Search

Your search keyword '"Zheng, Jiamao"' showing total 30 results
Start Over Author "Zheng, Jiamao"
30 results on '"Zheng, Jiamao"'

6. Abstract 215: Developing an integrated prognostic score using germline risk variants and RNA expression from primary breast cancers for prognostication of survival across subtypes

Author

Rajagopal, Padma Sheila, primary, Liang, Yanyu, additional, Barbeira, Alvaro, additional, Melia, Owen, additional, Zheng, Jiamao, additional, Zheng, Yonglan, additional, Yoshimatsu, Toshio, additional, Huo, Dezheng, additional, Gao, Guimin, additional, Olopade, Olufunmilayo F., additional, and Im, Hae K., additional

Published
2021
Full Text
View/download PDF

11. Quantification of PRL/Stat5 signaling with a novel pGL4-CISH reporter

Author

Zheng Jiamao, Antico Giovanni, Fang Feng, and Clevenger Charles V

Subjects
Biotechnology, TP248.13-248.65
Abstract

Abstract Background Elevations of serum prolactin (PRL) are associated with an increased risk for breast cancer. PRL signaling through its prolactin receptor (PRLr) involves the Jak2/Stat5 pathway. Luciferase-based reporter assays have been widely used to evaluate the activity of this pathway. However, the existing reporters are often not sensitive enough to monitor the effect of PRL in this pathway. Results In this study, a new biologically relevant reporter, pGL4-CISH, was generated to study the PRL/Jak2/Stat5 signaling pathway. The sensitivity of pGL4-CISH to detect PRL was superior to that of several other commonly utilized Stat5-responsive reporters. Interestingly, the enhanced function pGL4-CISH was restricted to the estrogen receptor positive (ER+) human breast cancer cell lines T47D and MCF7, but not in the ER-MDA-231, BT-474, or MCF10A cell lines. Overexpression of Stat5 further enhanced the effect of PRL on pGL4-CISH. Conclusion These studies demonstrate that pGL4-CISH is a novel and sensitive reporter for assessing the activity of the PRL/Stat5 signaling pathway in the ER+ human breast cancer cells.

Published
2008
Full Text
View/download PDF

16. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Author

Barbeira, Alvaro N., Dickinson, Scott P., Torres, Jason M., Zheng, Jiamao, Torstenson, Eric S., Wheeler, Heather E., Shah, Kaanan P., Bonazzola, Rodrigo, Garcia, Tzintzuni, Edwards, Todd, Nicolae, Dan L., Cox, Nancy J., and Im, Hae Kyung

Subjects
0303 health sciences, education.field_of_study, business.industry, Computer science, Concordance, 030305 genetics & heredity, Aggregate (data warehouse), Population, Genome-wide association study, Genomics, Computational biology, Expression (mathematics), 03 medical and health sciences, Software, Component (UML), Gene expression, business, education, Gene, 030304 developmental biology
Abstract

To gain biological insight into the discoveries made by GWAS and meta-analysis studies, effective integration of functional data generated by large-scale efforts such as the GTEx Project is needed. PrediXcan is a gene-level approach that addresses this need by estimating the genetically determined component of gene expression. These predicted expression traits can then be tested for association with phenotype in order to test for mediating role of gene expression levels. Furthermore, due to the polygenic nature of many complex traits, efforts to aggregate multiple GWAS studies and conduct meta-analyses have successfully increased our ability to identify variants of small effect sizes. To take advantage of the results generated by these efforts and to avoid the problems associated with accessing and handling individual-level data (e.g. consent limitations, large computational/storage costs) we have developed an extension of PrediXcan. The new method, MetaXcan, infers the results of PrediXcan using only summary statistics from large-scale GWAS or meta-analyses. Here we show that the concordance between PrediXcan and MetaXcan is excellent when the right reference population is used (R2 > 0.95) and robust to population mismatches (R2 > 0.85). We provide open source local and web-based software for easy implementation through (https://github.com/hakyimlab/MetaXcan)

Published
2016
Full Text
View/download PDF

21. Multidisciplinary Analysis of Cyclophilin A Function in Human Breast Cancer

Author

NORTHWESTERN UNIV EVANSTON IL, Zheng, Jiamao, NORTHWESTERN UNIV EVANSTON IL, and Zheng, Jiamao

Abstract

The goal of this project was to understand how cyclophilin A (CypA) regulates the prolactin receptor (PRLr) signaling. The data have demonstrated that CypA, serving as a molecular switch via its peptidyl-prolyl isomerase (PPI) activity, binds to and regulates the function of the PRLr. Furthermore, point mutagenesis analysis has implied that a single prolyl imide bond (Pro-334) within the X-Box motif of intracellular domain of the PRLr is most likely responsible for the observed effects of CypA on the PRLr signaling. Finally, we have conducted several proof-of-concept studies that may lead to novel anti-breast cancer agents., The original document contains color images.

Published
2011

22. Multidisciplinary Analysis of Cyclophilin A Function in Human Breast Cancer

Author

NORTHWESTERN UNIV EVANSTON IL, Zheng, Jiamao, NORTHWESTERN UNIV EVANSTON IL, and Zheng, Jiamao

Abstract

The ongoing purpose of this work is to examine the effects of altered cyclophilin A (CypA) levels and activity on the prolactin receptor (PRLr) associated signaling and its role in breast cancer development and/or progression. To this end, we have further demonstrated that siRNA-mediated CypA knockdown or the use of CypA inhibitors such as cyclosphorine A (CsA) analogs-CsD and CsH significantly abrogated the PRLr signaling and breast cancer cell growth in vitro. In addition, by using a novel antibody phage display technology, we have developed several synthetic antibodies, which exhibit nanomolar affinities for the CypA. Experiments are currently underway to test these potential synthetic antibodies in vitro and in vivo., The original document contains color images.

Published
2010

23. Multidisciplinary Analysis of Cyclophilin a Function in Human Breast Cancer

Author

NORTHWESTERN UNIV CHICAGO IL, Zheng, Jiamao, NORTHWESTERN UNIV CHICAGO IL, and Zheng, Jiamao

Abstract

The major goal of the proposed project is to understand how cyclophilin A (CypA) modulates the prolactin (PRL) receptor (PRLr)-associated signaling and to determine the effects of altered CypA levels and activity on PRL signaling and breast cancer phenotype by combining biophysical structural investigations with studies in cell and animal models. The knowledge we obtained from this study will contribute to a greater understanding of the mechanism of PRL action. Our recent data suggest that CypA, serving as a molecular switch via its peptidyl-prolyl isomerase (PPI) activity, binds to and regulates the function of the PRLr through its X-box motif. From a translation perspective, we have also shown that the X-box peptide significantly blocks PRLr signaling. Given that the PRLr-triggered signals directly contribute to PRL-induced proliferation, survival, and motility of human breast cancer, the proposed study in detail on the effect of CypA on PRLr structure and function will have a significant impact on human breast cancer., The original document contains color images.

Published
2009

24. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Author

Barbeira, Alvaro N., Dickinson, Scott P., Bonazzola, Rodrigo, Zheng, Jiamao, Wheeler, Heather E., Torres, Jason M., Torstenson, Eric S., Shah, Kaanan P., Garcia, Tzintzuni, Edwards, Todd L., Stahl, Eli A., Huckins, Laura M., Aguet, François, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segrè, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frésard, Laure, Gamazon, Eric R., Garrido-Martín, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Jo, Brian, Kang, Eun Yong, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muñoz-Aguirre, Manuel, Ndungu, Anne W., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Li, Jin Billy, Li, Qin, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Zhang, Rui, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Nicolae, Dan L., Cox, Nancy J., and Im, Hae Kyung

Abstract

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.

Published
2018
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results