Search Advanced

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 9: 9481-9504. doi: 10.3934/mbe.2022441
Previous Article Next Article
Research article

A novel defined risk signature of interferon response genes predicts the prognosis and correlates with immune infiltration in glioblastoma

  • 1.
    Department of Neurosurgery, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
  • 2.
    Department of Neuro-Psychiatric Institute, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
  • 3.
    Department of Neurosurgery, Wuxi People's Hospital of Nanjing Medical University, Wuxi, China
  • 4.
    Department of Neurosurgery, Changzhou Wujin People's Hospital, Changzhou, China

  • Academic Editor: Yi Jiang
    †The authors contributed equally to this work.
  • Received: 03 April 2022 Revised: 08 June 2022 Accepted: 20 June 2022 Published: 29 June 2022

  • Background

    Interferons (IFNs) have been implemented as anti-tumor immunity agents in clinical trials of glioma, but only a subset of glioblastoma (GBM) patients profits from it. The predictive role of IFNs stimulated genes in GBM needs further exploration to investigate the clinical role of IFNs.

     Methods

    This study screened 526 GBM patients from three independent cohorts. The transcriptome data with matching clinical information were analyzed using R. Immunohistochemical staining data from the Human Protein Atlas and DNA methylation data from MethSurv were used for validation in protein and methylation level respectively.

     Results

    We checked the survival effect of all 491 IFNs response genes, and found 54 genes characterized with significant hazard ratio in overall survival (OS). By protein-protein interaction analysis, 10 hub genes were selected out for subsequent study. And based on the expression of these 10 genes, GBM patients could be divided into two subgroups with significant difference in OS. Furthermore, the least absolute shrinkage and selection operator cox regression model was utilized to construct a multigene risk signature, including STAT3, STAT2 and SOCS3, which could serve as an independent prognostic predictor for GBM. The risk model was validated in two independent GBM cohorts. The GBM patients with high risk scores mainly concentrated in the GBM Mesenchymal subtype. The higher risk group was enriched in hypoxia, angiogenesis, EMT, glycolysis and immune pathways, and had increased Macrophage M2 infiltration and high expression of immune checkpoint CD274 (namely PD-L1).

     Conclusions

    Our findings revealed the three-gene risk model could be an independent prognostic predictor for GBM, and they were crucial participants in immunosuppressive microenvironment of GBM.

    Citation: Yong Xiao, Zhen Wang, Mengjie Zhao, Wei Ji, Chong Xiang, Taiping Li, Ran Wang, Kun Yang, Chunfa Qian, Xianglong Tang, Hong Xiao, Yuanjie Zou, Hongyi Liu. A novel defined risk signature of interferon response genes predicts the prognosis and correlates with immune infiltration in glioblastoma[J]. Mathematical Biosciences and Engineering, 2022, 19(9): 9481-9504. doi: 10.3934/mbe.2022441

    Related Papers:

  • Background

    Interferons (IFNs) have been implemented as anti-tumor immunity agents in clinical trials of glioma, but only a subset of glioblastoma (GBM) patients profits from it. The predictive role of IFNs stimulated genes in GBM needs further exploration to investigate the clinical role of IFNs.

     Methods

    This study screened 526 GBM patients from three independent cohorts. The transcriptome data with matching clinical information were analyzed using R. Immunohistochemical staining data from the Human Protein Atlas and DNA methylation data from MethSurv were used for validation in protein and methylation level respectively.

     Results

    We checked the survival effect of all 491 IFNs response genes, and found 54 genes characterized with significant hazard ratio in overall survival (OS). By protein-protein interaction analysis, 10 hub genes were selected out for subsequent study. And based on the expression of these 10 genes, GBM patients could be divided into two subgroups with significant difference in OS. Furthermore, the least absolute shrinkage and selection operator cox regression model was utilized to construct a multigene risk signature, including STAT3, STAT2 and SOCS3, which could serve as an independent prognostic predictor for GBM. The risk model was validated in two independent GBM cohorts. The GBM patients with high risk scores mainly concentrated in the GBM Mesenchymal subtype. The higher risk group was enriched in hypoxia, angiogenesis, EMT, glycolysis and immune pathways, and had increased Macrophage M2 infiltration and high expression of immune checkpoint CD274 (namely PD-L1).

     Conclusions

    Our findings revealed the three-gene risk model could be an independent prognostic predictor for GBM, and they were crucial participants in immunosuppressive microenvironment of GBM.


    加载中


    [1] S. Lapointe, A. Perry, N. A. Butowski, Primary brain tumours in adults, Lancet, 392 (2018), 432-446. DOI: 10.1016/S0140-6736(18)30990-5 doi: 10.1016/S0140-6736(18)30990-5
    [2] S. A. Grossman, X. Ye, S. Piantadosi, S. Desideri, L. B. Nabors, M. Rosenfeld, et al., Survival of patients with newly diagnosed glioblastoma treated with radiation and temozolomide in research studies in the United States, Clin. Cancer Res., 16 (2010), 2443-2449. DOI: 10.1158/1078-0432.CCR-09-3106 doi: 10.1158/1078-0432.CCR-09-3106
    [3] M. S. Uddin, A. Al Mamun, B. S. Alghamdi, D. Tewari, P. Jeandet, M. S. Sarwar, et al., Epigenetics of glioblastoma multiforme: From molecular mechanisms to therapeutic approaches, Semin. Cancer Biol., 83 (2022), 100-120. DOI: 10.1016/j.semcancer.2020.12.015 doi: 10.1016/j.semcancer.2020.12.015
    [4] H. W. Sim, K. L. McDonald, Z. Lwin, E. H. Barnes, M. Rosenthal, M. C. Foote, et al., A randomized phase II trial of veliparib, radiotherapy, and temozolomide in patients with unmethylated MGMT glioblastoma: The VERTU study, Neurol. Oncol., 23 (2021), 1736-1749. DOI: 10.1093/neuonc/noab111 doi: 10.1093/neuonc/noab111
    [5] X. R. Ni, C. C. Guo, Y. J. Yu, Z. H. Yu, H. P. Cai, W. C. Wu, et al., Combination of levetiracetam and IFN-alpha increased temozolomide efficacy in MGMT-positive glioma, Cancer Chemother. Pharmacol., 86 (2020), 773-782. DOI: 10.1007/s00280-020-04169-y doi: 10.1007/s00280-020-04169-y
    [6] Y. Ochiai, K. Sumi, E. Sano, S. Yoshimura, S. Yamamuro, A. Ogino, et al., Antitumor effects of ribavirin in combination with TMZ and IFN-beta in malignant glioma cells, Oncol. Lett., 20 (2020), 178. DOI: 10.3892/ol.2020.12039 doi: 10.3892/ol.2020.12039
    [7] A. Natsume, K. Aoki, F. Ohka, S. Maeda, M. Hirano, A. Adilijiang, et al., Genetic analysis in patients with newly diagnosed glioblastomas treated with interferon-beta plus temozolomide in comparison with temozolomide alone, J. Neurooncol., 148 (2020), 17-27. DOI: 10.1007/s11060-020-03505-9 doi: 10.1007/s11060-020-03505-9
    [8] K.Yuki, A. Natsume, H. Yokoyama, Y. Kondo, M. Ohno, T. Kato, et al., Induction of oligodendrogenesis in glioblastoma-initiating cells by IFN-mediated activation of STAT3 signaling, Cancer Lett., 284 (2009), 71-79. DOI: 10.1016/j.canlet.2009.04.020 doi: 10.1016/j.canlet.2009.04.020
    [9] S. Maeda, H. Wada, Y. Naito, H. Nagano, S. Simmons, Y. Kagawa, et al., Interferon-alpha acts on the S/G2/M phases to induce apoptosis in the G1 phase of an IFNAR2-expressing hepatocellular carcinoma cell line, J. Biol. Chem., 289 (2014), 23786-23795. DOI: 10.1074/jbc.M114.551879 doi: 10.1074/jbc.M114.551879
    [10] Y. Yang, A. L. Shaffer III, N. T. Emre, M. Ceribelli, M. Zhang, G. Wright, et al., Exploiting synthetic lethality for the therapy of ABC diffuse large B cell lymphoma, Cancer Cell, 21 (2012), 723-737. DOI: 10.1016/j.ccr.2012.05.024 doi: 10.1016/j.ccr.2012.05.024
    [11] M. Ilander, A. Kreutzman, P. Rohon, T. Melo, E. Faber, K. Porkka, et al., Enlarged memory T-cell pool and enhanced Th1-type responses in chronic myeloid leukemia patients who have successfully discontinued IFN-alpha monotherapy, PLoS One, 9 (2014), e87794. DOI: 10.1371/journal.pone.0087794 doi: 10.1371/journal.pone.0087794
    [12] N. Bacher, V. Raker, C. Hofmann, E. Graulich, M. Schwenk, R. Baumgrass, et al., Interferon-alpha suppresses cAMP to disarm human regulatory T cells, Cancer Res., 73 (2013), 5647-5656. DOI: 10.1158/0008-5472.CAN-12-3788 doi: 10.1158/0008-5472.CAN-12-3788
    [13] A. Kane, I. Yang, Interferon-gamma in brain tumor immunotherapy, Neurosurg. Clin. N Am., 21 (2010), 77-86. DOI: 10.1016/j.nec.2009.08.011 doi: 10.1016/j.nec.2009.08.011
    [14] V. Galani, S. S. Papadatos, G. Alexiou, A. Galani, A. P. Kyritsis, In vitro and in vivo preclinical effects of type I IFNs on gliomas, J. Interferon Cytokine Res., 37 (2017), 139-146. DOI: 10.1089/jir.2016.0094 doi: 10.1089/jir.2016.0094
    [15] B. X. Wang, R. Rahbar, E. N. Fish, Interferon: Current status and future prospects in cancer therapy, J. Interferon Cytokine Res., 31 (2011), 545-552. DOI: 10.1089/jir.2010.0158 doi: 10.1089/jir.2010.0158
    [16] J. Lei, M. H. Zhou, F. C. Zhang, K. Wu, S. W. Liu, H. Q. Niu, Interferon regulatory factor transcript levels correlate with clinical outcomes in human glioma, Aging (Albany NY), 13 (2021), 12086-12098. DOI: 10.18632/aging.202915 doi: 10.18632/aging.202915
    [17] F. J. Reu, S. I. Bae, L. Cherkassky, D. W. Leaman, D. Lindner, N. Beaulieu, et al., Overcoming resistance to interferon-induced apoptosis of renal carcinoma and melanoma cells by DNA demethylation, J. Clin. Oncol., 24 (2006), 3771-3779. DOI: 10.1200/JCO.2005.03.4074 doi: 10.1200/JCO.2005.03.4074
    [18] Y. Yang, Y. Zhou, J. Hou, C. Bai, Z. Li, J. Fan, et al., Hepatic IFIT3 predicts interferon-alpha therapeutic response in patients of hepatocellular carcinoma, Hepatology, 66 (2017), 152-166. DOI: 10.1002/hep.29156 doi: 10.1002/hep.29156
    [19] Z. Zhao, F. Meng, W. Wang, Z. Wang, C. Zhang, T. Jiang, Comprehensive RNA-seq transcriptomic profiling in the malignant progression of gliomas, Sci. Data, 4 (2017), 170024. DOI: 10.1038/sdata.2017.24 doi: 10.1038/sdata.2017.24
    [20] Cancer Genome Atlas Research N, Comprehensive genomic characterization defines human glioblastoma genes and core pathways, Nature, 455 (2008), 1061-1068. DOI: 10.1038/nature07385 doi: 10.1038/nature07385
    [21] H. Mizuno, K. Kitada, K. Nakai, A. Sarai, PrognoScan: A new database for meta-analysis of the prognostic value of genes, BMC Med. Genomics, 2 (2009), 18. DOI: 10.1186/1755-8794-2-18 doi: 10.1186/1755-8794-2-18
    [22] V. Modhukur, T. Iljasenko, T. Metsalu, K. Lokk, T. Laisk-Podar, et al., MethSurv: A web tool to perform multivariable survival analysis using DNA methylation data, Epigenomics, 10 (2018), 277-288. DOI: 10.2217/epi-2017-0118 doi: 10.2217/epi-2017-0118
    [23] A. Liberzon, C. Birger, H. Thorvaldsdóttir, M. Ghandi, J. P. Mesirov, P. Tamayo, The molecular signatures database (MSigDB) hallmark gene set collection, Cell Syst., 1 (2015), 417-425. DOI: 10.1016/j.cels.2015.12.004 doi: 10.1016/j.cels.2015.12.004
    [24] T. Li, J. Fu, Z. Zeng, D. Cohen, J. Li, Q. Chen, et al., TIMER2.0 for analysis of tumor-infiltrating immune cells, Nucleic Acids Res., 48 (2020), W509-W514. DOI: 10.1093/nar/gkaa407 doi: 10.1093/nar/gkaa407
    [25] A. M. Newman, C. L. Liu, M. R. Green, A. J. Gentles, W. Feng, Y. Xu, et al., Robust enumeration of cell subsets from tissue expression profiles, Nat. Methods, 12 (2015), 453-457. DOI: 10.1038/nmeth.3337 doi: 10.1038/nmeth.3337
    [26] M. Uhlén, L. Fagerberg, B. M. Hallström, C. Lindskog, P. Oksvold, A. Mardinoglu, et al., Proteomics. Tissue-based map of the human proteome, Science, 347 (2015), 1260419. DOI: 10.1126/science.1260419 doi: 10.1126/science.1260419
    [27] W. Ji, Y. Liu, B. Xu, J. Mei, C. Cheng, Y. Xiao, et al., Bioinformatics analysis of expression profiles and prognostic values of the signal transducer and activator of transcription family genes in glioma, Front. Genet., 12 (2021), 625234. DOI: 10.3389/fgene.2021.625234 doi: 10.3389/fgene.2021.625234
    [28] K. Dzobo, D. A. Senthebane, C. Ganz, N. E. Thomford, A. Wonkam, C. Dandara, Advances in therapeutic targeting of cancer stem cells within the tumor microenvironment: An updated review, Cells, 9 (2020), 1896. DOI: 10.3390/cells9081896 doi: 10.3390/cells9081896
    [29] C. Hou, Y. Ishi, H. Motegi, M. Okamoto, Y. Ou, J. Chen, et al., Overexpression of CD44 is associated with a poor prognosis in grade II/III gliomas, J. Neurooncol., 145 (2019), 201-210. DOI: 10.1007/s11060-019-03288-8 doi: 10.1007/s11060-019-03288-8
    [30] A. Vakilian, H. Khorramdelazad, P. Heidari, Z. S. Rezaei, G. Hassanshahi, CCL2/CCR2 signaling pathway in glioblastoma multiforme, Neurochem. Int., 103 (2017), 1-7. DOI: 10.1016/j.neuint.2016.12.013 doi: 10.1016/j.neuint.2016.12.013
    [31] S. H. Hayes, G. M. Seigel, Immunoreactivity of ICAM-1 in human tumors, metastases and normal tissues, Int. J. Clin. Exp. Pathol., 2 (2009), 553-560.
    [32] T. Cartwright, N. D. Perkins, C. L. Wilson, NFKB1: A suppressor of inflammation, ageing and cancer, Febs. J., 283 (2016), 1812-1822. DOI: 10.1111/febs.13627 doi: 10.1111/febs.13627
    [33] Q. Guo, X. Xiao, J. Zhang, MYD88 is a potential prognostic gene and immune signature of tumor microenvironment for gliomas, Front. Oncol., 11 (2021), 654388. DOI: 10.3389/fonc.2021.654388 doi: 10.3389/fonc.2021.654388
    [34] Y. E. Hadisaputri, T. Miyazaki, T. Yokobori, M. Sohda, M. Sakai, D. Ozawa, et al., TNFAIP3 overexpression is an independent factor for poor survival in esophageal squamous cell carcinoma, Int. J. Oncol., 50 (2017), 1002-1010. DOI: 10.3892/ijo.2017.3869 doi: 10.3892/ijo.2017.3869
    [35] M. P. Ventero, M. Fuentes-Baile, C. Quereda, E. Perez-Valeciano, C. Alenda, P. Garcia-Morales, et al., Radiotherapy resistance acquisition in Glioblastoma. Role of SOCS1 and SOCS3, PLoS One, 14 (2019), e0212581. DOI: 10.1371/journal.pone.0212581 doi: 10.1371/journal.pone.0212581
    [36] O. Gusyatiner, M. E. Hegi, Glioma epigenetics: From subclassification to novel treatment options, Semin. Cancer Biol., 51 (2018), 50-58. DOI: 10.1016/j.semcancer.2017.11.010 doi: 10.1016/j.semcancer.2017.11.010
    [37] R. Chaligne, F. Gaiti, D. Silverbush, J. S. Schiffman, H. R. Weisman, L. Kluegel, et al., Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states, Nat. Genet., 53 (2021), 1469-1479. DOI: 10.1038/s41588-021-00927-7 doi: 10.1038/s41588-021-00927-7
    [38] J. Lu, Z. Xu, H. Duan, H. Ji, Z. Zhen, B. Li, et al., Tumor-associated macrophage interleukin-beta promotes glycerol-3-phosphate dehydrogenase activation, glycolysis and tumorigenesis in glioma cells, Cancer Sci., 111 (2020), 1979-1990. DOI: 10.1111/cas.14408 doi: 10.1111/cas.14408
    [39] J. Ye, Y. Yang, J. Jin, M. Ji, Y. Gao, Y. Feng, et al., Targeted delivery of chlorogenic acid by mannosylated liposomes to effectively promote the polarization of TAMs for the treatment of glioblastoma, Bioact. Mater., 5 (2020), 694-708. DOI: 10.1016/j.bioactmat.2020.05.001 doi: 10.1016/j.bioactmat.2020.05.001
    [40] D. Akhavan, D. Alizadeh, D. Wang, M. R. Weist, J. K. Shepphird, C. E. Brown, CAR T cells for brain tumors: Lessons learned and road ahead, Immunol. Rev., 290 (2019), 60-84. DOI: 10.1111/imr.12773 doi: 10.1111/imr.12773
    [41] C. Neftel, J. Laffy, M. G. Filbin, T. Hara, M. E. Shore, G. J. Rahme, et al., An integrative model of cellular states, plasticity, and genetics for glioblastoma, Cell, 178 (2019), 835-849. DOI: 10.1016/j.cell.2019.06.024 doi: 10.1016/j.cell.2019.06.024
    [42] J. Chen, Y. Li, Q. Zheng, C. Bao, J. He, B. Chen, et al., Circular RNA profile identifies circPVT1 as a proliferative factor and prognostic marker in gastric cancer, Cancer Lett., 388 (2017), 208-219. DOI: 10.1016/j.canlet.2016.12.006 doi: 10.1016/j.canlet.2016.12.006
    [43] F. M. Tian, F. Q. Meng, X. B. Wang, Overexpression of long-noncoding RNA ZFAS1 decreases survival in human NSCLC patients, Eur. Rev. Med. Pharmacol. Sci., 20 (2016), 5126-5131.
    [44] M. Zhou, Z. Zhang, S. Bao, P. Hou, C. Yan, J. Su, et al., Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer, Brief Bioinform., 22 (2021), bbaa047. DOI: 10.1093/bib/bbaa047 doi: 10.1093/bib/bbaa047
    [45] Y. Ye, Q. Dai, S. Li, J. He, H. Qi, A novel defined risk signature of the ferroptosis-related genes for predicting the prognosis of ovarian cancer, Front. Mol. Biosci., 8 (2021), 645845. DOI: 10.3389/fmolb.2021.645845 doi: 10.3389/fmolb.2021.645845
    [46] N. Au-Yeung, R. Mandhana, C. M. Horvath, Transcriptional regulation by STAT1 and STAT2 in the interferon JAK-STAT pathway, Jakstat, 2 (2013), e23931. DOI: 10.4161/jkst.23931 doi: 10.4161/jkst.23931
    [47] J. Xu, M. H. Lee, M. Chakhtoura, B. L. Green, K. P. Kotredes, R. W. Chain, et al., STAT2 is required for TLR-induced murine dendritic cell activation and cross-presentation, J. Immunol., 197 (2016), 326-336. DOI: 10.4049/jimmunol.1500152 doi: 10.4049/jimmunol.1500152
    [48] L. Wang, D. Xu, L. Cai, J. Dai, Y. Li, H. Xu, Expression and survival analysis of the STAT gene family in diffuse gliomas using integrated bioinformatics, Curr. Res. Transl. Med., 69 (2021), 103274. DOI: 10.1016/j.retram.2020.103274 doi: 10.1016/j.retram.2020.103274
    [49] K. Swiatek-Machado, B. Kaminska, STAT signaling in glioma cells, Adv. Exp. Med. Biol., 986 (2013), 189-208. DOI: 10.1007/978-94-007-4719-7_10 doi: 10.1007/978-94-007-4719-7_10
    [50] Y. Wang, Y. Shen, S. Wang, Q. Shen, X. Zhou, The role of STAT3 in leading the crosstalk between human cancers and the immune system, Cancer Lett., 415 (2018), 117-128. DOI: 10.1016/j.canlet.2017.12.003 doi: 10.1016/j.canlet.2017.12.003
    [51] K. V. Myers, K. J. Pienta, S. R. Amend, Cancer cells and M2 macrophages: Cooperative invasive ecosystem engineers, Cancer Control, 27 (2020), 1073274820911058. DOI: 10.1177/1073274820911058 doi: 10.1177/1073274820911058
    [52] R. Mahony, S. Ahmed, C. Diskin, N. J. Stevenson, SOCS3 revisited: A broad regulator of disease, now ready for therapeutic use, Cell Mol. Life Sci., 73 (2016), 3323-3336. DOI: 10.1007/s00018-016-2234-x doi: 10.1007/s00018-016-2234-x
    [53] Y. Yu, S. K. Sung, C. H. Lee, M. Ha, J. Kang, E. J. Kwon, et al., SOCS3 is related to cell proliferation in neuronal tissue: An integrated analysis of bioinformatics and experiments, Front. Genet., 12 (2021), 743786. DOI: 10.3389/fgene.2021.743786 doi: 10.3389/fgene.2021.743786
    [54] B. C. McFarland, M. P. Marks, A. L. Rowse, S. C. Fehling, M. Gerigk, H. Qin, et al., Loss of SOCS3 in myeloid cells prolongs survival in a syngeneic model of glioma, Oncotarget, 7 (2016), 20621-20635. DOI: 10.18632/oncotarget.7992 doi: 10.18632/oncotarget.7992
    [55] H. Zhou, R. Miki, M. Eeva, F. M. Fike, D. Seligson, L. Yang, et al., Reciprocal regulation of SOCS1 and SOCS3 enhances resistance to ionizing radiation in glioblastoma multiforme, Clin. Cancer Res., 13 (2007), 2344-2353. DOI: 10.1158/1078-0432.CCR-06-2303 doi: 10.1158/1078-0432.CCR-06-2303
    [56] D. F. Quail, J. A. Joyce, The microenvironmental landscape of brain tumors, Cancer Cell, 31 (2017), 326-341. DOI: 10.1016/j.ccell.2017.02.009 doi: 10.1016/j.ccell.2017.02.009
    [57] Y. Masugi, R. Nishihara, J. Yang, K. Mima, A. Da Silva, Y. Shi, et al., Tumour CD274 (PD-L1) expression and T cells in colorectal cancer, Gut, 66 (2017), 1463-1473. DOI:10.1136/gutjnl-2016-311421 doi: 10.1136/gutjnl-2016-311421
  • mbe-19-09-441-supplementary.docx
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Mathematical Biosciences and Engineering
3.9

Metrics

Article views(2148) PDF downloads(134) Cited by(0)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Figures(12)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog