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Journal of Neuro-Oncology

, Volume 137, Issue 2, pp 395–407 | Cite as

Transforming growth factor beta induced (TGFBI) is a potential signature gene for mesenchymal subtype high-grade glioma

  • Yuan-Bo Pan
  • Chi-Hao Zhang
  • Si-Qi Wang
  • Peng-Hui Ai
  • Kui Chen
  • Liang Zhu
  • Zhao-Liang Sun
  • Dong-Fu FengEmail author
Clinical Study

Abstract

Previous study revealed that higher expression of transforming growth factor beta induced (TGFBI) is correlated to poorer cancer-specific survival and higher proportion of tumor necrosis and Fuhrman grades III and IV in clear cell renal cell carcinomas. However, the relationships between TGFBI expression and malignant phenotypes of gliomas remain unclear. We downloaded and analyzed data from seven GEO datasets (GSE68848, GSE4290, GSE13041, GSE4271, GSE83300, GSE34824 and GSE84010), the TCGA database and the REMBRANDT database to investigate whether TGFBI could be a biomarker of glioma. From microarray data (GSE68848, GSE4290) and RNA-seq data (TCGA), TGFBI expression levels were observed to correlate positively with pathological grade, and TGFBI expression levels were significantly higher in gliomas than in normal brain tissues. Furthermore, in GSE13041, GSE4271 and the TCGA cohort, TGFBI expression in the mesenchymal (Mes) subtype high-grade glioma (HGG) was significantly higher than that in the proneural subtype. Kaplan–Meier survival analysis of GBM patients in the GSE83300 dataset, REMBRANDT and TCGA cohort revealed that patients in the top 50% TGFBI expression group survived for markedly shorter periods than those in the bottom 50%. Analysis of grade III gliomas showed that the median survival time was significantly shorter in the TGFBI high expression group than in the TGFBI low expression group. In addition, we found that TGFBI expression levels might relate to several classical molecular characterizations of glioma, such as, IDH mutation, TP53 mutation, EGFR amplification, etc. These results suggest that TGFBI expression positively correlates with glioma pathological grades and that TGFBI is a potential signature gene for Mes subtype HGG and a potential prognostic molecule.

Keywords

TGFBI Glioma Mesenchymal Signature gene Biomarker TCGA 

Notes

Acknowledgements

We would like to express our thanks to National Library of Medicine for giving user the privilege to freely download the raw data of various GEO series. We would like to thank the TCGA and REMBRANDT database for providing raw data with a large amount of clinical information.

Funding

This study was supported by the Key Program from the Ministry of Science and Technology of China (2016YFC0106104).

Compliance with ethical standards

Conflict of interest

The authors declare no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

As personal identifying information was not included in the REMBRANDT database and TCGA database, thus the informed consent was not required in this study.

Supplementary material

11060_2017_2729_MOESM1_ESM.docx (15 kb)
Supplementary material 1 (DOCX 15 KB)
11060_2017_2729_MOESM2_ESM.docx (14 kb)
Supplementary material 2 (DOCX 14 KB)
11060_2017_2729_MOESM3_ESM.tiff (9.4 mb)
Supplementary material 3—Overall survival curves of grade II and III astrocytoma/ODG patients from REMBRADNT cohort based on TGFBI expression level. a-d. Different histological subtypes (astrocytoma and ODG) of grade III/II glioma patients were divided into top 50% and bottom 50% expression groups according to TGFBI expression levels. Kaplan-Meier survival curves for the top 50% expression group and bottom 50% expression group. a. In grade III astrocytoma, the median survival time was shorter in the high TGFBI expression group (n=19) (20.1 months) than in the low TGFBI expression group (n=19) (42.53 months, p=0. 3266). b. Top 50% group (n=10) in grade III ODG patients from REMBRANDT cohort had a significantly shorter median survival period than low 50% group (n=10) (11.33 months vs 61.72 months, p=0.0071). c. There was no significant difference of median survival time between top 50% (n=22) and low 50% (n=22) groups of grade II astrocytomas (65.13 months vs 68.3 months, p=0.3992). d. There was no significant difference of median survival period between high 50% (n=8) and low 50% (n=8) groups of grade II ODGs (45.3 months vs 42.8 months, p=0.6214) (TIFF 9 KB)

References

  1. 1.
    Yan W, Zhang W, Jiang T (2011) Oncogene addiction in gliomas: implications for molecular targeted therapy. J Exp Clin Cancer Res 30:58.  https://doi.org/10.1186/1756-9966-30-58 CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Gorovets D, Kannan K, Shen R, Kastenhuber ER, Islamdoust N, Campos C, Pentsova E, Heguy A, Jhanwar SC, Mellinghoff IK, Chan TA, Huse JT (2012) IDH mutation and neuroglial developmental features define clinically distinct subclasses of lower grade diffuse astrocytic glioma. Clin Cancer Res 18:2490–2501.  https://doi.org/10.1158/1078-0432.ccr-11-2977 CrossRefPubMedGoogle Scholar
  3. 3.
    Hegi ME, Diserens AC, Gorlia T, Hamou MF, de Tribolet N, Weller M, Kros JM, Hainfellner JA, Mason W, Mariani L, Bromberg JE, Hau P, Mirimanoff RO, Cairncross JG, Janzer RC, Stupp R (2005) MGMT gene silencing and benefit from temozolomide in glioblastoma. N Engl J Med 352:997–1003.  https://doi.org/10.1056/NEJMoa043331 CrossRefGoogle Scholar
  4. 4.
    Pekmezci M, Rice T, Molinaro AM, Walsh KM, Decker PA, Hansen H, Sicotte H, Kollmeyer TM, McCoy LS, Sarkar G, Perry A, Giannini C, Tihan T, Berger MS, Wiemels JL, Bracci PM, Eckel-Passow JE, Lachance DH, Clarke J, Taylor JW, Luks T, Wiencke JK, Jenkins RB, Wrensch MR (2017) Adult infiltrating gliomas with WHO 2016 integrated diagnosis: additional prognostic roles of ATRX and TERT. Acta Neuropatholo.  https://doi.org/10.1007/s00401-017-1690-1 CrossRefGoogle Scholar
  5. 5.
    Karsy M, Guan J, Cohen AL, Jensen RL, Colman H (2017) New molecular considerations for glioma: IDH, ATRX, BRAF, TERT, H3 K27M. Curr Neurol Neurosci Rep 17:19  https://doi.org/10.1007/s11910-017-0722-5 CrossRefPubMedGoogle Scholar
  6. 6.
    Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD, Misra A, Nigro JM, Colman H, Soroceanu L, Williams PM, Modrusan Z, Feuerstein BG, Aldape K (2006) Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 9:157–173.  https://doi.org/10.1016/j.ccr.2006.02.019 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Li A, Walling J, Ahn S, Kotliarov Y, Su Q, Quezado M, Oberholtzer JC, Park J, Zenklusen JC, Fine HA (2009) Unsupervised analysis of transcriptomic profiles reveals six glioma subtypes. Cancer Res 69:2091–2099.  https://doi.org/10.1158/0008-5472.can-08-2100 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Verhaak RG, Hoadley KA, Purdom E, Wang V, Qi Y, Wilkerson MD, Miller CR, Ding L, Golub T, Mesirov JP, Alexe G, Lawrence M, O’Kelly M, Tamayo P, Weir BA, Gabriel S, Winckler W, Gupta S, Jakkula L, Feiler HS, Hodgson JG, James CD, Sarkaria JN, Brennan C, Kahn A, Spellman PT, Wilson RK, Speed TP, Gray JW, Meyerson M, Getz G, Perou CM, Hayes DN (2010) Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17:98–110.  https://doi.org/10.1016/j.ccr.2009.12.020 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Yan W, Zhang W, You G, Zhang J, Han L, Bao Z, Wang Y, Liu Y, Jiang C, Kang C, You Y, Jiang T (2012) Molecular classification of gliomas based on whole genome gene expression: a systematic report of 225 samples from the Chinese Glioma Cooperative Group. Neuro-oncology 14:1432–1440.  https://doi.org/10.1093/neuonc/nos263 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Skonier J, Neubauer M, Madisen L, Bennett K, Plowman GD, Purchio AF (1992) cDNA cloning and sequence analysis of beta ig-h3, a novel gene induced in a human adenocarcinoma cell line after treatment with transforming growth factor-beta. DNA Cell Biol 11:511–522.  https://doi.org/10.1089/dna.1992.11.511 CrossRefPubMedGoogle Scholar
  11. 11.
    Lin B, Madan A, Yoon JG, Fang X, Yan X, Kim TK, Hwang D, Hood L, Foltz G (2010) Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma. PloS ONE 5:e10210.  https://doi.org/10.1371/journal.pone.0010210 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Lebdai S, Verhoest G, Parikh H, Jacquet SF, Bensalah K, Chautard D, Rioux Leclercq N, Azzouzi AR, Bigot P (2015) Identification and validation of TGFBI as a promising prognosis marker of clear cell renal cell carcinoma. Urol Oncol 33:69.  https://doi.org/10.1016/j.urolonc.2014.06.005 e11–68CrossRefPubMedGoogle Scholar
  13. 13.
    Sturm D, Witt H, Hovestadt V, Khuong-Quang DA, Jones DT, Konermann C, Pfaff E, Tonjes M, Sill M, Bender S, Kool M, Zapatka M, Becker N, Zucknick M, Hielscher T, Liu XY, Fontebasso AM, Ryzhova M, Albrecht S, Jacob K, Wolter M, Ebinger M, Schuhmann MU, van Meter T, Fruhwald MC, Hauch H, Pekrun A, Radlwimmer B, Niehues T, von Komorowski G, Durken M, Kulozik AE, Madden J, Donson A, Foreman NK, Drissi R, Fouladi M, Scheurlen W, von Deimling A, Monoranu C, Roggendorf W, Herold-Mende C, Unterberg A, Kramm CM, Felsberg J, Hartmann C, Wiestler B, Wick W, Milde T, Witt O, Lindroth AM, Schwartzentruber J, Faury D, Fleming A, Zakrzewska M, Liberski PP, Zakrzewski K, Hauser P, Garami M, Klekner A, Bognar L, Morrissy S, Cavalli F, Taylor MD, van Sluis P, Koster J, Versteeg R, Volckmann R, Mikkelsen T, Aldape K, Reifenberger G, Collins VP, Majewski J, Korshunov A, Lichter P, Plass C, Jabado N, Pfister SM (2012) Hotspot mutations in H3F3A and IDH1 define distinct epigenetic and biological subgroups of glioblastoma. Cancer Cell 22:425–437.  https://doi.org/10.1016/j.ccr.2012.08.024 CrossRefGoogle Scholar
  14. 14.
    Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4:249–264.  https://doi.org/10.1093/biostatistics/4.2.249 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Li W, Li K, Zhao L, Zou H (2014) Bioinformatics analysis reveals disturbance mechanism of MAPK signaling pathway and cell cycle in Glioblastoma multiforme. Gene 547:346–350.  https://doi.org/10.1016/j.gene.2014.06.042 CrossRefPubMedGoogle Scholar
  16. 16.
    Garcia-Laencina PJ, Abreu PH, Abreu MH, Afonoso N (2015) Missing data imputation on the 5-year survival prediction of breast cancer patients with unknown discrete values. Comput Biol Med 59:125–133.  https://doi.org/10.1016/j.compbiomed.2015.02.006 CrossRefPubMedGoogle Scholar
  17. 17.
    Yan H, Parsons DW, Jin G, McLendon R, Rasheed BA, Yuan W, Kos I, Batinic-Haberle I, Jones S, Riggins GJ, Friedman H, Friedman A, Reardon D, Herndon J, Kinzler KW, Velculescu VE, Vogelstein B, Bigner DD (2009) IDH1 and IDH2 mutations in gliomas. N Engl J Med 360:765–773.  https://doi.org/10.1056/NEJMoa0808710 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Wiestler B, Capper D, Holland-Letz T, Korshunov A, von Deimling A, Pfister SM, Platten M, Weller M, Wick W (2013) ATRX loss refines the classification of anaplastic gliomas and identifies a subgroup of IDH mutant astrocytic tumors with better prognosis. Acta Neuropathol 126:443–451.  https://doi.org/10.1007/s00401-013-1156-z CrossRefPubMedGoogle Scholar
  19. 19.
    Ikemura M, Shibahara J, Mukasa A, Takayanagi S, Aihara K, Saito N, Aburatani H, Fukayama M (2016) Utility of ATRX immunohistochemistry in diagnosis of adult diffuse gliomas. Histopathology 69:260–267.  https://doi.org/10.1111/his.12927 CrossRefPubMedGoogle Scholar
  20. 20.
    Reuss DE, Sahm F, Schrimpf D, Wiestler B, Capper D, Koelsche C, Schweizer L, Korshunov A, Jones DT, Hovestadt V, Mittelbronn M, Schittenhelm J, Herold-Mende C, Unterberg A, Platten M, Weller M, Wick W, Pfister SM, von Deimling A (2015) ATRX and IDH1-R132H immunohistochemistry with subsequent copy number analysis and IDH sequencing as a basis for an “integrated” diagnostic approach for adult astrocytoma, oligodendroglioma and glioblastoma. Acta Neuropathol 129:133–146.  https://doi.org/10.1007/s00401-014-1370-3 CrossRefPubMedGoogle Scholar
  21. 21.
    Nam JO, Kim JE, Jeong HW, Lee SJ, Lee BH, Choi JY, Park RW, Park JY, Kim IS (2003) Identification of the alphavbeta3 integrin-interacting motif of betaig-h3 and its anti-angiogenic effect. J Biol Chem 278:25902–25909.  https://doi.org/10.1074/jbc.M300358200 CrossRefPubMedGoogle Scholar
  22. 22.
    Ma C, Rong Y, Radiloff DR, Datto MB, Centeno B, Bao S, Cheng AW, Lin F, Jiang S, Yeatman TJ, Wang XF (2008) Extracellular matrix protein betaig-h3/TGFBI promotes metastasis of colon cancer by enhancing cell extravasation. Genes Dev 22:308–321.  https://doi.org/10.1101/gad.1632008 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Hourihan RN, O’Sullivan GC, Morgan JG (2003) Transcriptional gene expression profiles of oesophageal adenocarcinoma and normal oesophageal tissues. Anticancer Res 23:161–165PubMedGoogle Scholar
  24. 24.
    Shang D, Liu Y, Yang P, Chen Y, Tian Y (2012) TGFBI-promoted adhesion, migration and invasion of human renal cell carcinoma depends on inactivation of von Hippel-Lindau tumor suppressor. Urology 79:966.  https://doi.org/10.1016/j.urology.2011.12.011 e961–967CrossRefPubMedGoogle Scholar
  25. 25.
    Hoersch S, Andrade-Navarro MA (2010) Periostin shows increased evolutionary plasticity in its alternatively spliced region. BMC Evol Biol 10:30.  https://doi.org/10.1186/1471-2148-10-30 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Calaf GM, Echiburu-Chau C, Zhao YL, Hei TK (2008) BigH3 protein expression as a marker for breast cancer. Int J Mol Med 21:561–568PubMedGoogle Scholar
  27. 27.
    Irigoyen M, Pajares MJ, Agorreta J, Ponz-Sarvise M, Salvo E, Lozano MD, Pio R, Gil-Bazo I, Rouzaut A (2010) TGFBI expression is associated with a better response to chemotherapy in NSCLC. Mol Cancer 9:130.  https://doi.org/10.1186/1476-4598-9-130 CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Gundersen GG, Kim I, Chapin CJ (1994) Induction of stable microtubules in 3T3 fibroblasts by TGF-beta and serum. J Cell Sci 107(Pt 3):645–659PubMedGoogle Scholar
  29. 29.
    Sandler A, Gray R, Perry MC, Brahmer J, Schiller JH, Dowlati A, Lilenbaum R, Johnson DH (2006) Paclitaxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer. N Engl J Med 355:2542–2550.  https://doi.org/10.1056/NEJMoa061884 CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Schiff PB, Fant J, Horwitz SB (1979) Promotion of microtubule assembly in vitro by taxol. Nature 277:665–667CrossRefGoogle Scholar
  31. 31.
    Scatena CD, Stewart ZA, Mays D, Tang LJ, Keefer CJ, Leach SD, Pietenpol JA (1998) Mitotic phosphorylation of Bcl-2 during normal cell cycle progression and Taxol-induced growth arrest. J Biol Chem 273:30777–30784CrossRefGoogle Scholar
  32. 32.
    Goncalves A, Braguer D, Kamath K, Martello L, Briand C, Horwitz S, Wilson L, Jordan MA (2001) Resistance to Taxol in lung cancer cells associated with increased microtubule dynamics. Proc Natl Acad Sci USA 98:11737–11742.  https://doi.org/10.1073/pnas.191388598 CrossRefPubMedGoogle Scholar
  33. 33.
    Ahmed AA, Mills AD, Ibrahim AE, Temple J, Blenkiron C, Vias M, Massie CE, Iyer NG, McGeoch A, Crawford R, Nicke B, Downward J, Swanton C, Bell SD, Earl HM, Laskey RA, Caldas C, Brenton JD (2007) The extracellular matrix protein TGFBI induces microtubule stabilization and sensitizes ovarian cancers to paclitaxel. Cancer Cell 12:514–527.  https://doi.org/10.1016/j.ccr.2007.11.014 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Nam EJ, Sa KH, You DW, Cho JH, Seo JS, Han SW, Park JY, Kim SI, Kyung HS, Kim IS, Kang YM (2006) Up-regulated transforming growth factor beta-inducible gene h3 in rheumatoid arthritis mediates adhesion and migration of synoviocytes through alpha v beta3 integrin: regulation by cytokines. Arthritis Rheum 54:2734–2744.  https://doi.org/10.1002/art.22076 CrossRefPubMedGoogle Scholar
  35. 35.
    Jeon ST, Kim WJ, Lee SM, Lee MY, Park SB, Lee SH, Kim IS, Suk K, Choi BK, Choi EM, Kwon BS, Lee WH (2010) Reverse signaling through BAFF differentially regulates the expression of inflammatory mediators and cytoskeletal movements in THP-1 cells. Immunol Cell Biol 88:148–156.  https://doi.org/10.1038/icb.2009.75 CrossRefPubMedGoogle Scholar
  36. 36.
    Yun SJ, Kim MO, Kim SO, Park J, Kwon YK, Kim IS, Lee EH (2002) Induction of TGF-beta-inducible gene-h3 (betaig-h3) by TGF-beta1 in astrocytes: implications for astrocyte response to brain injury. Brain Res Mol Brain Res 107:57–64CrossRefGoogle Scholar
  37. 37.
    Hegi ME, Diserens AC, Godard S, Dietrich PY, Regli L, Ostermann S, Otten P, Van Melle G, de Tribolet N, Stupp R (2004) Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide. Clin Cancer Res 10:1871–1874CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Department of Neurosurgery, Shanghai Ninth People’s HospitalShanghai Jiaotong University School of MedicineShanghaiChina
  2. 2.Department of General Surgery, Shanghai Ninth People’s HospitalShanghai Jiaotong University School of MedicineShanghaiChina
  3. 3.Department of RadiologyAffiliated Hospital of Medical School of Ningbo UniversityNingboChina
  4. 4.Department of Neurology, Ruijin HospitalShanghai Jiaotong University School of MedicineShanghaiChina

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