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1.  Comprehensive molecular characterization of gastric adenocarcinoma 
Bass, Adam J. | Thorsson, Vesteinn | Shmulevich, Ilya | Reynolds, Sheila M. | Miller, Michael | Bernard, Brady | Hinoue, Toshinori | Laird, Peter W. | Curtis, Christina | Shen, Hui | Weisenberger, Daniel J. | Schultz, Nikolaus | Shen, Ronglai | Weinhold, Nils | Kelsen, David P. | Bowlby, Reanne | Chu, Andy | Kasaian, Katayoon | Mungall, Andrew J. | Robertson, A. Gordon | Sipahimalani, Payal | Cherniack, Andrew | Getz, Gad | Liu, Yingchun | Noble, Michael S. | Pedamallu, Chandra | Sougnez, Carrie | Taylor-Weiner, Amaro | Akbani, Rehan | Lee, Ju-Seog | Liu, Wenbin | Mills, Gordon B. | Yang, Da | Zhang, Wei | Pantazi, Angeliki | Parfenov, Michael | Gulley, Margaret | Piazuelo, M. Blanca | Schneider, Barbara G. | Kim, Jihun | Boussioutas, Alex | Sheth, Margi | Demchok, John A. | Rabkin, Charles S. | Willis, Joseph E. | Ng, Sam | Garman, Katherine | Beer, David G. | Pennathur, Arjun | Raphael, Benjamin J. | Wu, Hsin-Ta | Odze, Robert | Kim, Hark K. | Bowen, Jay | Leraas, Kristen M. | Lichtenberg, Tara M. | Weaver, Stephanie | McLellan, Michael | Wiznerowicz, Maciej | Sakai, Ryo | Getz, Gad | Sougnez, Carrie | Lawrence, Michael S. | Cibulskis, Kristian | Lichtenstein, Lee | Fisher, Sheila | Gabriel, Stacey B. | Lander, Eric S. | Ding, Li | Niu, Beifang | Ally, Adrian | Balasundaram, Miruna | Birol, Inanc | Bowlby, Reanne | Brooks, Denise | Butterfield, Yaron S. N. | Carlsen, Rebecca | Chu, Andy | Chu, Justin | Chuah, Eric | Chun, Hye-Jung E. | Clarke, Amanda | Dhalla, Noreen | Guin, Ranabir | Holt, Robert A. | Jones, Steven J.M. | Kasaian, Katayoon | Lee, Darlene | Li, Haiyan A. | Lim, Emilia | Ma, Yussanne | Marra, Marco A. | Mayo, Michael | Moore, Richard A. | Mungall, Andrew J. | Mungall, Karen L. | Nip, Ka Ming | Robertson, A. Gordon | Schein, Jacqueline E. | Sipahimalani, Payal | Tam, Angela | Thiessen, Nina | Beroukhim, Rameen | Carter, Scott L. | Cherniack, Andrew D. | Cho, Juok | Cibulskis, Kristian | DiCara, Daniel | Frazer, Scott | Fisher, Sheila | Gabriel, Stacey B. | Gehlenborg, Nils | Heiman, David I. | Jung, Joonil | Kim, Jaegil | Lander, Eric S. | Lawrence, Michael S. | Lichtenstein, Lee | Lin, Pei | Meyerson, Matthew | Ojesina, Akinyemi I. | Pedamallu, Chandra Sekhar | Saksena, Gordon | Schumacher, Steven E. | Sougnez, Carrie | Stojanov, Petar | Tabak, Barbara | Taylor-Weiner, Amaro | Voet, Doug | Rosenberg, Mara | Zack, Travis I. | Zhang, Hailei | Zou, Lihua | Protopopov, Alexei | Santoso, Netty | Parfenov, Michael | Lee, Semin | Zhang, Jianhua | Mahadeshwar, Harshad S. | Tang, Jiabin | Ren, Xiaojia | Seth, Sahil | Yang, Lixing | Xu, Andrew W. | Song, Xingzhi | Pantazi, Angeliki | Xi, Ruibin | Bristow, Christopher A. | Hadjipanayis, Angela | Seidman, Jonathan | Chin, Lynda | Park, Peter J. | Kucherlapati, Raju | Akbani, Rehan | Ling, Shiyun | Liu, Wenbin | Rao, Arvind | Weinstein, John N. | Kim, Sang-Bae | Lee, Ju-Seog | Lu, Yiling | Mills, Gordon | Laird, Peter W. | Hinoue, Toshinori | Weisenberger, Daniel J. | Bootwalla, Moiz S. | Lai, Phillip H. | Shen, Hui | Triche, Timothy | Van Den Berg, David J. | Baylin, Stephen B. | Herman, James G. | Getz, Gad | Chin, Lynda | Liu, Yingchun | Murray, Bradley A. | Noble, Michael S. | Askoy, B. Arman | Ciriello, Giovanni | Dresdner, Gideon | Gao, Jianjiong | Gross, Benjamin | Jacobsen, Anders | Lee, William | Ramirez, Ricardo | Sander, Chris | Schultz, Nikolaus | Senbabaoglu, Yasin | Sinha, Rileen | Sumer, S. Onur | Sun, Yichao | Weinhold, Nils | Thorsson, Vésteinn | Bernard, Brady | Iype, Lisa | Kramer, Roger W. | Kreisberg, Richard | Miller, Michael | Reynolds, Sheila M. | Rovira, Hector | Tasman, Natalie | Shmulevich, Ilya | Ng, Santa Cruz Sam | Haussler, David | Stuart, Josh M. | Akbani, Rehan | Ling, Shiyun | Liu, Wenbin | Rao, Arvind | Weinstein, John N. | Verhaak, Roeland G.W. | Mills, Gordon B. | Leiserson, Mark D. M. | Raphael, Benjamin J. | Wu, Hsin-Ta | Taylor, Barry S. | Black, Aaron D. | Bowen, Jay | Carney, Julie Ann | Gastier-Foster, Julie M. | Helsel, Carmen | Leraas, Kristen M. | Lichtenberg, Tara M. | McAllister, Cynthia | Ramirez, Nilsa C. | Tabler, Teresa R. | Wise, Lisa | Zmuda, Erik | Penny, Robert | Crain, Daniel | Gardner, Johanna | Lau, Kevin | Curely, Erin | Mallery, David | Morris, Scott | Paulauskis, Joseph | Shelton, Troy | Shelton, Candace | Sherman, Mark | Benz, Christopher | Lee, Jae-Hyuk | Fedosenko, Konstantin | Manikhas, Georgy | Potapova, Olga | Voronina, Olga | Belyaev, Smitry | Dolzhansky, Oleg | Rathmell, W. Kimryn | Brzezinski, Jakub | Ibbs, Matthew | Korski, Konstanty | Kycler, Witold | ŁaŸniak, Radoslaw | Leporowska, Ewa | Mackiewicz, Andrzej | Murawa, Dawid | Murawa, Pawel | Spychała, Arkadiusz | Suchorska, Wiktoria M. | Tatka, Honorata | Teresiak, Marek | Wiznerowicz, Maciej | Abdel-Misih, Raafat | Bennett, Joseph | Brown, Jennifer | Iacocca, Mary | Rabeno, Brenda | Kwon, Sun-Young | Penny, Robert | Gardner, Johanna | Kemkes, Ariane | Mallery, David | Morris, Scott | Shelton, Troy | Shelton, Candace | Curley, Erin | Alexopoulou, Iakovina | Engel, Jay | Bartlett, John | Albert, Monique | Park, Do-Youn | Dhir, Rajiv | Luketich, James | Landreneau, Rodney | Janjigian, Yelena Y. | Kelsen, David P. | Cho, Eunjung | Ladanyi, Marc | Tang, Laura | McCall, Shannon J. | Park, Young S. | Cheong, Jae-Ho | Ajani, Jaffer | Camargo, M. Constanza | Alonso, Shelley | Ayala, Brenda | Jensen, Mark A. | Pihl, Todd | Raman, Rohini | Walton, Jessica | Wan, Yunhu | Demchok, John A. | Eley, Greg | Mills Shaw, Kenna R. | Sheth, Margi | Tarnuzzer, Roy | Wang, Zhining | Yang, Liming | Zenklusen, Jean Claude | Davidsen, Tanja | Hutter, Carolyn M. | Sofia, Heidi J. | Burton, Robert | Chudamani, Sudha | Liu, Jia
Nature  2014;513(7517):202-209.
Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies.
doi:10.1038/nature13480
PMCID: PMC4170219  PMID: 25079317
2.  Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers 
Nucleic Acids Research  2014;42(21):12973-12983.
Thousands of unique mutations in transcription factors (TFs) arise in cancers, and the functional and biological roles of relatively few of these have been characterized. Here, we used structure-based methods developed specifically for DNA-binding proteins to systematically predict the consequences of mutations in several TFs that are frequently mutated in cancers. The explicit consideration of protein–DNA interactions was crucial to explain the roles and prevalence of mutations in TP53 and RUNX1 in cancers, and resulted in a higher specificity of detection for known p53-regulated genes among genetic associations between TP53 genotypes and genome-wide expression in The Cancer Genome Atlas, compared to existing methods of mutation assessment. Biophysical predictions also indicated that the relative prevalence of TP53 missense mutations in cancer is proportional to their thermodynamic impacts on protein stability and DNA binding, which is consistent with the selection for the loss of p53 transcriptional function in cancers. Structure and thermodynamics-based predictions of the impacts of missense mutations that focus on specific molecular functions may be increasingly useful for the precise and large-scale inference of aberrant molecular phenotypes in cancer and other complex diseases.
doi:10.1093/nar/gku1031
PMCID: PMC4245936  PMID: 25378323
3.  The Somatic Genomic Landscape of Glioblastoma 
Cell  2013;155(2):462-477.
We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.
doi:10.1016/j.cell.2013.09.034
PMCID: PMC3910500  PMID: 24120142
4.  Increasing Coverage of Transcription Factor Position Weight Matrices through Domain-level Homology 
PLoS ONE  2012;7(8):e42779.
Transcription factor-DNA interactions, central to cellular regulation and control, are commonly described by position weight matrices (PWMs). These matrices are frequently used to predict transcription factor binding sites in regulatory regions of DNA to complement and guide further experimental investigation. The DNA sequence preferences of transcription factors, encoded in PWMs, are dictated primarily by select residues within the DNA binding domain(s) that interact directly with DNA. Therefore, the DNA binding properties of homologous transcription factors with identical DNA binding domains may be characterized by PWMs derived from different species. Accordingly, we have implemented a fully automated domain-level homology searching method for identical DNA binding sequences.
By applying the domain-level homology search to transcription factors with existing PWMs in the JASPAR and TRANSFAC databases, we were able to significantly increase coverage in terms of the total number of PWMs associated with a given species, assign PWMs to transcription factors that did not previously have any associations, and increase the number of represented species with PWMs over an order of magnitude. Additionally, using protein binding microarray (PBM) data, we have validated the domain-level method by demonstrating that transcription factor pairs with matching DNA binding domains exhibit comparable DNA binding specificity predictions to transcription factor pairs with completely identical sequences.
The increased coverage achieved herein demonstrates the potential for more thorough species-associated investigation of protein-DNA interactions using existing resources. The PWM scanning results highlight the challenging nature of transcription factors that contain multiple DNA binding domains, as well as the impact of motif discovery on the ability to predict DNA binding properties. The method is additionally suitable for identifying domain-level homology mappings to enable utilization of additional information sources in the study of transcription factors. The domain-level homology search method, resulting PWM mappings, web-based user interface, and web API are publicly available at http://dodoma.systemsbiology.netdodoma.systemsbiology.net.
doi:10.1371/journal.pone.0042779
PMCID: PMC3428306  PMID: 22952610

Results 1-4 (4)