乙型肝炎病毒（HBV）感染是全世界發病率和死亡率的主要原因。然而，對其發病機理的了解不足通常會導致免疫逃逸和預後的複發。因此，基於資料探勘和全基因組RNA-seq數據的強效系統方法對於進一步分析致病機理和鑑定用於藥物設計的生物標記至關重要。在這項研究中，系統生物學方法被應用於通過雙向RNA序列數據修剪在HBV感染下的宿主/病原體遺傳和表觀遺傳相互作用網絡（HPI-GEN）中的假陽性。然後，通過主要網絡投影（PNP）方法和KEGG途徑的註釋，從核心串擾信號途徑中識別出與細胞功能障礙相關的重要生物標誌物作為藥物靶標。此外，基於預先訓練的基於深度學習的藥物-靶標相互作用（DTI）模型和從數據庫中獲得經驗證的藥理特性，即藥物調節能力，毒性和敏感性，將有前途的多靶點藥物組合設計為一種多分子藥物，為治療HBV感染創造了更多可能性。因此，通過擬議的系統醫學發現和重新定位程序，我們不僅闡明了乙肝病毒感染期間的病因機制，而且還有效地提供了治療乙肝的潛在藥物組合。

Hepatitis B Virus (HBV) infection is a major cause of morbidity and mortality worldwide. However, poor understanding of its pathogenesis often gives rise to intractable immune escape and prognosis recurrence. Thus, a valid systematic approach based on big data mining and genome-wide RNA-seq data is imperative to further investigate the pathogenetic mechanism and identify biomarkers for drug design. In this study, systems biology method was applied to trim false positives from the host/pathogen genetic and epigenetic interaction network (HPI-GEN) under HBV infection by two-side RNA-seq data. Then, via the principal network projection (PNP) approach and the annotation of KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, significant biomarkers related to cellular dysfunctions were identified from the core cross-talk signaling pathways as drug targets. Further, based on the pre-trained deep learning-based drug-target interaction (DTI) model and the validated pharmacological properties from databases, i.e., drug regulation ability, toxicity, and sensitivity, a combination of promising multi-target drugs was designed as a multiple-molecule drug to create more possibility for the treatment of HBV infection. Therefore, with the proposed systems medicine discovery and repositioning procedure, we not only shed light on the etiologic mechanism during HBV infection but also efficiently provided a potential drug combination for therapeutic treatment of Hepatitis B.

Contents
致謝 i
摘要 ii
Abstract iii
Contents iv
1. Introduction 1
2. Materials and Methods 2
2.1. The Construction of the HPI-GEN in HepaRG Cell Line during HBV Infection and the Application of Deep Learning-Based DTI Model for New Drug Design: An Overview 2
2.2. Big Data Mining and Data Preprocessing of RNA-seq Data for Human and Pathogen 2
2.3. Text Mining of Human and Pathogen Protein Interactions 3
2.4. Dynamic Models of Candidate HPI-GEN for Human Cells and HBV During the Infection 3
2.5. Parameter Estimation of the Dynamic Models of Candidate HPI-GEN by System Identification Approach 6
2.6. Determination of Significant Interaction Pairs 12
2.7. Extracting Core Network Structure from the Real HPI-GEN by Using PNP Approach 14
2.8. Deep Learning-Based Drug-Target Interaction Prediction 16
2.8.1. Data Preparation 16
2.8.2. Parameters Tuning Process Based on Deep Learning Algorithm 18
2.8.3. Measurement of Prediction Quality 19
3. Results 20
3.1. Overview of Systems Medicine Discovery Procedure 20
3.2. Extracting Core Signaling Pathways from Identified HPI-GEN and Core HPI-GEN in HBV Infection 26
3.3. Analysis of Core Interspecies Cross-Talk Pathways to Investigate Host/Pathogen Offensive/Defensive Mechanism during HBV Infection 26
3.3.1. Inception of HBV Infection 27
3.3.2. Liver Microenvironment and Immune Pathogenesis under HBV Infection 27
3.3.3. Toll Pathway as the First Line of Defense against Infection 27
3.3.4. TNF-α-Stimulated Signaling Pathways 28
3.3.5. TAK-STAT Signaling Pathways 29
3.3.6. TNFs-Induced Apoptotic Pathways 29
3.3.7. Virus Proteins-Induced Pathogenic Mechanism 30
3.4. Drugs Discovery and Repositioning Based on Selected Biomarkers for HBV 31
3.4.1. Deep Learning-Based Drug-Target Interaction Prediction Model 35
3.4.2. Systems Discovery and Design of the Multiple-Molecule Drug for HBV Infection 36
4. Discussion 39
4.1. Apoptosis in HBV Infection 39
4.2. Autophagy in HBV Infection 40
4.3. Inflammation and Innate Immune Response in HBV Infection 40
4.4. Discovery of Potential Drug Combination 41
5. Conclusions 41
References 42

References
1. Chang, M.-H., Hepatitis B virus infection. Seminars in Fetal and Neonatal Medicine 2007, 12, (3), 160-167.
2. World Health Organization Global hepatitis report, 2017. Geneva, Switzerland: World Health Organization. http://apps.who.int/iris/bitstream/handle/10665/255016/9789241565455-eng.pdf?sequence=1 (March, 18, 2020),
3. Hong, X.; Kim, E. S.; Guo, H., Epigenetic regulation of hepatitis B virus covalently closed circular DNA: Implications for epigenetic therapy against chronic hepatitis B. Hepatology 2017, 66, (6), 2066-2077.
4. Fanning, G. C.; Zoulim, F.; Hou, J.; Bertoletti, A., Therapeutic strategies for hepatitis B virus infection: towards a cure. Nature Reviews Drug Discovery 2019, 18, (11), 827-844.
5. Gehring, A. J.; Protzer, U., Targeting Innate and Adaptive Immune Responses to Cure Chronic HBV Infection. Gastroenterology 2019, 156, (2), 325-337.
6. Pol, S.; Nalpas, B.; Driss, F.; Michel, M.-L.; Tiollais, P.; Denis, J.; Bréchot, C., Efficacy and limitations of a specific immunotherapy in chronic hepatitis B. Journal of Hepatology 2001, 34, (6), 917-921.
7. Shih, C.; Chou, S.-F.; Yang, C.-C.; Huang, J.-Y.; Choijilsuren, G.; Jhou, R.-S., Control and Eradication Strategies of Hepatitis B Virus. Trends in Microbiology 2016, 24, (9), 739-749.
8. Nassal, M., HBV cccDNA: viral persistence reservoir and key obstacle for a cure of chronic hepatitis B. Gut 2015, 64, (12), 1972.
9. Nosengo, N., Can you teach old drugs new tricks? Nature 2016, 534, 314-316.
10. Scannell, J. W.; Blanckley, A.; Boldon, H.; Warrington, B., Diagnosing the decline in pharmaceutical R&D efficiency. Nature Reviews Drug Discovery 2012, 11, (3), 191-200.
11. Rao, V. S.; Srinivas, K.; Sujini, G. N.; Kumar, G. N., Protein-protein interaction detection: methods and analysis. Int J Proteomics 2014, 2014, 147648. https://doi.org/10.1155/2014/147648.
12. Droit, A.; Poirier, G.; Hunter, J., Experimental and bioinformatic approaches for interrogating protein-protein interactions to determine protein function. Journal of molecular endocrinology 2005, 34, 263-80.
13. Ashburn, T. T.; Thor, K. B., Drug repositioning: identifying and developing new uses for existing drugs. Nature Reviews Drug Discovery 2004, 3, (8), 673-683.
14. Antolin, A. A.; Workman, P.; Mestres, J.; Al-Lazikani, B., Polypharmacology in Precision Oncology: Current Applications and Future Prospects. Curr Pharm Des 2016, 22, (46), 6935-6945.
15. Mueller, H.; Wildum, S.; Luangsay, S.; Walther, J.; Lopez, A.; Tropberger, P.; Ottaviani, G.; Lu, W.; Parrott, N.; Zhang, J. D.; Schmucki, R.; Racek, T.; Hoflack, J.-C.; Küng, E.; Point, F.; Zhou, X.; Steiner, G.; Luetgehetmann, M.; Rapp, G.; Javanbakht, H., A Novel Orally Available Small Molecule That Inhibits Hepatitis B Virus Expression. Journal of Hepatology 2017, 68, 412-420.
16. Stark, C.; Breitkreutz, B.-J.; Reguly, T.; Boucher, L.; Breitkreutz, A.; Tyers, M., BioGRID: a general repository for interaction datasets. Nucleic Acids Res 2006, 34, (Database issue), D535-D539.
17. Salwinski, L.; Miller, C. S.; Smith, A. J.; Pettit, F. K.; Bowie, J. U.; Eisenberg, D., The Database of Interacting Proteins: 2004 update. Nucleic Acids Res 2004, 32, (Database issue), D449-D451.
18. Bader, G. D.; Betel, D.; Hogue, C. W. V., BIND: the Biomolecular Interaction Network Database. Nucleic Acids Res 2003, 31, (1), 248-250.
19. Orchard, S.; Ammari, M.; Aranda, B.; Breuza, L.; Briganti, L.; Broackes-Carter, F.; Campbell, N. H.; Chavali, G.; Chen, C.; del-Toro, N.; Duesbury, M.; Dumousseau, M.; Galeota, E.; Hinz, U.; Iannuccelli, M.; Jagannathan, S.; Jimenez, R.; Khadake, J.; Lagreid, A.; Licata, L.; Lovering, R. C.; Meldal, B.; Melidoni, A. N.; Milagros, M.; Peluso, D.; Perfetto, L.; Porras, P.; Raghunath, A.; Ricard-Blum, S.; Roechert, B.; Stutz, A.; Tognolli, M.; van Roey, K.; Cesareni, G.; Hermjakob, H., The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res 2014, 42, (Database issue), D358-D363.
20. Licata, L.; Briganti, L.; Peluso, D.; Perfetto, L.; Iannuccelli, M.; Galeota, E.; Sacco, F.; Palma, A.; Nardozza, A. P.; Santonico, E.; Castagnoli, L.; Cesareni, G., MINT, the molecular interaction database: 2012 update. Nucleic Acids Res 2012, 40, (Database issue), D857-D861.
21. Min, H.; Yoon, S., Got target?: computational methods for microRNA target prediction and their extension. Experimental & Molecular Medicine 2010, 42, (4), 233-244.
22. Friard, O.; Re, A.; Taverna, D.; De Bortoli, M.; Corá, D., CircuitsDB: a database of mixed microRNA/transcription factor feed-forward regulatory circuits in human and mouse. BMC Bioinformatics 2010, 11, 435-435.
23. Zheng, G.; Tu, K.; Yang, Q.; Xiong, Y.; Wei, C.; Xie, L.; Zhu, Y.; Li, Y., ITFP: an integrated platform of mammalian transcription factors. Bioinformatics 2008, 24, (20), 2416-2417.
24. Bovolenta, L. A.; Acencio, M. L.; Lemke, N., HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions. BMC Genomics 2012, 13, (1), 405.
25. Wingender, E.; Chen, X.; Hehl, R.; Karas, H.; Liebich, I.; Matys, V.; Meinhardt, T.; Prüss, M.; Reuter, I.; Schacherer, F., TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res 2000, 28, (1), 316-319.
26. Calderone, A.; Licata, L.; Cesareni, G., VirusMentha: a new resource for virus-host protein interactions. Nucleic Acids Res 2014, 43, (D1), D588-D592.
27. Orchard, S.; Kerrien, S.; Abbani, S.; Aranda, B.; Bhate, J.; Bidwell, S.; Bridge, A.; Briganti, L.; Brinkman, F. S. L.; Cesareni, G.; Chatr-aryamontri, A.; Chautard, E.; Chen, C.; Dumousseau, M.; Goll, J.; Hancock, R. E. W.; Hannick, L. I.; Jurisica, I.; Khadake, J.; Lynn, D. J.; Mahadevan, U.; Perfetto, L.; Raghunath, A.; Ricard-Blum, S.; Roechert, B.; Salwinski, L.; Stümpflen, V.; Tyers, M.; Uetz, P.; Xenarios, I.; Hermjakob, H., Protein interaction data curation: the International Molecular Exchange (IMEx) consortium. Nature Methods 2012, 9, (4), 345-350.
28. del-Toro, N.; Dumousseau, M.; Orchard, S.; Jimenez, R. C.; Galeota, E.; Launay, G.; Goll, J.; Breuer, K.; Ono, K.; Salwinski, L.; Hermjakob, H., A new reference implementation of the PSICQUIC web service. Nucleic Acids Res 2013, 41, (W1), W601-W606.
29. Wu, Z.-J.; Zhu, Y.; Huang, D.-R.; Wang, Z.-Q., Constructing the HBV-human protein interaction network to understand the relationship between HBV and hepatocellular carcinoma. J Exp Clin Cancer Res 2010, 29, (1), 146-146.
30. Qureshi, A.; Thakur, N.; Monga, I.; Thakur, A.; Kumar, M., VIRmiRNA: a comprehensive resource for experimentally validated viral miRNAs and their targets. Database 2014, 2014. https://doi.org/10.1093/database/bau103.
31. Li, C.-W.; Wang, W.-H.; Chen, B.-S., Investigating the specific core genetic-and-epigenetic networks of cellular mechanisms involved in human aging in peripheral blood mononuclear cells. Oncotarget 2016, 7, (8), 8556-8579.
32. Xiao, F.; Zuo, Z.; Cai, G.; Kang, S.; Gao, X.; Li, T., miRecords: an integrated resource for microRNA–target interactions. Nucleic Acids Res 2008, 37, (suppl_1), D105-D110.
33. Li, J.-H.; Liu, S.; Zhou, H.; Qu, L.-H.; Yang, J.-H., starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res 2013, 42, (D1), D92-D97.
34. Hsu, S.-D.; Lin, F.-M.; Wu, W.-Y.; Liang, C.; Huang, W.-C.; Chan, W.-L.; Tsai, W.-T.; Chen, G.-Z.; Lee, C.-J.; Chiu, C.-M.; Chien, C.-H.; Wu, M.-C.; Huang, C.-Y.; Tsou, A.-P.; Huang, H.-D., miRTarBase: a database curates experimentally validated microRNA–target interactions. Nucleic Acids Res 2010, 39, (suppl_1), D163-D169.
35. Kim, D.; Lee, J.; So, C.; Jeon, H.; Jeong, M.; Choi, Y.; Yoon, W.; Sung, M.; Kang, J., A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining. IEEE Access 2019, 7, 1.
36. Lee, J.; Yoon, W.; Kim, S.; Kim, D.; Kim, S.; So, C.; Kang, J., BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics (Oxford, England) 2019, 1, 36.
37. Liu, H.; Hu, Z.-Z.; Zhang, J.; Wu, C., BioThesaurus: a web-based thesaurus of protein and gene names. Bioinformatics 2005, 22, (1), 103-105.
38. Vogel, C.; Marcotte, E. M., Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet 2012, 13, (4), 227-232.
39. Eulalio, A.; Huntzinger, E.; Izaurralde, E., Getting to the Root of miRNA-Mediated Gene Silencing. Cell 2008, 132, (1), 9-14.
40. Zhang, S.; Pointer, D.; Singer, G.; Feng, Y.; Park, K.; Zhao, L. J., Direct binding to nucleic acids by Vpr of human immunodeficiency virus type 1. Gene 1998, 212, (2), 157-166.
41. Williams, J. S.; Andrisani, O. M., The hepatitis B virus X protein targets the basic region-leucine zipper domain of CREB. Proceedings of the National Academy of Sciences 1995, 92, (9), 3819.
42. Cheong, J. H.; Yi, M.; Lin, Y.; Murakami, S., Human RPB5, a subunit shared by eukaryotic nuclear RNA polymerases, binds human hepatitis B virus X protein and may play a role in X transactivation. The EMBO journal 1995, 14, (1), 143-150.
43. Maguire, H. F.; Hoeffler, J. P.; Siddiqui, A., HBV X protein alters the DNA binding specificity of CREB and ATF-2 by protein-protein interactions. Science 1991, 252, (5007), 842.
44. Kuzhandaivelu, N.; Cong, Y. S.; Inouye, C.; Yang, W. M.; Seto, E., XAP2, a novel hepatitis B virus X-associated protein that inhibits X transactivation. Nucleic Acids Res 1996, 24, (23), 4741-4750.
45. Ganem, D.; Prince, A. M., Hepatitis B virus infection--natural history and clinical consequences. N Engl J Med 2004, 350, (11), 1118-29.
46. Mitra, B.; Thapa, R. J.; Guo, H.; Block, T. M., Host functions used by hepatitis B virus to complete its life cycle: Implications for developing host-targeting agents to treat chronic hepatitis B. Antiviral research 2018, 158, 185-198.
47. Walsh, D.; Mohr, I., Viral subversion of the host protein synthesis machinery. Nature Reviews Microbiology 2011, 9, (12), 860-875.
48. Lu, P.; Vogel, C.; Wang, R.; Yao, X.; Marcotte, E. M., Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nature Biotechnology 2007, 25, (1), 117-124.
49. Anderson, L.; Seilhamer, J., A comparison of selected mRNA and protein abundances in human liver. ELECTROPHORESIS 1997, 18, (3‐4), 533-537.
50. de Sousa Abreu, R.; Penalva, L. O.; Marcotte, E. M.; Vogel, C., Global signatures of protein and mRNA expression levels. Mol Biosyst 2009, 5, (12), 1512-1526.
51. Maier, T.; Güell, M.; Serrano, L., Correlation of mRNA and protein in complex biological samples. FEBS Letters 2009, 583, (24), 3966-3973.
52. Wang, Y. C.; Chen, B. S., Integrated cellular network of transcription regulations and protein-protein interactions. BMC Syst Biol 2010, 4, 20.
53. Akaike, H., A New Look at the Statistical Model Identification. In Selected Papers of Hirotugu Akaike, Parzen, E.; Tanabe, K.; Kitagawa, G., Eds. Springer New York: New York, NY, 1998; pp 215-222.
54. The UniProt, C., UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res 2018, 47, (D1), D506-D515.
55. Knox, C.; Law, V.; Jewison, T.; Liu, P.; Ly, S.; Frolkis, A.; Pon, A.; Banco, K.; Mak, C.; Neveu, V.; Djoumbou, Y.; Eisner, R.; Guo, A. C.; Wishart, D. S., DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res 2011, 39, (Database issue), 1035-1041.
56. Gaulton, A.; Bellis, L. J.; Bento, A. P.; Chambers, J.; Davies, M.; Hersey, A.; Light, Y.; McGlinchey, S.; Michalovich, D.; Al-Lazikani, B.; Overington, J. P., ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 2012, 40, (Database issue), D1100-D1107.
57. Kim, S.; Thiessen, P. A.; Bolton, E. E.; Chen, J.; Fu, G.; Gindulyte, A.; Han, L.; He, J.; He, S.; Shoemaker, B. A.; Wang, J.; Yu, B.; Zhang, J.; Bryant, S. H., PubChem Substance and Compound databases. Nucleic Acids Res 2016, 44, (D1), D1202-D1213.
58. Liu, T.; Lin, Y.; Wen, X.; Jorissen, R. N.; Gilson, M. K., BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities. Nucleic Acids Res 2006, 35, (suppl_1), D198-D201.
59. Khan, S. A.; Virtanen, S.; Kallioniemi, O. P.; Wennerberg, K.; Poso, A.; Kaski, S., Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis. Bioinformatics (Oxford, England) 2014, 30, (17), i497-i504.
60. Nandy, A.; Harle, M.; Basak, S., Mathematical descriptors of DNA sequences: Development and applications. General Papers ARKIVOC 2006, 9, 211-238.
61. Gron, A., Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O’Reilly Media, Inc.: Newton, Massachusetts, USA, 2017.
62. Raschka, S., Python Machine Learning. Packt Publishing: Birmingham, UK, 2015.
63. Abdi, H.; Williams, L. J., Principal component analysis. WIREs Computational Statistics 2010, 2, (4), 433-459.
64. Goodfellow, I.; Bengio, Y.; Courville, A., Deep Learning. The MIT Press: Cambridge, Massachusetts, USA, 2016.
65. Kingma, D.; Ba, J., Adam: A Method for Stochastic Optimization. International Conference on Learning Representations 2014, 9.
66. Bradley, A. P., The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition 1997, 30, (7), 1145-1159.
67. Tiollais, P.; Pourcel, C.; Dejean, A., The hepatitis B virus. Nature 1985, 317, (6037), 489-495.
68. Ganem, D.; Varmus, H. E., THE MOLECULAR BIOLOGY OF THE HEPATITIS B VIRUSES. Annual Review of Biochemistry 1987, 56, (1), 651-693.
69. Tuttleman, J. S.; Pourcel, C.; Summers, J., Formation of the pool of covalently closed circular viral DNA in hepadnavirus-infected cells. Cell 1986, 47, (3), 451-460.
70. Zakaria, M.; Sankhyan, A.; Ali, A.; Fatima, K.; Azhar, E.; Qadri, I., HBV/HCV Infection and Inflammation. J Genet Syndr Gene Ther 2014, 5: 241.
71. Chen, L.; Deng, H.; Cui, H.; Fang, J.; Zuo, Z.; Deng, J.; Li, Y.; Wang, X.; Zhao, L., Inflammatory responses and inflammation-associated diseases in organs. Oncotarget 2017, 9, (6), 7204-7218.
72. Garcia-Gomez, A.; Rodríguez-Ubreva, J.; Ballestar, E., Epigenetic interplay between immune, stromal and cancer cells in the tumor microenvironment. Clin Immunol 2018, 196, 64-71.
73. Ma, Z.; Cao, Q.; Xiong, Y.; Zhang, E.; Lu, M., Interaction between Hepatitis B Virus and Toll-Like Receptors: Current Status and Potential Therapeutic Use for Chronic Hepatitis B. Vaccines (Basel) 2018, 6, (1), 6.
74. Jacobs, M. D.; Harrison, S. C., Structure of an IκBα/NF-κB Complex. Cell 1998, 95, (6), 749-758.
75. Tanaka, T.; Narazaki, M.; Kishimoto, T., IL-6 in inflammation, immunity, and disease. Cold Spring Harb Perspect Biol 2014, 6, (10), a016295-a016295.
76. Lee, Y.; Park, U. S.; Choi, I.; Yoon, S. K.; Park, Y. M.; Lee, Y. I., Human interleukin 6 gene is activated by hepatitis B virus-X protein in human hepatoma cells. Clinical Cancer Research 1998, 4, (7), 1711.
77. Ivashkiv, L. B.; Donlin, L. T., Regulation of type I interferon responses. Nat Rev Immunol 2014, 14, (1), 36-49.
78. Schoenborn, J.; Wilson, C., Regulation of Interferon‐γ During Innate and Adaptive Immune Responses. Advances in immunology 2007, 96, 41-101.
79. Nolan, G. P.; Fujita, T.; Bhatia, K.; Huppi, C.; Liou, H. C.; Scott, M. L.; Baltimore, D., The bcl-3 proto-oncogene encodes a nuclear I kappa B-like molecule that preferentially interacts with NF-kappa B p50 and p52 in a phosphorylation-dependent manner. Molecular and Cellular Biology 1993, 13, (6), 3557.
80. Kashatus, D.; Cogswell, P.; Baldwin, A. S., Expression of the Bcl-3 proto-oncogene suppresses p53 activation. Genes Dev 2006, 20, (2), 225-235.
81. Dann, S. G.; Thomas, G., The amino acid sensitive TOR pathway from yeast to mammals. FEBS Letters 2006, 580, (12), 2821-2829.
82. Lee, D.-F.; Kuo, H.-P.; Chen, C.-T.; Hsu, J.-M.; Chou, C.-K.; Wei, Y.; Sun, H.-L.; Li, L.-Y.; Ping, B.; Huang, W.-C.; He, X.; Hung, J.-Y.; Lai, C.-C.; Ding, Q.; Su, J.-L.; Yang, J.-Y.; Sahin, A. A.; Hortobagyi, G. N.; Tsai, F.-J.; Tsai, C.-H.; Hung, M.-C., IKKβ Suppression of TSC1 Links Inflammation and Tumor Angiogenesis via the mTOR Pathway. Cell 2007, 130, (3), 440-455.
83. Richter, J. D.; Sonenberg, N., Regulation of cap-dependent translation by eIF4E inhibitory proteins. Nature 2005, 433, (7025), 477-480.
84. Mohr, I., Phosphorylation and dephosphorylation events that regulate viral mRNA translation. Virus Research 2006, 119, (1), 89-99.
85. Ryu, D.-K.; Ahn, B.-Y.; Ryu, W.-S., Proximity between the cap and 5′ ε stem–loop structure is critical for the suppression of pgRNA translation by the hepatitis B viral polymerase. Virology 2010, 406, (1), 56-64.
86. Sugatani, T.; Hruska, K. A., Akt1/Akt2 and mammalian target of rapamycin/Bim play critical roles in osteoclast differentiation and survival, respectively, whereas Akt is dispensable for cell survival in isolated osteoclast precursors. J Biol Chem 2005, 280, (5), 3583-3589.
87. Inoki, K.; Li, Y.; Zhu, T.; Wu, J.; Guan, K.-L., TSC2 is phosphorylated and inhibited by Akt and suppresses mTOR signalling. Nature Cell Biology 2002, 4, (9), 648-657.
88. Ogawara, Y.; Kishishita, S.; Obata, T.; Isazawa, Y.; Suzuki, T.; Tanaka, K.; Masuyama, N.; Gotoh, Y., Akt Enhances Mdm2-mediated Ubiquitination and Degradation of p53. J Biol Chem 2002, 277, 21843-50.
89. Chiu, A. P.; Tschida, B. R.; Sham, T.-T.; Lo, L. H.; Moriarity, B. S.; Li, X.-X.; Lo, R. C.; Hinton, D. E.; Rowlands, D. K.; Chan, C.-O.; Mok, D. K. W.; Largaespada, D. A.; Warner, N.; Keng, V. W., HBx-K130M/V131I Promotes Liver Cancer in Transgenic Mice via AKT/FOXO1 Signaling Pathway and Arachidonic Acid Metabolism. Molecular Cancer Research 2019, 17, (7), 1582.
90. Burton, T. R.; Gibson, S. B., The role of Bcl-2 family member BNIP3 in cell death and disease: NIPping at the heels of cell death. Cell Death Differ 2009, 16, (4), 515-523.
91. Liu, J.; Cao, L.; Chen, J.; Song, S.; Lee, I. H.; Quijano, C.; Liu, H.; Keyvanfar, K.; Chen, H.; Cao, L.-Y.; Ahn, B.-H.; Kumar, N. G.; Rovira, I. I.; Xu, X.-L.; van Lohuizen, M.; Motoyama, N.; Deng, C.-X.; Finkel, T., Bmi1 regulates mitochondrial function and the DNA damage response pathway. Nature 2009, 459, (7245), 387-392.
92. Alkema, M.; Wiegant, J.; Raap, A. K.; Bems, A.; van Lohuizen, M., Characterization and chromosomal localization of the human proto-oncogene BMI-1. Human Molecular Genetics 1993, 2, (10), 1597-1603.
93. Danial, N. N.; Korsmeyer, S. J., Cell Death: Critical Control Points. Cell 2004, 116, (2), 205-219.
94. Oh, H.-M.; Yu, C.-R.; Dambuza, I.; Marrero, B.; Egwuagu, C. E., STAT3 protein interacts with Class O Forkhead transcription factors in the cytoplasm and regulates nuclear/cytoplasmic localization of FoxO1 and FoxO3a proteins in CD4(+) T cells. J Biol Chem 2012, 287, (36), 30436-30443.
95. Shlomai, A.; Shaul, Y., The metabolic activator FOXO1 binds hepatitis B virus DNA and activates its transcription. Biochemical and Biophysical Research Communications 2009, 381, (4), 544-548.
96. Hirata, Y.; Takahashi, M.; Morishita, T.; Noguchi, T.; Matsuzawa, A., Post-Translational Modifications of the TAK1-TAB Complex. Int J Mol Sci 2017, 18, (1), 205.
97. Shaulian, E.; Karin, M., AP-1 as a regulator of cell life and death. Nature Cell Biology 2002, 4, (5), E131-E136.
98. Schonthaler, H. B.; Guinea-Viniegra, J.; Wagner, E. F., Targeting inflammation by modulating the Jun/AP-1 pathway. Annals of the Rheumatic Diseases 2011, 70, (Suppl 1), i109.
99. Akira, S., The role of IL-18 in innate immunity. Current Opinion in Immunology 2000, 12, (1), 59-63.
100. Qin, W.; Hu, L.; Zhang, X.; Jiang, S.; Li, J.; Zhang, Z.; Wang, X., The Diverse Function of PD-1/PD-L Pathway Beyond Cancer. Front Immunol 2019, 10, 2298-2298.
101. Motokura, T.; Bloom, T.; Kim, H. G.; Jüppner, H.; Ruderman, J. V.; Kronenberg, H. M.; Arnold, A., A novel cyclin encoded by a bcl1-linked candidate oncogene. Nature 1991, 350, (6318), 512-515.
102. Fujioka, S.; Niu, J.; Schmidt, C.; Sclabas, G. M.; Peng, B.; Uwagawa, T.; Li, Z.; Evans, D. B.; Abbruzzese, J. L.; Chiao, P. J., NF-κB and AP-1 Connection: Mechanism of NF-κB-Dependent Regulation of AP-1 Activity. Molecular and Cellular Biology 2004, 24, (17), 7806.
103. Rebollo, A.; Dumoutier, L.; Renauld, J. C.; Zaballos, A.; Ayllón, V.; Martínez-A, C., Bcl-3 expression promotes cell survival following interleukin-4 deprivation and is controlled by AP1 and AP1-like transcription factors. Molecular and cellular biology 2000, 20, (10), 3407-3416.
104. Lee, J.-Y.; Koga, H.; Kawaguchi, Y.; Tang, W.; Wong, E.; Gao, Y.-S.; Pandey, U. B.; Kaushik, S.; Tresse, E.; Lu, J.; Taylor, J. P.; Cuervo, A. M.; Yao, T.-P., HDAC6 controls autophagosome maturation essential for ubiquitin-selective quality-control autophagy. The EMBO Journal 2010, 29, (5), 969-980.
105. Aaronson, D. S.; Horvath, C. M., A road map for those who don't know JAK-STAT. Science 2002, 296, (5573), 1653-5.
106. Stark, G. R.; Kerr, I. M.; Williams, B. R.; Silverman, R. H.; Schreiber, R. D., How cells respond to interferons. Annu Rev Biochem 1998, 67, 227-64.
107. Ferrari, S. M.; Fallahi, P.; Ruffilli, I.; Elia, G.; Ragusa, F.; Paparo, S. R.; Patrizio, A.; Mazzi, V.; Colaci, M.; Giuggioli, D.; Ferri, C.; Antonelli, A., Immunomodulation of CXCL10 Secretion by Hepatitis C Virus: Could CXCL10 Be a Prognostic Marker of Chronic Hepatitis C? J Immunol Res 2019, 2019, 5878960. https://doi.org/10.1155/2019/5878960.
108. Park, J.-W.; Li, Z.; Choi, J.-S.; Oh, H.-J.; Park, S.-H.; Yoon, K.-C., Expression of CXCL9, -10, and -11 in the Aqueous Humor of Patients With Herpetic Endotheliitis. Cornea 2012, 31, (11), 1246-50.
109. Nordmann, A.; Wixler, L.; Boergeling, Y.; Wixler, V.; Ludwig, S., A new splice variant of the human guanylate-binding protein 3 mediates anti-influenza activity through inhibition of viral transcription and replication. The FASEB Journal 2011, 26, (3), 1290-1300.
110. Ueda, T.; Watanabe-Fukunaga, R.; Fukuyama, H.; Nagata, S.; Fukunaga, R., Mnk2 and Mnk1 are essential for constitutive and inducible phosphorylation of eukaryotic initiation factor 4E but not for cell growth or development. Molecular and cellular biology 2004, 24, (15), 6539-6549.
111. Porter, A. G.; Jänicke, R. U., Emerging roles of caspase-3 in apoptosis. Cell Death & Differentiation 1999, 6, (2), 99-104.
112. Stennicke, H.; Jürgensmeier, J.; Shin, H.; Deveraux, Q.; Wolf, B.; Yang, X.; Zhou, Q.; Ellerby, H.; Ellerby, L.; Bredesen, D.; Green, D.; Reed, J.; Froelich, C.; Salvesen, G., Pro-caspase-3 Is a Major Physiologic Target of Caspase8. J Biol Chem 1998, 273, 27084-90.
113. Wang, J.; Chun, H. J.; Wong, W.; Spencer, D. M.; Lenardo, M. J., Caspase-10 is an initiator caspase in death receptor signaling. Proceedings of the National Academy of Sciences 2001, 98, (24), 13884.
114. Dikic, I.; Elazar, Z., Mechanism and medical implications of mammalian autophagy. Nature Reviews Molecular Cell Biology 2018, 19, (6), 349-364.
115. Gottlieb, T. M.; Jackson, S. P., The DNA-dependent protein kinase: Requirement for DNA ends and association with Ku antigen. Cell 1993, 72, (1), 131-142.
116. Liu, X.; Zou, H.; Slaughter, C.; Wang, X., DFF, a Heterodimeric Protein That Functions Downstream of Caspase-3 to Trigger DNA Fragmentation during Apoptosis. Cell 1997, 89, (2), 175-184.
117. Dan, H.; Sun, M.; Kaneko, S.; Feldman, R.; Nicosia, S.; Wang, H.-G.; Tsang, B.; Cheng, J., Akt Phosphorylation and Stabilization of X-linked Inhibitor of Apoptosis Protein (XIAP). J Biol Chem 2004, 279, 5405-12.
118. Scott, F. L.; Denault, J.-B.; Riedl, S. J.; Shin, H.; Renatus, M.; Salvesen, G. S., XIAP inhibits caspase-3 and -7 using two binding sites: evolutionarily conserved mechanism of IAPs. The EMBO Journal 2005, 24, (3), 645-655.
119. Ahnesorg, P.; Smith, P.; Jackson, S. P., XLF Interacts with the XRCC4-DNA Ligase IV Complex to Promote DNA Nonhomologous End-Joining. Cell 2006, 124, (2), 301-313.
120. Wang, S.; Qiu, L.; Yan, X.; Jin, W.; Wang, Y.; Chen, L.; Wu, E.; Ye, X.; Gao, G. F.; Wang, F.; Chen, Y.; Duan, Z.; Meng, S., Loss of microRNA 122 expression in patients with hepatitis B enhances hepatitis B virus replication through cyclin G1-modulated P53 activity. Hepatology 2012, 55, (3), 730-741.
121. Wang, X. W.; Gibson, M. K.; Vermeulen, W.; Yeh, H.; Forrester, K.; Stürzbecher, H. W.; Hoeijmakers, J. H.; Harris, C. C., Abrogation of p53-induced apoptosis by the hepatitis B virus X gene. Cancer Res 1995, 55, (24), 6012-6.
122. Lee, S. G.; Rho, H. M., Transcriptional repression of the human p53 gene by hepatitis B viral X protein. Oncogene 2000, 19, (3), 468-71.
123. Moll, U. M.; Petrenko, O., The MDM2-p53 Interaction. Molecular Cancer Research 2003, 1, (14), 1001.
124. Cregan, S. P.; MacLaurin, J. G.; Craig, C. G.; Robertson, G. S.; Nicholson, D. W.; Park, D. S.; Slack, R. S., Bax-Dependent Caspase-3 Activation Is a Key Determinant in p53-Induced Apoptosis in Neurons. The Journal of Neuroscience 1999, 19, (18), 7860.
125. Chipuk, J. E.; Kuwana, T.; Bouchier-Hayes, L.; Droin, N. M.; Newmeyer, D. D.; Schuler, M.; Green, D. R., Direct Activation of Bax by p53 Mediates Mitochondrial Membrane Permeabilization and Apoptosis. Science 2004, 303, (5660), 1010.
126. Sofer, A.; Lei, K.; Johannessen, C. M.; Ellisen, L. W., Regulation of mTOR and cell growth in response to energy stress by REDD1. Molecular and cellular biology 2005, 25, (14), 5834-5845.
127. Ellisen, L. W.; Ramsayer, K. D.; Johannessen, C. M.; Yang, A.; Beppu, H.; Minda, K.; Oliner, J. D.; McKeon, F.; Haber, D. A., REDD1, a Developmentally Regulated Transcriptional Target of p63 and p53, Links p63 to Regulation of Reactive Oxygen Species. Molecular Cell 2002, 10, (5), 995-1005.
128. Pineau, P.; Volinia, S.; McJunkin, K.; Marchio, A.; Battiston, C.; Terris, B.; Mazzaferro, V.; Lowe, S. W.; Croce, C. M.; Dejean, A., miR-221 overexpression contributes to liver tumorigenesis. Proc Natl Acad Sci U S A 2010, 107, (1), 264-269.
129. Fu, X.; Tan, D.; Hou, Z.; Hu, Z.; Liu, G., miR-338-3p is down-regulated by hepatitis B virus X and inhibits cell proliferation by targeting the 3'-UTR region of CyclinD1. Int J Mol Sci 2012, 13, (7), 8514-39.
130. Lu, R.; Yang, Z.; Xu, G.; Yu, S., miR-338 modulates proliferation and autophagy by PI3K/AKT/mTOR signaling pathway in cervical cancer. Biomedicine & Pharmacotherapy 2018, 105, 633-644.
131. Darnell, J. E.; Kerr, I. M.; Stark, G. R., Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins. Science 1994, 264, (5164), 1415.
132. Wu, M.; Xu, Y.; Lin, S.; Zhang, X.; Xiang, L.; Yuan, Z., Hepatitis B virus polymerase inhibits the interferon-inducible MyD88 promoter by blocking nuclear translocation of Stat 1. The Journal of general virology 2008, 88, 3260-9.
133. Gao, D.; Zhai, A.; Qian, J.; Li, A.; Li, Y.; Song, W.; Zhao, H.; Yu, X.; Wu, J.; Zhang, Q.; Kao, W.; Wei, L.; Zhang, F.; Zhong, Z., Down-regulation of suppressor of cytokine signaling 3 by miR-122 enhances interferon-mediated suppression of hepatitis B virus. Antiviral Research 2015, 118, 20-28.
134. Li, A.; Song, W.; Qian, J.; Li, Y.; He, J.; Zhang, Q.; Li, W.; Zhai, A.; Kao, W.; Hu, Y.; Li, H.; Wu, J.; Ling, H.; Zhong, Z.; Zhang, F., MiR-122 modulates type I interferon expression through blocking suppressor of cytokine signaling 1. The International Journal of Biochemistry & Cell Biology 2013, 45, (4), 858-865.
135. Xavier, G.; Antoine, B.; Yoshua, B., Deep Sparse Rectifier Neural Networks. In PMLR: 2011; Vol. 15, pp 315-323.
136. Srivastava, N.; Hinton, G.; Krizhevsky, A.; Sutskever, I.; Salakhutdinov, R., Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 2014, 15, (1), 1929–1958.
137. Srivastava, N.; Hinton, G.; Krizhevsky, A.; Sutskever, I.; Salakhutdinov, R., Dropout: A Simple Way to Prevent Neural Networks from Overfitting. Journal of Machine Learning Research 2014, 15, 1929-1958.
138. Cao, D. S.; Zhang, L. X.; Tan, G. S.; Xiang, Z.; Zeng, W. B.; Xu, Q. S.; Chen, A. F., Computational Prediction of DrugTarget Interactions Using Chemical, Biological, and Network Features. Mol Inform 2014, 33, (10), 669-81.
139. Byvatov, E.; Fechner, U.; Sadowski, J.; Schneider, G., Comparison of support vector machine and artificial neural network systems for drug/nondrug classification. J Chem Inf Comput Sci 2003, 43, (6), 1882-9.
140. Liu, Y.; Wu, M.; Miao, C.; Zhao, P.; Li, X.-L., Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction. PLoS Comput Biol 2016, 12, (2), e1004760-e1004760.
141. LeBeau, J. E., The role of the LD50 determination in drug safety evaluation. Regulatory Toxicology and Pharmacology 1983, 3, (1), 71-74.
142. Wilhelm, S.; Carter, C.; Lynch, M.; Lowinger, T.; Dumas, J.; Smith, R. A.; Schwartz, B.; Simantov, R.; Kelley, S., Discovery and development of sorafenib: a multikinase inhibitor for treating cancer. Nature Reviews Drug Discovery 2006, 5, (10), 835-844.
143. Ibrahim, N.; Yu, Y.; Walsh, W. R.; Yang, J. L., Molecular targeted therapies for cancer: sorafenib mono-therapy and its combination with other therapies (review). Oncol Rep 2012, 27, (5), 1303-11.
144. Miao, R.; Xu, X.; Wang, Z.; Liu, S.; Qu, K.; Chen, W.; Liu, C., Synergistic effect of nutlin-3 combined with aspirin in hepatocellular carcinoma HepG2 cells through activation of Bcl-2/Bax signaling pathway. Mol Med Rep 2018, 17, (3), 3735-3743.
145. Tokalov, S. V.; Abolmaali, N. D., Protection of p53 wild type cells from taxol by nutlin-3 in the combined lung cancer treatment. BMC Cancer 2010, 10, (1), 57.
146. Zheng, T.; Wang, J.; Song, X.; Meng, X.; Pan, S.; Jiang, H.; Liu, L., Nutlin-3 cooperates with doxorubicin to induce apoptosis of human hepatocellular carcinoma cells through p53 or p73 signaling pathways. J Cancer Res Clin Oncol 2010, 136, (10), 1597-604.
147. Fernandez-Fernandez, B.; Montoya-Ferrer, A.; Sanz, A. B.; Sanchez-Niño, M. D.; Izquierdo, M. C.; Poveda, J.; Sainz-Prestel, V.; Ortiz-Martin, N.; Parra-Rodriguez, A.; Selgas, R.; Ruiz-Ortega, M.; Egido, J.; Ortiz, A., Tenofovir nephrotoxicity: 2011 update. AIDS Res Treat 2011, 2011, 354908-354908.
148. Martin, P.; Lau, D. T.; Nguyen, M. H.; Janssen, H. L.; Dieterich, D. T.; Peters, M. G.; Jacobson, I. M., A Treatment Algorithm for the Management of Chronic Hepatitis B Virus Infection in the United States: 2015 Update. Clin Gastroenterol Hepatol 2015, 13, (12), 2071-87.e16.
149. Lee, Y. B.; Lee, J.-H.; Lee, D. H.; Cho, H.; Ahn, H.; Choi, W.-M.; Cho, Y. Y.; Lee, M.; Yoo, J.-J.; Cho, Y.; Cho, E. J.; Yu, S. J.; Kim, Y. J.; Yoon, J.-H.; Kim, C. Y.; Lee, H.-S., Efficacy of Entecavir-Tenofovir Combination Therapy for Chronic Hepatitis B Patients with Multidrug-Resistant Strains. Antimicrobial Agents and Chemotherapy 2014, 58, (11), 6710.
150. Marcellin, P.; Ahn, S. H.; Ma, X.; Caruntu, F. A.; Tak, W. Y.; Elkashab, M.; Chuang, W.-L.; Lim, S.-G.; Tabak, F.; Mehta, R.; Petersen, J.; Foster, G. R.; Lou, L.; Martins, E. B.; Dinh, P.; Lin, L.; Corsa, A.; Charuworn, P.; Subramanian, G. M.; Reiser, H.; Reesink, H. W.; Fung, S.; Strasser, S. I.; Trinh, H.; Buti, M.; Gaeta, G. B.; Hui, A. J.; Papatheodoridis, G.; Flisiak, R.; Chan, H. L. Y., Combination of Tenofovir Disoproxil Fumarate and Peginterferon α-2a Increases Loss of Hepatitis B Surface Antigen in Patients With Chronic Hepatitis B. Gastroenterology 2016, 150, (1), 134-144.e10.
151. Fung, J.; Lai, C. L.; Seto, W. K.; Yuen, M. F., Nucleoside/nucleotide analogues in the treatment of chronic hepatitis B. J Antimicrob Chemother 2011, 66, (12), 2715-25.
152. Kew, M. C., Hepatitis B virus x protein in the pathogenesis of hepatitis B virus-induced hepatocellular carcinoma. Journal of Gastroenterology and Hepatology 2011, 26, (s1), 144-152.
153. Diao, J.; Khine, A. A.; Sarangi, F.; Hsu, E.; Iorio, C.; Tibbles, L. A.; Woodgett, J. R.; Penninger, J.; Richardson, C. D., X protein of hepatitis B virus inhibits Fas-mediated apoptosis and is associated with up-regulation of the SAPK/JNK pathway. J Biol Chem 2001, 276, (11), 8328-40.
154. Lee, Y. I.; Kang-Park, S.; Do, S. I.; Lee, Y. I., The hepatitis B virus-X protein activates a phosphatidylinositol 3-kinase-dependent survival signaling cascade. J Biol Chem 2001, 276, (20), 16969-77.
155. Gottlob, K.; Fulco, M.; Levrero, M.; Graessmann, A., The Hepatitis B Virus HBx Protein Inhibits Caspase 3 Activity. J Biol Chem 1999, 273, 33347-53.
156. Su, F.; Theodosis, C. N.; Schneider, R. J., Role of NF-κB and Myc Proteins in Apoptosis Induced by Hepatitis B Virus HBx Protein. Journal of Virology 2001, 75, (1), 215.
157. Wang, T.; Wang, Y.; Wu, M.-C.; Guan, X.-Y.; Yin, Z.-F., Activating mechanism of transcriptor NF-kappaB regulated by hepatitis B virus X protein in hepatocellular carcinoma. World J Gastroenterol 2004, 10, (3), 356-360.
158. Park, U. S.; Park, S. K.; Lee, Y. I.; Park, J. G.; Lee, Y. I., Hepatitis B virus-X protein upregulates the expression of p21waf1/cip1 and prolongs G1-->S transition via a p53-independent pathway in human hepatoma cells. Oncogene 2000, 19, (30), 3384-3394.
159. Al-Anazi, M. R.; Nazir, N.; Colak, D.; Al-Ahdal, M. N.; Al-Qahtani, A. A., Deletion and Functional Analysis of Hepatitis B Virus X Protein: Evidence for an Effect on Cell Cycle Regulators. Cellular Physiology and Biochemistry 2018, 49, (5), 1987-1998.
160. Abbas, T.; Dutta, A., p21 in cancer: intricate networks and multiple activities. Nature Reviews Cancer 2009, 9, (6), 400-414.
161. Park, U. S.; Park, S. K.; Lee, Y. I.; Park, J. G.; Lee, Y. I., Hepatitis B virus-X protein upregulates the expression of p21wafl/cipl and prolongs G1→S transition via a p53-independent pathway in human hepatoma cells. Oncogene 2000, 19, (30), 3384-3394.
162. Tang, H.; Da, L.; Mao, Y.; Li, Y.; Li, D.; Xu, Z.; Li, F.; Wang, Y.; Tiollais, P.; Li, T.; Zhao, M., Hepatitis B virus X protein sensitizes cells to starvation-induced autophagy via up-regulation of beclin 1 expression. Hepatology 2009, 49, (1), 60-71.
163. Liu, B.; Fang, M.; Hu, Y.; Huang, B.; Li, N.; Chang, C.; Huang, R.; Xu, X.; Yang, Z.; Chen, Z.; Liu, W., Hepatitis B virus X protein inhibits autophagic degradation by impairing lysosomal maturation. Autophagy 2014, 10, (3), 416-30.
164. Rautou, P.-E.; Mansouri, A.; Lebrec, D.; Durand, F.; Valla, D.; Moreau, R., Autophagy in liver diseases. Journal of Hepatology 2010, 53, (6), 1123-1134.
165. Li, J.; Liu, Y.; Wang, Z.; Liu, K.; Wang, Y.; Liu, J.; Ding, H.; Yuan, Z., Subversion of Cellular Autophagy Machinery by Hepatitis B Virus for Viral Envelopment. Journal of Virology 2011, 85, (13), 6319.
166. Sir, D.; Tian, Y.; Chen, W.-l.; Ann, D. K.; Yen, T.-S. B.; Ou, J.-h. J., The early autophagic pathway is activated by hepatitis B virus and required for viral DNA replication. Proceedings of the National Academy of Sciences 2010, 107, (9), 4383.
167. Yang, C.-J.; Liu, Y.-P.; Dai, H.-Y.; Shiue, Y.-L.; Tsai, C.-J.; Huang, M.-S.; Yeh, Y.-T., Nuclear HDAC6 inhibits invasion by suppressing NF-κB/MMP2 and is inversely correlated with metastasis of non-small cell lung cancer. Oncotarget 2015, 6, (30), 30263-30276.
168. Kim, M.; Lu, F.; Zhang, Y., Loss of HDAC-Mediated Repression and Gain of NF-κB Activation Underlie Cytokine Induction in ARID1A- and PIK3CA-Mutation-Driven Ovarian Cancer. Cell Reports 2016, 17, (1), 275-288.
169. Jung, K. H.; Noh, J. H.; Kim, J. K.; Eun, J. W.; Bae, H. J.; Chang, Y. G.; Kim, M. G.; Park, W. S.; Lee, J. Y.; Lee, S. Y.; Chu, I. S.; Nam, S. W., Histone deacetylase 6 functions as a tumor suppressor by activating c-Jun NH2-terminal kinase-mediated beclin 1-dependent autophagic cell death in liver cancer. Hepatology 2012, 56, (2), 644-57.
170. Jones, S. A., Directing Transition from Innate to Acquired Immunity: Defining a Role for IL-6. The Journal of Immunology 2005, 175, (6), 3463.
171. Busca, A.; Kumar, A., Innate immune responses in hepatitis B virus (HBV) infection. Virol J 2014, 11, 22-22.
172. Ong, E. Z.; Chan, K. R.; Ooi, E. E., Viral Manipulation of Host Inhibitory Receptor Signaling for Immune Evasion. PLoS Pathog 2016, 12, (9), e1005776-e1005776.
173. Luedde, T.; Schwabe, R. F., NF-κB in the liver--linking injury, fibrosis and hepatocellular carcinoma. Nat Rev Gastroenterol Hepatol 2011, 8, (2), 108-118.
174. Schönrich, G.; Raftery, M. J., The PD-1/PD-L1 Axis and Virus Infections: A Delicate Balance. Front Cell Infect Microbiol 2019, 9, 207-207.
175. Germanidis, G.; Argentou, N.; Hytiroglou, P.; Vassiliadis, T.; Patsiaoura, K.; Germenis, A.; Speletas, M., Liver FOXP3 and PD1/PDL1 Expression is Down-Regulated in Chronic HBV Hepatitis on Maintained Remission Related to the Degree of Inflammation. Front Immunol 2013, 4, (207).
176. Hong, F.; Jaruga, B.; Kim, W. H.; Radaeva, S.; El-Assal, O. N.; Tian, Z.; Nguyen, V.-A.; Gao, B., Opposing roles of STAT1 and STAT3 in T cell–mediated hepatitis: regulation by SOCS. The Journal of Clinical Investigation 2002, 110, (10), 1503-1513.
177. Dufour, J.-F.; Clavien, P. A., Signaling Pathways in Liver Diseases. Springer: New York, NY, USA, 2010; p 1-526.