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Niture S, Ramalinga M, Kedir H, Patacsil D, Niture SS, Li J, Mani H, Suy S, Collins S, Kumar D. TNFAIP8 promotes prostate cancer cell survival by inducing autophagy. Oncotarget 2018; 9:26884-26899. [PMID: 29928491 PMCID: PMC6003558 DOI: 10.18632/oncotarget.25529] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 05/03/2018] [Indexed: 01/11/2023] Open
Abstract
Tumor necrosis factor-α-inducible protein 8 (TNFAIP8) is a TNF-α inducible anti-apoptotic protein with multiple roles in tumor growth and survival. Mechanisms of cell survival by TNFAIP8 remain elusive. We investigated the role of TNFAIP8 in the regulation of the cell cycle, autophagy, cell survival and neuroendocrine differentiation in prostate cancer cells. We showed that TNFAIP8 dysregulates cell-cycle-related proteins, in PC3 cells. Oncogenic cell survival, drug resistance and dysregulation of cell cycle-related proteins are often associated with autophagy. We demonstrated that TNFAIP8 induces autophagy by increasing expression of autophagy effectors such as LC3β I/II, Beclin1, 4EBP1, p62, and SIRT1. We also demonstrated that TNFAIP8 interacts with autophagy-related protein 3 (ATG3). TNFα treatment increased the expression of TNFAIP8, which was associated with increased autophagy and decreased apoptosis. We also observed an increase in expression of neuroendocrine differentiation markers, synaptophysin and chromogranin A, and drug resistance to anticancer drugs, docetaxel and doxorubicin, in cells transfected with TNFAIP8. Collectively, our findings reveal that by the creation of cellular autophagy events, TNFAIP8 promotes cell survival and drug resistance in prostate cancer cells.
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Affiliation(s)
- Suryakant Niture
- Julius L. Chambers Biomedical Biotechnology Research Institute, North Carolina Central University Durham, 27707 NC, USA.,Cancer Research Laboratory, University of the District of Columbia, Washington, 20008 DC, USA
| | - Malathi Ramalinga
- Cancer Research Laboratory, University of the District of Columbia, Washington, 20008 DC, USA
| | - Habib Kedir
- Julius L. Chambers Biomedical Biotechnology Research Institute, North Carolina Central University Durham, 27707 NC, USA.,Cancer Research Laboratory, University of the District of Columbia, Washington, 20008 DC, USA
| | - Dorrelyn Patacsil
- Cancer Research Laboratory, University of the District of Columbia, Washington, 20008 DC, USA
| | | | - James Li
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, 20008 DC, USA
| | - Haresh Mani
- Department of Pathology, Inova Fairfax Hospital, Falls Church, 22042 VA, USA
| | - Simeng Suy
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, 20008 DC, USA
| | - Sean Collins
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, 20008 DC, USA
| | - Deepak Kumar
- Julius L. Chambers Biomedical Biotechnology Research Institute, North Carolina Central University Durham, 27707 NC, USA.,Cancer Research Laboratory, University of the District of Columbia, Washington, 20008 DC, USA.,Lombardi Comprehensive Cancer Center, Georgetown University, Washington, 20008 DC, USA
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Cheng Y, Ma Z, Kim BH, Wu W, Cayting P, Boyle AP, Sundaram V, Xing X, Dogan N, Li J, Euskirchen G, Lin S, Lin Y, Visel A, Kawli T, Yang X, Patacsil D, Keller CA, Giardine B, Kundaje A, Wang T, Pennacchio LA, Weng Z, Hardison RC, Snyder MP. Principles of regulatory information conservation between mouse and human. Nature 2015; 515:371-375. [PMID: 25409826 PMCID: PMC4343047 DOI: 10.1038/nature13985] [Citation(s) in RCA: 189] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Accepted: 10/21/2014] [Indexed: 11/09/2022]
Abstract
To broaden our understanding of the evolution of gene regulation mechanisms, we generated occupancy profiles for 34 orthologous transcription factors (TFs) in human-mouse erythroid progenitor, lymphoblast and embryonic stem-cell lines. By combining the genome-wide transcription factor occupancy repertoires, associated epigenetic signals, and co-association patterns, here we deduce several evolutionary principles of gene regulatory features operating since the mouse and human lineages diverged. The genomic distribution profiles, primary binding motifs, chromatin states, and DNA methylation preferences are well conserved for TF-occupied sequences. However, the extent to which orthologous DNA segments are bound by orthologous TFs varies both among TFs and with genomic location: binding at promoters is more highly conserved than binding at distal elements. Notably, occupancy-conserved TF-occupied sequences tend to be pleiotropic; they function in several tissues and also co-associate with many TFs. Single nucleotide variants at sites with potential regulatory functions are enriched in occupancy-conserved TF-occupied sequences.
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Affiliation(s)
- Yong Cheng
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Zhihai Ma
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Bong-Hyun Kim
- Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Weisheng Wu
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Philip Cayting
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Alan P Boyle
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Vasavi Sundaram
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Xiaoyun Xing
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Nergiz Dogan
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jingjing Li
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Ghia Euskirchen
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Shin Lin
- Department of Genetics, Stanford University, Stanford, CA 94305, USA.,Division of Cardiovascular Medicine, Stanford University, Stanford, CA 94304, USA
| | - Yiing Lin
- Department of Genetics, Stanford University, Stanford, CA 94305, USA.,Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Axel Visel
- Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94701,USA.,Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA.,School of Natural Sciences, University of California, Merced, CA 95343,USA
| | - Trupti Kawli
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Xinqiong Yang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Dorrelyn Patacsil
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Cheryl A Keller
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Belinda Giardine
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | | | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Ting Wang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Len A Pennacchio
- Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94701,USA.,Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Ross C Hardison
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
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Patacsil D, Tran AT, Cho YS, Suy S, Saenz F, Malyukova I, Ressom H, Collins SP, Clarke R, Kumar D. Gamma-tocotrienol induced apoptosis is associated with unfolded protein response in human breast cancer cells. J Nutr Biochem 2011; 23:93-100. [PMID: 21429729 DOI: 10.1016/j.jnutbio.2010.11.012] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2010] [Revised: 11/04/2010] [Accepted: 11/09/2010] [Indexed: 12/01/2022]
Abstract
Gamma-tocotrienol (γ-T3) is a member of the vitamin E family. Tocotrienols (T3s) are powerful antioxidants and possess anticancer, neuroprotective and cholesterol-lowering properties. Tocotrienols inhibit the growth of various cancer cell lines without affecting normal cells. Less is known about the exact mechanisms of action of T3s on cell death and other growth inhibitory pathways. In the present study, we demonstrate that γ-T3 induces apoptosis in MDA-MB 231 and MCF-7 breast cancer cells as evident by PARP cleavage and caspase-7 activation. Gene expression analysis of MCF-7 cells treated with γ-T3 revealed alterations in the expression of multiple genes involved in cell growth and proliferation, cell death, cell cycle, cellular development, cellular movement and gene expression. Further analysis of differentially modulated genes using Ingenuity Pathway Analysis software suggested modulation of canonical signal transduction or metabolic pathways such as NRF-2-mediated oxidative stress response, TGF-β signaling and endoplasmic reticulum (ER) stress response. Analysis of ER-stress-related proteins in MCF-7 and MDA-MB 231 cells treated with γ-T3 demonstrated activation of PERK and pIRE1α pathway to induce ER stress. Activating transcription factor 3 (ATF3) was identified as the most up-regulated gene (16.8-fold) in response to γ-T3. Activating transcription factor 3 knockdown using siRNA suggested an essential role of ATF3 in γ-T3-induced apoptosis. In summary, we demonstrate that γ-T3 modulates ER stress signaling and have identified ATF3 as a molecular target for γ-T3 in breast cancer cells.
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Affiliation(s)
- Dorrelyn Patacsil
- Cancer Research Laboratory, Department of Biological and Environmental Sciences, University of the District of Columbia, Washington, DC 20008, USA
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Liang LR, Lu S, Wang X, Lu Y, Mandal V, Patacsil D, Kumar D. FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis. BMC Bioinformatics 2006; 7 Suppl 4:S7. [PMID: 17217525 PMCID: PMC1780132 DOI: 10.1186/1471-2105-7-s4-s7] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Background Microarray techniques have revolutionized genomic research by making it possible to monitor the expression of thousands of genes in parallel. As the amount of microarray data being produced is increasing at an exponential rate, there is a great demand for efficient and effective expression data analysis tools. Comparison of gene expression profiles of patients against those of normal counterpart people will enhance our understanding of a disease and identify leads for therapeutic intervention. Results In this paper, we propose an innovative approach, fuzzy membership test (FM-test), based on fuzzy set theory to identify disease associated genes from microarray gene expression profiles. A new concept of FM d-value is defined to quantify the divergence of two sets of values. We further analyze the asymptotic property of FM-test, and then establish the relationship between FM d-value and p-value. We applied FM-test to a diabetes expression dataset and a lung cancer expression dataset, respectively. Within the 10 significant genes identified in diabetes dataset, six of them have been confirmed to be associated with diabetes in the literature and one has been suggested by other researchers. Within the 10 significantly overexpressed genes identified in lung cancer data, most (eight) of them have been confirmed by the literatures which are related to the lung cancer. Conclusion Our experiments on synthetic datasets show that FM-test is effective and robust. The results in diabetes and lung cancer datasets validated the effectiveness of FM-test. FM-test is implemented as a Web-based application and is available for free at .
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Affiliation(s)
- Lily R Liang
- Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC, 20008, USA
| | - Shiyong Lu
- Department of Computer Science, Wayne State University, Detroit, MI, 48202, USA
| | | | - Yi Lu
- Department of Computer Science, Wayne State University, Detroit, MI, 48202, USA
| | - Vinay Mandal
- Department of Computer Science, Wayne State University, Detroit, MI, 48202, USA
| | - Dorrelyn Patacsil
- Department of Biological and Environmental Sciences, University of the District of Columbia, Washington, DC, 20008, USA
| | - Deepak Kumar
- Department of Biological and Environmental Sciences, University of the District of Columbia, Washington, DC, 20008, USA
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