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Most Variable Genes and Transcription Factors in Acute Lymphoblastic Leukemia Patients

  • Anil Kumar TomarEmail author
  • Rahul Agarwal
  • Bishwajit Kundu
Original research article
  • 35 Downloads

Abstract

Acute lymphoblastic leukemia (ALL) is a hematologic tumor caused by cell cycle aberrations due to accumulating genetic disturbances in the expression of transcription factors (TFs), signaling oncogenes and tumor suppressors. Though survival rate in childhood ALL patients is increased up to 80% with recent medical advances, treatment of adults and childhood relapse cases still remains challenging. Here, we have performed bioinformatics analysis of 207 ALL patients’ mRNA expression data retrieved from the ICGC data portal with an objective to mark out the decisive genes and pathways responsible for ALL pathogenesis and aggression. For analysis, 3361 most variable genes, including 276 transcription factors (out of 16,807 genes) were sorted based on the coefficient of variance. Silhouette width analysis classified 207 ALL patients into 6 subtypes and heat map analysis suggests a need of large and multicenter dataset for non-overlapping subtype classification. Overall, 265 GO terms and 32 KEGG pathways were enriched. The lists were dominated by cancer-associated entries and highlight crucial genes and pathways that can be targeted for designing more specific ALL therapeutics. Differential gene expression analysis identified upregulation of two important genes, JCHAIN and CRLF2 in dead patients’ cohort suggesting their possible involvement in different clinical outcomes in ALL patients undergoing the same treatment.

Keywords

Gene expression KEGG pathways Leukemia Most variable genes Subtype classification 

Notes

Acknowledgements

This work was supported by grants received by AKT from Science and Engineering Research Board (SERB), Department of Science & Technology, Govt. of India, New Delhi, under National-Postdoctoral Fellowship Scheme (File Number: PDF/2015/000979). Authors also thank the IIT Delhi HPC facility for computational resources.

Compliance with Ethical Standards

Conflict of interest

Authors declare no conflict of interest.

Supplementary material

12539_2019_325_MOESM1_ESM.xlsx (7.9 mb)
Supplementary material 1 (XLSX 8120 KB)

References

  1. 1.
    Chiaretti S, Foa R (2009) T-cell acute lymphoblastic leukemia. Haematologica 94:160–162.  https://doi.org/10.3324/haematol.2008.004150 CrossRefGoogle Scholar
  2. 2.
    Pui CH, Behm FG, Singh B, Schell MJ, Williams DL, Rivera GK, Kalwinsky DK, Sandlund JT, Crist WM, Raimondi SC (1990) Heterogeneity of presenting features and their relation to treatment outcome in 120 children with T-cell acute lymphoblastic leukemia. Blood 75:174–179Google Scholar
  3. 3.
    Paul S, Kantarjian H, Jabbour EJ (2016) Adult acute lymphoblastic leukemia. Mayo Clin Proc 91:1645–1666.  https://doi.org/10.1016/j.mayocp.2016.09.010 CrossRefGoogle Scholar
  4. 4.
    Redaelli A, Laskin BL, Stephens JM, Botteman MF, Pashos CL (2005) A systematic literature review of the clinical and epidemiological burden of acute lymphoblastic leukaemia (ALL). Eur J Cancer Care (Engl) 14:53–62.  https://doi.org/10.1111/j.1365-2354.2005.00513.x CrossRefGoogle Scholar
  5. 5.
    You MJ, Medeiros LJ, Hsi ED (2015) T-lymphoblastic leukemia/lymphoma. Am J Clin Pathol 144:411–422.  https://doi.org/10.1309/AJCPMF03LVSBLHPJ CrossRefGoogle Scholar
  6. 6.
    Salzer WL, Devidas M, Carroll WL, Winick N, Pullen J, Hunger SP, Camitta BA (2010) Long-term results of the pediatric oncology group studies for childhood acute lymphoblastic leukemia 1984–2001: a report from the children’s oncology group. Leukemia 24:355–370.  https://doi.org/10.1038/leu.2009.261 CrossRefGoogle Scholar
  7. 7.
    Ferrando AA, Neuberg DS, Staunton J, Loh ML, Huard C, Raimondi SC, Behm FG, Pui CH, Downing JR, Gilliland DG, Lander ES, Golub TR, Look AT (2002) Gene expression signatures define novel oncogenic pathways in T cell acute lymphoblastic leukemia. Cancer Cell 1:75–87CrossRefGoogle Scholar
  8. 8.
    Sherr CJ (1996) Cancer cell cycles. Science 274:1672–1677CrossRefGoogle Scholar
  9. 9.
    Pui CH, Robison LL, Look AT (2008) Acute lymphoblastic leukaemia. Lancet 371:1030–1043.  https://doi.org/10.1016/S0140-6736(08)60457-2 CrossRefGoogle Scholar
  10. 10.
    Kuiper RP, Schoenmakers EF, van Reijmersdal SV, Hehir-Kwa JY, van Kessel AG, van Leeuwen FN, Hoogerbrugge PM (2007) High-resolution genomic profiling of childhood ALL reveals novel recurrent genetic lesions affecting pathways involved in lymphocyte differentiation and cell cycle progression. Leukemia 21:1258–1266.  https://doi.org/10.1038/sj.leu.2404691 CrossRefGoogle Scholar
  11. 11.
    Mullighan CG, Su X, Zhang J, Radtke I, Phillips LA, Miller CB, Ma J, Liu W, Cheng C, Schulman BA, Harvey RC, Chen IM, Clifford RJ, Carroll WL, Reaman G, Bowman WP, Devidas M, Gerhard DS, Yang W, Relling MV, Shurtleff SA, Campana D, Borowitz MJ, Pui CH, Smith M, Hunger SP, Willman CL, Downing JR, Children’s Oncology Group (2009) Deletion of IKZF1 and prognosis in acute lymphoblastic leukemia. N Engl J Med 360:470–480.  https://doi.org/10.1056/NEJMoa0808253 CrossRefGoogle Scholar
  12. 12.
    Harvey RC, Mullighan CG, Chen IM, Wharton W, Mikhail FM, Carroll AJ, Kang H, Liu W, Dobbin KK, Smith MA, Carroll WL, Devidas M, Bowman WP, Camitta BM, Reaman GH, Hunger SP, Downing JR, Willman CL (2010) Rearrangement of CRLF2 is associated with mutation of JAK kinases, alteration of IKZF1, Hispanic/Latino ethnicity, and a poor outcome in pediatric B-progenitor acute lymphoblastic leukemia. Blood 115:5312–5321.  https://doi.org/10.1182/blood-2009-09-245944 CrossRefGoogle Scholar
  13. 13.
    Roberts KG, Morin RD, Zhang J, Hirst M, Zhao Y, Su X, Chen SC, Payne-Turner D, Churchman ML, Harvey RC, Chen X, Kasap C, Yan C, Becksfort J, Finney RP, Teachey DT, Maude SL, Tse K, Moore R, Jones S, Mungall K, Birol I, Edmonson MN, Hu Y, Buetow KE, Chen IM, Carroll WL, Wei L, Ma J, Kleppe M, Levine RL, Garcia-Manero G, Larsen E, Shah NP, Devidas M, Reaman G, Smith M, Paugh SW, Evans WE, Grupp SA, Jeha S, Pui CH, Gerhard DS, Downing JR, Willman CL, Loh M, Hunger SP, Marra MA, Mullighan CG (2012) Genetic alterations activating kinase and cytokine receptor signaling in high-risk acute lymphoblastic leukemia. Cancer Cell 22:153–166.  https://doi.org/10.1016/j.ccr.2012.06.005 CrossRefGoogle Scholar
  14. 14.
    Li S, Wang C, Wang W, Liu W, Zhang G (2018) Abnormally high expression of POLD1, MCM2, and PLK4 promotes relapse of acute lymphoblastic leukemia. Medicine (Baltimore) 97(20):e10734.  https://doi.org/10.1097/MD.0000000000010734 CrossRefGoogle Scholar
  15. 15.
    Sędek Ł, Theunissen P, Sobral da Costa E, van der Sluijs-Gelling A, Mejstrikova E, Gaipa G, Sonsala A, Twardoch M, Oliveira E, Novakova M, Buracchi C, van Dongen JJM, Orfao A, van der Velden VHJ, Szczepański T, EuroFlow Consortium (2018) Differential expression of CD73, CD86 and CD304 in normal vs. leukemic B-cell precursors and their utility as stable minimal residual disease markers in childhood B-cell precursor acute lymphoblastic leukemia. J Immunol Methods.  https://doi.org/10.1016/j.jim.2018.03.005 Google Scholar
  16. 16.
    Wilkerson MD, Hayes DN (2010) ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics 26:1572–1573.  https://doi.org/10.1093/bioinformatics/btq170 CrossRefGoogle Scholar
  17. 17.
    Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K (2013) cluster: Cluster analysis basics and extensions. R package v1.14.4 edn. https://www.rdocumentation.org/packages/cluster
  18. 18.
    Schwender H (2012) siggenes: Multiple testing using SAM and Efron’s empirical Bayes approaches. R package v1.46.0 edn. https://www.rdocumentation.org/packages/siggenes
  19. 19.
    Cox DR (1972) Regression models and life tables. J R Stat Soc B 34:187–220Google Scholar
  20. 20.
    Kaplan E, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457–481.  https://doi.org/10.2307/2281868 CrossRefGoogle Scholar
  21. 21.
    Huang DW, Sherman BT, Tan Q, Kir J, Liu D, Bryant D, Guo Y, Stephens R, Baseler MW, Lane HC, Lempicki RA (2007) DAVID bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res 35:W169–W175.  https://doi.org/10.1093/nar/gkm415 CrossRefGoogle Scholar
  22. 22.
    Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47.  https://doi.org/10.1093/nar/gkv007 CrossRefGoogle Scholar
  23. 23.
    Ishii Y, Kasukabe T, Honma Y (2005) Immediate up-regulation of the calcium-binding protein S100P and its involvement in the cytokinin-induced differentiation of human myeloid leukemia cells. Biochim Biophys Acta 1745:156–165.  https://doi.org/10.1016/j.bbamcr.2005.01.005 CrossRefGoogle Scholar
  24. 24.
    Clarke C, Gross SR, Ismail TM, Rudland PS, Al-Medhtiy M, Santangeli M, Barraclough R (2017) Activation of tissue plasminogen activator by metastasis-inducing S100P protein. Biochem J 474(19):3227–3240.  https://doi.org/10.1042/BCJ20170578 CrossRefGoogle Scholar
  25. 25.
    Westcott MM, Liu J, Rajani K, D’Agostino R Jr, Lyles DS, Porosnicu M (2015) Interferon beta and interferon alpha 2a differentially protect head and neck cancer cells from vesicular stomatitis virus-induced oncolysis. J Virol 89:7944–7954.  https://doi.org/10.1128/JVI.00757-15 CrossRefGoogle Scholar
  26. 26.
    Giansanti F, Panella G, Leboffe L, Antonini G (2016) Lactoferrin from milk: nutraceutical and pharmacological properties. Pharmaceuticals (Basel) 9(4):E61.  https://doi.org/10.3390/ph9040061 CrossRefGoogle Scholar
  27. 27.
    Benaissa M, Peyrat JP, Hornez L, Mariller C, Mazurier J, Pierce A (2005) Expression and prognostic value of lactoferrin mRNA isoforms in human breast cancer. Int J Cancer 114:299–306.  https://doi.org/10.1002/ijc.20728 CrossRefGoogle Scholar
  28. 28.
    Hoedt E, Hardiville S, Mariller C, Elass E, Perraudin JP, Pierce A (2010) Discrimination and evaluation of lactoferrin and delta-lactoferrin gene expression levels in cancer cells and under inflammatory stimuli using TaqMan real-time PCR. Biometals 23:441–452.  https://doi.org/10.1007/s10534-010-9305-5 CrossRefGoogle Scholar
  29. 29.
    Lee SH, Hwang HM, Pyo CW, Hahm DH, Choi SY (2010) E2F1-directed activation of Bcl-2 is correlated with lactoferrin-induced apoptosis in Jurkat leukemia T lymphocytes. Biometals 23:507–514.  https://doi.org/10.1007/s10534-010-9341-1 CrossRefGoogle Scholar
  30. 30.
    Lu Y, Zhang TF, Shi Y, Zhou HW, Chen Q, Wei BY, Wang X, Yang TX, Chinn YE, Kang J, Fu CY (2016) PFR peptide, one of the antimicrobial peptides identified from the derivatives of lactoferrin, induces necrosis in leukemia cells. Sci Rep 6:20823.  https://doi.org/10.1038/srep20823 CrossRefGoogle Scholar
  31. 31.
    Mader JS, Salsman J, Conrad DM, Hoskin DW (2005) Bovine lactoferricin selectively induces apoptosis in human leukemia and carcinoma cell lines. Mol Cancer Ther 4:612–624.  https://doi.org/10.1158/1535-7163.MCT-04-0077 CrossRefGoogle Scholar
  32. 32.
    Richardson A, de Antueno R, Duncan R, Hoskin DW (2009) Intracellular delivery of bovine lactoferricin’s antimicrobial core (RRWQWR) kills T-leukemia cells. Biochem Biophys Res Commun 388:736–741.  https://doi.org/10.1016/j.bbrc.2009.08.083 CrossRefGoogle Scholar
  33. 33.
    Eiring AM, Khorashad JS, Agarwal A, Mason CC, Yu F, Redwine HM, Bowler AD, Gantz KC, Reynolds KR, Clair PM (2015) MS4A3 improves imatinib response and survival in BCR-ABL1 primary TKI resistance and in blastic transformation of chronic myeloid leukemia. Blood 126:14Google Scholar
  34. 34.
    Yokoi H, Kasahara M, Mori K, Ogawa Y, Kuwabara T, Imamaki H, Kawanishi T, Koga K, Ishii A, Kato Y, Mori KP, Toda N, Ohno S, Muramatsu H, Muramatsu T, Sugawara A, Mukoyama M, Nakao K (2012) Pleiotrophin triggers inflammation and increased peritoneal permeability leading to peritoneal fibrosis. Kidney Int 81:160–169.  https://doi.org/10.1038/ki.2011.305 CrossRefGoogle Scholar
  35. 35.
    Chang Y, Zuka M, Perez-Pinera P, Astudillo A, Mortimer J, Berenson JR, Deuel TF (2007) Secretion of pleiotrophin stimulates breast cancer progression through remodeling of the tumor microenvironment. Proc Natl Acad Sci USA 104:10888–10893.  https://doi.org/10.1073/pnas.0704366104 CrossRefGoogle Scholar
  36. 36.
    Du ZY, Shi MH, Ji CH, Yu Y (2015) Serum pleiotrophin could be an early indicator for diagnosis and prognosis of non-small cell lung cancer. Asian Pac J Cancer Prev 16:1421–1425CrossRefGoogle Scholar
  37. 37.
    Ma Y, Ye F, Xie X, Zhou C, Lu W (2011) Significance of PTPRZ1 and CIN85 expression in cervical carcinoma. Arch Gynecol Obstet 284:699–704.  https://doi.org/10.1007/s00404-010-1693-9 CrossRefGoogle Scholar
  38. 38.
    Makinoshima H, Ishii G, Kojima M, Fujii S, Higuchi Y, Kuwata T, Ochiai A (2012) PTPRZ1 regulates calmodulin phosphorylation and tumor progression in small-cell lung carcinoma. BMC Cancer 12:537.  https://doi.org/10.1186/1471-2407-12-537 CrossRefGoogle Scholar
  39. 39.
    Shi Y, Ping YF, Zhou W, He ZC, Chen C, Bian BS, Zhang L, Chen L, Lan X, Zhang XC, Zhou K, Liu Q, Long H, Fu TW, Zhang XN, Cao MF, Huang Z, Fang X, Wang X, Feng H, Yao XH, Yu SC, Cui YH, Zhang X, Rich JN, Bao S, Bian XW (2017) Tumour-associated macrophages secrete pleiotrophin to promote PTPRZ1 signalling in glioblastoma stem cells for tumour growth. Nat Commun 8:15080.  https://doi.org/10.1038/ncomms15080 CrossRefGoogle Scholar
  40. 40.
    Thirumoorthy N, Shyam Sunder A, Manisenthil Kumar K, Senthil Kumar M, Ganesh G, Chatterjee M (2011) A review of metallothionein isoforms and their role in pathophysiology. World J Surg Oncol 9:54.  https://doi.org/10.1186/1477-7819-9-54 CrossRefGoogle Scholar
  41. 41.
    Han YC, Zheng ZL, Zuo ZH, Yu YP, Chen R, Tseng GC, Nelson JB, Luo JH (2013) Metallothionein 1 h tumour suppressor activity in prostate cancer is mediated by euchromatin methyltransferase 1. J Pathol 230:184–193.  https://doi.org/10.1002/path.4169 CrossRefGoogle Scholar
  42. 42.
    Zheng Y, Jiang L, Hu Y, Xiao C, Xu N, Zhou J, Zhou X (2017) Metallothionein 1H (MT1H) functions as a tumor suppressor in hepatocellular carcinoma through regulating Wnt/beta-catenin signaling pathway. BMC Cancer 17:161.  https://doi.org/10.1186/s12885-017-3139-2 CrossRefGoogle Scholar
  43. 43.
    Zhou T, Li Y, Yang L, Tang T, Zhang L, Shi J (2017) Annexin A3 as a prognostic biomarker for breast cancer: a retrospective study. Biomed Res Int 2017:2603685.  https://doi.org/10.1155/2017/2603685 Google Scholar
  44. 44.
    Hamelin-Peyron C, Vlaeminck-Guillem V, Haidous H, Schwall GP, Poznanovic S, Gorius-Gallet E, Michel S, Larue A, Guillotte M, Ruffion A, Choquet-Kastylevsky G, Ataman-Onal Y (2014) Prostate cancer biomarker annexin A3 detected in urines obtained following digital rectal examination presents antigenic variability. Clin Biochem 47:901–908.  https://doi.org/10.1016/j.clinbiochem.2014.05.063 CrossRefGoogle Scholar
  45. 45.
    Wang K, Li J (2016) Overexpression of ANXA3 is an independent prognostic indicator in gastric cancer and its depletion suppresses cell proliferation and tumor growth. Oncotarget 7:86972–86984.  https://doi.org/10.18632/oncotarget.13493 Google Scholar
  46. 46.
    Olsson M, Beck S, Kogner P, Martinsson T, Caren H (2016) Genome-wide methylation profiling identifies novel methylated genes in neuroblastoma tumors. Epigenetics 11:74–84.  https://doi.org/10.1080/15592294.2016.1138195 CrossRefGoogle Scholar
  47. 47.
    Lopes MR, Pereira JK, de Melo Campos P, Machado-Neto JA, Traina F, Saad ST, Favaro P (2017) De novo AML exhibits greater microenvironment dysregulation compared to AML with myelodysplasia-related changes. Sci Rep 7:40707.  https://doi.org/10.1038/srep40707 CrossRefGoogle Scholar
  48. 48.
    Yamamoto S, Yako Y, Fujioka Y, Kajita M, Kameyama T, Kon S, Ishikawa S, Ohba Y, Ohno Y, Kihara A, Fujita Y (2016) A role of the sphingosine-1-phosphate (S1P)-S1P receptor 2 pathway in epithelial defense against cancer (EDAC). Mol Biol Cell 27:491–499.  https://doi.org/10.1091/mbc.E15-03-0161 CrossRefGoogle Scholar
  49. 49.
    Altieri F, Di Stadio CS, Federico A, Miselli G, De Palma M, Rippa E, Arcari P (2017) Epigenetic alterations of gastrokine 1 gene expression in gastric cancer. Oncotarget 8:16899–16911.  https://doi.org/10.18632/oncotarget.14817 Google Scholar
  50. 50.
    Xing R, Cui JT, Xia N, Lu YY (2015) GKN1 inhibits cell invasion in gastric cancer by inactivating the NF-kappaB pathway. Discov Med 19:65–71Google Scholar
  51. 51.
    Park JH, Nishidate T, Kijima K, Ohashi T, Takegawa K, Fujikane T, Hirata K, Nakamura Y, Katagiri T (2010) Critical roles of mucin 1 glycosylation by transactivated polypeptide N-acetylgalactosaminyltransferase 6 in mammary carcinogenesis. Cancer Res 70:2759–2769.  https://doi.org/10.1158/0008-5472.CAN-09-3911 CrossRefGoogle Scholar
  52. 52.
    Bhutia YD, Babu E, Prasad PD, Ganapathy V (2014) The amino acid transporter SLC6A14 in cancer and its potential use in chemotherapy. Asian J Pharm Sci 9:293–303.  https://doi.org/10.1016/j.ajps.2014.04.004 CrossRefGoogle Scholar
  53. 53.
    Ganapathy ME, Ganapathy V (2005) Amino acid transporter ATB0,+ as a delivery system for drugs and prodrugs. Curr Drug Targets Immune Endocr Metabol Disord 5:357–364CrossRefGoogle Scholar
  54. 54.
    Mi H, Huang X, Muruganujan A, Tang H, Mills C, Kang D, Thomas PD (2017) PANTHER version 11: expanded annotation data from gene ontology and reactome pathways, and data analysis tool enhancements. Nucleic Acids Res 45:D183–D189.  https://doi.org/10.1093/nar/gkw1138 CrossRefGoogle Scholar
  55. 55.
    Zhu H (2014) Targeting forkhead box transcription factors FOXM1 and FOXO in leukemia (Review). Oncol Rep 32:1327–1334.  https://doi.org/10.3892/or.2014.3357 CrossRefGoogle Scholar
  56. 56.
    Somerville TD, Wiseman DH, Spencer GJ, Huang X, Lynch JT, Leong HS, Williams EL, Cheesman E, Somervaille TC (2015) Frequent derepression of the mesenchymal transcription factor gene FOXC1 in acute myeloid leukemia. Cancer Cell 28:329–342.  https://doi.org/10.1016/j.ccell.2015.07.017 CrossRefGoogle Scholar
  57. 57.
    Sarkar A, Hochedlinger K (2013) The sox family of transcription factors: versatile regulators of stem and progenitor cell fate. Cell Stem Cell 12:15–30.  https://doi.org/10.1016/j.stem.2012.12.007 CrossRefGoogle Scholar
  58. 58.
    Oliemuller E, Kogata N, Bland P, Kriplani D, Daley F, Haider S, Shah V, Sawyer EJ, Howard BA (2017) SOX11 promotes invasive growth and ductal carcinoma in situ progression. J Pathol 243(2):193–207.  https://doi.org/10.1002/path.4939 CrossRefGoogle Scholar
  59. 59.
    Xie C, Han Y, Liu Y, Han L, Liu J (2014) miRNA-124 down-regulates SOX8 expression and suppresses cell proliferation in non-small cell lung cancer. Int J Clin Exp Pathol 7:7518–7526Google Scholar
  60. 60.
    Alharbi RA, Pettengell R, Pandha HS, Morgan R (2013) The role of HOX genes in normal hematopoiesis and acute leukemia. Leukemia 27:1000–1008.  https://doi.org/10.1038/leu.2012.356 CrossRefGoogle Scholar
  61. 61.
    Peng HX, Liu XD, Luo ZY, Zhang XH, Luo XQ, Chen X, Jiang H, Xu L (2017) Upregulation of the proto-oncogene Bmi-1 predicts a poor prognosis in pediatric acute lymphoblastic leukemia. BMC Cancer 17:76.  https://doi.org/10.1186/s12885-017-3049-3 CrossRefGoogle Scholar
  62. 62.
    Yu M, Al-Dallal S, Al-Haj L, Panjwani S, McCartney AS, Edwards SM, Manjunath P, Walker C, Awgulewitsch A, Hentges KE (2016) Transcriptional regulation of the proto-oncogene Zfp521 by SPI1 (PU.1) and HOXC13. Genesis 54:519–533.  https://doi.org/10.1002/dvg.22963 CrossRefGoogle Scholar
  63. 63.
    Akasaka T, Balasas T, Russell LJ, Sugimoto KJ, Majid A, Walewska R, Karran EL, Brown DG, Cain K, Harder L, Gesk S, Martin-Subero JI, Atherton MG, Bruggemann M, Calasanz MJ, Davies T, Haas OA, Hagemeijer A, Kempski H, Lessard M, Lillington DM, Moore S, Nguyen-Khac F, Radford-Weiss I, Schoch C, Struski S, Talley P, Welham MJ, Worley H, Strefford JC, Harrison CJ, Siebert R, Dyer MJ (2007) Five members of the CEBP transcription factor family are targeted by recurrent IGH translocations in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Blood 109:3451–3461.  https://doi.org/10.1182/blood-2006-08-041012 CrossRefGoogle Scholar
  64. 64.
    Chadwick N, Zeef L, Portillo V, Fennessy C, Warrander F, Hoyle S, Buckle AM (2009) Identification of novel Notch target genes in T cell leukaemia. Mol Cancer 8:35.  https://doi.org/10.1186/1476-4598-8-35 CrossRefGoogle Scholar
  65. 65.
    Bielinska E, Matiakowska K, Haus O (2017) Heterogeneity of human WT1 gene. Postepy Hig Med Dosw (Online) 71:595–601CrossRefGoogle Scholar
  66. 66.
    Shen Y, Park CS, Suppipat K, Mistretta TA, Puppi M, Horton TM, Rabin K, Gray NS, Meijerink JP, Lacorazza HD (2017) Inactivation of KLF4 promotes T-cell acute lymphoblastic leukemia and activates the MAP2K7 pathway. Leukemia 31(6):1314–1324.  https://doi.org/10.1038/leu.2016.339 CrossRefGoogle Scholar
  67. 67.
    Kronke J, Hurst SN, Ebert BL (2014) Lenalidomide induces degradation of IKZF1 and IKZF3. Oncoimmunology 3:e941742.  https://doi.org/10.4161/21624011.2014.941742 CrossRefGoogle Scholar
  68. 68.
    Winandy S, Wu P, Georgopoulos K (1995) A dominant mutation in the Ikaros gene leads to rapid development of leukemia and lymphoma. Cell 83:289–299CrossRefGoogle Scholar
  69. 69.
    Xu JH, Wang T, Wang XG, Wu XP, Zhao ZZ, Zhu CG, Qiu HL, Xue L, Shao HJ, Guo MX, Li WX (2010) PU.1 can regulate the ZNF300 promoter in APL-derived promyelocytes HL-60. Leuk Res 34:1636–1646.  https://doi.org/10.1016/j.leukres.2010.04.009 CrossRefGoogle Scholar
  70. 70.
    de Bruijn M, Dzierzak E (2017) Runx transcription factors in the development and function of the definitive hematopoietic system. Blood 129:2061–2069.  https://doi.org/10.1182/blood-2016-12-689109 CrossRefGoogle Scholar
  71. 71.
    Selvarajan V, Osato M, Nah GS, Yan J, Chung TH, Voon DC, Ito Y, Ham MF, Salto-Tellez M, Shimizu N, Choo SN, Fan S, Chng WJ, Ng SB (2017) RUNX3 is oncogenic in natural killer/T-cell lymphoma and is transcriptionally regulated by MYC. Leukemia 31(10):2219–2227.  https://doi.org/10.1038/leu.2017.40 CrossRefGoogle Scholar
  72. 72.
    Lourenco AR, Coffer PJ (2017) A tumor suppressor role for C/EBPalpha in solid tumors: more than fat and blood. Oncogene 36(37):5221–5230.  https://doi.org/10.1038/onc.2017.151 CrossRefGoogle Scholar
  73. 73.
    Wilkinson B, Chen JY, Han P, Rufner KM, Goularte OD, Kaye J (2002) TOX: an HMG box protein implicated in the regulation of thymocyte selection. Nat Immunol 3:272–280.  https://doi.org/10.1038/ni767 CrossRefGoogle Scholar
  74. 74.
    Mullighan CG, Phillips LA, Su X, Ma J, Miller CB, Shurtleff SA, Downing JR (2008) Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia. Science 322:1377–1380.  https://doi.org/10.1126/science.1164266 CrossRefGoogle Scholar
  75. 75.
    Gordon SM, Chaix J, Rupp LJ, Wu J, Madera S, Sun JC, Lindsten T, Reiner SL (2012) The transcription factors T-bet and Eomes control key checkpoints of natural killer cell maturation. Immunity 36:55–67.  https://doi.org/10.1016/j.immuni.2011.11.016 CrossRefGoogle Scholar
  76. 76.
    Lazarevic V, Glimcher LH, Lord GM (2013) T-bet: a bridge between innate and adaptive immunity. Nat Rev Immunol 13:777–789.  https://doi.org/10.1038/nri3536 CrossRefGoogle Scholar
  77. 77.
    Yu H, Yang J, Jiao S, Li Y, Zhang W, Wang J (2014) T-box transcription factor 21 expression in breast cancer and its relationship with prognosis. Int J Clin Exp Pathol 7:6906–6913Google Scholar
  78. 78.
    Schnell SA, Ambesi-Impiombato A, Sanchez-Martin M, Belver L, Xu L, Qin Y, Kageyama R, Ferrando AA (2015) Therapeutic targeting of HES1 transcriptional programs in T-ALL. Blood 125:2806–2814.  https://doi.org/10.1182/blood-2014-10-608448 CrossRefGoogle Scholar
  79. 79.
    Tian C, Tang Y, Wang T, Yu Y, Wang X, Wang Y, Zhang Y (2015) HES1 is an independent prognostic factor for acute myeloid leukemia. Onco Targets Ther 8:899–904.  https://doi.org/10.2147/OTT.S83511 CrossRefGoogle Scholar
  80. 80.
    Dou H, Chen X, Huang Y, Su Y, Lu L, Yu J, Yin Y, Bao L (2017) Prognostic significance of P2RY8-CRLF2 and CRLF2 overexpression may vary across risk subgroups of childhood B-cell acute lymphoblastic leukemia. Genes Chromosomes Cancer 56:135–146.  https://doi.org/10.1002/gcc.22421 CrossRefGoogle Scholar
  81. 81.
    Palmi C, Savino AM, Silvestri D, Bronzini I, Cario G, Paganin M, Buldini B, Galbiati M, Muckenthaler MU, Bugarin C, Della Mina P, Nagel S, Barisone E, Casale F, Locatelli F, Lo Nigro L, Micalizzi C, Parasole R, Pession A, Putti MC, Santoro N, Testi AM, Ziino O, Kulozik AE, Zimmermann M, Schrappe M, Villa A, Gaipa G, Basso G, Biondi A, Valsecchi MG, Stanulla M, Conter V, Te Kronnie G, Cazzaniga G (2016) CRLF2 over-expression is a poor prognostic marker in children with high risk T-cell acute lymphoblastic leukemia. Oncotarget 7:59260–59272.  https://doi.org/10.18632/oncotarget.10610 CrossRefGoogle Scholar
  82. 82.
    Cruz-Rodriguez N, Combita AL, Enciso LJ, Quijano SM, Pinzon PL, Lozano OC, Castillo JS, Li L, Bareno J, Cardozo C, Solano J, Herrera MV, Cudris J, Zabaleta J (2016) High expression of ID family and IGJ genes signature as predictor of low induction treatment response and worst survival in adult Hispanic patients with B-acute lymphoblastic leukemia. J Exp Clin Cancer Res 35:64.  https://doi.org/10.1186/s13046-016-0333-z CrossRefGoogle Scholar
  83. 83.
    Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447–D452.  https://doi.org/10.1093/nar/gku1003 CrossRefGoogle Scholar

Copyright information

© International Association of Scientists in the Interdisciplinary Areas 2019

Authors and Affiliations

  1. 1.Kusuma School of Biological SciencesIndian Institute of Technology DelhiNew DelhiIndia
  2. 2.Department of Reproductive BiologyAll India Institute of Medical SciencesNew DelhiIndia

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