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K. Ponnusamy et al.
References
1. Palumbo A, Anderson K. Multiple myelo- ma. N Engl J Med. 2011;364(11):1046-1060. 2.Morgan GJ, Walker BA, Davies FE. The genetic architecture of multiple myeloma.
Nat Rev Cancer. 2012;12(5):335-348. 3.Manier S, Salem KZ, Park J, Landau DA, Getz G, Ghobrial IM. Genomic complexity of multiple myeloma and its clinical impli- cations. Nat Rev Clin Oncol. 2017;
14(2):100-113.
4. Shi W, Liao Y, Willis SN, et al.
Transcriptional profiling of mouse B cell terminal differentiation defines a signature for antibody-secreting plasma cells. Nat Immunol. 2015;16(6):663-673.
5. Ha SC, Kim D, Hwang H-Y, Rich A, Kim Y-G, Kim KK. The crystal structure of the second Z-DNA binding domain of human DAI (ZBP1) in complex with Z-DNA reveals an unusual binding mode to Z- DNA. Proc Natl Acad Sci U S A. 2008;105 (52):20671-20676.
6. Schwartz T, Behlke J, Lowenhaupt K, Heinemann U, Rich A. Structure of the DLM-1–Z-DNA complex reveals a con- served family of Z-DNA-binding proteins. Nat Struct Biol. 2001;8(9):761-765.
7. Maelfait J, Liverpool L, Bridgeman A, Ragan KB, Upton JW, Rehwinkel J. Sensing of viral and endogenous RNA by ZBP1/DAI induces necroptosis. EMBO J. 2017; 36(17):2529-2543.
8. Thapa RJ, Ingram JP, Ragan KB, et al. DAI senses influenza A virus genomic RNA and activates RIPK3-dependent cell death. Cell Host Microbe. 2016;20(5):674-681.
9. Sridharan H, Ragan KB, Guo H, et al. Murine cytomegalovirus IE3-dependent transcription is required for DAI/ZBP1- mediated necroptosis. EMBO Rep. 2017;18(8):1429-1441.
10. Upton JW, Kaiser WJ, Mocarski ES. DAI/ZBP1/DLM-1 complexes with RIP3 to mediate virus-induced programmed necro- sis that is targeted by murine cytomegalovirus vIRA. Cell Host Microbe. 2012;11(3):290-297.
11. Newton K, Wickliffe KE, Maltzman A, et al. RIPK1 inhibits ZBP1-driven necroptosis during development. Nature. 2016; 540(7631):129-133.
12. Lin J, Kumari S, Kim C, et al. RIPK1 coun- teracts ZBP1-mediated necroptosis to inhibit inflammation. Nature. 2016; 540(7631):124-128.
13. Jiao H, Wachsmuth L, Kumari S, et al. Z- nucleic-acid sensing triggers ZBP1-depen- dent necroptosis and inflammation. Nature. 2020;580(7803):391-395.
14. Tanaka Y, Chen ZJ. STING specifies IRF3 phosphorylation by TBK1 in the cytosolic DNA signaling pathway. Sci Signal. 2012;5(214):ra20.
15.Ablasser A, Goldeck M, Cavlar T, et al. cGAS produces a 2′-5′-linked cyclic dinu- cleotide second messenger that activates STING. Nature. 2013;498(7454):380-384.
16. Mankan AK, Schmidt T, Chauhan D, et al. Cytosolic RNA:DNA hybrids activate the cGAS-STING axis. EMBO J. 2014; 33(24):2937-2946.
17. Takaoka A, Wang Z, Choi MK, et al. DAI
(DLM-1/ZBP1) is a cytosolic DNA sensor and an activator of innate immune response. Nature. 2007;448(7152):501-505.
18. Ishii KJ, Kawagoe T, Koyama S, et al. TANK-binding kinase-1 delineates innate and adaptive immune responses to DNA vaccines. Nature. 2008;451(7179):725-729.
19. Yang D, Liang Y, Zhao S, et al. ZBP1 medi- ates interferon-induced necroptosis. Cell Mol Immunol. 2020;17:356-368.
20. Kuriakose T, Man SM, Malireddi RKS, et al. ZBP1/DAI is an innate sensor of influenza virus triggering the NLRP3 inflammasome and programmed cell death pathways. Sci Immunol. 2016;1(2):aag2045.
21. Sarin V, Yu K, Ferguson ID, et al. Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcrip- tomic correlation analysis. Leukemia. 2020;34(10):2754–2765.
22.Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15-21.
23. Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14(4):417- 419.
24. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.
25. Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 2015;43(7):e47.
26. Zhang Y, Liu T, Meyer CA, et al. Model- based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137.
27. Ramírez F, Ryan DP, Grüning B, et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016;44(W1):W160-165.
28. Thorvaldsdóttir H, Robinson JT, Mesirov JP. Integrative Genomics Viewer (IGV): high-performance genomics data visualiza- tion and exploration. Brief Bioinform. 2013;14(2):178-192.
29. Heinz S, Benner C, Spann N, et al. Simple combinations of lineage-determining tran- scription factors prime cis-regulatory ele- ments required for macrophage and B cell identities. Mol Cell. 2010;38(4):576-589.
minal center B and plasma cell fates by dynamical control of IRF4. Immunity. 2013;38(5):918-929.
35. Buehler E, Chen Y-C, Martin S. C911: a bench-level control for sequence specific siRNA off-target effects. PLoS One. 2012;7(12):e51942.
36. Zuber J, McJunkin K, Fellmann C, et al. Toolkit for evaluating genes required for proliferation and survival using tetracy- cline-regulated RNAi. Nat Biotechnol. 2011;29(1):79-83.
37. Laganà A, Perumal D, Melnekoff D, et al. Integrative network analysis identifies novel drivers of pathogenesis and progres- sion in newly diagnosed multiple myelo- ma. Leukemia. 2018;32(1):120-130.
38. Kuiper R, Broyl A, de Knegt Y, et al. A gene expression signature for high-risk multiple myeloma. Leukemia. 2012;26(11):2406- 2413.
39. Muvaffak A, Pan Q, Yan H, et al. Evaluating TBK1 as a therapeutic target in cancers with activated IRF3. Mol Cancer Res. 2014;12(7):1055-1066.
40. Wang Z, Choi MK, Ban T, et al. Regulation of innate immune responses by DAI (DLM- 1/ZBP1) and other DNA-sensing molecules. Proc Natl Acad Sci U S A. 2008; 105(14):5477-5482.
41. Shaffer AL, Emre NCT, Lamy L, et al. IRF4 addiction in multiple myeloma. Nature. 2008;454(7201):226-231.
42. Zheng R, Wan C, Mei S, et al. Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis. Nucleic Acids Res. 2019;47(D1):D729-D735.
43. Jin Y, Chen K, De Paepe A, et al. Active enhancer and chromatin accessibility land- scapes chart the regulatory network of pri- mary multiple myeloma. Blood. 2018; 131(19):2138-2150.
44. Kesavardhana S, Malireddi RKS, Burton AR, et al. The Zα2 domain of ZBP1 is a molecular switch regulating influenza- induced PANoptosis and perinatal lethality during development. J Biol Chem. 2020;295(24): 8325-8330.
45. Yang D, Liang Y, Zhao S, et al. ZBP1 medi- ates interferon-induced necroptosis. Cell Mol Immunol. 2020;17(4):356-368.
46. Hose D, Rème T, Hielscher T, et al. Proliferation is a central independent prog- nostic factor and target for personalized and risk-adapted treatment in multiple myeloma. Haematologica. 2011;96(1):87-
30. Wang S, Sun H, Ma J, et al. Target analysis
by integration of transcriptome and ChIP-
seq data with BETA. Nat Protoc. 2013;8(12):2502-2515. 95.
31. Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowl- edge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545-15550.
32. Kuleshov MV, Jones MR, Rouillard AD, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016;44(W1): W90-97.
33. Cattoretti G, Shaknovich R, Smith PM, Jäck H-M, Murty VV, Alobeid B. Stages of ger- minal center transit are defined by B cell transcription factor coexpression and rela- tive abundance. J Immunol. 2006; 177(10):6930-6939.
34. Ochiai K, Maienschein-Cline M, Simonetti G, et al. Transcriptional regulation of ger-
47. Rebsamen M, Heinz LX, Meylan E, et al. DAI/ZBP1 recruits RIP1 and RIP3 through RIP homotypic interaction motifs to acti- vate NF-kappaB. EMBO Rep. 2009; 10(8):916-922.
48. Tian W-L, Jiang Z-X, Wang F, et al. IRF3 is involved in human acute myeloid leukemia through regulating the expression of miR- 155. Biochem Biophys Res Commun. 2016;478(3):1130-1135.
49. Pillai S, Nguyen J, Johnson J, Haura E, Coppola D, Chellappan S. Tank binding kinase 1 is a centrosome-associated kinase necessary for microtubule dynamics and mitosis. Nat Commun. 2015;6(1):1-14.
50. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic fea- tures. Bioinformatics. 2010;26(6):841-842.
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