Advances in cancer DNA methylation analysis with methPLIER: use of non-negative matrix factorization and knowledge-based constraints to enhance biological interpretability

참고문헌 (66)

1. Zemach, A., "Genome-wide evolutionary analysis of eukaryotic DNA methylation", Science, 328, pp.916~919 (2010)
2. Greenberg, M. V. C., "The diverse roles of DNA methylation in mammalian development and disease", Nat. Rev. Mol. Cell Biol, 20, pp.590~607 (2019)
3. Kulis, M, "DNA Methylation and Cancer", Adv. Genet, 70, pp.27~56 (2010)
4. Plongthongkum, N., "Advances in the profiling of DNA modifications: cytosine methylation and beyond", Nat. Rev. Genet, 15, pp.647~661 (2014)
5. Hamamoto, R., "Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine", Biomolecules, 10, pp.62~ (2019)
6. Naumov, V. A., "Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips", Epigenetics, 8, pp.921~934 (2013)
7. Fasanelli, F., "Hypomethylation of smoking-related genes is associated with future lung cancer in four prospective cohorts", Nat. Commun, 6, pp.10192~ (2015)
8. Wang, Z., "Epigenomic analysis of 5-hydroxymethylcytosine(5hmC)reveals novel DNA methylation markers for lung cancers", Neoplasia, 22, pp.154~161 (2020)
9. Pidsley, R., "A data-driven approach to preprocessing Illumina 450K methylation array data", BMC Genomics, 14, pp.293~ (2013)
10. Felling, RJ, "Neuronal activation and insight into the plasticity of DNA methylation", Epigenomics, 4, pp.125~127 (2012)
11. McEwen, L. M., "Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC Bead Chip array", Clin. Epigenetics, 10, pp.123~ (2018)
12. Collado-Torres, L, "Reproducible RNA-seq analysis using recount2", Nat. Bio technol, 35, pp.319~321 (2017)
13. Taroni, J. N., "MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease", Cell Syst, 8, pp.380~394 (2019)
14. Hamamoto, R, "Application of non-negative matrix factorization in oncology:one approach for establishing precision medicine", Brief Bioinform, 23, pp.bbac246~ (2022)
15. Sandoval, J., "A prognostic DNA methylation signature for stage I non-small cell lung cancer", J. Clin. Oncol, 31, pp.4140~4147 (2013)
16. Barrett, T., "NCBI GEO : archive for functional genomics data sets–update", Nucleic Acids Res, 41, pp.D991~D995 (2013)
17. Wei, J. -H., "A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma", Nat. Commun, 6, pp.8699~ (2015)
18. Davis, C. A., "The Encyclopedia of DNA elements(ENCODE) : data portal update", Nucleic Acids Res, 46, pp.D794~D801 (2018)
19. Subramanian, A., "Gene set enrichment analysis : a knowledge-based approach for interpreting genome-wide expression profiles", Proc. Natl Acad. Sci. USA, 102, pp.15545~15550 (2005)
20. Liberzon, A., "Molecular signatures database (MSigDB) 3.0", Bioinformatics, 27, pp.1739~1740 (2011)
21. Liberzon, A., "The Molecular Signatures Database(MSigDB)hallmark gene set collection", Cell Syst, 1, pp.417~425 (2015)
22. Mao, W., "Pathway-level information extractor (PLIER) for gene expression data", Nat. Methods, 16, pp.607~610 (2019)
23. Kanehisa, M., "KEGG as a reference resource for gene and protein annotation", Nucleic Acids Res, 44, pp.D457~D462 (2016)
24. Abbas, A. R., "Deconvo lution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus", PLoS One, 4, pp.e6098~ (2009)
25. Sturm, D., "New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs", Cell, 164, pp.1060~1072 (2016)
26. Titus, A. J., "methyLiftover : cross-platform DNA methylation data integration", Bioinformatics, 32, pp.2517~2519 (2016)
27. Zhou, W., "Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes", Nucleic Acids Res, 45, pp.e22~ (2017)
28. McInnes, L., "UMAP : Uniform Manifold Approximation and Projection", J. Open Source Softw, 3, pp.861~ (2018)
29. Ward, J. H., "Hierarchical Grouping to Optimize an Objective Function", J. Am. Stat. Assoc, 58, pp.236~244 (1963)
30. Hartigan, J. A., "A k-means clustering algorithm", Appl Stat, 28, pp.100~108 (1979)
31. McLeay, R. C., "Motif Enrichment Analysis : a unified framework and an evaluation on ChIP data", BMC Bioinforma, 11, pp.165~ (2010)
32. Tian, Y., "ChAMP : updated methylation analysis pipeline for Illumina Bead Chips", Bioinformatics, 33, pp.3982~3984 (2017)
33. Aryee, M. J., "Minfi : aflexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays", Bioinformatics, 30, pp.1363~1369 (2014)
34. Barbie, D. A., "Systematic RNA interference reveals that oncogenic KRAS driven cancers require TBK1", Nature, 462, pp.108~112 (2009)
35. Renaud, S., "Prognostic value of the KRAS G12V mutation in 841 surgically resected Caucasian lung adenocarcinoma cases", Br. J. Cancer, 113, pp.1206~1215 (2015)
36. Vitos-Faleato, J., "Requirement for epithelial p38α in KRAS-driven lung tumor progression", Proc. Natl Acad. Sci. USA, 117, pp.2588~2596 (2020)
37. Maksimovic, J., "SWAN : Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips", Genome Biol, 13, pp.R44~ (2012)
38. Dedeurwaerder, S., "Evaluation of the Infinium Methylation 450 K technology", Epigenomics, 3, pp.771~784 (2011)
39. Teschendorff, A. E., "A beta-mixture quantile normalization method for cor recting probe design bias in Illumina Infinium 450 k DNA methylation data", Bioinformatics, 29, pp.189~196 (2013)
40. Shiraishi, K., "Association of variations in HLA class II and other loci with susceptibility to EGFR-mutated lung adenocarcinoma", Nat. Commun, 7, pp.12451~ (2016)
41. Artacho-Cordón, F., "Matrix metalloproteinases : potential therapy to prevent the development of second malignancies after breast radiotherapy", Surg. Oncol, 21, pp.e143~e151 (2012)
42. Pereira, I. T., "Fibronectin affects transient MMP2 gene expression through DNA demethylation changes in non-invasive breast cancer cell lines", PLoS One, 9, pp.e105806~ (2014)
43. Wu, Y., "The clinicopathological significance of HES1 promoter hypomethy lation in patients with colorectal cancer", Onco Targets Ther, 10, pp.5827~5834 (2017)
44. Klajic, J., "DNA methylation status of key cell-cycle regulators such as CDKNA2", p16 and CCNA1 correlates with treatment response to doxorubicin and 5-fluorouracil in locally advanced breast tumors, 2014, pp.20, 6357~6366
45. Maeda, Y., "Airway epithelial transcription factor NK2 homeobox 1 inhibits mucous cell metaplasia and Th2 inflammation", Am. J. Respir. Crit. Care Med, 184, pp.421~429 (2011)
46. Cao, Y., "Epigenetic mechanisms modulate thyroid transcription factor 1-mediated transcription of the surfactant protein B gene", J. Biol. Chem, 285, pp.2152~2164 (2010)
47. Hosono, Y., "MYBPH, a transcriptional target of TTF-1, inhibits ROCK1, and reduces cell motility and metastasis", EMBO J, 31, pp.481~493 (2012)
48. Song, J., "Aberrant DNA methylation and expression of SPDEF and FOXA2 in airway epithelium of patients with COPD", Clin. Epigenetics, 9, pp.42~ (2017)
49. Locke, W. J., "DNA Methylation Cancer Biomarkers : Translation to the Clinic", Front. Genet, 10, pp.1150~ (2019)
50. Sadikovic, B, "Correction : Clinical epigenomics : genome-wide DNA methy lation analysis for the diagnosis of Mendelian disorders", Genet. Med, 23, pp.2228~ (2021)
51. Paparella, A., "Genome-wide DNA methylation profiling and exome sequencing resolved a long-time misdiagnosed case", J. Hum. Genet, 67, pp.547~551 (2022)
52. Moore, L. D., "DNA methylation and its basic function", Neuropsychopharmacology, 38, pp.23~38 (2013)
53. He, X. -J., "Regulation and function of DNA methylation in plants and animals", Cell Res, 21, pp.442~465 (2011)
54. Witte, T., "Pan-cancer patterns of DNA methylation", Genome Med, 6, pp.66~ (2014)
55. Esteller, M., "CpG island hypermethylation and tumor suppressor genes : a booming present, a brighter future", Oncogene, 21, pp.5427~5440 (2002)
56. Takasawa, K., "DNA hypermethylation enhanced telomerase reverse tran scriptase expression in human-induced pluripotent stem cells", Hum. Cell, 31, pp.78~86 (2018)
57. Lee, D. D., "DNA hypermethylation within TERT promoter upregulates TERT expression in cancer", J. Clin. Invest, 129, pp.223~229 (2019)
58. Rauluseviciute, I., "DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation", BMC Med Genom, 13, pp.6~ (2020)
59. Gu, Y., "Promoter DNA methylation analysis reveals a novel diagnostic CpG based biomarker and RAB25 hypermethylation in clear cell renel cell carcinoma", Int J. Biol. Sci. Rep, 7, pp.142000~ (2017)
60. Zuo, Q., "Methylation in the promoters of HS3ST2 and CCNA1 genes is associated with cervical cancer in Uygur women in Xinjiang", Int J. Biol. Markers, 29, pp.e354~e362 (2014)
61. Wang, Y., "Association of promoter methylation of RUNX3 gene with the development of esophageal cancer : a meta analysis", PLoS One, 9, pp.e107598~ (2014)
62. Kim, T. Y., "Methylation of RUNX3 in various types of human cancers and premalignant stages of gastric carcinoma", Lab. Invest, 84, pp.479~484 (2004)
63. Sato, K., "Epigenetic inactivation of the RUNX3 gene in lung cancer", Oncol. Rep, 15, pp.129~135 (2006)
64. Morris, T. J., "Analysis pipelines and packages for Infinium Human Methylation450 BeadChip(450k)data", Methods, 72, pp.3~8 (2015)
65. Assenov, Y., "Comprehensive analysis of DNA methylation data with RnBeads", Nat. Methods, 11, pp.1138~1140 (2014)
66. Müller, F., "RnBeads 2.0: comprehensive analysis of DNA methylation data", Genome biol, 20, pp.55~ (2019)

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