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16 results on '"Uusküla-Reimand, Liis"'

1. X-linked myotubular myopathy is associated with epigenetic alterations and is ameliorated by HDAC inhibition

Author

Volpatti, Jonathan R., Ghahramani-Seno, Mehdi M., Mansat, Mélanie, Sabha, Nesrin, Sarikaya, Ege, Goodman, Sarah J., Chater-Diehl, Eric, Celik, Alper, Pannia, Emanuela, Froment, Carine, Combes-Soia, Lucie, Maani, Nika, Yuki, Kyoko E., Chicanne, Gaëtan, Uusküla-Reimand, Liis, Monis, Simon, Alvi, Sana Akhtar, Genetti, Casie A., Payrastre, Bernard, Beggs, Alan H., Bonnemann, Carsten G., Muntoni, Francesco, Wilson, Michael D., Weksberg, Rosanna, Viaud, Julien, and Dowling, James J.

Published
2022
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3. Author Correction: Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

Author

Rheinbay, Esther, Nielsen, Morten Muhlig, Abascal, Federico, Wala, Jeremiah A., Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M., Juul, Randi Istrup, Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzós, Andrés, Herrmann, Carl, Maruvka, Yosef E., Shen, Ciyue, Amin, Samirkumar B., Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A., Busanovich, John, Carlevaro-Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A., Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P., Haradhvala, Nicholas J., Hong, Chen, Isaev, Keren, Johnson, Todd A., Juul, Malene, Kahles, Andre, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric Minwei, Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D., Saksena, Gordon, Schumacher, Steven E., Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M. C., Umer, Husen M., Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E., Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S., von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J., Rubin, Mark A., Sander, Chris, Stein, Lincoln D., Stuart, Joshua M., Tsunoda, Tatsuhiko, Wheeler, David A., Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J., López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob Skou, and Getz, Gad

Published
2023
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5. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

Author

Rheinbay, Esther, Nielsen, Morten Muhlig, Abascal, Federico, Wala, Jeremiah A., Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M., Juul, Randi Istrup, Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzós, Andrés, Herrmann, Carl, Maruvka, Yosef E., Shen, Ciyue, Amin, Samirkumar B., Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A., Busanovich, John, Carlevaro-Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A., Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P., Haradhvala, Nicholas J., Hong, Chen, Isaev, Keren, Johnson, Todd A., Juul, Malene, Kahles, Andre, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric Minwei, Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D., Saksena, Gordon, Schumacher, Steven E., Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M. C., Umer, Husen M., Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E., Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S., von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J., Rubin, Mark A., Sander, Chris, Stein, Lincoln D., Stuart, Joshua M., Tsunoda, Tatsuhiko, Wheeler, David A., Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J., López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob Skou, and Getz, Gad

Published
2020
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7. Untangling the roles of TOP2A and TOP2B in transcription and cancer.

Author

Uusküla-Reimand, Liis and Wilson, Michael D.

Subjects
*DNA topoisomerase I, *TRANSCRIPTION factors, *DOUBLE-strand DNA breaks, *DNA ligases, *MITOCHONDRIAL DNA, *DNA topoisomerase II, *DNA repair, *DNA structure
Abstract

The article presents molecular biology research study on the roles of Type II topoisomerases (TOP2) A and B in transcription and cancer. Topics include double-strand breaks (DSBs)also contribute to the emergence of chromosomal translocations and mutations that drive cancer; and regulation of chromatin topology and transcription with discoveries linking TOP2 activities with cancer pathogenesis.

Published
2022
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8. MACE: model based analysis of ChIP-exo

Author

Wang, Liguo, Chen, Junsheng, Wang, Chen, Uusküla-Reimand, Liis, Chen, Kaifu, Medina-Rivera, Alejandra, Young, Edwin J., Zimmermann, Michael T., Yan, Huihuang, Sun, Zhifu, Zhang, Yuji, Wu, Stephen T., Huang, Haojie, Wilson, Michael D., Kocher, Jean-Pierre A., and Li, Wei

Published
2014
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9. Analyses of non-coding somatic drivers in 2,658cancer whole genomes

Author

Group, PCAWG Drivers, Functional Interpretation Working, Group, PCAWG Structural Variation Working, Consortium, PCAWG, PCAWG Consortium, Rheinbay, Esther, Nielsen, Morten M., Abascal, Federico, Wala, Jeremiah A, Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M, Juul, Randi I., Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzós, Andrés, Herrmann, Carl, Maruvka, Yosef E., Shen, Ciyue, Amin, Samirkumar B., Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A., Busanovich, John, Carlevaro-Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A., Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P., Haradhvala, Nicholas J., Hong, Chen, Isaev, Keren, Johnson, Todd A., Juul, Malene, Kahles, André, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric M., Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D., Saksena, Gordon, Schumacher, Steven E, Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M.C., Umer, Husen M., Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E., Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S., von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J., Rubin, Mark A., Sander, Chris, Stein, Lincoln D., Stuart, Joshua M., Tsunoda, Tatsuhiko, Wheeler, David A., Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J., López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob S., and Getz, Gad

Subjects
Cancer genomics, Computational biology and bioinformatics
Abstract

The discovery of drivers of cancer has traditionally focused on protein-coding genes14. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5 region of TP53, in the 3 untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that althoughpoint mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available., Nature, 578 (7793), ISSN:0028-0836, ISSN:1476-4687

Published
2020
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10. Interactome Rewiring Following Pharmacological Targeting of BET Bromodomains

Author

Lambert, Jean-Philippe, Picaud, Sarah, Fujisawa, Takao, Hou, Huayun, Savitsky, Pavel, Uusküla-Reimand, Liis, Gupta, Gagan D, Abdouni, Hala, Lin, Zhen-Yuan, Tucholska, Monika, Knight, James D R, Gonzalez-Badillo, Beatriz, St-Denis, Nicole, Newman, Joseph A, Stucki, Manuel, Pelletier, Laurence, Bandeira, Nuno, Wilson, Michael D, Filippakopoulos, Panagis, Gingras, Anne-Claude, University of Zurich, and Filippakopoulos, Panagis

Subjects
Models, Molecular, Proteomics, Protein Conformation, JQ1, 610 Medicine & health, Antineoplastic Agents, Cell Cycle Proteins, Protein Serine-Threonine Kinases, Article, 1307 Cell Biology, Structure-Activity Relationship, protein crystallography, Neoplasms, bromodomain, 1312 Molecular Biology, Humans, Protein Interaction Domains and Motifs, Molecular Targeted Therapy, Protein Interaction Maps, rRNA, nucleolus, Cell Proliferation, KacY, rewiring, Nuclear Proteins, RNA-Binding Proteins, Azepines, Triazoles, BET, 10174 Clinic for Gynecology, Gene Expression Regulation, Neoplastic, HEK293 Cells, proteomic network, AP-MS, K562 Cells, HeLa Cells, Protein Binding, Signal Transduction, Transcription Factors
Abstract

Summary Targeting bromodomains (BRDs) of the bromo-and-extra-terminal (BET) family offers opportunities for therapeutic intervention in cancer and other diseases. Here, we profile the interactomes of BRD2, BRD3, BRD4, and BRDT following treatment with the pan-BET BRD inhibitor JQ1, revealing broad rewiring of the interaction landscape, with three distinct classes of behavior for the 603 unique interactors identified. A group of proteins associate in a JQ1-sensitive manner with BET BRDs through canonical and new binding modes, while two classes of extra-terminal (ET)-domain binding motifs mediate acetylation-independent interactions. Last, we identify an unexpected increase in several interactions following JQ1 treatment that define negative functions for BRD3 in the regulation of rRNA synthesis and potentially RNAPII-dependent gene expression that result in decreased cell proliferation. Together, our data highlight the contributions of BET protein modules to their interactomes allowing for a better understanding of pharmacological rewiring in response to JQ1., Graphical Abstract, Highlights • Treatment with JQ1 induces an extensive BET proteins interactome rewiring • Structural and biophysical studies expand the target space for BET bromodomains • Two distinct short linear motifs mediate BET ET domain interactions • BRD3 negatively regulates proliferation through Pol I and II mechanisms, Lambert, Picaud, et al. report that pharmacological bromodomain inhibition rewires the interactome of the Bromo and Extra-Terminal (BET) proteins, resulting in loss (e.g., histones), maintenance, or gain of interactions. They reveal new binding modalities and an unsuspected negative role for BRD3 in proliferation.

Published
2019

12. Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks.

Author

Zhu, Helen, Uusküla-Reimand, Liis, Isaev, Keren, Wadi, Lina, Alizada, Azad, Shuai, Shimin, Huang, Vincent, Aduluso-Nwaobasi, Dike, Paczkowska, Marta, Abd-Rabbo, Diala, Ocsenas, Oliver, Liang, Minggao, Thompson, J. Drew, Li, Yao, Ruan, Luyao, Krassowski, Michal, Dzneladze, Irakli, Simpson, Jared T., Lupien, Mathieu, and Stein, Lincoln D.

Subjects
*SOMATIC mutation, *CANCER genes, *CHROMATIN, *GENETIC mutation, *GENE regulatory networks, *CELL proliferation, *GENOMES
Abstract

A comprehensive catalog of cancer driver mutations is essential for understanding tumorigenesis and developing therapies. Exome-sequencing studies have mapped many protein-coding drivers, yet few non-coding drivers are known because genome-wide discovery is challenging. We developed a driver discovery method, ActiveDriverWGS, and analyzed 120,788 cis -regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project. We found 30 CRMs with enriched SNVs and indels (FDR < 0.05). These frequently mutated regulatory elements (FMREs) were ubiquitously active in human tissues, showed long-range chromatin interactions and mRNA abundance associations with target genes, and were enriched in motif-rewiring mutations and structural variants. Genomic deletion of one FMRE in human cells caused proliferative deficiencies and transcriptional deregulation of cancer genes CCNB1IP1 , CDH1 , and CDKN2B , validating observations in FMRE-mutated tumors. Pathway analysis revealed further sub-significant FMREs at cancer genes and processes, indicating an unexplored landscape of infrequent driver mutations in the non-coding genome. • Pan-cancer driver analysis highlights frequently mutated regulatory elements (FMREs) • FMREs are active in many tissues and interact with genes via chromatin loops • FMRE deletion in human cells caused alterations in pathway activity and proliferation • Additional less-frequent regulatory mutations are enriched at cancer genes and pathways Cancer is driven by somatic mutations in critical genes, but few non-coding drivers are known. In a pan-cancer analysis, Zhu et al. identified frequently mutated, multi-tissue regulatory elements with chromatin loops to distal genes. Genomic deletion of one region caused deregulation of cancer genes, pathways, and proliferation in human cells. [ABSTRACT FROM AUTHOR]

Published
2020
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13. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

Author

Rheinbay, Esther, Nielsen, Morten Muhlig, Abascal, Federico, Wala, Jeremiah A, Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M, Juul, Randi Istrup, Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzos, Andrés, Herrmann, Carl, Maruvka, Yosef E, Shen, Ciyue, Amin, Samirkumar B, Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A, Busanovich, John, Carlevaro Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A, Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P, Haradhvala, Nicholas J, Hong, Chen, Isaev, Keren, Johnson, Todd A, Juul, Malene, Kahles, Andre, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric Minwei, Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D, Saksena, Gordon, Schumacher, Steven E, Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M C, Umer, Husen M, Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E, Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S, Von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J, Rubin, Mark Andrew, Sander, Chris, Stein, Lincoln D, Stuart, Joshua M, Tsunoda, Tatsuhiko, Wheeler, David A, Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J, López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob Skou, and Getz, Gad

Subjects
610 Medicine & health, 3. Good health
Abstract

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

14. Dual Regulatory Functions of SUFU and Targetome of GLI2 in SHH Subgroup Medulloblastoma.

Author

Yin, Wen-Chi, Satkunendran, Thevagi, Mo, Rong, Morrissy, Sorana, Zhang, Xiaoyun, Huang, Eunice Shiao, Uusküla-Reimand, Liis, Hou, Huayun, Son, Joe Eun, Liu, Weifan, Liu, Yulu C., Zhang, Jianing, Parker, Jessica, Wang, Xin, Farooq, Hamza, Selvadurai, Hayden, Chen, Xin, Sau-Wai Ngan, Elly, Cheng, Steven Y., and Dirks, Peter B.

Subjects
*MEDULLOBLASTOMA, *PUBLISHED articles
Published
2020
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15. Dual Regulatory Functions of SUFU and Targetome of GLI2 in SHH Subgroup Medulloblastoma.

Author

Yin, Wen-Chi, Satkunendran, Thevagi, Mo, Rong, Morrissy, Sorana, Zhang, Xiaoyun, Huang, Eunice Shiao, Uusküla-Reimand, Liis, Hou, Huayun, Son, Joe Eun, Liu, Weifan, Liu, Yulu C., Zhang, Jianing, Parker, Jessica, Wang, Xin, Farooq, Hamza, Selvadurai, Hayden, Chen, Xin, Sau-Wai Ngan, Elly, Cheng, Steven Y., and Dirks, Peter B.

Subjects
*MEDULLOBLASTOMA, *LABORATORY mice, *UBIQUITIN, *GENE targeting, *MOLECULAR genetics
Abstract

Summary SUFU alterations are common in human Sonic Hedgehog (SHH) subgroup medulloblastoma (MB). However, its tumorigenic mechanisms have remained elusive. Here, we report that loss of Sufu alone is unable to induce MB formation in mice, due to insufficient Gli2 activation. Simultaneous loss of Spop , an E3 ubiquitin ligase targeting Gli2, restores robust Gli2 activation and induces rapid MB formation in Sufu knockout background. We also demonstrated a tumor-promoting role of Sufu in Smo-activated MB (∼60% of human SHH MB) by maintaining robust Gli activity. Having established Gli2 activation as a key driver of SHH MB, we report a comprehensive analysis of its targetome. Furthermore, we identified Atoh1 as a target and molecular accomplice of Gli2 that activates core SHH MB signature genes in a synergistic manner. Overall, our work establishes the dual role of SUFU in SHH MB and provides mechanistic insights into transcriptional regulation underlying Gli2-mediated SHH MB tumorigenesis. Graphical Abstract Highlights • Sufu exerts tumor-promoting and -suppressive functions in SHH medulloblastoma • Sufu ; Spop double knockout medulloblastoma mouse model unveils GLI2 targetome • ATOH1 and GLI2 cooperate to activate target genes in SHH medulloblastoma Yin et al. demonstrate that SUFU exerts both tumor-promoting and -suppressive functions in the SHH subgroup of medulloblastoma. Performing transcriptomic and genomic analyses in the Sufu ; Spop double knockout medulloblastoma mouse model, the authors unveil the GLI2 targetome and identify ATOH1 as a key molecular accomplice of GLI2 in medulloblastoma. [ABSTRACT FROM AUTHOR]

Published
2019
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16. Break Check: Transcription-Driven Topoisomerase II Collisions near Chromatin Loop Anchors Are Hotspots for DNA Damage and Translocations.

Author

Uusküla-Reimand L and Wilson MD

Subjects
Chromatin, Chromosomes, DNA, DNA Damage, DNA Topoisomerases, Type II genetics, DNA-Binding Proteins genetics
Abstract

In this issue of Molecular Cell, Gothe, Maman et al. and Canela et al. demonstrate that type II topoisomerase (TOP2B/TOP2A)-mediated DNA breaks, and the oncogenic translocations they generate, are dependent on transcription and governed by chromatin architecture., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

Published
2019
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