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Identification of Hub Genes and Key Pathways Associated with Peripheral T-cell Lymphoma

Current Medical Science volume 40, pages 885–899 (2020)Cite this article

Summary

Peripheral T-cell lymphoma (PTCL) is a very aggressive and heterogeneous hematological malignancy and has no effective targeted therapy. The molecular pathogenesis of PTCL remains unknown. In this study, we chose the gene expression profile of GSE6338 from the Gene Expression Omnibus (GEO) database to identify hub genes and key pathways and explore possible molecular pathogenesis of PTCL by bioinformatic analysis. Differentially expressed genes (DEGs) between PTCL and normal T cells were selected using GEO2R tool. Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, the Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) were utilized to construct protein-protein interaction (PPI) network and perform module analysis of these DEGs. A total of 518 DEGs were identified, including 413 down-regulated and 105 up-regulated genes. The down-regulated genes were enriched in osteoclast differentiation, Chagas disease and mitogen-activated protein kinase (MAPK) signaling pathway. The up-regulated genes were mainly associated with extracellular matrix (ECM)-receptor interaction, focal adhesion and pertussis. Four important modules were detected from the PPI network by using MCODE software. Fifteen hub genes with a high degree of connectivity were selected. Our study identified DEGs, hub genes and pathways associated with PTCL by bioinformatic analysis. Results provide a basis for further study on the pathogenesis of PTCL.

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References

  1. Leval LD, Bisig B, Thielen C, et al. Molecular classification of T-cell lymphomas. Crit Rev Oncol Hematol, 2009,72(2):125–143

    PubMed  Google Scholar 

  2. Foss FM, Zinzani PL, Vose JM, et al. Peripheral T-cell lymphoma. Blood, 2011,117(25):6756–6767

    CAS  PubMed  Google Scholar 

  3. Armitage James O.. The aggressive peripheral T-cell lymphomas: 2012 update on diagnosis, risk stratification, and management. Am. J. Hematol, 2012,87:511–519

    PubMed  Google Scholar 

  4. Scarisbrick JJ, Kim YH, Whittaker SJ, et al. Prognostic factors, prognostic indices and staging in mycosis fungoides and Sézary syndrome: where are we now? Br J Dermatol, 2014,170(6):1226–1236

    CAS  PubMed  Google Scholar 

  5. Martin-Sanchez E, Odqvist L, Rodriguez-Pinilla SM, et al. PIM Kinases as Potential Therapeutic Targets in a Subset of Peripheral T Cell Lymphoma Cases. Plos One, 2014,9(9):e112148

    PubMed  PubMed Central  Google Scholar 

  6. Pearson Joel D, Lee Jason KH, Bacani Julinor TC, et al. NPM-ALK: The Prototypic Member of a Family of Oncogenic Fusion Tyrosine Kinases. J Signal Transduct, 2012,2012(4):123253

    PubMed  PubMed Central  Google Scholar 

  7. Barreca A, Lasorsa E, Riera L, et al. Anaplastic lymphoma kinase in human cancer. J Mol Endocrinol, 2011,47(1):11–23

    Google Scholar 

  8. O’Leary H, Savage KJ. The spectrum of peripheral T-cell lymphomas. Curr Opin Hematol, 2009,16(4):292

    PubMed  Google Scholar 

  9. Gambacorti-Passerini C, Messa C, Pogliani EM. Crizotinib in anaplastic large-cell lymphoma. N Engl J Med, 2011,364(8):775–776

    PubMed  Google Scholar 

  10. Intlekofer AM, Younes A. From empiric to mechanism-based therapy for peripheral T cell lymphoma. Int J Hematol, 2014,99(3):249–262

    CAS  PubMed  Google Scholar 

  11. Horwitz SM, Advani RH, Bartlett NL, et al. Objective responses in relapsed T-cell lymphomas with singleagent brentuximab vedotin. Blood, 2014,123(20):3095–3100

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Dunleavy K, Piekarz RL, Zain J, et al. New Strategies in Peripheral T-cell lymphoma: Understanding Tumor Biology and Developing Novel Therapies. Clin Cancer Res, 2010,16(23):5608

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Moskowitz AJ, Lunning MA, Horwitz SM. How I treat the peripheral T-cell lymphomas. Blood, 2014,123(17):2636–2644

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Piccaluga PP, Agostinelli C, Califano A, et al. Gene expression analysis of peripheral T cell lymphoma, unspecified, reveals distinct profiles and new potential therapeutic targets. J Clin Invest, 2007,117(3):823–834

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Davis S, Meltzer PS. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics, 2007,23(14):1846–1847

    PubMed  Google Scholar 

  16. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 2000,25(1):25–29

    CAS  PubMed  Google Scholar 

  17. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res, 2000,27(1):29–34.

    Google Scholar 

  18. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 2009,4(1):44–57

    CAS  Google Scholar 

  19. Szklarczyk D, Franceschini A, Wyder S, et al.. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res, 2015,43:D447

    CAS  PubMed  Google Scholar 

  20. Ono K, Muetze T, Kolishovski G, et al. CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API. F1000Res, 2015,4

  21. Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 2003,4(1):2

    PubMed  PubMed Central  Google Scholar 

  22. Swerdlow SH, Campo E, Pileri SA, et al. The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood, 2016,127(20):2375–2390

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Wang C, Mckeithan TW, Gong Q, et al. IDH2R172 mutations define a unique subgroup of patients with angioimmunoblastic T-cell lymphoma. Blood, 2015,126(15):1741–1752

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Piccaluga PP, Tabanelli V, Pileri SA. Molecular genetics of peripheral T-cell lymphomas. Int J Hematol, 2014,99(3):219–226

    CAS  PubMed  Google Scholar 

  25. Paluch EK, Aspalter IM, Sixt M. Focal Adhesion-Independent Cell Migration. Annu Rev Cell Dev Biol, 2016,32(1):469

    CAS  PubMed  Google Scholar 

  26. Zhu JJ, Luo J, Wang W, et al. Inhibition of FASN reduces the synthesis of medium-chain fatty acids in goat mammary gland. Animal, 2014,8(9):1469–1478

    CAS  PubMed  Google Scholar 

  27. Wang Y, Zhang M, Xu H, et al. Discovery and validation of the tumor-suppressive function of long noncoding RNA PANDA in human diffuse large B-cell lymphoma through the inactivation of MAPK/ERK signaling pathway. Oncotarget, 2017,8(42):72182–72196

    PubMed  PubMed Central  Google Scholar 

  28. Morachis JM, Murawsky CM, Emerson BM. Regulation of the p53 transcriptional response by structurally diverse core promoters. Genes Dev, 2010,24(2):135–147

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Islam S, Qi W, Morales C, et al. Disruption of Aneuploidy and Senescence Induced by Aurora Inhibition Promotes Intrinsic Apoptosis in Double Hit or Double Expressor Diffuse Large B-cell Lymphomas. Mol Cancer Ther, 2017,16(10):2083–2093

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Jr LA, Schafernak KT, Geyer JT, et al. Pediatric-type nodal follicular lymphoma: a biologically distinct lymphoma with frequent MAPK pathway mutations. Blood, 2016,128(8):1093–1100

    Google Scholar 

  31. Li Y, Shi X, Yang W, et al. Transcriptome profiling of lncRNA and co-expression networks in esophageal squamous cell carcinoma by RNA sequencing. Tumour Biol, 2016,37(10):1–10

    Google Scholar 

  32. Li S, Li H, Xu Y, et al. Identification of candidate biomarkers for epithelial ovarian cancer metastasis using microarray data. Oncol Lett, 2017,14(4):3967–3974

    PubMed  PubMed Central  Google Scholar 

  33. Ning X, Deng Y.. Identification of key pathways and genes influencing prognosis in bladder urothelial carcinoma. Onco Targets Ther, 2017,10:1673–1686

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Ott GR, Cheng M, Learn KS, et al. Discovery of Clinical Candidate CEP-37440, a Selective Inhibitor of Focal Adhesion Kinase (FAK) and Anaplastic Lymphoma Kinase (ALK). J Med Chem, 2016,59(16):7478–7496

    CAS  Google Scholar 

  35. Bosch R, Dieguez-Gonzalez R, Moreno MJ, et al. Focal adhesion protein expression in human diffuse large B-cell lymphoma. Histopathology, 2014,65(1):119–131

    Google Scholar 

  36. Uddin S, Hussain AR, Siraj AK, et al. Role of phosphatidylinositol 3,-kinase/AKT pathway in diffuse large B-cell lymphoma survival. Blood, 2006,108(13):4178–4186

    CAS  Google Scholar 

  37. Hasselblom S, Hansson U, Olsson M, et al. High immunohistochemical expression of p-AKT predicts inferior survival in patients with diffuse large B-cell lymphoma treated with immunochemotherapy. Br J Haematol, 2010,149(4):560–568

    CAS  Google Scholar 

  38. Hong JY, Hong ME, Choi MK, et al. The impact of activated p-AKT expression on clinical outcomes in diffuse large B-cell lymphoma: a clinicopathological study of 262 cases. Ann Oncol, 2014,25(1):182–188

    CAS  Google Scholar 

  39. Bai R, Ouyang TC, Morris S, et al. Nucleophosminanaplastic lymphoma kinase associated with anaplastic large-cell lymphoma activates the phosphatidylinositol 3-kinase/Akt antiapoptotic signaling pathway. Blood, 2000,96(13):4319

    CAS  Google Scholar 

  40. Chow C, Liu AY, Chan WS, et al. AKT plays a role in the survival of the tumor cells of extranodal NK/T-cell lymphoma, nasal type. Haematologica, 2005,90(2):274

    CAS  PubMed  Google Scholar 

  41. Huang Y, De RA, De LL, et al. Gene expression profiling identifies emerging oncogenic pathways operating in extranodal NK/T-cell lymphoma, nasal type. Blood, 2010,115(6):1226

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Rassidakis GZ, Feretzaki M, Atwell C, et al. Inhibition of Akt increases p27Kip1 levels and induces cell cycle arrest in anaplastic large cell lymphoma. Blood, 2005,105(2):827–829

    CAS  PubMed  Google Scholar 

  43. Slupianek A, Nieborowska-Skorska M, Hoser G, et al. Role of phosphatidylinositol 3-kinase-Akt pathway in nucleophosmin/anaplastic lymphoma kinase-mediated lymphomagenesis. Cancer Res, 2001,61(5):2194–2199

    CAS  PubMed  Google Scholar 

  44. Yamanaka Y, Tagawa H, Takahashi N, et al. Aberrant overexpression of microRNAs activate AKT signaling via down-regulation of tumor suppressors in natural killer-cell lymphoma/leukemia. Blood, 2009,114(15):3265–3275

    CAS  PubMed  Google Scholar 

  45. Hong JY, Hong ME, Choi MK, et al. The Clinical Significance of Activated p-AKT Expression in Peripheral T-cell Lymphoma. Anticancer Res, 2015,35(4):2465–2474

    PubMed  Google Scholar 

  46. Huang W, August A. The signaling symphony: T cell receptor tunes cytokine-mediated T cell differentiation. J Leukoc Biol, 2015,97(3):477–485

    CAS  PubMed  Google Scholar 

  47. Martinez DB, Cuadros ME, Ruizdl PA, et al. Differential expression of NF-kappaB pathway genes among peripheral T-cell lymphomas. Leukemia, 2005,19(12):2254

    Google Scholar 

  48. Xiang L, Xie G, Ou J, et al. The Extra Domain A of Fibronectin Increases VEGF-C Expression in Colorectal Carcinoma Involving the PI3K/AKT Signaling Pathway. Plos One, 2012,7(4):e35378

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Lossos IS, Czerwinski DK, Alizadeh AA, et al.. Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N Engl J Med, 2004,350:1828–1837

    CAS  PubMed  Google Scholar 

  50. Malumbres R, Chen J, Tibshirani R, et al. Paraffin-based 6-gene model predicts outcome in diffuse large B-cell lymphoma patients treated with R-CHOP. Blood, 2008,111(12):5509

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Vanesa G, Miguel GJ, Javier S, et al. Extracellular Tumor-Related mRNA in Plasma of Lymphoma Patients and Survival Implications. Plos One, 2009, 4(12):e8173

    Google Scholar 

  52. Zamani-Ahmadmahmudi M, Aghasharif S, Ilbeigi K. Prognostic efficacy of the human B-cell lymphoma prognostic genes in predicting disease-free survival (DFS) in the canine counterpart. BMC Vet Res, 2017,13(1):17

    PubMed  PubMed Central  Google Scholar 

  53. Zeisberg M, Neilson EG. Biomarkers for epithelialmesenchymal transitions. J Clin Invest, 2009,119(6):1429–1437

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Brandt S, Montagna C, Georgis A, et al. The combined expression of the stromal markers fibronectin and SPARC improves the prediction of survival in diffuse large B-cell lymphoma. Exp Hematol Oncol, 2013,2(1):27

    PubMed  PubMed Central  Google Scholar 

  55. Zhang H, Teng X, Liu Z, et al. Gene expression profile analyze the molecular mechanism of CXCR7 regulating papillary thyroid carcinoma growth and metastasis. J Exp Clin Cancer Res, 2015,34(1):16

    PubMed  PubMed Central  Google Scholar 

  56. Zenz R, Wagner EF. Jun signalling in the epidermis: From developmental defects to psoriasis and skin tumors. Int J Biochem Cell Biol, 2006,38(7):1043–1049

    CAS  PubMed  Google Scholar 

  57. Zhang J, Wu Z, Savin A, et al. The c-Jun and JunB transcription factors facilitate the transit of classical Hodgkin lymphoma tumour cells through G1. Sci Rep, 2018,8(1):16019

    PubMed  PubMed Central  Google Scholar 

  58. Ruco LP, Pomponi D, Pigott R, et al. Cytokine production (IL-1 alpha, IL-1 beta, and TNF alpha) and endothelial cell activation (ELAM-1 and HLA-DR) in reactive lymphadenitis, Hodgkin’s disease, and in non-Hodgkin’s lymphomas. An immunocytochemical study. Am J Pathol, 1990,137(5):1163–1171

    CAS  PubMed  Google Scholar 

  59. Goto N, Tsurumi H, Takemura M, et al. Serum Soluble Tumor Necrosis Factor Receptor 1 Level is Associated with the Outcome of Diffuse Large B-Cell Lymphoma Patients Treated with the CHOP or R-CHOP Regimen. J Clin Exp Hematop, 2014,91(4):117–127

    Google Scholar 

  60. Nakamura N, Goto N, Tsurumi H, et al. Serum level of soluble tumor necrosis factor receptor 2 is associated with the outcome of patients with diffuse large B-cell lymphoma treated with the R-CHOP regimen. Eur J Haematol, 2013,91(4):322–331

    CAS  PubMed  Google Scholar 

  61. Honma Y, Sugita N, Kobayashi T, et al. TNF-α expression in tumor cells as a novel prognostic marker for diffuse large B-cell lymphoma, not otherwise specified. Am J Surg Pathol, 2014,38(2):228–234

    Google Scholar 

  62. Dlouhy I, Filella X, Rovira J, et al.. High serum levels of soluble interleukin-2 receptor (sIL2-R), interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF) are associated with adverse clinical features and predict poor outcome in diffuse large B-cell lymphoma. Leuk Res, 2017,59:20

    CAS  PubMed  Google Scholar 

  63. Kato H, Nagasaka T, Ichikawa A, et al. Tumor necrosis factor-beta gene expression and its relationship to the clinical features and histopathogenesis of peripheral T-cell lymphomas. Leuk Lymphoma, 1994,16(1–2):125–133

    CAS  PubMed  Google Scholar 

  64. Nocturne G, Boudaoud S, Ly B, et al.. Impact of anti-TNF therapy on NK cells function and on immunosurveillance against B-cell lymphomas. J Autoimmun, 2017,80:56–64

    CAS  PubMed  Google Scholar 

  65. Ramezani S, Shirdel A, Rafatpanah H, et al. Assessment of HTLV-1 proviral load, LAT, BIM, c-FOS and RAD51 gene expression in adult T cell leukemia/lymphoma. Med Microbiol Immunol, 2017,206(4):327–335

    CAS  PubMed  Google Scholar 

  66. Boi M, Todaro M, Vurchio V, et al. Therapeutic efficacy of the bromodomain inhibitor OTX015/MK-8628 in ALK-positive anaplastic large cell lymphoma: an alternative modality to overcome resistant phenotypes. Oncotarget, 2016,7(48):79637–79653

    PubMed  PubMed Central  Google Scholar 

  67. Guo X, Koff JL, Moffitt AB, et al. Molecular impact of selective NFKB1 and NFKB2 signaling on DLBCL phenotype. Oncogene, 2017,36(29):4224–4232

    CAS  PubMed  Google Scholar 

  68. Sebestyén A, Hajdu M, Kis L, et al. Smad4-independent, PP2A-dependent apoptotic effect of exogenous transforming growth factor beta 1 in lymphoma cells. Exp Cell Res, 2007,313(15):3167–3174

    PubMed  Google Scholar 

  69. Macdonald I, Wang H, Grand R, et al. Transforming growth factor-beta 1 cooperates with anti-immunoglobulin for the induction of apoptosis in group I (biopsy-like) Burkitt lymphoma cell lines. Blood, 1996,87(3):1147

    CAS  PubMed  Google Scholar 

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Author notes

  1. The authors contributed equally to this study.

Affiliations

  1. Department of Pathology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China

    Hai-xia Gao, Si-jing Li, Jing Niu, Jing Xue & Xin-xia Li

  2. Xinjiang Medical University, Urumqi, 830011, China

    Hai-xia Gao, Si-jing Li, Jing Niu & Jing Xue

  3. Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, 832002, China

    Hai-xia Gao

  4. Department of Ultrasound, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, 832002, China

    Meng-bo Wang & Jun Li

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  1. Hai-xia Gao
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Correspondence to Xin-xia Li.

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The study was supported by grants from the National Natural Science Foundation of China (No. 81660036) and the Project of the Bingtuan Science and Technology (No. 2019DB012).

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The authors declare that there is no conflict of interest with any financial organization or corporation or individual that can inappropriately influence this work.

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Gao, Hx., Wang, Mb., Li, Sj. et al. Identification of Hub Genes and Key Pathways Associated with Peripheral T-cell Lymphoma. CURR MED SCI 40, 885–899 (2020). https://doi.org/10.1007/s11596-020-2250-9

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  • DOI: https://doi.org/10.1007/s11596-020-2250-9

Key words

  • peripheral T-cell lymphomas
  • bioinformatic analysis
  • protein-protein interaction
  • hub genes
  • pathways