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2. Physachenolide C induces complete regression of established murine melanoma tumors via apoptosis and cell cycle arrest

Author

Anngela C. Adams, Anne M. Macy, Paul Kang, Karla F. Castro-Ochoa, E.M. Kithsiri Wijeratne, Ya-Ming Xu, Manping X. Liu, Alexandra Charos, Marcus W. Bosenberg, A.A. Leslie Gunatilaka, Aparna R. Sertil, and K. Taraszka Hastings

Subjects
Melanoma, Mouse model, Natural products, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Melanoma is an aggressive skin cancer that metastasizes to other organs. While immune checkpoint blockade with anti-PD-1 has transformed the treatment of advanced melanoma, many melanoma patients fail to respond to anti-PD-1 therapy or develop acquired resistance. Thus, effective treatment of melanoma still represents an unmet clinical need. Our prior studies support the anti-cancer activity of the 17β-hydroxywithanolide class of natural products, including physachenolide C (PCC). As single agents, PCC and its semi-synthetic analog demonstrated direct cytotoxicity in a panel of murine melanoma cell lines, which share common driver mutations with human melanoma; the IC50 values ranged from 0.19–1.8 µM. PCC treatment induced apoptosis of tumor cells both in vitro and in vivo. In vivo treatment with PCC alone caused the complete regression of established melanoma tumors in all mice, with a durable response in 33% of mice after discontinuation of treatment. T cell-mediated immunity did not contribute to the therapeutic efficacy of PCC or prevent tumor recurrence in YUMM2.1 melanoma model. In addition to apoptosis, PCC treatment induced G0-G1 cell cycle arrest of melanoma cells, which upon removal of PCC, re-entered the cell cycle. PCC-induced cycle cell arrest likely contributed to the in vivo tumor recurrence in a portion of mice after discontinuation of treatment. Thus, 17β-hydroxywithanolides have the potential to improve the therapeutic outcome for patients with advanced melanoma.

Published
2022
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3. Physachenolide C induces complete regression of established murine melanoma tumors via apoptosis and cell cycle arrest

Author

A. A. L. Gunatilaka, E. M. K. Wijeratne, Anne M. Macy, Ya-Ming Xu, Aparna R. Sertil, Anngela C Adams, Alexandra Charos, Karen Taraszka Hastings, Marcus Bosenberg, K. F. Castro-Ochoa, Manping X. Liu, and Paul Kang

Subjects
Cancer Research, Cell cycle checkpoint, ID, intradermal, Cell, macromolecular substances, PCC, physachenolide C, Mouse model, YUMM, Yale University Mouse Melanoma, PI, propidium iodide, In vivo, medicine, mAb, monoclonal antibody, Melanoma, RC254-282, Original Research, Natural products, IFN-γ, interferon gamma, business.industry, BET, bromo and extraterminal domain, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Cell cycle, IT, intratumoral, PE, phycoerythrin, medicine.disease, 7-AAD, 7-Aminoactinomycin D, Immune checkpoint, medicine.anatomical_structure, Oncology, Apoptosis, Cancer research, IAP, anti-apoptotic inhibitors of apoptosis proteins, bacteria, FITC, fluorescein isothiocyanate, Skin cancer, business, IP, intraperitoneal
Abstract

Highlights • PCC and LG-134 had direct cytotoxicity in murine melanoma cell lines (IC50 values ranged from 0.19–1.8 µM). • PCC treatment induced apoptosis of tumor cells both in vitro and in vivo. • PCC treatment induced G0-G1 cell cycle arrest of melanoma cells. • PCC treatment caused complete regression of established melanoma tumors in all mice. • 17β-hydroxywithanolides have the potential to improve melanoma therapeutic outcome., Melanoma is an aggressive skin cancer that metastasizes to other organs. While immune checkpoint blockade with anti-PD-1 has transformed the treatment of advanced melanoma, many melanoma patients fail to respond to anti-PD-1 therapy or develop acquired resistance. Thus, effective treatment of melanoma still represents an unmet clinical need. Our prior studies support the anti-cancer activity of the 17β-hydroxywithanolide class of natural products, including physachenolide C (PCC). As single agents, PCC and its semi-synthetic analog demonstrated direct cytotoxicity in a panel of murine melanoma cell lines, which share common driver mutations with human melanoma; the IC50 values ranged from 0.19–1.8 µM. PCC treatment induced apoptosis of tumor cells both in vitro and in vivo. In vivo treatment with PCC alone caused the complete regression of established melanoma tumors in all mice, with a durable response in 33% of mice after discontinuation of treatment. T cell-mediated immunity did not contribute to the therapeutic efficacy of PCC or prevent tumor recurrence in YUMM2.1 melanoma model. In addition to apoptosis, PCC treatment induced G0-G1 cell cycle arrest of melanoma cells, which upon removal of PCC, re-entered the cell cycle. PCC-induced cycle cell arrest likely contributed to the in vivo tumor recurrence in a portion of mice after discontinuation of treatment. Thus, 17β-hydroxywithanolides have the potential to improve the therapeutic outcome for patients with advanced melanoma.

Published
2021

4. Treatment of generalized deep morphea and eosinophilic fasciitis with the Janus kinase inhibitor tofacitinib

Author

Michael Girardi, Peter Heald, Brett A. King, William Damsky, Sa Rang Kim, and Alexandra Charos

Subjects
eosinophilic fasciitis, ECP, extracorporeal photopheresis, morphea, Case Report, Dermatology, JAK-STAT, 030207 dermatology & venereal diseases, 03 medical and health sciences, 0302 clinical medicine, HES, hypereosinophilic syndrome, TGF-β, transforming growth factor beta, GDM, generalized deep morphea, medicine, EF, eosinophilic fasciitis, Janus kinase inhibitor, ROM, range of motion, 030203 arthritis & rheumatology, tofacitinib, Tofacitinib, Hypereosinophilic syndrome, business.industry, JAK-STAT signaling pathway, Interleukin, transforming growth factor-β, medicine.disease, Eosinophilic fasciitis, IL, interleukin, Cancer research, interleukin-4, JAK, Janus kinase, Janus kinase, business, Morphea
Published
2018
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5. Abstract 4622: The YUMMER.G mouse melanoma model recapitulates the heterogeneous response to immune checkpoint blockade based on patient sex

Author

Julie Y. Ramseier, Alexandra Charos, Marcus Bosenberg, William Damsky, and Koonam Park

Subjects
Cancer Research, biology, business.industry, Melanoma, medicine.medical_treatment, Cancer, Immunotherapy, medicine.disease, Immune checkpoint, Blockade, Oncology, CDKN2A, Immunity, biology.protein, medicine, Cancer research, PTEN, business
Abstract

Existing murine melanoma models, such as syngeneic transplantation of the B16 melanoma cell line, are aggressive, but poorly immunogenic, and as a result, studying the response to immunotherapy in these models has been challenging. Furthermore, in humans, a heterogeneous response to immune checkpoint inhibitor therapy has been observed between male and female melanoma patients, yet no immunogenic murine cancer model exists to study this sex-related dimorphism. To address these challenges, we created the YUMMER.G model, a melanoma cell line driven by human-relevant Braf activation and loss of Pten and Cdkn2a. YUMMER.G is related to the previously described YUMMER1.7 model; however important differences include: diploid state, female genotype, and Mc1re/e (pheomelanin producing) background. YUMMER.G was created by treatment with UV-light, resulting in a neoantigen rich subclone. Subcutaneous injection of 2 million YUMMER.G cells into C57BL/6J mice resulted in melanoma formation in both male and female mice. Treatment of established tumors with anti-CTLA-4 resulted in a comparable response between male and female mice, with complete, durable tumor regression in 100% of female mice and 88% of male mice. However, when established YUMMER.G tumors were treated with anti-PD-1, 63% of female mice, but only 13% of male mice exhibited complete tumor regression (p = 0.0330). These findings demonstrate the important role of host sex in the response to immunotherapy, and they parallel the sex-related differences in checkpoint inhibitor efficacy that have been observed in human patients. In summary, the YUMMER.G model is a human-relevant, immunogenic mouse melanoma model that will serve as a valuable platform for further investigating the mechanisms that mediate the sex-related dimorphism in anti-tumor immunity and response to immunotherapy. Citation Format: Julie Y. Ramseier, Alexandra Charos, Koonam Park, William Damsky, Marcus W. Bosenberg. The YUMMER.G mouse melanoma model recapitulates the heterogeneous response to immune checkpoint blockade based on patient sex [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 4622.

Published
2019
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6. Architecture of the human regulatory network derived from ENCODE data

Author

Debasish Raha, Seth Frietze, Renqiang Min, Peggy J. Farnham, Manoj Hariharan, Koon-Kiu Yan, Yong Cheng, Minyi Shi, Gili Zilberman-Schapira, Ekta Khurana, Nitin Bhardwaj, Preti Jain, Serafim Batzoglou, Yao Fu, Michael Snyder, Arif Harmanci, David Z. Chen, Richard M. Myers, Catharine L. Eastman, Anshul Kundaje, Fabian Grubert, Roger P. Alexander, Henriette O'Geen, Alexej Abyzov, P. Alves, E. Christopher Partridge, Jing Wang, Declan Clarke, Maya Kasowski, Jing Jane Leng, Joel Rozowsky, Linfeng Wu, Ghia Euskirchen, Nicholas Addleman, Sherman M. Weissman, Teri Slifer, Brian Reed, Jason Gertz, Chao Cheng, Florencia Pauli, Jin Lian, Lucía Ramírez, Zhengqing Ouyang, Xinmeng Jasmine Mu, Alexandra Charos, Hannah Monahan, Philip Cayting, Dorrelyn Patacsil, Timothy E. Reddy, Xinqiong Yang, Alan P. Boyle, Mark Gerstein, Phil Lacroute, Arend Sidow, Stephen G. Landt, and Kevin Y. Yip

Subjects
Encyclopedias as Topic, RNA, Untranslated, Gene regulatory network, Genomics, Computational biology, Regulatory Sequences, Nucleic Acid, Biology, ENCODE, Polymorphism, Single Nucleotide, Article, Cell Line, Humans, GATA1 Transcription Factor, Gene Regulatory Networks, Protein Interaction Maps, Phosphorylation, Selection, Genetic, Transcription factor, Gene, Alleles, Cis-regulatory module, Genetics, Multidisciplinary, Genome, Human, Gene Expression Profiling, Molecular Sequence Annotation, DNA, Organ Specificity, Regulatory sequence, Human genome, Transcription Initiation Site, K562 Cells, Transcription Factors
Abstract

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

Published
2012
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7. A highly integrated and complex PPARGC1A transcription factor binding network in HepG2 cells

Author

Alexandra Charos, Brian Reed, Michael Snyder, Sherman M. Weissman, Anna Szekely, and Debasish Raha

Subjects
Chromatin Immunoprecipitation, Transcription, Genetic, Gene regulatory network, Computational biology, Biology, Genetics, Coding region, Cluster Analysis, Humans, Gene Regulatory Networks, Nucleotide Motifs, HSF1, Gene, Transcription factor, Genetics (clinical), Heat-Shock Proteins, Regulation of gene expression, Binding Sites, Research, High-Throughput Nucleotide Sequencing, Promoter, Hep G2 Cells, Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha, Protein Transport, Gene Expression Regulation, Carrier Proteins, Chromatin immunoprecipitation, Protein Binding, Transcription Factors
Abstract

PPARGC1A is a transcriptional coactivator that binds to and coactivates a variety of transcription factors (TFs) to regulate the expression of target genes. PPARGC1A plays a pivotal role in regulating energy metabolism and has been implicated in several human diseases, most notably type II diabetes. Previous studies have focused on the interplay between PPARGC1A and individual TFs, but little is known about how PPARGC1A combines with all of its partners across the genome to regulate transcriptional dynamics. In this study, we describe a core PPARGC1A transcriptional regulatory network operating in HepG2 cells treated with forskolin. We first mapped the genome-wide binding sites of PPARGC1A using chromatin-IP followed by high-throughput sequencing (ChIP-seq) and uncovered overrepresented DNA sequence motifs corresponding to known and novel PPARGC1A network partners. We then profiled six of these site-specific TF partners using ChIP-seq and examined their network connectivity and combinatorial binding patterns with PPARGC1A. Our analysis revealed extensive overlap of targets including a novel link between PPARGC1A and HSF1, a TF regulating the conserved heat shock response pathway that is misregulated in diabetes. Importantly, we found that different combinations of TFs bound to distinct functional sets of genes, thereby helping to reveal the combinatorial regulatory code for metabolic and other cellular processes. In addition, the different TFs often bound near the promoters and coding regions of each other's genes suggesting an intricate network of interdependent regulation. Overall, our study provides an important framework for understanding the systems-level control of metabolic gene expression in humans.

Published
2012

8. A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

Author

Zhi Lu, Giltae Song, Troy W. Whitfield, Vishwanath R. Iyer, Teresa Vales, Angelika Merkel, Max Libbrecht, David Haussler, Ting Wang, Kristen Lee, Lingyun Song, Richard M. Myers, Alfonso Valencia, Rachel A. Harte, Xiaoqin Xu, Lucas D. Ward, Hazuki Takahashi, Nathan C. Sheffield, Thomas Derrien, Georgi K. Marinov, Eric D. Nguyen, Bernard B. Suh, Brian J. Raney, Richard Sandstrom, Thomas D. Tullius, Benoit Miotto, Alexander Dobin, Youhan Xu, Lukas Habegger, Ian Dunham, Brian A. Risk, Paul G. Giresi, Morgan C. Giddings, Hualin Xi, Anshul Kundaje, Robert S. Harris, Devin Absher, Peter J. Bickel, Yanbao Yu, Browen Aken, Colin Kingswood, Bryan R. Lajoie, Peter J. Good, Katrina Learned, Laura Elnitski, Shirley Pepke, Brandon King, Piero Carninci, Xinqiong Yang, Ghia Euskirchen, Kathryn Beal, Christelle Borel, Michael Muratet, Robert L. Grossman, David G. Knowles, Zarmik Moqtaderi, Veronika Boychenko, Steven P. Wilder, Michael L. Tress, Florencia Pauli, Alan P. Boyle, Andrea Tanzer, Philipp Kapranov, Serafim Batzoglou, Audra K. Johnson, Jun Neri, Nitin Bhardwaj, Elise A. Feingold, Venkat S. Malladi, Michael M. Hoffman, William Stafford Noble, Andrea Sboner, Mark Gerstein, Stephanie L. Parker, Jacqueline Dumais, Felix Schlesinger, Deborah R. Winter, Randall H. Brown, Thanh Truong, Rebecca F. Lowdon, Paolo Ribeca, Brooke Rhead, Peggy J. Farnham, Krista Thibeault, Terrence S. Furey, Donna Karolchik, Alec Victorsen, Xiaoan Ruan, Rehab F. Abdelhamid, Amy S. Nesmith, Jing Wang, Nicholas M. Luscombe, Alina R. Cao, Diane Trout, Teri Slifer, Peter E. Newburger, Cricket A. Sloan, Dimitra Lotakis, Stephen M. J. Searle, Ali Mortazavi, Alexandra Bignell, Alex Reynolds, Orion J. Buske, Chris Zaleski, Theresa K. Canfield, Ian Bell, Jin Lian, Vanessa K. Swing, Katalin Toth Fejes, Catherine Ucla, Robert E. Thurman, Jacqueline Chrast, Wei Lin, Tim Hubbard, Gary Saunders, Minyi Shi, Vihra Sotirova, Sherman M. Weissman, Jason D. Lieb, Richard Humbert, Kevin M. Bowling, Assaf Gordon, Tarjei S. Mikkelsen, Jing Leng, Thomas R. Gingeras, Fabian Grubert, Nader Jameel, Jost Vielmetter, Hannah Monahan, Preti Jain, Lindsay L. Waite, Tony Shafer, Joel Rozowsky, Michael Coyne, Brian Reed, M. Kay, Harsha P. Gunawardena, Ross C. Hardison, Gavin Sherlock, Alexandra Charos, Joseph D. Fleming, Ann S. Zweig, Jason Gertz, Rajinder Kaul, Xianjun Dong, Alexandre Reymond, Carrie A. Davis, Haiyan Huang, Chao Cheng, Marco Mariotti, Phil Lacroute, Jason A. Dilocker, Kenneth McCue, R. Robilotto, Stylianos E. Antonarakis, Sridar V. Chittur, Justin Jee, Barbara J. Wold, Sudipto K. Chakrabortty, Erica Dumais, Amartya Sanyal, Nathan Boley, Tianyuan Wang, Julien Lagarde, Anthony Kirilusha, Jonathan B. Preall, Kevin Roberts, Erika Giste, Hugo Y. K. Lam, Alvis Brazma, Gregory J. Hannon, Eric Rynes, Philippe Batut, Kevin Struhl, Margus Lukk, Manching Ku, Suganthi Balasubramanian, Sonali Jha, Jorg Drenkow, W. James Kent, Michael Snyder, Jie Wang, Anna Battenhouse, Charles B. Epstein, Rami Rauch, Christopher Shestak, John A. Stamatoyannopoulos, Gaurab Mukherjee, Cédric Howald, Tanya Kutyavin, Huaien Wang, Scott A. Tenenbaum, Wan Ting Poh, Kate R. Rosenbloom, Manolis Kellis, Pauline A. Fujita, Linfeng Wu, Anita Bansal, Molly Weaver, Linda L. Grasfeder, Peter J. Sabo, Qiang Li, Melissa S. Cline, Robert M. Kuhn, Darin London, Seth Frietze, Atif Shahab, Shane Neph, Damian Keefe, James B. Brown, Mark Diekhans, Webb Miller, Katherine Aylor Fisher, Jiang Du, Hadar H. Sheffer, Sarah Djebali, Frank Doyle, Nathan Lamarre-Vincent, Chia-Lin Wei, Laura A.L. Dillon, Jennifer Harrow, Robert C. Altshuler, Tyler Alioto, Raymond K. Auerbach, Adam Frankish, Rebekka O. Sprouse, Patrick J. Collins, E. Christopher Partridge, Zheng Liu, Yoichiro Shibata, Elliott H. Margulies, Abigail K. Ebersol, Kimberly A. Showers, Eric D. Green, Krishna M. Roskin, Job Dekker, Barbara N. Pusey, Ekta Khurana, Gilberto DeSalvo, Yijun Ruan, Hao Wang, Jainab Khatun, Henriette O'Geen, Alexej Abyzov, Brian Williams, Ryan M. McDaniell, Maya Kasowski, Manoj Hariharan, Felix Kokocinski, Gloria Despacio-Reyes, Zhancheng Zhang, Subhradip Karmakar, Ewan Birney, Koon-Kiu Yan, Xian Chen, Shinny Vong, Daniel Sobral, Nick Bild, Seul K.C. Kim, Timo Lassmann, Li Wang, Minerva E. Sanchez, Vaughan Roach, Theodore Gibson, Stephen C. J. Parker, Michael F. Lin, Patrick A. Navas, Laurence R. Meyer, Luiz O. F. Penalva, Bradley E. Bernstein, Kevin P. White, Emilie Aït Yahya Graison, Juan M. Vaquerizas, Sushma Iyengar, Kimberly M. Newberry, Akshay Bhinge, Xiaolan Zhang, Kim Bell, Yoshihide Hayashizaki, Lucas Lochovsky, Noam Shoresh, Hagen Tilgner, Philip Cayting, Dorrelyn Patacsil, Timothy E. Reddy, Eric Haugen, Katherine E. Varley, M. van Baren, Nathan D. Trinklein, Bum Kyu Lee, Tristan Frum, Marianne Lindahl-Allen, Timothy Durham, Roderic Guigó, Christopher W. Maier, Micha Sammeth, Debasish Raha, Timothy R. Dreszer, Benedict Paten, Robbyn Issner, Michael R. Brent, Kevin Y. Yip, Kim Blahnik, Jason Ernst, Zhiping Weng, Henry Amrhein, Arend Sidow, Javier Herrero, Hui Gao, Stephen G. Landt, Pouya Kheradpour, Galt P. Barber, Gregory E. Crawford, Toby Hunt, HudsonAlpha Institute for Biotechnology [Huntsville, AL], ENCODE Project Consortium : Myers RM, Stamatoyannopoulos J, Snyder M, Dunham I, Hardison RC, Bernstein BE, Gingeras TR, Kent WJ, Birney E, Wold B, Crawford GE, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Mikkelsen TS, Kheradpour P, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Lin MF, Kellis M, Gingeras TR, Davis CA, Kapranov P, Dobin A, Zaleski C, Schlesinger F, Batut P, Chakrabortty S, Jha S, Lin W, Drenkow J, Wang H, Bell K, Gao H, Bell I, Dumais E, Dumais J, Antonarakis SE, Ucla C, Borel C, Guigo R, Djebali S, Lagarde J, Kingswood C, Ribeca P, Sammeth M, Alioto T, Merkel A, Tilgner H, Carninci P, Hayashizaki Y, Lassmann T, Takahashi H, Abdelhamid RF, Hannon G, Fejes-Toth K, Preall J, Gordon A, Sotirova V, Reymond A, Howald C, Graison E, Chrast J, Ruan Y, Ruan X, Shahab A, Ting Poh W, Wei CL, Crawford GE, Furey TS, Boyle AP, Sheffield NC, Song L, Shibata Y, Vales T, Winter D, Zhang Z, London D, Wang T, Birney E, Keefe D, Iyer VR, Lee BK, McDaniell RM, Liu Z, Battenhouse A, Bhinge AA, Lieb JD, Grasfeder LL, Showers KA, Giresi PG, Kim SK, Shestak C, Myers RM, Pauli F, Reddy TE, Gertz J, Partridge EC, Jain P, Sprouse RO, Bansal A, Pusey B, Muratet MA, Varley KE, Bowling KM, Newberry KM, Nesmith AS, Dilocker JA, Parker SL, Waite LL, Thibeault K, Roberts K, Absher DM, Wold B, Mortazavi A, Williams B, Marinov G, Trout D, Pepke S, King B, McCue K, Kirilusha A, DeSalvo G, Fisher-Aylor K, Amrhein H, Vielmetter J, Sherlock G, Sidow A, Batzoglou S, Rauch R, Kundaje A, Libbrecht M, Margulies EH, Parker SC, Elnitski L, Green ED, Hubbard T, Harrow J, Searle S, Kokocinski F, Aken B, Frankish A, Hunt T, Despacio-Reyes G, Kay M, Mukherjee G, Bignell A, Saunders G, Boychenko V, Van Baren M, Brown RH, Khurana E, Balasubramanian S, Zhang Z, Lam H, Cayting P, Robilotto R, Lu Z, Guigo R, Derrien T, Tanzer A, Knowles DG, Mariotti M, James Kent W, Haussler D, Harte R, Diekhans M, Kellis M, Lin M, Kheradpour P, Ernst J, Reymond A, Howald C, Graison EA, Chrast J, Tress M, Rodriguez JM, Snyder M, Landt SG, Raha D, Shi M, Euskirchen G, Grubert F, Kasowski M, Lian J, Cayting P, Lacroute P, Xu Y, Monahan H, Patacsil D, Slifer T, Yang X, Charos A, Reed B, Wu L, Auerbach RK, Habegger L, Hariharan M, Rozowsky J, Abyzov A, Weissman SM, Gerstein M, Struhl K, Lamarre-Vincent N, Lindahl-Allen M, Miotto B, Moqtaderi Z, Fleming JD, Newburger P, Farnham PJ, Frietze S, O'Geen H, Xu X, Blahnik KR, Cao AR, Iyengar S, Stamatoyannopoulos JA, Kaul R, Thurman RE, Wang H, Navas PA, Sandstrom R, Sabo PJ, Weaver M, Canfield T, Lee K, Neph S, Roach V, Reynolds A, Johnson A, Rynes E, Giste E, Vong S, Neri J, Frum T, Johnson EM, Nguyen ED, Ebersol AK, Sanchez ME, Sheffer HH, Lotakis D, Haugen E, Humbert R, Kutyavin T, Shafer T, Dekker J, Lajoie BR, Sanyal A, James Kent W, Rosenbloom KR, Dreszer TR, Raney BJ, Barber GP, Meyer LR, Sloan CA, Malladi VS, Cline MS, Learned K, Swing VK, Zweig AS, Rhead B, Fujita PA, Roskin K, Karolchik D, Kuhn RM, Haussler D, Birney E, Dunham I, Wilder SP, Keefe D, Sobral D, Herrero J, Beal K, Lukk M, Brazma A, Vaquerizas JM, Luscombe NM, Bickel PJ, Boley N, Brown JB, Li Q, Huang H, Gerstein M, Habegger L, Sboner A, Rozowsky J, Auerbach RK, Yip KY, Cheng C, Yan KK, Bhardwaj N, Wang J, Lochovsky L, Jee J, Gibson T, Leng J, Du J, Hardison RC, Harris RS, Song G, Miller W, Haussler D, Roskin K, Suh B, Wang T, Paten B, Noble WS, Hoffman MM, Buske OJ, Weng Z, Dong X, Wang J, Xi H, Tenenbaum SA, Doyle F, Penalva LO, Chittur S, Tullius TD, Parker SC, White KP, Karmakar S, Victorsen A, Jameel N, Bild N, Grossman RL, Snyder M, Landt SG, Yang X, Patacsil D, Slifer T, Dekker J, Lajoie BR, Sanyal A, Weng Z, Whitfield TW, Wang J, Collins PJ, Trinklein ND, Partridge EC, Myers RM, Giddings MC, Chen X, Khatun J, Maier C, Yu Y, Gunawardena H, Risk B, Feingold EA, Lowdon RF, Dillon LA, Good PJ, Harrow J, Searle S., Becker, Peter B, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Department of Physics, Kellis, Manolis, Epstein, Charles B., Bernstein, Bradley E., Shoresh, Noam, Ernst, Jason, Mikkelsen, Tarjei Sigurd, Kheradpour, Pouya, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael J., Durham, Timothy, Ku, Manching, Truong, Thanh, Ward, Lucas D., Altshuler, Robert Charles, Lin, Michael F., ENCODE Project Consortium, Antonarakis, Stylianos, and Miotto, Benoit

Subjects
RNA, Messenger/genetics, [SDV]Life Sciences [q-bio], Messenger, Genoma humà, Genome, Medical and Health Sciences, 0302 clinical medicine, Models, ddc:576.5, Biology (General), Conserved Sequence, Genetics, 0303 health sciences, General Neuroscience, RNA-Binding Proteins, Genomics, Biological Sciences, Chromatin, 3. Good health, [SDV] Life Sciences [q-bio], DNA-Binding Proteins, Gene Components, 030220 oncology & carcinogenesis, DNA methylation, Encyclopedia, HIV/AIDS, Proteïnes de la sang -- Aspectes genètics, General Agricultural and Biological Sciences, Databases, Nucleic Acid, Human, Research Article, Quality Control, Process (engineering), QH301-705.5, 1.1 Normal biological development and functioning, Computational biology, Biology, ENCODE, General Biochemistry, Genetics and Molecular Biology, Chromatin/metabolism, Vaccine Related, 03 medical and health sciences, Databases, Genetic, Underpinning research, Humans, RNA, Messenger, RNA-Binding Proteins/genetics/metabolism, Vaccine Related (AIDS), Gene, 030304 developmental biology, Internet, General Immunology and Microbiology, Nucleic Acid, Agricultural and Veterinary Sciences, Base Sequence, Models, Genetic, Genome, Human, Prevention, Human Genome, Computational Biology, DNA Methylation, ENCODE Project Consortium, Gene Expression Regulation, DNA-Binding Proteins/genetics/metabolism, RNA, Human genome, Immunization, Generic health relevance, Developmental Biology
Abstract

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome., National Human Genome Research Institute (U.S.), National Institutes of Health (U.S.)

Published
2011
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9. Genome-wide occupancy of SREBP1 and its partners NFY and SP1 reveals novel functional roles and combinatorial regulation of distinct classes of genes

Author

Alexandra Charos, Brian Reed, Michael Snyder, Sherman M. Weissman, and Anna Szekely

Subjects
Transcriptional Activation, Cancer Research, lcsh:QH426-470, Sp1 Transcription Factor, Computational Biology/Transcriptional Regulation, Computational biology, Genome, Cell Line, Tumor, Genetics, Humans, Diabetes and Endocrinology/Type 2 Diabetes, Promoter Regions, Genetic, Molecular Biology, Gene, Genetics (clinical), Ecology, Evolution, Behavior and Systematics, Regulation of gene expression, Tiling array, Models, Genetic, biology, Genome, Human, Genetics and Genomics/Functional Genomics, Genetics and Genomics, Genetics and Genomics/Bioinformatics, Sterol regulatory element-binding protein, Insulin receptor, lcsh:Genetics, CCAAT-Binding Factor, Gene Expression Regulation, Hepatocytes, biology.protein, Sterol Regulatory Element Binding Protein 1, Chromatin immunoprecipitation, Research Article, Protein Binding
Abstract

The sterol regulatory element-binding protein (SREBP) family member SREBP1 is a critical transcriptional regulator of cholesterol and fatty acid metabolism and has been implicated in insulin resistance, diabetes, and other diet-related diseases. We globally identified the promoters occupied by SREBP1 and its binding partners NFY and SP1 in a human hepatocyte cell line using chromatin immunoprecipitation combined with genome tiling arrays (ChIP-chip). We find that SREBP1 occupies the promoters of 1,141 target genes involved in diverse biological pathways, including novel targets with roles in lipid metabolism and insulin signaling. We also identify a conserved SREBP1 DNA-binding motif in SREBP1 target promoters, and we demonstrate that many SREBP1 target genes are transcriptionally activated by treatment with insulin and glucose using gene expression microarrays. Finally, we show that SREBP1 cooperates extensively with NFY and SP1 throughout the genome and that unique combinations of these factors target distinct functional pathways. Our results provide insight into the regulatory circuitry in which SREBP1 and its network partners coordinate a complex transcriptional response in the liver with cues from the diet., Author Summary Transcription factors (TFs) are DNA-binding proteins that regulate the transcription of their target genes. TFs typically bind in proximity to the transcription start sites of their target genes in a region called the promoter. SREBP1 is a TF that increases the transcription of numerous genes involved in cholesterol and fat metabolism and has been linked to diet-related diseases such as insulin resistance and type 2 diabetes. Using microarray technology, we identified all of the promoters in the human genome that are bound by SREBP1 and two associated TFs called NFY and SP1 in a human liver cell line. Our findings greatly expand the number of genes and biological pathways that may be regulated by SREBP1 and reveal that different combinations of SREBP1 and its partners preferentially target genes involved in different pathways. Thus, in contrast to traditional studies that focus on individual genes, we have used a genomics approach to provide a novel global view of the regulatory circuitry in which SREBP1 and its partners coordinate a transcriptional response in the liver with cues from the diet.

Published
2008

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