator, and Food Hygiene and Environmental Health

Subjects
Male, TCDD, Polychlorinated Dibenzodioxins, 116 Chemical sciences, AHR, Pharmacology, Quinolones, medicine.disease_cause, Rats, Sprague-Dawley, lcsh:Chemistry, chemistry.chemical_compound, 0302 clinical medicine, Medicine, 2.1 Biological and endogenous factors, Aetiology, Receptor, lcsh:QH301-705.5, Spectroscopy, GENE-EXPRESSION, 0303 health sciences, biology, Liver Disease, Experimental autoimmune encephalomyelitis, immunomodulator, General Medicine, respiratory system, 3. Good health, Computer Science Applications, Liver, EXPERIMENTAL AUTOIMMUNE ENCEPHALOMYELITIS, 030220 oncology & carcinogenesis, 2,3,7,8-TETRACHLORODIBENZO-P-DIOXIN TCDD, Agonist, medicine.drug_class, ORAL LAQUINIMOD, CANCER-RISK, Catalysis, Article, Inorganic Chemistry, 03 medical and health sciences, Immune system, In vivo, Genetics, Animals, EXPOSURE, Physical and Theoretical Chemistry, Molecular Biology, 030304 developmental biology, SUPPRESSION, Chemical Physics, RECEPTOR, IDENTIFICATION, business.industry, Organic Chemistry, Immunity, Aryl hydrocarbon receptor, medicine.disease, Rats, laquinimod, Oxidative Stress, chemistry, lcsh:Biology (General), lcsh:QD1-999, REPLICATION, biology.protein, 1182 Biochemistry, cell and molecular biology, Sprague-Dawley, Other Biological Sciences, business, Digestive Diseases, Transcriptome, Other Chemical Sciences, Laquinimod, Oxidative stress
Abstract

IMA-08401 (C2) is a novel aryl hydrocarbon receptor (AHR) agonist and selective AHR modulator (SAHRM) that is structurally similar to laquinimod (LAQ). Both compounds are converted to the AHR-active metabolite DELAQ (IMA-06201) in vivo. SAHRMs have been proposed as therapeutic options for various autoimmune disorders. Clinical trials on LAQ have not reported any significant toxic outcomes and C2 has shown low toxicity in rats, however, their functional resemblance to the highly toxic AHR agonist 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) raises questions. Here, we characterize the hepatic transcriptomic changes induced by acute (single-dose) and subacute exposure (repeated dosing for 5 days followed by a 5-day recovery period) to C2 in Sprague-Dawley rats. Exposure to C2 leads to activation of the AHR, as shown by altered transcription of Cyp1a1. We identify a heightened response early after exposure that drops off by day 10. Acute exposure to C2 leads to changes to transcription of genes involved in antiviral and antibacterial responses, which highlights the immunomodulator effects of this AHR agonist. Subacute exposure causes an oxidative stress response in the liver, the consequences of which require further study on target tissues such as the CNS and immune system, both of which may be compromised in this patient population.

Published
2019
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13. Abstract PR02: Mutational analysis of head and neck squamous cell carcinoma stratified by smoking status

Author

Paul C. Boutros, Joe S. Mymryk, Danielle MacNeil, Stephenie D. Prokopec, John Yoo, Christopher J. Howlett, Neil Mundi, Kevin Fung, William Stecho, Eric Winquist, Steven F. Gameiro, Axel Sahovaler, John W. Barrett, Anthony C. Nichols, Paul Plantinga, and Farhad Ghasemi

Subjects
Oncology, Mutational analysis, Cancer Research, medicine.medical_specialty, business.industry, Internal medicine, medicine, Smoking status, business, medicine.disease, Head and neck squamous-cell carcinoma
Abstract

Smoking has historically been recognized as a negative prognostic factor in head and neck squamous cell carcinoma (HNSCC). This study aimed to assess the mutational differences between heavy smokers (>20 pack-years) and never smokers among the HNSCC patients within The Cancer Genome Atlas (TCGA). Single nucleotide variation (SNV) and copy number aberration (CNA) differences between heavy smokers and never smokers were compared within HPV-positive (n=67) and negative (n=431) TCGA HNSCC cohorts, and the impact of these mutations on survival was assessed. No genes were differentially mutated between smoking and never smoking patients with HPV-positive tumors. By contrast, in HPV-negative tumors, NSD1 and COL1A11 were found to be more frequently mutated in heavy smokers, while CASP8 was more frequently altered in never smokers. HPV-negative patients with NSD1 mutations experienced significantly improved overall survival compared with NSD1 wild-type patients. This improved prognosis was validated in an independent cohort of 77 oral cavity cancers and a meta-analysis that included two additional datasets (688 total patients, hazard ratio for death 0.44, 95% CI 0.30-0.65). NSD1 mutations are more common in HPV-negative heavy smokers and define a cohort with favorable prognosis, and may represent a clinically useful biomarker to guide treatment deintensification for HPV-negative patients. Citation Format: Farhad Ghasemi, Stephenie D. Prokopec, Danielle MacNeil, Neil Mundi, Christopher Howlett, William Stecho, Kevin Fung, John Yoo, Eric Winquist, Steven Gameiro, Axel Sahovaler, Paul Plantinga, Joe S. Mymryk, John W. Barrett, Paul C. Boutros, Anthony C. Nichols. Mutational analysis of head and neck squamous cell carcinoma stratified by smoking status [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; 2019 Apr 29-30; Austin, TX. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_2):Abstract nr PR02.

Published
2020
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14. Sex disparities in head & neck cancer driver genes: An analysis of the TCGA dataset

Author

Peter Y.F. Zeng, Joe S. Mymryk, Stephenie D. Prokopec, Mushfiq Hassan Shaikh, Mohammed Imran Khan, Paul C. Boutros, Kevin Fung, Anthony C. Nichols, Hugh Andrew Jinwook Kim, Danielle MacNeil, Farhad Ghasemi, Adrian Mendez, Steven F. Gameiro, David A. Palma, John W. Barrett, Krupal B. Patel, Neil Mundi, Eric Di Gravio, John Yoo, and Myung Woul Han

Subjects
Male, Oncology, False discovery rate, Cancer Research, medicine.medical_specialty, Multivariate analysis, Disease, 03 medical and health sciences, Sex Factors, 0302 clinical medicine, Internal medicine, medicine, Humans, Healthcare Disparities, 030223 otorhinolaryngology, Gene, business.industry, Confounding, medicine.disease, Survival Analysis, Head and neck squamous-cell carcinoma, Head and Neck Neoplasms, 030220 oncology & carcinogenesis, Cohort, Biomarker (medicine), Female, Oral Surgery, business
Abstract

Objectives Survival in head and neck squamous cell carcinoma (HNSCC) has been associated with patient sex, typically with males experiencing poorer outcomes. It is unclear if this disparity is based in divergent tumor biology. We analyzed the TCGA HNSCC cohort to uncover disparities in the somatic single nucleotide variation (SNV), copy number alteration (CNA) and mRNA abundance profiles between males and females. Critically, we stratified our results by tumor HPV status to control for this significant confounder. Methods SNV, CNA and mRNA abundance differences between males and females were compared separately for the HPV-positive (n = 67) and negative (n = 431) TCGA HNSCC cohorts. Overall survival outcomes were compared in males and females in both HPV-positive and HPV-negative subsets of patients. Results Females were found to have poorer overall survival than males (p = 0.048), largely due to higher rates of HPV-positive disease among men. SNV analysis revealed that in HPV-positive disease, there were no differences by sex after accounting for the false discovery rate (FDR). In HPV-negative tumors, BRWD3 mutations occurred more frequently in the tumors of female patients compared to males after adjusting for the FDR (p = 0.02). Further, HPV-negative BRWD3 mutant tumors were found to have significantly worse 5-year overall survival compared to wildtype on multivariate analysis (p = 0.02). There were 88 heterozygous deletions and 14 amplifications that were differentially altered between male and female HPV-negative tumors and associated with expression changes. Pathway analysis of these genes revealed that tumors from males were enriched in five pathways including chemokine and phosphophatidylinositol signaling. Conclusions Reanalysis of the TCGA HNSCC dataset stratified by sex revealed that males in this cohort had a significant survival advantage, due to a higher proportion of HPV-positive disease. Mutations in BRWD3 were more frequent in HPV-negative tumors of females and were associated with poorer overall survival. BRWD3 may represent a novel biomarker of patient outcomes, but will require additional validation.

Published
2020
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15. Mutational analysis of head and neck squamous cell carcinoma stratified by smoking status

Author

Mohammed Imran Khan, Danielle MacNeil, David A. Palma, Eric Winquist, Paul C. Boutros, Anthony C. Nichols, Nicole Pinto, Steven F. Gameiro, Kara M. Ruicci, William Stecho, Christopher J. Howlett, Farhad Ghasemi, Stephenie D. Prokopec, Paul Plantinga, John Yoo, Axel Sahovaler, Joe S. Mymryk, Kevin Fung, John W. Barrett, and Neil Mundi

Subjects
0301 basic medicine, Oncology, medicine.medical_specialty, Favorable prognosis, Oral cavity, Pediatrics, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, Internal medicine, Cancer genome, Tobacco, Genetics, Medicine, Dental/Oral and Craniofacial Disease, Cancer, Tobacco Smoke and Health, business.industry, HUMAN-PAPILLOMAVIRUS, SURVIVAL, METHYLATION, CANCER, Hazard ratio, Head & neck cancer, General Medicine, medicine.disease, Head and neck squamous-cell carcinoma, Mutational analysis, 030104 developmental biology, Infectious Diseases, Good Health and Well Being, 030220 oncology & carcinogenesis, Cohort, Sexually Transmitted Infections, Smoking status, business, Research Article
Abstract

Smoking has historically been recognized as a negative prognostic factor in head and neck squamous cell carcinoma (HNSCC). This study aimed to assess the mutational differences between heavy smokers (>20 pack years) and never smokers among the HNSCC patients within The Cancer Genome Atlas (TCGA). Single nucleotide variation and copy number aberration differences between heavy smokers and never smokers were compared within human papillomavirus-positive (HPV-positive) (n = 67) and HPV-negative (n = 431) TCGA cohorts with HNSCC, and the impact of these mutations on survival were assessed. No genes were differentially mutated between smoking and never-smoking patients with HPV-positive tumors. By contrast, in HPV-negative tumors, NSD1 and COL1A11 were found to be more frequently mutated in heavy smokers, while CASP8 was more frequently altered in never smokers. HPV-negative patients with NSD1 mutations experienced significantly improved overall survival compared with NSD1 WT patients. This improved prognosis was validated in an independent cohort of 77 oral cavity cancer patients and a meta-analysis that included 2 additional data sets (688 total patients, hazard ratio for death 0.44, 95% CI, 0.30-0.65). NSD1 mutations are more common in HPV-negative heavy smokers, define a cohort with favorable prognosis, and may represent a clinically useful biomarker to guide treatment deintensification for HPV-negative patients.

Published
2019

16. 2,3,7,8-Tetrachlorodibenzo-p-dioxin modifies alternative splicing in mouse liver

Author

Cindy Q. Yao, Stephenie D. Prokopec, Jesus Valdes-Flores, Ana B. Villasenor-Altamirano, Paul C. Boutros, Raimo Pohjanvirta, Guillermo Elizondo, John D. Watson, Franco, Rodrigo, Food Hygiene and Environmental Health, Helsinki One Health (HOH), and Raimo Pohjanvirta / Principal Investigator

Subjects
DISRUPTION, 0301 basic medicine, Male, TCDD, Polychlorinated Dibenzodioxins, Microarrays, Artificial Gene Amplification and Extension, Inbred C57BL, Biochemistry, Polymerase Chain Reaction, Hippocampus, Exon, chemistry.chemical_compound, Mice, 0302 clinical medicine, Medicine and Health Sciences, 2.1 Biological and endogenous factors, heterocyclic compounds, AH RECEPTOR, Multidisciplinary, Chromosome Biology, Liver Disease, Brain, EXON, REPRESSOR, Animal Models, Lipids, 3. Good health, Cell biology, Nucleic acids, Bioassays and Physiological Analysis, Experimental Organism Systems, Liver, RNA splicing, Toxicity, Medicine, Environmental Pollutants, Anatomy, Drug, Research Article, ARYL-HYDROCARBON RECEPTOR, EXPRESSION, Gene isoform, Chromosome Structure and Function, General Science & Technology, Science, 1.1 Normal biological development and functioning, DNA transcription, Mouse Models, Biology, Research and Analysis Methods, Chromosomes, MECHANISMS, Dose-Response Relationship, 03 medical and health sciences, Model Organisms, Genetics, Animals, Molecular Biology Techniques, Gene, Molecular Biology, BINDING DOMAIN, IDENTIFICATION, Biology and life sciences, Dose-Response Relationship, Drug, Alternative splicing, Cell Biology, Aryl hydrocarbon receptor, Mice, Inbred C57BL, Alternative Splicing, 030104 developmental biology, chemistry, RNA processing, Agent Orange & Dioxin, biology.protein, Animal Studies, 1182 Biochemistry, cell and molecular biology, RNA, Gene expression, Generic health relevance, Xenobiotic, Digestive Diseases, Oils, 030217 neurology & neurosurgery
Abstract

Alternative splicing is a co-transcriptional mechanism that generates protein diversity by including or excluding exons in different combinations, thereby expanding the diversity of protein isoforms of a single gene. Abnormalities in this process can result in deleterious effects to human health, and several xenobiotics are known to interfere with splicing regulation through multiple mechanisms. These changes could lead to human diseases such as cancer, neurological disorders, autoimmune diseases, and developmental disorders. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is an environmental contaminant generated as a byproduct of various industrial activities. Exposure to this dioxin has been linked to a wide range of pathologies through the alteration of multiple cellular processes. However, the effects of TCDD exposure on alternative splicing have not yet been studied. Here, we investigated whether a single po. dose of 5 μg/kg or 500 μg/kg TCDD influence hepatic alternative splicing in adult male C57BL/6Kou mouse. We identified several genes whose alternative splicing of precursor messenger RNAs was modified following TCDD exposure. In particular, we demonstrated that alternative splicing of Cyp1a1, Ahrr, and Actn1 was significantly altered after TCDD treatment. These findings show that the exposure to TCDD has an impact on alternative-splicing, and suggest a new avenue for understanding TCDD-mediated toxicity and pathogenesis.

Published
2019

17. Lestaurtinib is a potent inhibitor of anaplastic thyroid cancer cell line models

Author

Hon S. Leong, Paul C. Boutros, James C. Lacefield, Matthew R. Lowerison, Alessandro Datti, Joe S. Mymryk, Kara M. Ruicci, John W. Barrett, Stephenie D. Prokopec, Kevin Fung, Karlee Searle, Frederick S. Vizeacoumar, Nicole Pinto, Anthony C. Nichols, Danielle MacNeil, John Yoo, and Ahmad, Aamir

Subjects
0301 basic medicine, Embryology, medicine.medical_treatment, Cancer Treatment, lcsh:Medicine, Apoptosis, Chick Embryo, Thyroid Carcinoma, Anaplastic, Lung and Intrathoracic Tumors, Targeted therapy, Diagnostic Radiology, 0302 clinical medicine, Thymic Tumors, Cell Movement, Ultrasound Imaging, thyroid cancer, Medicine and Health Sciences, Anaplastic, Cell Cycle and Cell Division, lcsh:Science, Endocrine Tumors, Cancer, Tumor, Multidisciplinary, medicine.diagnostic_test, Lestaurtinib, Pharmaceutics, Radiology and Imaging, Cell Cycle, Cell cycle, 3. Good health, inhibitor, lestaurtinib, Cell Motility, Oncology, Optical Equipment, 5.1 Pharmaceuticals, Cell Processes, 030220 oncology & carcinogenesis, Biomedical Imaging, Engineering and Technology, Drug, Development of treatments and therapeutic interventions, Anatomy, medicine.drug, Research Article, General Science & Technology, Imaging Techniques, Carbazoles, Equipment, Antineoplastic Agents, Cell Migration, Research and Analysis Methods, high-throughput screening, Carcinomas, Cell Line, Flow cytometry, Dose-Response Relationship, 03 medical and health sciences, Cell and Developmental Biology, Rare Diseases, Drug Therapy, In vivo, Diagnostic Medicine, Cell Line, Tumor, medicine, Animals, Humans, Thyroid Neoplasms, Anaplastic thyroid cancer, Furans, Cell Proliferation, Chemotherapy, Dose-Response Relationship, Drug, business.industry, thyroid cancer, cell models, high-throughput screening, lestaurtinib, inhibitor, lcsh:R, Embryos, Thyroid Carcinoma, Cancers and Neoplasms, Biology and Life Sciences, Prisms, Cell Biology, Janus Kinase 2, medicine.disease, Xenograft Model Antitumor Assays, cell models, 030104 developmental biology, Cell culture, Cancer research, lcsh:Q, Thyroid Carcinomas, business, Developmental Biology
Abstract

Anaplastic thyroid cancer (ATC) is a rare and lethal human malignancy with no known effective therapies in the majority of cases. Despite the use of conventional treatments such as chemotherapy, radiation and surgical resection, this disease remains almost universally fatal. In the present study, we identified the JAK2 inhibitor Lestaurtinib as a potent compound when testing against 13 ATC cell lines. Lestaurtinib demonstrated a potent antiproliferative effect in vitro at nanomolar concentrations. Furthermore, Lestaurtinib impeded cell migration and the ability to form colonies from single cells using scratch-wound and colony formation assays, respectively. Flow cytometry was used for cell cycle analysis following drug treatment and demonstrated arrest at the G2/M phase of the cell cycle, indicative of a cytostatic effect. In vivo studies using the chick chorioallantoic membrane xenograft models demonstrated that treatment with Lestaurtinib resulted in a significant decrease in endpoint tumor volume and vascularity using power Doppler ultrasound imaging. Overall, this study provides evidence that Lestaurtinib is a potent antiproliferative agent with potential antiangiogenic activity that warrants further investigation as a targeted therapy for ATC.

Published
2018

18. Accurate Reference-Free Somatic Variant-Calling by Integrating Genomic, Sequencing and Population Data

Author

Christopher M. Lalansingh, Anthony C. Nichols, Szyca L, Paul C. Boutros, Cindy Q. Yao, Kathleen E. Houlahan, Takafumi N. Yamaguchi, John W. Barrett, Stephenie D. Prokopec, Lawrence E. Heisler, Espiritu Smg, Ren X. Sun, Morgan Black, and Constance H. Li

Subjects
0303 health sciences, education.field_of_study, Somatic cell, Genomic sequencing, Population, Context (language use), Computational biology, Biology, medicine.disease, Primary tumor, 3. Good health, Reference free, 03 medical and health sciences, 0302 clinical medicine, Population data, medicine, Precision and recall, education, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

The detection of somatic single nucleotide variants (SNVs) is critical in both research and clinical applications. Studies of human cancer typically use matched normal (reference) samples from a distant tissue to increase SNV prediction accuracy. This process both doubles sequencing costs and poses challenges when reference samples are not readily available, such as for many cell-lines. To address these challenges, we created S22S: an approach for the prediction of somatic mutations without need for matched reference tissue. S22S takes underlying sequence data, augments them with genomic background context and population frequency information, and classifies SNVs as somatic or non-somatic. We validated S22S using primary tumor/normal pairs from four tumor types, spanning two different sequencing technologies. S22S robustly identifies somatic SNVs, with the area under the precision recall curve reaching 0.97 in kidney clear cell carcinoma, comparable to the best tumor/normal analysis pipelines. S22S is freely available at http://labs.oicr.on.ca/Boutros-lab/software/s22s.

Published
2018
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19. The Origins and Consequences of Localized and Global Somatic Hypermutation

Author

Fan F, Fouad Yousif, Park Dh, Stephenie D. Prokopec, Szyca L, Christopher M. Lalansingh, Ren X. Sun, and Paul C. Boutros

Subjects
Genetics, APOBEC, 0303 health sciences, Mutation rate, Somatic hypermutation, Cancer, Biology, medicine.disease, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, CDKN2A, 030220 oncology & carcinogenesis, Kataegis, Mutation (genetic algorithm), medicine, Gene, 030304 developmental biology
Abstract

Cancer is a disease of the genome, but the dramatic inter-patient variability in mutation number is poorly understood. Tumours of the same type can differ by orders of magnitude in their mutation rate. To understand potential drivers and consequences of the underlying heterogeneity in mutation rate across tumours, we evaluated both local and global measures of mutation density: both single-stranded and double-stranded DNA breaks in 2,460 tumours of 38 cancer types. We find that SCNAs in thousands of genes are associated with elevated rates of point-mutations, while similarly point-mutation patterns in dozens of genes are associated with specific patterns of DNA double-stranded breaks. These candidate drivers of mutation density are enriched for known cancer drivers, and preferentially occur early in tumour evolution, appearing clonally in all cells of a tumour. To supplement this understanding of global mutation density, we developed and validated a tool called SeqKat to identify localized “rainstorms” of point-mutations (kataegis). We show that rates of kataegis differ by four orders of magnitude across tumour types, with malignant lymphomas showing the highest. Tumours withTP53mutations were 2.6-times more likely to harbour a kataegic event than those without, and 239 SCNAs were associated with elevated rates of kataegis, including loss of the tumour-suppressorCDKN2A. We identify novel subtypes of kataegic events not associated with aberrant APOBEC activity, and find that these are localized to specific cellular regions, enriched for MYC-target genes. Kataegic events were associated with patient survival in some, but not all tumour types, highlighting a combination of global and tumour-type specific effects. Taken together, we reveal a landscape of genes driving localized and tumour-specific hyper-mutation, and reveal novel mutational processes at play in specific tumour types.

Published
2018
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20. Transcriptional profiling of rat hypothalamus response to 2,3,7,8-tetrachlorodibenzo-ρ-dioxin

Author

Kathleen E. Houlahan, Sanna Lensu, Paul C. Boutros, Stephenie D. Prokopec, Allan B. Okey, Ivy D. Moffat, Jere Lindén, Raimo Pohjanvirta, Departments of Faculty of Veterinary Medicine, Food Hygiene and Environmental Health, and Raimo Pohjanvirta / Principal Investigator

Subjects
Male, FOOD-INTAKE, TCDD, Polychlorinated Dibenzodioxins, Time Factors, Transcription, Genetic, Microarray, TISSUE GROWTH-FACTOR, AHR, AH GENE BATTERY, 413 Veterinary science, Toxicology, Toxicogenetics, feed restriction, Transcriptome, NAD(P)H Dehydrogenase (Quinone), RESISTANT RAT, heterocyclic compounds, MESSENGER-RNA EXPRESSION, hypothalamus, Wasting, reproductive and urinary physiology, Oligonucleotide Array Sequence Analysis, biology, ta3141, 3. Good health, PROBE LEVEL, Hypothalamus, Toxicity, ENERGY-BALANCE, medicine.symptom, microarray, ARYL-HYDROCARBON RECEPTOR, endocrine system, medicine.medical_specialty, ta3111, Species Specificity, Internal medicine, Cytochrome P-450 CYP1A1, medicine, Animals, Rats, Long-Evans, RNA, Messenger, Wasting Syndrome, Rats, Wistar, Gene Expression Profiling, ta1184, Lethal dose, Aryl hydrocarbon receptor, stomatognathic diseases, Endocrinology, INDUCED ANOREXIA, Gene Expression Regulation, biology.protein
Abstract

In some mammals, halogenated aromatic hydrocarbon (HAH) exposure causes wasting syndrome, defined as significant weight loss associated with lethal outcomes. The most potent HAH in causing wasting is 2,3,7,8-tetrachlorodibenzo-r-dioxin (TCDD), which exerts its toxic effects through the aryl hydrocarbon receptor (AHR). Since TCDD toxicity is thought to predominantly arise from dysregulation of AHR-transcribed genes, it was hypothesized that wasting syndrome is a result of to TCDD-induced dysregulation of genes involved in regulation of food-intake. As the hypothalamus is the central nervous systems' regulatory center for food-intake and energy balance. Therefore, mRNA abundances in hypothalamic tissue from two rat strains with widely differing sensitivities to TCDD-induced wasting syndrome: TCDD-sensitive Long–Evans rats and TCDD-resistant Han/Wistar rats, 23h after exposure to TCDD (100 mg/kg) or corn oil vehicle. TCDD exposure caused minimal transcriptional dysregulation in the hypothalamus, with only 6 genes significantlyaltered in Long–Evans rats and 15 genes in Han/Wistar rats. Two of the most dysregulated genes were Cyp1a1 and Nqo1, which are induced by TCDD across a wide range of tissues and are considered sensitive markers of TCDD exposure. The minimal response of the hypothalamic transcriptome to a lethal dose of TCDD at an early time-point suggests that the hypothalamus is not the predominant site of initial events leading to hypophagia and associated wasting. TCDD may affect feeding behaviour via events upstream or downstream of the hypothalamus, and further work is required to evaluate this at the level of individual hypothalamic nuclei and subregions. a 2014 The Authors. Published by Elsevier Ireland Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Published
2015
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21. Identification of a neutrophil-related gene expression signature that is enriched in adult systemic lupus erythematosus patients with active nephritis: Clinical/pathologic associations and etiologic mechanisms

Author

Carolina Landolt-Marticorena, Heather N. Reich, James W. Scholey, Dennisse Bonilla, Babak Noamani, Paul C. Boutros, Paul R. Fortin, Stephenie D. Prokopec, Nan-Hua Chang, Joan E. Wither, Zahi Touma, Carmen Avila-Casado, and Zhou, Xu-jie

Subjects
0301 basic medicine, Male, Kidney Disease, Physiology, Microarrays, Neutrophils, Biopsy, Lupus nephritis, Gene Expression, lcsh:Medicine, Cell Count, Biochemistry, Transcriptome, White Blood Cells, 0302 clinical medicine, Animal Cells, Medicine and Health Sciences, Medicine, lcsh:Science, screening and diagnosis, Multidisciplinary, Proteinuria, medicine.diagnostic_test, Middle Aged, Lupus Nephritis, Body Fluids, 3. Good health, Detection, Blood, Bioassays and Physiological Analysis, Biomarker (medicine), Female, Renal biopsy, Cellular Types, Anatomy, medicine.symptom, Nephritis, Research Article, Adult, General Science & Technology, Immune Cells, Immunology, Lupus, Surgical and Invasive Medical Procedures, Research and Analysis Methods, Systemic Lupus Erythematosus, Autoimmune Disease, Autoimmune Diseases, 03 medical and health sciences, Young Adult, Rheumatology, Clinical Research, Genetics, Humans, 030203 arthritis & rheumatology, Blood Cells, Lupus Erythematosus, business.industry, Gene Expression Profiling, Inflammatory and immune system, lcsh:R, Biology and Life Sciences, Cell Biology, medicine.disease, 4.1 Discovery and preclinical testing of markers and technologies, Gene expression profiling, 030104 developmental biology, Clinical Immunology, lcsh:Q, Interferons, Clinical Medicine, business, Biomarkers
Abstract

Both a lack of biomarkers and relatively ineffective treatments constitute impediments to management of lupus nephritis (LN). Here we used gene expression microarrays to contrast the transcriptomic profiles of active SLE patients with and without LN to identify potential biomarkers for this condition. RNA isolated from whole peripheral blood of active SLE patients was used for transcriptomic profiling and the data analyzed by linear modeling, with corrections for multiple testing. Results were validated in a second cohort of SLE patients, using NanoString technology. The majority of genes demonstrating altered transcript abundance between patients with and without LN were neutrophil-related. Findings in the validation cohort confirmed this observation and showed that levels of RNA abundance in renal remission were similar to active patients without LN. In secondary analyses, RNA abundance correlated with disease activity, hematuria and proteinuria, but not renal biopsy changes. As abundance levels of the individual transcripts correlated strongly with each other, a composite neutrophil score was generated by summing all levels before examining additional correlations. There was a modest correlation between the neutrophil score and the blood neutrophil count, which was largely driven by the dose of glucocorticosteroids and not the proportion of low density and/or activated neutrophils. Analysis of longitudinal data revealed no correlation between baseline neutrophil score or changes over the first year of follow-up with subsequent renal flare or treatment outcomes, respectively. The findings argue that although the neutrophil score is associated with LN, its clinical utility as a biomarker may be limited.

Published
2018

22. MP73-06 DRUG RESISTANCE CONSEQUENCES OF TUMOR HETEROGENEITY IN METASTATIC RENAL CELL CARCINOMA USING ULTRA-FAST PATIENT DERIVED XENOGRAFTS AND MULTIREGIONAL GENOMIC SEQUENCING

Author

Matthew R. Lowerison, James C. Lacefield, Slavic Fedyshyn, Ann F. Chambers, Paul C. Boutros, Stephenie D. Prokopec, Nicholas Power, and Hon S. Leong

Subjects
Oncology, medicine.medical_specialty, business.industry, Renal cell carcinoma, Urology, Internal medicine, Genomic sequencing, Medicine, Ultra fast, Drug resistance, business, medicine.disease, Tumor heterogeneity
Published
2017
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23. Anti-nucleosome antibodies outperform traditional biomarkers as longitudinal indicators of disease activity in systemic lupus erythematosus

Author

Stephenie D. Prokopec, Timothy Li, Stacey Morrison, Wendy Lou, James W. Scholey, Carolina Landolt-Marticorena, Paul C. Boutros, Dafna D. Gladman, Heather Reich, Murray B. Urowitz, Joan E. Wither, and Paul R. Fortin

Subjects
Adult, Male, Time Factors, Adolescent, Cross-sectional study, Sensitivity and Specificity, Severity of Illness Index, Young Adult, Rheumatology, Severity of illness, Humans, Lupus Erythematosus, Systemic, Medicine, Pharmacology (medical), Longitudinal Studies, Prospective Studies, Young adult, skin and connective tissue diseases, Prospective cohort study, Aged, biology, business.industry, Anti-dsDNA antibodies, Complement C3, DNA, Middle Aged, Clinical Science, Antibodies, Anti-Idiotypic, Nucleosomes, Cross-Sectional Studies, Immunology, biology.protein, Biomarker (medicine), Female, Analysis of variance, Antibody, business, Biomarkers
Abstract

Objective. The aim of this study was to determine whether anti-nucleosome antibodies function as activity-specific biomarkers in SLE. Methods. Fifty-one patients were recruited and followed prospectively with periodic clinical and biochemical assessments over a 14-month period. Disease activity was determined by the SLEDAI-2K. Anti-nucleosome antibody levels were measured by an ELISA and its utility as an activity-specific biomarker as compared with that of anti-dsDNA antibodies and C3 was assessed both at baseline and in longitudinal analysis. Results. Anti-nucleosome antibodies were significantly elevated in SLE patients vs controls and showed a moderate positive correlation with disease activity. The utility of anti-nucleosome antibodies in identifying patients with active disease in a cross-sectional analysis was comparable to that of anti-dsDNA antibodies and C3. Analysis of variance demonstrated that the level of anti-nucleosome antibodies and C3 varied significantly with changes in disease activity over time. Changes in clinical state were not mirrored by changes in anti-dsDNA antibodies. In time-dependent analysis, anti-nucleosome antibodies showed a better fit over time than anti-dsDNA antibodies and C3. In pairwise comparisons, C3 and anti-nucleosome antibodies outperformed other models, including the conventional pairing of C3 and anti-dsDNA antibodies, however, no biomarker alone or as a group accurately predicted impending remissions or exacerbations. Conclusion. Anti-nucleosome antibodies demonstrate greater fidelity as a biomarker for changes in SLE disease activity than traditional biomarkers, supporting the routine monitoring of this antibody in clinical practice.

Published
2014
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24. Rethinking Lupus Nephritis Classification on a Molecular Level

Author

Jianying Zhang, Paul C. Boutros, Ana Malvar, Carmen Avila-Casado, Valeria Alberton, Joan E. Wither, Brad H. Rovin, Heather N. Reich, Lianbo Yu, Salem Almaani, James W. Scholey, Samir V. Parikh, and Stephenie D. Prokopec

Subjects
Nephrology, medicine.medical_specialty, Pathology, Kidney Disease, mRNA, Clinical Sciences, Lupus nephritis, Lupus, lcsh:Medicine, Disease, Autoimmune Disease, Article, Correlation, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, Internal medicine, Biopsy, RPS classification, 2.1 Biological and endogenous factors, Medicine, Aetiology, ISN/RPS classification, ISN, Cancer, 030304 developmental biology, lupus nephritis, 030203 arthritis & rheumatology, 0303 health sciences, Kidney, medicine.diagnostic_test, business.industry, lcsh:R, General Medicine, medicine.disease, Phenotype, 3. Good health, medicine.anatomical_structure, Renal pathology, business
Abstract

The International Society of Nephrology/Renal Pathology Society (ISN/RPS) lupus nephritis (LN) classification is under reconsideration, given challenges with inter-rater reliability and resultant inconsistent relationship with treatment response. Integration of molecular classifiers into histologic evaluation can improve diagnostic precision and identify therapeutic targets. This study described the relationship between histological and molecular phenotypes and clinical responses in LN. Renal compartmental mRNA abundance was measured in 54 biopsy specimens from LN patients and correlated to ISN/RPS classification and individual histologic lesions. A subset of transcripts was also evaluated in sequential biopsies of a separate longitudinal cohort of 36 patients with paired samples obtained at the time of flare and at follow up. Unsupervised clustering based on mRNA abundance did not demonstrate a relationship with the (ISN/RPS) classification, nor did univariate statistical analysis. Exploratory analyses suggested a correlation with individual histologic lesions. Glomerular FN1 (fibronectin), SPP1 (secreted phosphoprotein 1), and LGALS3 (galectin 3) abundance correlated with disease activity and changed following treatment. Exploratory analyses suggested relationships between specific transcripts and individual histologic lesions, with the important representation of interferon-regulated genes. Our findings suggested that the current LN classification could be refined by the inclusion of molecular descriptors. Combining molecular and pathologic kidney biopsy phenotypes may hold promise to better classify disease and identify actionable treatment targets and merits further exploration in larger cohorts.

Published
2019
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25. Abstract 3771: Oncogenes and tumour-suppressors drive differential retinoblastoma evolution

Author

Diane Rushlow, Hilary Racher, Julie Livingstone, Shadrielle Melijah G. Espiritu, Donco Matveski, Doroto H. Sendorek, Stephenie D. Prokopec, John D. Watson, Adriana Salcedo, Fouad Yousif, Paul C. Boutros, and Brenda L. Gallie

Subjects
Cancer Research, Oncology, law, Retinoblastoma, Cancer research, medicine, Suppressor, Biology, medicine.disease, Differential (mathematics), law.invention
Abstract

Unlike any other tumour type, retinoblastomas can be driven by only two tumour-initiating events: bi-allelic loss of the tumour suppressor RB1 or amplification of the MYCN oncogene. These mutations drive morphologically indistinguishable tumours that arise at different ages, providing a unique model system to evaluate the influence of initiating mutation on tumour evolution. We performed high-resolution copy number analysis of 101 retinoblastoma and whole genome sequencing of 23. These data reveal that different initiating mutations cause probabilistic changes in somatic point and copy number mutations, but large changes in genomic rearrangements and mitochondrial number. Independent of the initiating mutation, retinoblastomas harbour multiple subclonal populations that preferentially accrue point mutations after subclonal diversification. These subclonal structures suggest caution when choosing chemotherapeutic strategies for primary treatment. Overall, initiating mutations influence evolutionary trajectory more than specific driver mutations: RB1- and MYCN-driven tumours harbour distinct mutational processes, sequences of mutation acquisition and patterns of subclonal diversification. These data show how tumour-initiating mutations drive clinical behaviour by subtly biasing multiple evolutionary processes. Validation in other tumour types is underway. Citation Format: Adriana Salcedo, John D. Watson, Hilary Racher, Diane Rushlow, Shadrielle Melijah G. Espiritu, Doroto H. Sendorek, Stephenie D. Prokopec, Donco Matveski, Fouad Yousif, Julie Livingstone, Brenda L. Gallie, Paul C. Boutros. Oncogenes and tumour-suppressors drive differential retinoblastoma evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3771.

Published
2019
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26. Long-term hemodynamic and molecular effects persist after discontinued renin–angiotensin system blockade in patients with type 1 diabetes mellitus

Author

Stuart Yang, James W. Scholey, Bernard Zinman, Stephenie D. Prokopec, Judith A. Miller, Chris R. J. Kennedy, David Z.I. Cherney, Heather N. Reich, Paul C. Boutros, Vesta Lai, and Rahim Moineddin

Subjects
Adult, Male, medicine.medical_specialty, Time Factors, Urinary system, Hemodynamics, Angiotensin-Converting Enzyme Inhibitors, Inflammation, Drug Administration Schedule, Losartan, Renin-Angiotensin System, Vascular Stiffness, Enalapril, Internal medicine, Renin–angiotensin system, medicine, Humans, Skin, Ontario, Type 1 diabetes, Kidney, business.industry, Middle Aged, medicine.disease, Blockade, Oxidative Stress, Diabetes Mellitus, Type 1, Treatment Outcome, Endocrinology, medicine.anatomical_structure, Nephrology, Cytokines, Female, Endothelium, Vascular, Animal studies, Chemokines, medicine.symptom, business, Angiotensin II Type 1 Receptor Blockers, Diabetic Angiopathies
Abstract

Animal studies suggest temporary renin-angiotensin system (RAS) blockade enhances long-term vascular protective effects; however, this is not established in humans. Here we evaluated the long-term effects of prior RAS blockade on hemodynamic function, urinary measures of inflammation, and tissue antioxidant mRNA expression in patients with type 1 diabetes mellitus (T1DM) who participated in the 5-year Renin Angiotensin System Study (RASS). At 4 years after completing the RASS and discontinuing study medication, renal hemodynamic responses to clamped hyperglycemia were significantly greater in 18 patients in the RAS blockade group compared to 9 patients of the placebo-treated group. Individuals who had received RAS blockade also exhibited higher flow-mediated vasodilatation, reduced urinary cytokine excretion in response to hyperglycemia, and increased skin mRNA expression of superoxide dismutase-1 and catalase. Thus, patients with uncomplicated T1DM who received prior RAS blockade for 5 years maintain long-term effects on renal hemodynamic and systemic vascular function, inflammatory pathways in the kidney, and antioxidant enzyme expression in skin 4 years after discontinuation of therapy. Our findings suggest that sustained long-term protective effects of finite RAS inhibition requires further study.

Published
2013
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27. Validating reference genes within a mouse model system of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) toxicity

Author

Paul C. Boutros, Raimo Pohjanvirta, John D. Watson, Arturas Petronis, Natalie S. Fox, Nicholas Buchner, Stephenie D. Prokopec, Lauren C. Chong, and Denise Y.F. Mak

Subjects
Male, Normalization (statistics), Hypoxanthine Phosphoribosyltransferase, TCDD, Candidate gene, Polychlorinated Dibenzodioxins, Multivariate analysis, Gene Expression, Mice, Transgenic, Computational biology, Biology, Real-Time Polymerase Chain Reaction, Bioinformatics, Toxicology, mRNA abundance, Mouse model, Mice, 03 medical and health sciences, Peptide Elongation Factor 1, 0302 clinical medicine, Reference genes, Gene expression, Genotype, Animals, RNA, Messenger, Gene, 030304 developmental biology, 0303 health sciences, Genes, Essential, General Medicine, Quantitative real-time PCR, Mice, Inbred C57BL, Normalization, Real-time polymerase chain reaction, Mice, Inbred DBA, 030220 oncology & carcinogenesis, Multivariate Analysis, Female, Algorithms
Abstract

Background Quantitative real-time PCR (qPCR) is the “gold-standard” technique for measuring mRNA abundances. To correctly compare samples and generate biologically valid results, qPCR data usually require comprehensive normalization to account for sample content variation between reactions. The most common normalization approaches use one or more endogenous controls (reference or house-keeping genes) to adjust the measured levels of experimental genes appropriately. Ideal reference genes are those that display minimal variation across experimental conditions, and thus can vary widely across different biological systems. In particular, toxicogenomic studies of transcriptionally-disruptive toxins, like 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), require careful consideration of reference genes. Results We examined seven candidate reference genes in 199 mice varying in genotype and time/dose of TCDD exposure. We assessed gene-stability in four ways: (1) the variance of the raw Cq values across biological replicates, (2) the fold-change from basal mRNA levels following treatment, (3) the inter- and intra-group stability evaluated using the NormFinder algorithm, (4) the comparative ΔCq method for each candidate gene. Univariate analyses showed Hprt and Eef1a1 are the two most stable individual reference genes. It has been suggested that using multiple genes would produce a more consistent normalization factor; multivariate analysis was performed using NormFinder. In general, stability increased with the number of genes used, but specific gene-combinations synergized. Conclusions We have validated seven reference genes for use in analyzing mRNA abundances in mouse models of TCDD toxicity. The use of multiple reference genes increases stability, providing more consistent normalization and more reliable results. The number of reference genes used should be maximized, based on experimental capabilities (platform, sample availability, etc.). Our results show the benefit of validating reference genes using multiple methods prior to generating large biological datasets.

Published
2013
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28. Compendium of TCDD-mediated transcriptomic response datasets in mammalian model systems

Author

Ivy D. Moffat, Cindy Q. Yao, Stephenie D. Prokopec, Ren X. Sun, Kathleen E. Houlahan, Christine P'ng, Paul C. Boutros, Renee Pang, Sanna Lensu, Lauren C. Chong, Ashley B. Smith, Jere Lindén, Alexander H. Wu, Allan B. Okey, Raimo Pohjanvirta, Jamie Lee, Nicholas J. Harding, John D. Watson, Veterinary Pathology and Parasitology, Food Hygiene and Environmental Health, and Raimo Pohjanvirta / Principal Investigator

Subjects
0301 basic medicine, Male, TCDD, Polychlorinated Dibenzodioxins, Bioinformatics, Microarray datasets, AHR, White adipose tissue, Biology, Web Browser, Proteomics, 413 Veterinary science, Medical and Health Sciences, Cell Line, Transcriptome, 03 medical and health sciences, Mice, 0302 clinical medicine, Transcription (biology), Information and Computing Sciences, medicine, Genetics, Animals, Humans, heterocyclic compounds, Gene, Gene Expression Profiling, Computational Biology, Biological Sciences, Aryl hydrocarbon receptor, medicine.disease, 3. Good health, Rats, Chloracne, stomatognathic diseases, 030104 developmental biology, Gene Expression Regulation, 030220 oncology & carcinogenesis, Agent Orange & Dioxin, biology.protein, Environmental Pollutants, Female, DNA microarray, Software, Biotechnology
Abstract

Background 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is the most potent congener of the dioxin class of environmental contaminants. Exposure to TCDD causes a wide range of toxic outcomes, ranging from chloracne to acute lethality. The severity of toxicity is highly dependent on the aryl hydrocarbon receptor (AHR). Binding of TCDD to the AHR leads to changes in transcription of numerous genes. Studies evaluating the transcriptional changes brought on by TCDD may provide valuable insight into the role of the AHR in human health and disease. We therefore compiled a collection of transcriptomic datasets that can be used to aid the scientific community in better understanding the transcriptional effects of ligand-activated AHR. Results Specifically, we have created a datasets package – TCDD.Transcriptomics – for the R statistical environment, consisting of 63 unique experiments comprising 377 samples, including various combinations of 3 species (human derived cell lines, mouse and rat), 4 tissue types (liver, kidney, white adipose tissue and hypothalamus) and a wide range of TCDD exposure times and doses. These datasets have been fully standardized using consistent preprocessing and annotation packages (available as of September 14, 2015). To demonstrate the utility of this R package, a subset of “AHR-core” genes were evaluated across the included datasets. Ahrr, Nqo1 and members of the Cyp family were significantly induced following exposure to TCDD across the studies as expected while Aldh3a1 was induced specifically in rat liver. Inmt was altered only in liver tissue and primarily by rat-AHR. Conclusions Analysis of the “AHR-core” genes demonstrates a continued need for studies surrounding the impact of AHR-activity on the transcriptome; genes believed to be consistently regulated by ligand-activated AHR show surprisingly little overlap across species and tissues. Until now, a comprehensive assessment of the transcriptome across these studies was challenging due to differences in array platforms, processing methods and annotation versions. We believe that this package, which is freely available for download (http://labs.oicr.on.ca/boutros-lab/tcdd-transcriptomics) will prove to be a highly beneficial resource to the scientific community evaluating the effects of TCDD exposure as well as the variety of functions of the AHR. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3446-z) contains supplementary material, which is available to authorized users.

Published
2017

29. 2,3,7,8 Tetrachlorodibenzo-p-dioxin-induced RNA abundance changes identify Ackr3, Col18a1, Cyb5a and Glud1 as candidate mediators of toxicity

Author

Stephenie D. Prokopec, Raimo Pohjanvirta, John D. Watson, Allan B. Okey, Ashley B. Smith, Paul C. Boutros, Departments of Faculty of Veterinary Medicine, Food Hygiene and Environmental Health, and Raimo Pohjanvirta / Principal Investigator

Subjects
0301 basic medicine, Male, TCDD, Polychlorinated Dibenzodioxins, Health, Toxicology and Mutagenesis, Messenger, Drug Resistance, 413 Veterinary science, Inbred C57BL, Toxicology, mRNA abundance, Transcriptome, Chemokine receptor, Mice, Glutamate Dehydrogenase, Receptors, NanoString, heterocyclic compounds, CXCR, reproductive and urinary physiology, Aryl hydrocarbon receptor, Genetics, biology, Tetrachlorodibenzo-p-dioxin, General Medicine, Pharmacology and Pharmaceutical Sciences, 3. Good health, Glutamate dehydrogenase 1, Receptors, Glutamate, Liver, Toxicity, Female, Glutamate, Drug, Chemical and Drug Induced Liver Injury, endocrine system, Collagen Type VIII, Environmental, Dose-Response Relationship, 03 medical and health sciences, Molecular Toxicology, Animals, Outbred Strains, Animals, Rats, Long-Evans, RNA, Messenger, Gene, Receptors, CXCR, Dose-Response Relationship, Drug, Gene Expression Profiling, Cytochrome P450, Long-Evans, 2,3,7,8 Tetrachlorodibenzo-p-dioxin, Molecular biology, Carcinogens, Environmental, Rats, Mice, Inbred C57BL, stomatognathic diseases, Kinetics, 030104 developmental biology, Cytochromes b5, Outbred Strains, Gene Expression Regulation, biology.protein, Carcinogens, RNA, Cytochrome b5, type A, 8 Tetrachlorodibenzo-p-dioxin
Abstract

2,3,7,8 Tetrachlorodibenzo-p-dioxin (TCDD) is an aromatic, long-lived environmental contaminant. While the pathogenesis of TCDD-induced toxicity is poorly understood, it has been shown that the aryl hydrocarbon receptor (AHR) is required. However, the specific transcriptomic changes that lead to toxic outcomes have not yet been identified. We previously identified a panel of 33 genes that respond to TCDD treatment in two TCDD-sensitive rodent species. To identify genes involved in the onset of hepatic toxicity, we explored 25 of these in-depth using liver from two rat strains: the TCDD-resistant Han/Wistar (H/W) and the TCDD-sensitive Long–Evans (L–E). Time course and dose–response analyses of mRNA abundance following TCDD insult indicate that eight genes are similarly regulated in livers of both strains of rat, suggesting that they are not central to the severe L–E-specific TCDD-induced toxicities. The remaining 17 genes exhibited various divergent mRNA abundances between L–E and H/W strains after TCDD treatment. Several genes displayed a biphasic response where the initial response to TCDD treatment was followed by a secondary response, usually of larger magnitude in L–E liver. This secondary response was most often an exaggeration of the original TCDD-induced response. Only cytochrome b5 type A (microsomal) (Cyb5a) had equivalent TCDD sensitivity to the prototypic AHR-responsive cytochrome P450, family 1, subfamily a, polypeptide 1 (Cyp1a1), while six genes were less sensitive. Four genes showed an early inter-strain difference that was sustained throughout most of the time course (atypical chemokine receptor 3 (Ackr3), collagen, type XVIII, alpha 1 (Col18a1), Cyb5a and glutamate dehydrogenase 1 (Glud1)), and of those genes examined in this study, are most likely to represent genes involved in the pathogenesis of TCDD-induced hepatotoxicity in L–E rats. Electronic supplementary material The online version of this article (doi:10.1007/s00204-016-1720-0) contains supplementary material, which is available to authorized users.

Published
2017

30. Genomic hallmarks of localized, non-indolent prostate cancer

Author

Michèle Orain, Yu Jia Shiah, Ken Kron, Lawrence E. Heisler, Mathieu Lupien, Xuemei Luo, Andre P. Masella, Michelle Sam, Paul C. Boutros, Shaylan K. Govind, Daryl Waggott, Veronica Y. Sabelnykova, Natalie S. Fox, Musaddeque Ahmed, Julia F. Hopkins, Lee Timms, Clement Fung, Francis Nguyen, Zhiyuan Wang, Taryne Chong, Alain Bergeron, Julie Livingstone, Yves Fradet, Melvin L.K. Chua, Timothy Beck, Alexander Murison, Bernard Têtu, Ada Wong, Ren X. Sun, Constance H. Li, Kathleen E. Houlahan, John Douglas Mcpherson, Cenk Sahinalp, Housheng Hansen He, Junyan Zhang, Robert G. Bristow, Jeremy Johns, Neil E. Fleshner, Alejandro Berlin, Michelle Chan-Seng-Yue, Christine P'ng, Nicholas Buchner, Alister D'Costa, Richard de Borja, Xihui Lin, Louis Lacombe, Jeffrey Green, Hélène Hovington, Vincent Huang, Kenneth C. Chu, Haiying Kong, Emilie Lalonde, Nicholas J. Harding, Syed Haider, Esther Jung, Colin Collins, Shadrielle Melijah G. Espiritu, Takafumi N. Yamaguchi, Bryan Lo, Michael Xie, Valérie Picard, Michael Fraser, Stephenie D. Prokopec, Christopher I Cooper, Fouad Yousif, Theodorus van der Kwast, Robert E. Denroche, Alice Meng, Dominique Trudel, and Alan Dal Pra

Subjects
0301 basic medicine, Male, DNA Copy Number Variations, Somatic hypermutation, Genomics, Disease, Biology, Bioinformatics, 03 medical and health sciences, Prostate cancer, Recurrence, medicine, Humans, Exome, Neoplasm Metastasis, 610 Medicine & health, Chromothripsis, Multidisciplinary, Genome, Human, Prostatic Neoplasms, Methylation, DNA Methylation, medicine.disease, Prognosis, Human genetics, Prostatic Neoplasms, Castration-Resistant, 030104 developmental biology, DNA methylation, Mutation, Cancer research
Abstract

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

Published
2017
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31. VennDiagramWeb: a web application for the generation of highly customizable Venn and Euler diagrams

Author

Zhiyuan Wang, Felix Lam, Stephenie D. Prokopec, Paul C. Boutros, Natalie S. Fox, Holly E. Babaran, and Christopher M. Lalansingh

Subjects
0301 basic medicine, Theoretical computer science, Data Interpretation, Computer science, Interface (Java), Bioinformatics, 030106 microbiology, Bioengineering, Documentation, computer.software_genre, Biochemistry, Mathematical Sciences, law.invention, Computer graphics, 03 medical and health sciences, symbols.namesake, User-Computer Interface, Software, Structural Biology, law, Information and Computing Sciences, Computer Graphics, Web application, Humans, Graphics, Molecular Biology, Internet, business.industry, Programming language, Applied Mathematics, Computational Biology, Statistical, Biological Sciences, Visualization, Computer Science Applications, 030104 developmental biology, Networking and Information Technology R&D, Data Interpretation, Statistical, symbols, Euler diagram, Venn diagram, User interface, business, computer
Abstract

Background Visualization of data generated by high-throughput, high-dimensionality experiments is rapidly becoming a rate-limiting step in computational biology. There is an ongoing need to quickly develop high-quality visualizations that can be easily customized or incorporated into automated pipelines. This often requires an interface for manual plot modification, rapid cycles of tweaking visualization parameters, and the generation of graphics code. To facilitate this process for the generation of highly-customizable, high-resolution Venn and Euler diagrams, we introduce VennDiagramWeb: a web application for the widely used VennDiagram R package. VennDiagramWeb is hosted at http://venndiagram.res.oicr.on.ca/. Results VennDiagramWeb allows real-time modification of Venn and Euler diagrams, with parameter setting through a web interface and immediate visualization of results. It allows customization of essentially all aspects of figures, but also supports integration into computational pipelines via download of R code. Users can upload data and download figures in a range of formats, and there is exhaustive support documentation. Conclusions VennDiagramWeb allows the easy creation of Venn and Euler diagrams for computational biologists, and indeed many other fields. Its ability to support real-time graphics changes that are linked to downloadable code that can be integrated into automated pipelines will greatly facilitate the improved visualization of complex datasets. For application support please contact Paul.Boutros@oicr.on.ca. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1281-5) contains supplementary material, which is available to authorized users.

Published
2016

32. Inter-strain heterogeneity in rat hepatic transcriptomic responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)

Author

Nicholas J. Harding, Stephenie D. Prokopec, Raimo Pohjanvirta, Allan B. Okey, Cindy Q. Yao, Christine P'ng, John D. Watson, Lauren C. Chong, Paul C. Boutros, and Renee Pang

Subjects
Male, TCDD, Polychlorinated Dibenzodioxins, Time Factors, Transcription, Genetic, Microarray, Rodent, Time-course study, Toxicology, mRNA abundance, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, biology.animal, Cytochrome P-450 CYP1A1, NAD(P)H Dehydrogenase (Quinone), Animals, Rats, Long-Evans, heterocyclic compounds, RNA, Messenger, Rats, Wistar, Receptor, Gene, Crosses, Genetic, Aryl hydrocarbon receptor, Oligonucleotide Array Sequence Analysis, 030304 developmental biology, Dioxin, Pharmacology, Genetics, 0303 health sciences, Messenger RNA, Dose-Response Relationship, Drug, biology, Genetic Variation, Molecular biology, Rats, Inbred F344, Rats, Real-time RT-PCR, stomatognathic diseases, Liver, Receptors, Aryl Hydrocarbon, 030220 oncology & carcinogenesis, Toxicity, biology.protein
Abstract

The biochemical and toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) have been the subject of intense study for decades. It is now clear that essentially all TCDD-induced toxicities are mediated by DNA–protein interactions involving the Aryl Hydrocarbon Receptor (AHR). Nevertheless, it remains unknown which AHR target genes cause TCDD toxicities. Several groups, including our own, have developed rodent model systems to probe these questions. mRNA expression profiling of these model systems has revealed significant inter-species heterogeneity in rodent hepatic responses to TCDD. It has remained unclear if this variability also exists within a species, amongst rodent strains. To resolve this question, we profiled the hepatic transcriptomic response to TCDD of diverse rat strains (L-E, H/W, F344 and Wistar rats) and two lines derived from L-E×H/W crosses, at consistent age, sex, and dosing (100μg/kg TCDD for 19h). Using this uniquely consistent dataset, we show that the majority of TCDD-induced alterations in mRNA abundance are strain/line-specific: only 11 genes were affected by TCDD across all strains, including well-known dioxin-responsive genes such as Cyp1a1 and Nqo1. Our analysis identified two novel universally dioxin-responsive genes as well as 4 genes induced by TCDD in dioxin-sensitive rats only. These 6 genes are strong candidates to explain TCDD-related toxicities, so we validated them using 152 animals in time-course (0 to 384h) and dose–response (0 to 3000μg/kg) experiments. This study reveals that different rat strains exhibit dramatic transcriptional heterogeneity in their hepatic responses to TCDD and that inter-strain comparisons can help identify candidate toxicity-related genes.

Published
2012
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33. Male and female mice show significant differences in hepatic transcriptomic response to 2,3,7,8-tetrachlorodibenzo-p-dioxin

Author

John D. Watson, Stephenie D. Prokopec, Raimo Pohjanvirta, Jamie Lee, Paul C. Boutros, Ren X. Sun, Departments of Faculty of Veterinary Medicine, Food Hygiene and Environmental Health, and Raimo Pohjanvirta / Principal Investigator

Subjects
Male, NUCLEAR TRANSLOCATOR, TCDD, Polychlorinated Dibenzodioxins, Cytoplasmic and Nuclear, AHR, Receptors, Cytoplasmic and Nuclear, 010501 environmental sciences, 413 Veterinary science, 01 natural sciences, Medical and Health Sciences, 8-tetrachlorodibenzo-p-dioxin, Transcriptome, C57BL/6 MICE, Mice, Receptors, ABNORMAL LIVER DEVELOPMENT, 2.1 Biological and endogenous factors, heterocyclic compounds, Aetiology, Receptor, AH RECEPTOR, reproductive and urinary physiology, Aryl hydrocarbon receptor, GENE-EXPRESSION, Regulation of gene expression, 0303 health sciences, biology, FLAVIN-CONTAINING MONOOXYGENASE, Liver Disease, Sex hormone receptor, Biological Sciences, Phenotype, 3. Good health, Liver, MOUSE-LIVER, Female, Research Article, Biotechnology, ARYL-HYDROCARBON RECEPTOR, medicine.medical_specialty, endocrine system, Bioinformatics, 03 medical and health sciences, Sex Factors, Internal medicine, Information and Computing Sciences, Sex differences, medicine, Genetics, Animals, 2,3,7,8-tetrachlorodibenzo-p-dioxin, SPRAGUE-DAWLEY RATS, Constitutive Androstane Receptor, 030304 developmental biology, 0105 earth and related environmental sciences, Gene Expression Profiling, Gene expression profiling, stomatognathic diseases, Endocrinology, Gene Expression Regulation, Agent Orange & Dioxin, biology.protein, Digestive Diseases, Hormone
Abstract

Background 2,3,7,8–tetrachlorodibenzo-p-dixion (TCDD) is the most potent of the dioxin congeners, capable of causing a wide range of toxic effects across numerous animal models. Previous studies have demonstrated that males and females of the same species can display divergent sensitivity phenotypes to TCDD toxicities. Although it is now clear that most TCDD-induced toxic outcomes are mediated by the aryl hydrocarbon receptor (AHR), the mechanism of differential responses to TCDD exposure between sexes remains largely unknown. To investigate the differential sensitivities in male and female mice, we profiled the hepatic transcriptomic responses 4 days following exposure to various amounts of TCDD (125, 250, 500 or 1000 μg/kg) in adult male and female C57BL/6Kuo mice. Results Several key findings were revealed by our study. 1) Hepatic transcriptomes varied significantly between the sexes at all doses examined. 2) The liver transcriptome of males was more dysregulated by TCDD than that of females. 3) The alteration of “AHR-core” genes was consistent in magnitude, regardless of sex. 4) A subset of genes demonstrated sex-dependent TCDD-induced transcriptional changes, including Fmo3 and Nr1i3, which were significantly induced in livers of male mice only. In addition, a meta-analysis was performed to contrast transcriptomic profiles of various organisms and tissues following exposure to equitoxic doses of TCDD. Minimal overlap was observed in the differences between TCDD-sensitive or TCDD-resistant models. Conclusions Sex-dependent sensitivities to TCDD exposure are associated with a set of sex-specific TCDD-responsive genes. In addition, complex interactions between the aryl hydrocarbon and sex hormone receptors may affect the observable differences in sensitivity phenotypes between the sexes. Further work is necessary to better understand the roles of those genes altered by TCDD in a sex-dependent manner, and their association with changes to sex hormones and receptors. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1840-6) contains supplementary material, which is available to authorized users.

Published
2015

34. Abstract 2137: JAK2 as a novel therapeutic target in anaplastic thyroid cancer

Author

Kevin Fung, Nicole Pinto, Danielle MacNeil, Kara M. Ruicci, Alessandro Datti, Karlee Searle, John Yoo, John W. Barrett, Paul C. Boutros, Matthew R. Lowerison, Hon S. Leong, Anthony C. Nichols, and Stephenie D. Prokopec

Subjects
0301 basic medicine, Cancer Research, Programmed cell death, business.industry, Cell growth, Lestaurtinib, Cell, Cancer, medicine.disease, Thyroid carcinoma, 03 medical and health sciences, 030104 developmental biology, medicine.anatomical_structure, Oncology, Apoptosis, Cancer research, Medicine, Anaplastic thyroid cancer, business, medicine.drug
Abstract

Introduction: Thyroid carcinoma is the most common endocrine malignancy. Anaplastic thyroid cancer (ATC) is rare (1.3%) and represents arguably the most lethal human malignancy with 1-year survival rates of only 10%. There are currently no effective treatments for the majority of patients, highlighting an urgent need for novel therapeutics to manage this disease. Objective: To validate the functional importance of JAK2 as a therapeutic target in ATC. Methods: In this study, we have used siRNA knockdown to interrogate the JAK2 signaling pathway as a therapeutic target in ATC. We investigated the mechanism of action and cell death, and assayed for migration and invasion, in vitro. The chick chorioallantoic membrane (CAM) model was also utilized for drug testing, whereby 1x106 Cal62 ATC cells were on-planted to the chick embryo membrane. Two days post on-plant, CAM models were treated with the vehicle (DMSO) or lestaurtinib to measure outcomes including tumor volume and vascularity. Results: We identified the JAK2 inhibitor lestaurtinib as an inhibitory agent controlling cell line proliferation at submicromolar mean inhibitory concentrations. Immunoblotting revealed the inhibition of phosphorylation of the downstream signaling molecule STAT5 in a dose-dependent manner. Treatment of Cal62 cells resulted in a decrease in cell migration using the scratch-wound assay. The anti-proliferative effective of lestaurtinib did not cause apoptosis, autophagy or cell senescence. CAM models treated with a 4 uM dose of lestaurtinib showed a significant decrease in both tumor volume and vascularity. Conclusions: Lestaurtinib was found to provide potent control of ATC cell proliferation and migration, and was also found to decrease tumor growth and vascularity in a CAM model. Knockout studies are underway to confirm that the anticancer effect of this drug is indeed mediated through JAK2 signaling. If validated, JAK2 represents a novel therapeutic target for the treatment of aggressive thyroid cancers. Citation Format: Nicole C. Pinto, Kara Ruicci, Stephenie Prokopec, Karlee Searle, Matthew Lowerison, John Yoo, Kevin Fung, Danielle MacNeil, Hon S. Leong, Alessandro Datti, Paul C. Boutros, John W. Barrett, Anthony C. Nichols. JAK2 as a novel therapeutic target in anaplastic thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2137. doi:10.1158/1538-7445.AM2017-2137

Published
2017
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35. Spatial genomic heterogeneity within localized, multifocal prostate cancer

Author

Hanbo Chen, Julie Livingstone, Cherry Have, Thomas J. Hudson, Veronica Y. Sabelnykova, Ada Wong, Stephenie D. Prokopec, Timothy Beck, Shaylan K. Govind, Kenneth C. Chu, Gaetano Zafarana, Robert G. Bristow, Neil E. Fleshner, Alister D'Costa, Fouad Yousif, Jeremy Johns, James R. Hawley, Daryl Waggott, Lee Timms, John D. Watson, Colin Cooper, Paul C. Boutros, Bernard Têtu, Emilie Lalonde, Cenk Sahinalp, Dominique Trudel, Jenna Sykes, Esther Jung, David E. Neal, Trent T. Simmons, Faraz Hach, Michael Fraser, Christine P'ng, Robert E. Denroche, Lincoln Stein, Colin Collins, Xuemei Luo, Rosalind A. Eeles, Sohrab P. Shah, Melania Pintilie, Theodorus van der Kwast, Clement Fung, Francis Nguyen, Michelle Chan-Seng-Yue, Andrew M.K. Brown, John Douglas Mcpherson, Amin Zia, Alan Dal Pra, Nicholas J. Harding, Alice Meng, Lauren C. Chong, Philippe Lambin, Pablo H. Hennings-Yeomans, Richard de Borja, Nicholas Buchner, Andrew McPherson, Jianxin Wang, Yu Jia Shiah, Michelle Sam, Maud H.W. Starmans, Natalie S. Fox, Taryne Chong, Gregory M. Chen, Alejandro Berlin, Lakshmi Muthuswamy, Promovendi ODB, Radiotherapie, RS: GROW - Oncology, and RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy

Subjects
Male, DNA Copy Number Variations, Genomics, Biology, Bioinformatics, Genome, Polymorphism, Single Nucleotide, DNA sequencing, Proto-Oncogene Proteins c-myc, Prostate cancer, Genetic Heterogeneity, Cell Line, Tumor, Genetics, medicine, Humans, Point Mutation, 610 Medicine & health, Gene, Genetic Association Studies, Genetic heterogeneity, Genome, Human, Point mutation, Cancer, Prostatic Neoplasms, Middle Aged, medicine.disease, Cancer research, Neoplasm Grading
Abstract

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Published
2014

36. Sex-related differences in murine hepatic transcriptional and proteomic responses to TCDD

Author

John D. Watson, Jamie Lee, Stephenie D. Prokopec, Paul C. Boutros, Raimo Pohjanvirta, Departments of Faculty of Veterinary Medicine, Food Hygiene and Environmental Health, and Raimo Pohjanvirta / Principal Investigator

Subjects
Male, Proteomics, TCDD, Polychlorinated Dibenzodioxins, Proteome, Transcription, Genetic, Apoptosis, Toxicology, 413 Veterinary science, Computational biology, Mice, 0302 clinical medicine, Constitutive androstane receptor, Aryl hydrocarbon receptor, 0303 health sciences, Cell Cycle, Cell cycle, TOXICOGENOMIC ANALYSIS, CYTOCHROME-P450 GENES, Toxicity, MOUSE-LIVER, Environmental Pollutants, Female, 2,3,7,8-TETRACHLORODIBENZO-P-DIOXIN TCDD, ARYL-HYDROCARBON RECEPTOR, medicine.medical_specialty, Guinea Pigs, Biology, NUCLEAR RECEPTOR, 03 medical and health sciences, Sex Factors, Internal medicine, Sex differences, medicine, Animals, RNA, Messenger, SPRAGUE-DAWLEY RATS, 2,3,7,8-Tetrachlorodibenzo-p-dioxin, Transcription factor, Constitutive Androstane Receptor, 030304 developmental biology, Pharmacology, AH receptor, RESISTANT RAT STRAIN, Lipid metabolism, Lipid Metabolism, Rats, Mice, Inbred C57BL, Endocrinology, Nuclear receptor, GENE-EXPRESSION PROFILES, biology.protein, 030217 neurology & neurosurgery, Drug metabolism, Transcription Factors
Abstract

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is an environmental contaminant that produces myriad toxicities in most mammals. In rodents alone, there is a huge divergence in the toxicological response across species, as well as among different strains within a species. But there are also significant differences between males and females animals of a single strain. These differences are inconsistent across model systems: the severity of toxicity is greater in female rats than males, while male mice and guinea pigs are more sensitive than females. Because the specific events that underlie this difference remain unclear, we characterized the hepatic transcriptional response of adult male and female C57BL/6 mice to 500 mu g/kg TCDD at multiple time-points. The transcriptional profile diverged significantly between the sexes. Female mice demonstrated a large number of altered transcripts as early as 6 h following treatment, suggesting a large primary response. Conversely, male animals showed the greatest TCDD-mediated response 144 h following exposure, potentially implicating significant secondary responses. Nr1i3 was statistically significantly induced at all time-points in the sensitive male animals. This mRNA encodes the constitutive androstane receptor (CAR), a transcription factor involved in the regulation of xenobiotic metabolism, lipid metabolism, cell cycle and apoptosis. Surprisingly though, changes at the protein level (aside from the positive control, CYP1A1) were modest, with only FMO3 showing clear induction, and no genes with sex-differences. Thus, while male and female mice show transcriptional differences in their response to TCDD, their association with TCDD-induced toxicities remains unclear. (C) 2015 The Authors. Published by Elsevier Inc.

Published
2014

37. Cross-species transcriptomic analysis elucidates constitutive aryl hydrocarbon receptor activity

Author

Kathleen E. Houlahan, Allan B. Okey, Ivy D. Moffat, Paul C. Boutros, Christine P'ng, Sanna Lensu, Jere Lindén, Stephenie D. Prokopec, John D. Watson, Trent T. Simmons, Ren X. Sun, Lauren C. Chong, Raimo Pohjanvirta, Departments of Faculty of Veterinary Medicine, Veterinary Biosciences, Veterinary Pathology and Parasitology, and Food Hygiene and Environmental Health

Subjects
Male, HEPATIC GENE-EXPRESSION, 413 Veterinary science, Medical and Health Sciences, Transcriptome, DIOXIN RECEPTOR, Mice, 0302 clinical medicine, TCDD-induced toxicity, Receptors, Transcriptional regulation, ABNORMAL LIVER DEVELOPMENT, 2.1 Biological and endogenous factors, Cluster Analysis, Aetiology, Receptor, AH RECEPTOR, IN-VIVO, Aryl hydrocarbon receptor, Genetics, Regulation of gene expression, 0303 health sciences, Biological Sciences, respiratory system, Core-gene battery, Aryl Hydrocarbon, Organ Specificity, 030220 oncology & carcinogenesis, AHR endogenous ligands, 2,3,7,8-TETRACHLORODIBENZO-P-DIOXIN TCDD, Signal transduction, Research Article, Biotechnology, Signal Transduction, Protein Binding, Bioinformatics, 1.1 Normal biological development and functioning, education, RAT-LIVER, Constitutive gene expression, Biology, MICE LACKING, 03 medical and health sciences, Species Specificity, Underpinning research, Information and Computing Sciences, Animals, 030304 developmental biology, Aryl hydrocarbon receptor activity, Gene Expression Profiling, Computational Biology, CELL-CYCLE CONTROL, Rats, respiratory tract diseases, Gene expression profiling, Receptors, Aryl Hydrocarbon, Gene Expression Regulation, SUBCHRONIC EXPOSURE, biology.protein, Digestive Diseases
Abstract

Background Research on the aryl hydrocarbon receptor (AHR) has largely focused on variations in toxic outcomes resulting from its activation by halogenated aromatic hydrocarbons. But the AHR also plays key roles in regulating pathways critical for development, and after decades of research the mechanisms underlying physiological regulation by the AHR remain poorly characterized. Previous studies identified several core genes that respond to xenobiotic AHR ligands across a broad range of species and tissues. However, only limited inferences have been made regarding its role in regulating constitutive gene activity, i.e. in the absence of exogenous ligands. To address this, we profiled transcriptomic variations between AHR-active and AHR-less-active animals in the absence of an exogenous agonist across five tissues, three of which came from rats (hypothalamus, white adipose and liver) and two of which came from mice (kidney and liver). Because AHR status alone has been shown sufficient to alter transcriptomic responses, we reason that by contrasting profiles amongst AHR-variant animals, we may elucidate effects of the AHR on constitutive mRNA abundances. Results We found significantly more overlap in constitutive mRNA abundances amongst tissues within the same species than from tissues between species and identified 13 genes (Agt, Car3, Creg1, Ctsc, E2f6, Enpp1, Gatm, Gstm4, Kcnj8, Me1, Pdk1, Slc35a3, and Sqrdl) that are affected by AHR-status in four of five tissues. One gene, Creg1, was significantly up-regulated in all AHR-less-active animals. We also find greater overlap between tissues at the pathway level than at the gene level, suggesting coherency to the AHR signalling response within these processes. Analysis of regulatory motifs suggests that the AHR mostly mediates transcriptional regulation via direct binding to response elements. Conclusions These findings, though preliminary, present a platform for further evaluating the role of the AHR in regulation of constitutive mRNA levels and physiologic function. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-1053) contains supplementary material, which is available to authorized users.

Published
2014

38. Abstract 3767: Highly effective inhibitory agent identified by high-throughput screening of genetically characterized anaplastic thyroid cancer cell lines

Author

Kara M. Ruicci, Alessandro Datti, Kevin Fung, Anthony C. Nichols, Morgan Black, Paul C. Boutros, Danielle MacNeil, Nicole Pinto, John W. Barrett, John Yoo, and Stephenie D. Prokopec

Subjects
Cancer Research, Pathology, medicine.medical_specialty, Oncology, Cell culture, High-throughput screening, medicine, Cancer research, Anaplastic thyroid cancer, Biology, medicine.disease, Inhibitory postsynaptic potential
Abstract

Introduction While most types of thyroid cancer are treatable, anaplastic thyroid cancer (ATC) is the most lethal human malignancy. Current treatment strategies are largely ineffective with only 10% of patients surviving longer than one year. As such, new treatments are desperately needed to improve patient survival in this aggressive cancer. Objective Identify highly effective drugs using high-throughput screening methods with a large panel of kinase inhibitors that can be used in the treatment of ATC. Methods High-throughput screening (HTS) of 13 genetically characterized ATC cell lines was carried out over a 6-dose range using 320 kinase inhibitors. Dose-response curves were generated and drugs with high potency were identified. Drugs with the highest activity were selected for further evaluation including investigating mechanism of action and cell death, and assays for migration and invasion. Results Based on HTS studies, Lestaurtinib was identified as a highly effective agent with submicromolar mean inhibitory concentrations in all 13 ATC cell lines. Lestaurtinib was found to inhibit STAT5 phosphorylation, as well as cell line migration and invasion. The anti-proliferative effect of Lestaurtinib did not cause apoptosis, autophagy or cell senescence. Conclusions With the use of HTS, we have identified many (>20) kinase inhibitors as highly effective agents in the control of ATC. The kinase inhibitor Lestaurtinib was effective at controlling ATC cell proliferation, invasion and migration. Future in vivo analysis of Lestaurtinib with patient-derived xenografts are planned to continue preclinical development of this drug with the ultimate goal of improving outcomes for patients suffering with ATC. Citation Format: Nicole C. Pinto, Morgan Black, Kara Ruicci, John Yoo, Danielle MacNeil, Kevin Fung, Alessandro Datti, Stephenie Prokopec, Paul Boutros, John Barrett, Anthony Nichols. Highly effective inhibitory agent identified by high-throughput screening of genetically characterized anaplastic thyroid cancer cell lines. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3767.

Published
2016
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39. FRI0307 Changes in Urinary Biomarker Levels Can Predict Treatment Responses in Lupus Nephritis

Author

Carmen Avila-Casado, Zahi Touma, Joan E. Wither, Paul R. Fortin, Heather N. Reich, Dennisse Bonilla, Babak Noamani, James W. Scholey, Stephenie D. Prokopec, Paul C. Boutros, and Carolina Landolt-Marticorena

Subjects
Kidney, medicine.medical_specialty, biology, Clusterin, Adiponectin, business.industry, Urinary system, Immunology, Lupus nephritis, medicine.disease, Gastroenterology, General Biochemistry, Genetics and Molecular Biology, medicine.anatomical_structure, Rheumatology, Cystatin C, Internal medicine, biology.protein, Immunology and Allergy, Medicine, Biomarker (medicine), business, After treatment
Abstract

Background The relapsing and remitting nature of lupus nephritis (LN) poses a challenge to clinicians who must balance the risk of long term kidney damage with the side effects of treatment. Management of this condition would be greatly aided by the identification of biomarkers that accurately reflect and predict treatment responses. We previously identified and validated a panel of urinary biomarkers that are specifically elevated in SLE patients with active LN as compared to active patients without LN or LN patients in remission. Objectives To determine whether changes in the levels of these urinary biomarkers predict treatment responses. Methods 21 SLE patients with biopsy-proven LN were followed longitudinally for a minimum of 2 years after treatment. Levels of 15 urinary biomarkers including Clusterin, Cystatin C, NGAL, PF4, vWF,sVCAM-1, GM-CSF, GRO, IL-15, IL-6, MCP-1, Adiponectin, PAI-1, MMP-7, and TIMP-1, were measured by Luminex. Patients were classified as having a complete response (n=12), partial response (n=4), or treatment (Tx) failure (n=5) at 2 years following initiation of treatment, based upon previously established criteria. Urinary biomarker levels were considered abnormal if they were >2 SD above the mean for 24 healthy controls. Data were analyzed using non-parametric statistics. Results At 3–6 months following treatment, the changes in biomarker levels from the first visit were not significantly different between complete responders and partial responders or Tx failures. However, at 1 year (11–16 months) following treatment, 5 urinary biomarkers, sVCAM-1, Adiponectin, IL-15, vWF, and MCP-1, demonstrated significantly different changes from baseline in complete responders as compared to Tx failures, with the majority of responders demonstrating improvement and the majority of Tx failures demonstrating worsening. As urinary biomarker levels not corrected for urinary osmolality correlated best with clinical outcomes, subsequent analyses were done with the uncorrected values. Normalization of urinary Adiponectin by 11–16 months was the best predictor of a complete response, with 11 of 12 patients who normalized being complete responders and 1 a partial responder. Similar but slightly less discriminative results were obtained for the other 4 urinary biomarkers. Conversely, the presence of an abnormal urinary vWF at 11–16 months was the strongest predictor of an adverse outcome with 4 of 6 patients with abnormal levels being Tx failures. Notably, all patients that were Tx failures that had normal levels of urinary biomarkers at 11–16 months subsequently developed abnormal levels, whereas patients who were complete responders eventually normalized the majority of these 5 biomarkers. Partial responders demonstrated normalization with delayed kinetics. Conclusions Measurement of urinary biomarkers can provide valuable insight into treatment responses in lupus nephritis. Disclosure of Interest None declared

Published
2016
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40. Systematic evaluation of medium-throughput mRNA abundance platforms

Author

Allan B. Okey, Alexander H. Wu, Daryl Waggott, John D. Watson, Stephenie D. Prokopec, Ashley B. Smith, Raimo Pohjanvirta, and Paul C. Boutros

Subjects
Male, Polychlorinated Dibenzodioxins, Sample (statistics), Biology, Signal-To-Noise Ratio, Bioinformatics, computer.software_genre, Real-Time Polymerase Chain Reaction, Article, 03 medical and health sciences, 0302 clinical medicine, Signal-to-noise ratio, Abundance (ecology), Animals, Rats, Long-Evans, Sensitivity (control systems), RNA, Messenger, Rats, Wistar, Molecular Biology, Throughput (business), 030304 developmental biology, Oligonucleotide Array Sequence Analysis, Profiling (computer programming), 0303 health sciences, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Reproducibility of Results, Rats, Data set, ComputingMethodologies_PATTERNRECOGNITION, 030220 oncology & carcinogenesis, Data mining, DNA microarray, computer
Abstract

Profiling of mRNA abundances with high-throughput platforms such as microarrays and RNA-seq has become an important tool in both basic and biomedical research. However, these platforms remain prone to systematic errors and have challenges in clinical and industrial applications. As a result, it is standard practice to validate a subset of key results using alternate technologies. Similarly, clinical and industrial applications typically involve transitions from a high-throughput discovery platform to medium-throughput validation ones. These medium-throughput validation platforms have high technical reproducibility and reduced sample input needs, and low sensitivity to sample quality (e.g., for processing FFPE specimens). Unfortunately, while medium-throughput platforms have proliferated, there are no comprehensive comparisons of them. Here we fill that gap by comparing two key medium-throughput platforms—NanoString's nCounter Analysis System and ABI's OpenArray System—to gold-standard quantitative real-time RT-PCR. We quantified 38 genes and positive and negative controls in 165 samples. Signal:noise ratios, correlations, dynamic range, and detection accuracy were compared across platforms. All three measurement technologies showed good concordance, but with divergent price/time/sensitivity trade-offs. This study provides the first detailed comparison of medium-throughput RNA quantification platforms and provides a template and a standard data set for the evaluation of additional technologies.

Published
2012

41. Hepatic transcriptomic responses to TCDD in dioxin-sensitive and dioxin-resistant rats during the onset of toxicity

Author

Raimo Pohjanvirta, Cindy Q. Yao, Paul C. Boutros, Ivy D. Moffat, John D. Watson, Ashley B. Smith, Stephenie D. Prokopec, Alexander H. Wu, and Allan B. Okey

Subjects
Male, Polychlorinated Dibenzodioxins, Microarray, CYP1B1, Toxicology, Dioxins, Transcriptome, 03 medical and health sciences, Transactivation, 0302 clinical medicine, Species Specificity, Animals, Rats, Long-Evans, Rats, Wistar, Receptor, 030304 developmental biology, Pharmacology, 0303 health sciences, biology, Dose-Response Relationship, Drug, Gene Expression Profiling, CYP1A2, Aryl hydrocarbon receptor, Molecular biology, Drug Resistance, Multiple, Rats, Liver, Toxicity, biology.protein, Environmental Pollutants, 030217 neurology & neurosurgery
Abstract

The dioxin congener 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) causes a wide range of toxic effects in rodent species, all of which are mediated by a ligand-dependent transcription-factor, the aryl hydrocarbon receptor (AHR). The Han/Wistar (Kuopio) (H/W) strain shows exceptional resistance to many TCDD-induced toxicities; the LD{sub 50} of > 9600 {mu}g/kg for H/W rats is higher than for any other wild-type mammal known. We previously showed that this resistance primarily results from H/W rats expressing a variant AHR isoform that has a substantial portion of the AHR transactivation domain deleted. Despite this large deletion, H/W rats are not entirely refractory to the effects of TCDD; the variant AHR in these animals remains fully competent to up-regulate well-known dioxin-inducible genes. TCDD-sensitive (Long-Evans, L-E) and resistant (H/W) rats were treated with either corn-oil (with or without feed-restriction) or 100 {mu}g/kg TCDD for either four or ten days. Hepatic transcriptional profiling was done using microarrays, and was validated by RT-PCR analysis of 41 genes. A core set of genes was altered in both strains at all time points tested, including CYP1A1, CYP1A2, CYP1B1, Nqo1, Aldh3a1, Tiparp, Exoc3, and Inmt. Outside this core, the strains differed significantly in the breadth of response: three-fold more genes were alteredmore » in L-E than H/W rats. At ten days almost all expressed genes were dysregulated in L-E rats, likely reflecting emerging toxic responses. Far fewer genes were affected by feed-restriction, suggesting that only a minority of the TCDD-induced changes are secondary to the wasting syndrome.« less

Published
2010

42. Abstract 2966: The mutational landscape of localized gleason 6 and 7 prostate cancer

Author

Alice Meng, Xuemei Luo, Robert G. Bristow, Dominique Trudel, Lee Timms, Yves Fradet, Colin Collins, Shaylan K. Govind, Clement Fung, Francis Nguyen, Paul C. Boutros, Hélène Hovington, Alejandro Berlin, Junyan Zhang, Stephenie D. Prokopec, Michael Fraser, Haiying Kong, Louis Lacombe, Ada Wong, Vincent Huang, Julie Livingstone, Christopher I Cooper, Andre P. Masella, Michelle Sam, Taryne Chong, Veronica Y. Sabelnykova, Kathleen E. Houlahan, John Douglas Mcpherson, Nicholas J. Harding, Takafumi N. Yamaguchi, Michèle Orain, Lawrence E. Heisler, Nicholas Buchner, Jeremy Johns, Natalie S. Fox, Alister D'Costa, Fouad Yousif, Xihui Lin, Richard de Borja, Bryan Lo, Christine P'ng, Kenneth C. Chu, Emilie Lalonde, Theodorus H. van der Kwast, Timothy E. Beck, Thomas J. Hudson, Michael Xie, Robert E. Denroche, Bernard Têtu, and Valérie Picard

Subjects
Oncology, Genetics, Cancer Research, medicine.medical_specialty, Chromothripsis, business.industry, medicine.disease, Prostate cancer, Prostate tumours, medicine.anatomical_structure, Prostate, Kataegis, Localized disease, Internal medicine, medicine, business
Abstract

Prostate cancer (CaP) remains the most common male malignancy worldwide, leading to over 300,000 deaths per year. In Western countries, most prostate tumours are diagnosed while they are confined to the prostate and have relatively indolent histology, as assessed by the Gleason Score (GS). CaP is a C-class tumour, characterized by large number of driver copy-number aberrations and genomic rearrangements. Therefore, while previous sequencing studies have focused largely on the coding regions of late-stage disease, herein we comprehensively characterized the copy-number profiles of 250 localized prostate cancers and analyzed the whole genomes of 124 matched tumour/normal pairs derived from patients with GS6 and GS7 prostate cancer. Using this – the largest whole-genome sequencing dataset of prostate cancer to date – we confirm the C-class character of the disease and identify strong genomic subtypes that stretch across multiple types of somatic alteration, including SNVs, CNAs and genomic rearrangements. We provide the first assessments of localized hyper-mutation phenomena (chromothripsis and kataegis) in prostate cancer, and identify specific genes driving higher levels of these hyper-mutations. We identify unexpected biases in the location and role of both non-coding SNVs and genomic rearrangements, including clear association with epigenetic processes, and with genome-wide profiling of methylation in 92 samples. Finally, we demonstrate a stark paucity of clinically-actionable mutations in localized GS6 and GS7 disease, even lacking those common in high-risk localized disease, indicating that novel therapeutic development against the recurrent targets identified here will be key to allowing less-aggressive, targeted treatment of early-stage disease. Citation Format: Michael E. Fraser, Veronica Y. Sabelnykova, Takafumi N. Yamaguchi, Alice Meng, Lawrence E. Heisler, Junyan Zhang, Julie Livingstone, Vincent Huang, Andre P. Masella, Fouad Yousif, Michael Xie, Nicholas J. Harding, Xihui Lin, Haiying Kong, Stephenie D. Prokopec, Alejandro Berlin, Dominique Trudel, Xuemei Luo, Timothy E. Beck, Richard de Borja, Alister D'Costa, Robert E. Denroche, Natalie S. Fox, Emilie Lalonde, Ada Wong, Taryne Chong, Michelle Sam, Jeremy Johns, Lee Timms, Nicholas Buchner, Michele Orain, Valerie Picard, Helene Hovington, Kenneth C. Chu, Christine P'ng, Bryan Lo, Francis Nguyen, Kathleen E. Houlahan, Christopher Cooper, Shaylan K. Govind, Clement Fung, Louis Lacombe, Colin C. Collins, Yves Fradet, Bernard Tetu, Theodorus van der Kwast, John McPherson, Thomas J. Hudson, Rob G. Bristow, Paul Boutros. The mutational landscape of localized gleason 6 and 7 prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2966. doi:10.1158/1538-7445.AM2015-2966

Published
2015
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43. OP0091 A Low Density Granulocyte Gene Expression Signature Distinguishes Between Active Patients with and Without Nephritis in Systemic Lupus Erythematosus (SLE)

Author

Zahi Touma, Dennisse Bonilla, Stephenie D. Prokopec, Carolina Landolt-Marticorena, Heather N. Reich, Paul C. Boutros, Babak Noamani, James W. Scholey, Joan E. Wither, and Paul R. Fortin

Subjects
education.field_of_study, Systemic lupus erythematosus, medicine.diagnostic_test, business.industry, Immunology, Population, Lupus nephritis, Disease, medicine.disease, General Biochemistry, Genetics and Molecular Biology, Rheumatology, Gene expression, Cohort, Biopsy, medicine, Immunology and Allergy, business, education, Nephritis
Abstract

Background Nephritis is a major cause of morbidity and mortality in SLE. One of impediments to optimal management of this condition is a lack of biomarkers that forecast development of renal disease or that can be used to determine the response to therapy. Objectives In this study we used gene expression microarrays to contrast the gene expression profile in active lupus patients with and without nephritis to identify potential biomarkers and immune mechanisms associated with nephritis. Methods Affymetrix Human Gene 2.0ST arrays were used to assay gene expression in total RNA isolated from blood archived in PAXgene tubes for 38 active SLE patients with ≥4 ACR SLE classification criteria (25 biopsy proven nephritis, 13 active without nephritis) and 17 healthy controls. Data were analyzed with linear modeling, with corrections for multiple testing. Results were validated in a largely independent cohort of 22 healthy controls and 170 SLE patients (129 active (89 with and 40 without nephritis), 41 nephritis in remission), using Nanostring technology. Results Comparison of gene expression between healthy controls and all SLE patients revealed 27 genes that were increased >1 log 2 fold-change in SLE, the majority of which (25) were IFN-induced. When active SLE patients with and without nephritis were compared, there were 25 probes that demonstrated a >1 log 2 fold-change with a false discovery rate of q Conclusions Patients with lupus nephritis have higher levels of LDG gene expression than those without nephritis. Given the high rate of spontaneous NETosis in this cell population, the findings are consistent with the concept that high levels of NETosing neutrophils promote renal disease in SLE. Disclosure of Interest J. Wither Grant/research support from: CIHR and Eli Lilly and Company, S. Prokopec: None declared, B. Noamani: None declared, D. Bonilla: None declared, Z. Touma: None declared, H. Reich: None declared, J. Scholey: None declared, P. Fortin Grant/research support from: CIHR and Eli Lilly and Company, P. Boutros: None declared, C. Landolt-Marticorena: None declared

Published
2015
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44. Transcriptional profiling of rat white adipose tissue response to 2,3,7,8-tetrachlorodibenzo-ρ-dioxin

Author

Allan B. Okey, Jere Lindén, Paul C. Boutros, Ivy D. Moffat, Raimo Pohjanvirta, Kathleen E. Houlahan, Sanna Lensu, Stephenie D. Prokopec, Ren X. Sun, Departments of Faculty of Veterinary Medicine, Veterinary Biosciences, Veterinary Pathology and Parasitology, Food Hygiene and Environmental Health, and Raimo Pohjanvirta / Principal Investigator

Subjects
Male, TCDD, Polychlorinated Dibenzodioxins, Time Factors, Transcription, Genetic, Polychlorinated dibenzodioxins, AHR, AH GENE BATTERY, Adipose tissue, White adipose tissue, RESISTANT, 413 Veterinary science, Toxicology, feed restriction, Transcriptome, chemistry.chemical_compound, Gene Regulatory Networks, heterocyclic compounds, reproductive and urinary physiology, ta317, biology, 3. Good health, PROBE LEVEL, LUNG-CANCER CELLS, Toxicity, Environmental Pollutants, MESSENGER-RNA, ARYL-HYDROCARBON RECEPTOR, STRAIN, medicine.medical_specialty, Adipose Tissue, White, WEIGHT-LOSS, ta3111, Immune system, Species Specificity, transcriptomic profiling, white adipose tissue, Internal medicine, medicine, Animals, Humans, Rats, Long-Evans, Rats, Wistar, Caloric Restriction, Pharmacology, Gene Expression Profiling, ta1184, Lipid metabolism, Aryl hydrocarbon receptor, stomatognathic diseases, Endocrinology, Gene Expression Regulation, chemistry, DIOXIN-TREATED RATS, biology.protein
Abstract

Polychlorinated dibenzodioxins are environmental contaminants commonly produced as a by-product of industrial processes. The most potent of these, 2,3,7,8-tetrachlorodibenzo-rho-dioxin (TCDD), is highly lipophilic, leading to bioaccumulation. White adipose tissue (WAT) is a major site for energy storage, and is one of the organs in which TCDD accumulates. In laboratory animals, exposure to TCDD causes numerous metabolic abnormalities, including a wasting syndrome. We therefore investigated the molecular effects of TCDD exposure on WAT by profiling the transcriptomic response of WAT to 100 mu g/kg of TCDD at 1 or 4 days in TCDD-sensitive Long-Evans (Turku/AB; L-E) rats. A comparative analysis was conducted simultaneously in identically treated TCDD-resistant Han/Wistar (Kuopio; H/W) rats one day after exposure to the same dose. We sought to identify transcriptomic changes coinciding with the onset of toxicity, while gaining additional insight into later responses. More transcriptional responses to TCDD were observed at 4 days than at I day post-exposure, suggesting WAT shows mostly secondary responses. Two classic AHR-regulated genes, Cyp1a1 and Nqo1, were significantly induced by TCDD in both strains, while several genes involved in the immune response, including Ms4a7 and Fl1a1 were altered in L-E rats alone. We compared genes affected by TCDD in rat WAT and human adipose cells, and observed little overlap. Interestingly, very few genes involved in lipid metabolism exhibited altered expression levels despite the pronounced lipid mobilization from peripheral fat pads by TCDD in L-E rats. Of these genes, the lipolysis-associated Lpin1 was induced slightly over 2-fold in L-E rat WAT on day 4. (C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license.

Published
2015

45. Identification of Reference Proteins for Western Blot Analyses in Mouse Model Systems of 2,3,7,8-Tetrachlorodibenzo-P-Dioxin (TCDD) Toxicity

Author

Stephenie D. Prokopec, John D. Watson, Paul C. Boutros, Raimo Pohjanvirta, Departments of Faculty of Veterinary Medicine, Food Hygiene and Environmental Health, and Guo, Xuejiang

Subjects
Proteomics, Polychlorinated Dibenzodioxins, Proteome, Messenger, lcsh:Medicine, Toxicology, 413 Veterinary science, Biochemistry, RAT STRAIN, Mice, PCR DATA, Gene expression, MESSENGER-RNA EXPRESSION, lcsh:Science, TRANSCRIPTOMIC RESPONSES, GENE-EXPRESSION, Genetics, Multidisciplinary, medicine.diagnostic_test, Blotting, Reference Standards, Housekeeping gene, Blot, Liver, Western, Research Article, ARYL-HYDROCARBON RECEPTOR, POLYMERASE-CHAIN-REACTION, General Science & Technology, Blotting, Western, education, Biology, DIFFERENTIAL EXPRESSION, REVERSE TRANSCRIPTION, Western blot, medicine, Animals, RNA, Messenger, Messenger RNA, HOUSEKEEPING GENES, lcsh:R, Biology and Life Sciences, Computational Biology, Molecular biology, Membrane protein, Agent Orange & Dioxin, RNA, lcsh:Q, Protein Abundance
Abstract

Western blotting is a well-established, inexpensive and accurate way of measuring protein content. Because of technical variation between wells, normalization is required for valid interpretation of results across multiple samples. Typically this involves the use of one or more endogenous controls to adjust the measured levels of experimental molecules. Although some endogenous controls are widely used, validation is required for each experimental system. This is critical when studying transcriptional-modulators, such as toxicants like 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD).To address this issue, we examined hepatic tissue from 192 mice representing 47 unique combinations of strain, sex, Ahr-genotype, TCDD dose and treatment time. We examined 7 candidate reference proteins in each animal and assessed consistency of protein abundance through: 1) TCDD-induced fold-difference in protein content from basal levels, 2) inter- and intra- animal stability, and 3) the ability of each candidate to reduce instability of the other candidates. Univariate analyses identified HPRT as the most stable protein. Multivariate analysis indicated that stability generally increased with the number of proteins used, but gains from using >3 proteins were small. Lastly, by comparing these new data to our previous studies of mRNA controls on the same animals, we were able to show that the ideal mRNA and protein control-genes are distinct, and use of only 2-3 proteins provides strong stability, unlike in mRNA studies in the same cohort, where larger control-gene batteries were needed.

Published
2014
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46. TCDD dysregulation of 13 AHR-target genes in rat liver

Author

Ashley B. Smith, Paul C. Boutros, John D. Watson, Raimo Pohjanvirta, Allan B. Okey, Stephenie D. Prokopec, Departments of Faculty of Veterinary Medicine, and Food Hygiene and Environmental Health

Subjects
Male, Polychlorinated Dibenzodioxins, Toxicology, 413 Veterinary science, mRNA abundance, chemistry.chemical_compound, TCDD-induced toxicity, POLYCHLORINATED-BIPHENYLS, NAD(P)H Dehydrogenase (Quinone), heterocyclic compounds, MESSENGER-RNA EXPRESSION, Receptor, TRANSCRIPTOMIC RESPONSES, Aryl hydrocarbon receptor, Time course, biology, Chemistry, LIPID-PEROXIDATION, 3. Good health, Dose-response, Liver, 317 Pharmacy, Cytochrome P-450 CYP1B1, Toxicity, Aryl Hydrocarbon Hydroxylases, 2,3,7,8-TETRACHLORODIBENZO-P-DIOXIN TCDD, HUMAN CYTOCHROME-P450 1B1, ARYL-HYDROCARBON RECEPTOR, medicine.medical_specialty, NF-E2-Related Factor 2, CYP1B1, education, Xenobiotics, WASTING SYNDROME, Cytochrome P-450 CYP1A2, Internal medicine, medicine, Animals, Rats, Long-Evans, RNA, Messenger, Rats, Wistar, 2,3,7,8-Tetrachlorodibenzo-p-dioxin, Cytochrome P450 Family 2, Pharmacology, Dose-Response Relationship, Drug, DIBENZO-P-DIOXINS, CYP1A2, NFE2L2, Rats, stomatognathic diseases, Endocrinology, Gene Expression Regulation, Receptors, Aryl Hydrocarbon, SUBCHRONIC EXPOSURE, CYP2S1, Steroid Hydroxylases, biology.protein, Cytochromes, Dose–response, Xenobiotic
Abstract

Despite several decades of research, the complete mechanism by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other xenobiotic agonists of the aryl hydrocarbon receptor (AHR) cause toxicity remains unclear. While it has been shown that the AHR is required for all major manifestations of toxicity, the specific downstream changes involved in the development of toxic phenotypes remain unknown. Here we examine a panel of 13 genes that are AHR-regulated in many species and tissues. We profiled their hepatic mRNA abundances in two rat strains with very different sensitivities to TCDD: the TCDD-sensitive Long–Evans (Turku/AB; L–E) and the TCDD-resistant Han/Wistar (Kuopio; H/W). We evaluated doses ranging from 0 to 3000 μg/kg at 19 h after TCDD exposure and time points ranging from 1.5 to 384 h after exposure to 100 μg/kg TCDD. Twelve of 13 genes responded to TCDD in at least one strain, and seven of these showed statistically significant inter-strain differences in the time course analysis (Aldh3a1, Cyp1a2, Cyp1b1, Cyp2a1, Fmo1, Nfe2l2 and Nqo1). Cyp2s1 did not respond to TCDD in either rat strain. Five genes exhibited biphasic responses to TCDD insult (Ahrr, Aldh3a1, Cyp1b1, Nfe2l2 and Nqo1), suggesting a secondary event, such as association with additional transcriptional modulators. Of the 12more » genes that responded to TCDD during the dose–response analysis, none had an ED{sub 50} equivalent to that of Cyp1a1, the most sensitive gene in this study, while nine genes responded to doses at least 10–100 fold higher, in at least one strain (Ahrr (L–E), Aldh3a1 (both), Cyp1a2 (both), Cyp1b1 (both), Cyp2a1 (L–E), Inmt (both), Nfe2l2 (L–E), Nqo1 (L–E) and Tiparp (both)). These data shed new light on the association of the AHR target genes with TCDD toxicity, and in particular the seven genes exhibiting strain-specific differences represent strong candidate mediators of Type-II toxicities. - Highlights: • NanoString measured hepatic mRNA molecules following TCDD treatment. • TCDD-sensitive Long–Evans and TCDD-resistant Han/Wistar rats were compared. • Time courses and dose responses were analyzed for AHR-core gene changes. • 7 genes displayed inter-strain mRNA differences at times after TCDD exposure. • 2 of the AHR-core genes had significant inter-strain differences in their TCDD ED{sub 50}.« less

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47. A discrete cluster of urinary biomarkers discriminates between active systemic lupus erythematosus patients with and without glomerulonephritis

Author

Dennisse Bonilla, James W. Scholey, Babak Noamani, Carmen Avila-Casado, Stephenie D. Prokopec, Carolina Landolt-Marticorena, Paul R. Fortin, Heather N. Reich, Paul C. Boutros, Joan E. Wither, and Stacey Morrison

Subjects
Proteomics, Male, Pathology, Kidney Disease, 030232 urology & nephrology, Lupus nephritis, Urine, Gastroenterology, chemistry.chemical_compound, Glomerulonephritis, 0302 clinical medicine, Lupus Erythematosus, Systemic, screening and diagnosis, medicine.diagnostic_test, Urinary biomarkers, Middle Aged, Lupus Nephritis, 3. Good health, Detection, Area Under Curve, Public Health and Health Services, Female, Renal biopsy, Research Article, Adult, medicine.medical_specialty, Adolescent, Urinary system, Clinical Sciences, Immunology, Renal and urogenital, Lupus, Autoimmune Disease, Young Adult, 03 medical and health sciences, Systemic lupus erythematosus, Clinical Research, Internal medicine, medicine, Humans, Aged, 030203 arthritis & rheumatology, Creatinine, Lupus Erythematosus, Adiponectin, business.industry, Prevention, Systemic, medicine.disease, Rheumatology, 4.1 Discovery and preclinical testing of markers and technologies, Arthritis & Rheumatology, ROC Curve, chemistry, business, Biomarkers
Abstract

Background Management of lupus nephritis (LN) would be greatly aided by the discovery of biomarkers that accurately reflect changes in disease activity. Here, we used a proteomics approach to identify potential urinary biomarkers associated with LN. Methods Urine was obtained from 60 LN patients with paired renal biopsies, 25 active non-LN SLE patients, and 24 healthy controls. Using Luminex, 128 analytes were quantified and normalized to urinary creatinine levels. Data were analyzed by linear modeling and non-parametric statistics, with corrections for multiple comparisons. A second cohort of 33 active LN, 16 active non-LN, and 30 remission LN SLE patients was used to validate the results. Results Forty-four analytes were identified that were significantly increased in active LN as compared to active non-LN. This included a number of unique proteins (e.g., TIMP-1, PAI-1, PF4, vWF, and IL-15) as well as known candidate LN biomarkers (e.g., adiponectin, sVCAM-1, and IL-6), that differed markedly (>4-fold) between active LN and non-LN, all of which were confirmed in the validation cohort and normalized in remission LN patients. These proteins demonstrated an enhanced ability to discriminate between active LN and non-LN patients over several previously reported biomarkers. Ten proteins were found to significantly correlate with the activity score on renal biopsy, eight of which strongly discriminated between active proliferative and non-proliferative/chronic renal lesions. Conclusions A number of promising urinary biomarkers that correlate with the presence of active renal disease and/or renal biopsy changes were identified and appear to outperform many of the existing proposed biomarkers. Electronic supplementary material The online version of this article (doi:10.1186/s13075-016-1120-0) contains supplementary material, which is available to authorized users.

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48. Flavopiridol causes cell cycle inhibition and demonstrates anti-cancer activity in anaplastic thyroid cancer models.

Author

Nicole Pinto, Stephenie D Prokopec, Farhad Ghasemi, Jalna Meens, Kara M Ruicci, Imran M Khan, Neil Mundi, Krupal Patel, Myung W Han, John Yoo, Kevin Fung, Danielle MacNeil, Joe S Mymryk, Alessandro Datti, John W Barrett, Paul C Boutros, Laurie Ailles, and Anthony C Nichols

Subjects
Medicine, Science
Abstract

Anaplastic thyroid cancer (ATC) is a rare, but nearly uniformly fatal disease that is typically resistant to chemotherapy and radiation. Alternative strategies to target this cancer at a molecular level are necessary in order to improve dismal outcomes for ATC patients. We examined the effects of flavopiridol, a CDK inhibitor, in a panel of ATC cell lines. When cell lines were treated over a ten-point concentration range, CAL62, KMH2 and BHT-101 cell lines had a sub micromolar half-maximal inhibitory concentration, while no effect was seen in the non-cancerous cell line IMR-90. Flavopiridol treatment resulted in decreased levels of the cell cycle proteins CDK9 and MCL1, and induced cell cycle arrest. Flavopiridol also decreased the in vitro ability of ATC cells to form colonies and impeded migration using a transwell migration assay. In vivo, flavopiridol decreased tumor weight and tumor volume over time in a patient-derived xenograft model of ATC. Given the observed in vitro and in vivo activity, flavopiridol warrants further investigation for treatment of ATC.

Published
2020
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49. 2,3,7,8-Tetrachlorodibenzo-p-dioxin modifies alternative splicing in mouse liver.

Author

Ana B Villaseñor-Altamirano, John D Watson, Stephenie D Prokopec, Cindy Q Yao, Paul C Boutros, Raimo Pohjanvirta, Jesús Valdés-Flores, and Guillermo Elizondo

Subjects
Medicine, Science
Abstract

Alternative splicing is a co-transcriptional mechanism that generates protein diversity by including or excluding exons in different combinations, thereby expanding the diversity of protein isoforms of a single gene. Abnormalities in this process can result in deleterious effects to human health, and several xenobiotics are known to interfere with splicing regulation through multiple mechanisms. These changes could lead to human diseases such as cancer, neurological disorders, autoimmune diseases, and developmental disorders. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is an environmental contaminant generated as a byproduct of various industrial activities. Exposure to this dioxin has been linked to a wide range of pathologies through the alteration of multiple cellular processes. However, the effects of TCDD exposure on alternative splicing have not yet been studied. Here, we investigated whether a single po. dose of 5 μg/kg or 500 μg/kg TCDD influence hepatic alternative splicing in adult male C57BL/6Kou mouse. We identified several genes whose alternative splicing of precursor messenger RNAs was modified following TCDD exposure. In particular, we demonstrated that alternative splicing of Cyp1a1, Ahrr, and Actn1 was significantly altered after TCDD treatment. These findings show that the exposure to TCDD has an impact on alternative-splicing, and suggest a new avenue for understanding TCDD-mediated toxicity and pathogenesis.

Published
2019
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50. Identification of a neutrophil-related gene expression signature that is enriched in adult systemic lupus erythematosus patients with active nephritis: Clinical/pathologic associations and etiologic mechanisms.

Author

Joan E Wither, Stephenie D Prokopec, Babak Noamani, Nan-Hua Chang, Dennisse Bonilla, Zahi Touma, Carmen Avila-Casado, Heather N Reich, James Scholey, Paul R Fortin, Paul C Boutros, and Carolina Landolt-Marticorena

Subjects
Medicine, Science
Abstract

Both a lack of biomarkers and relatively ineffective treatments constitute impediments to management of lupus nephritis (LN). Here we used gene expression microarrays to contrast the transcriptomic profiles of active SLE patients with and without LN to identify potential biomarkers for this condition. RNA isolated from whole peripheral blood of active SLE patients was used for transcriptomic profiling and the data analyzed by linear modeling, with corrections for multiple testing. Results were validated in a second cohort of SLE patients, using NanoString technology. The majority of genes demonstrating altered transcript abundance between patients with and without LN were neutrophil-related. Findings in the validation cohort confirmed this observation and showed that levels of RNA abundance in renal remission were similar to active patients without LN. In secondary analyses, RNA abundance correlated with disease activity, hematuria and proteinuria, but not renal biopsy changes. As abundance levels of the individual transcripts correlated strongly with each other, a composite neutrophil score was generated by summing all levels before examining additional correlations. There was a modest correlation between the neutrophil score and the blood neutrophil count, which was largely driven by the dose of glucocorticosteroids and not the proportion of low density and/or activated neutrophils. Analysis of longitudinal data revealed no correlation between baseline neutrophil score or changes over the first year of follow-up with subsequent renal flare or treatment outcomes, respectively. The findings argue that although the neutrophil score is associated with LN, its clinical utility as a biomarker may be limited.

Published
2018
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