EgoNet identifies differential ego-modules and pathways related to prednisolone resistance in childhood acute lymphoblastic leukemia

References

• Seiter K, Sarkodee-Adoo C, Talavera F, et al. Acute lymphoblastic leukemia. Sarkodee-Adoo C, Talavera F, Sacher RA and Besa EC: Medscape Reference. WebMD. Accessed 17, 2014.
   Google Scholar
• Kaspers G, Pieters R, Van Zantwijk C, et al. Prednisolone resistance in childhood acute lymphoblastic leukemia: vitro-vivo correlations and cross-resistance to other drugs. Blood. 1998;92:259–266.
   PubMed Web of Science ®Google Scholar
• Ploner C, Schmidt S, Presul E, et al. Glucocorticoid-induced apoptosis and glucocorticoid resistance in acute lymphoblastic leukemia. J Steroid Biochem Mol Biol. 2005;93:153–160. doi: 10.1016/j.jsbmb.2004.12.017
   PubMed Web of Science ®Google Scholar
• Pui C-H, Carroll WL, Meshinchi S, et al. Biology, risk stratification, and therapy of pediatric acute leukemias: an update. J Clin Oncol. 2011;29:551–565. doi: 10.1200/JCO.2010.30.7405
   PubMed Web of Science ®Google Scholar
• Evans WE, Relling MV. Moving towards individualized medicine with pharmacogenomics. Nature. 2004;429:464–468. doi: 10.1038/nature02626
   PubMed Web of Science ®Google Scholar
• Klumper E, Pieters R, Veerman A, et al. In vitro cellular drug resistance in children with relapsed/refractory acute lymphoblastic leukemia. Blood. 1995;86:3861–3868.
   PubMed Web of Science ®Google Scholar
• Yeoh E-J, Ross ME, Shurtleff SA, et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell. 2002;1:133–143. doi: 10.1016/S1535-6108(02)00032-6
   PubMed Web of Science ®Google Scholar
• Flohr T, Schrauder A, Cazzaniga G, et al. Minimal residual disease-directed risk stratification using real-time quantitative PCR analysis of immunoglobulin and T-cell receptor gene rearrangements in the international multicenter trial AIEOP-BFM ALL 2000 for childhood acute lymphoblastic leukemia. Leukemia. 2008;22:771–782. doi: 10.1038/leu.2008.5
   PubMed Web of Science ®Google Scholar
• Holleman A, Cheok MH, den Boer ML, et al. Gene-expression patterns in drug-resistant acute lymphoblastic leukemia cells and response to treatment. N Engl J Med. 2004;351:533–542. doi: 10.1056/NEJMoa033513
   PubMed Web of Science ®Google Scholar
• Stam RW, Den Boer ML, Schneider P, et al. Association of high-level MCL-1 expression with in vitro and in vivo prednisone resistance in MLL-rearranged infant acute lymphoblastic leukemia. Blood. 2010;115:1018–1025. doi: 10.1182/blood-2009-02-205963
   PubMed Web of Science ®Google Scholar
• Sarang Z, Gyurina K, Scholtz B, et al. Altered expression of autophagy-related genes might contribute to glucocorticoid resistance in precursor B-cell-type acute lymphoblastic leukemia. Eur J Haematol. 2016;97:453–460. doi: 10.1111/ejh.12753
   PubMed Web of Science ®Google Scholar
• Yang R, Bai Y, Qin Z, et al. Egonet: identification of human disease ego-network modules. BMC Genomics. 2014;15:1. doi: 10.1186/1471-2164-15-S11-I1
   PubMed Web of Science ®Google Scholar
• Irizarry RA, Hobbs B, Collin F, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4:249–264. doi: 10.1093/biostatistics/4.2.249
   PubMed Web of Science ®Google Scholar
• Bolstad BM, Irizarry RA, Astrand M, et al. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003;19:185–193. doi: 10.1093/bioinformatics/19.2.185
   PubMed Web of Science ®Google Scholar
• Pepper SD, Saunders EK, Edwards LE, et al. The utility of MAS5 expression summary and detection call algorithms. BMC Bioinformatics. 2007;8:273. doi: 10.1186/1471-2105-8-273
   PubMed Web of Science ®Google Scholar
• Franceschini A, Szklarczyk D, Frankild S, et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 2013;41:D808–D815. doi: 10.1093/nar/gks1094
   PubMed Web of Science ®Google Scholar
• Goodman LA. Snowball sampling. Ann Math Stat. 1961;32:148–170. doi: 10.1214/aoms/1177705148
   Google Scholar
• Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol). 1995;57:289–300.
   Web of Science ®Google Scholar
• Huang J, Ling CX. Using AUC and accuracy in evaluating learning algorithms. IEEE Trans Knowl Data Eng. 2005;17:299–310. doi: 10.1109/TKDE.2005.50
   Web of Science ®Google Scholar
• Gillis J, Pavlidis P. The role of indirect connections in gene networks in predicting function. Bioinformatics. 2011;27:1860–1866. doi: 10.1093/bioinformatics/btr288
   PubMed Web of Science ®Google Scholar
• Wang J, Cheng J, Zhang C, et al. Cardioprotection effects of Sevoflurane by regulating the pathway of neuroactive ligand-receptor interaction in patients undergoing coronary artery bypass graft surgery. Comput Math Methods Med. 2017;2017:1–7. Article ID: 3618213.
   Web of Science ®Google Scholar
• Pui C-H, Relling MV, Downing JR. Acute lymphoblastic leukemia. N Engl J Med. 2004;350:1535–1548. doi: 10.1056/NEJMra023001
   PubMed Web of Science ®Google Scholar
• Bhojwani D, Kang H, Menezes RX, et al. Gene expression signatures predictive of early response and outcome in high-risk childhood acute lymphoblastic leukemia: a children’s Oncology Group Study. J Clin Oncol. 2008;26:4376–4384. doi: 10.1200/JCO.2007.14.4519
   PubMed Web of Science ®Google Scholar
• Conter V, Bartram CR, Valsecchi MG, et al. Molecular response to treatment redefines all prognostic factors in children and adolescents with B-cell precursor acute lymphoblastic leukemia: results in 3184 patients of the AIEOP-BFM ALL 2000 study. Blood. 2010;115:3206–3214. doi: 10.1182/blood-2009-10-248146
   PubMed Web of Science ®Google Scholar
• Cheok MH, Yang W, Pui C-H, et al. Treatment-specific changes in gene expression discriminate in vivo drug response in human leukemia cells. Nat Genet. 2003;34:85–90. doi: 10.1038/ng1151
   PubMed Web of Science ®Google Scholar
• Hogan LE, Meyer JA, Yang J, et al. Integrated genomic analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic strategies. Blood. 2011;118:5218–5226. doi: 10.1182/blood-2011-04-345595
   PubMed Web of Science ®Google Scholar
• Silveira VS, Scrideli CA, Moreno DA, et al. Gene expression pattern contributing to prognostic factors in childhood acute lymphoblastic leukemia. Leuk Lymphoma. 2013;54:310–314. doi: 10.3109/10428194.2012.710330
   PubMed Web of Science ®Google Scholar
• Ganguly A, Shields CL. Differential gene expression profile of retinoblastoma compared to normal retina; 2010.
   Google Scholar
• He D, Liu Z-P, Honda M, et al. Coexpression network analysis in chronic hepatitis B and C hepatic lesions reveals distinct patterns of disease progression to hepatocellular carcinoma. J Mol Cell Biol. 2012;4:140–152. doi: 10.1093/jmcb/mjs011
   PubMed Web of Science ®Google Scholar
• Liu Z-P, Wang Y, Zhang X-S, et al. Network-based analysis of complex diseases. IET Syst Biol. 2012;6:22–33. doi: 10.1049/iet-syb.2010.0052
   PubMed Web of Science ®Google Scholar
• Nibbe RK, Chowdhury SA, Koyutürk M, et al. Protein–protein interaction networks and subnetworks in the biology of disease. Wiley Interdiscip Rev Syst Biol Med. 2011;3:357–367. doi: 10.1002/wsbm.121
   PubMed Web of Science ®Google Scholar
• Wu Y, Jing R, Jiang L, et al. Combination use of protein–protein interaction network topological features improves the predictive scores of deleterious non-synonymous single-nucleotide polymorphisms. Amino Acids. 2014;46:2025–2035. doi: 10.1007/s00726-014-1760-9
   PubMed Web of Science ®Google Scholar
• Vert JP, Kanehisa M. Extracting active pathways from gene expression data. Bioinformatics. 2003;19(Suppl. 2):ii238–ii244.
   PubMedGoogle Scholar
• Tissing W, Meijerink J, den Boer M, et al. Molecular determinants of glucocorticoid sensitivity and resistance in acute lymphoblastic leukemia. Leukemia. 2003;17:17–25. doi: 10.1038/sj.leu.2402733
   PubMed Web of Science ®Google Scholar
• Van den Heuvel-Eibrink M, Sonneveld P, Pieters R. The prognostic significance of membrane transport-associated multidrug resistance (MDR) proteins in leukemia. Int J Clin Pharmacol Ther. 2000;38:94–111. doi: 10.5414/CPP38094
   PubMed Web of Science ®Google Scholar
• Gametchua B, Chen F, Sackey F, et al. Plasma membrane-resident glucocorticoid receptors in rodent lymphoma and human leukemia models. Steroids. 1999;64:107–119. doi: 10.1016/S0039-128X(98)00097-X
   PubMed Web of Science ®Google Scholar
• Sackey F, Watson CS, Gametchu B. Cell cycle regulation of membrane glucocorticoid receptor in CCRF-CEM human ALL cells: correlation to apoptosis. Am J Physiol Endocrinol Metab. 1997;273:E571–E583.
   Web of Science ®Google Scholar
• Messina M, Chiaretti S, Iacobucci I, et al. AID expression in BCR/ABL positive ALL is associated with a peculiar gene expression profile and deregulation of DNA repair and replication genes. Haematologica-The Hematology Journal Ferrata Storti Foundation via Giuseppe Belli 4, 27100 Pavia, Italy; 2009. p. 249.
   Google Scholar