Download PDF
J Neurol Surg A Cent Eur Neurosurg 2025; 86(01): 017-029
DOI: 10.1055/s-0043-1777761
Original Article

Elevated HSPB1 Expression Is Associated with a Poor Prognosis in Glioblastoma Multiforme Patients

Zhihua Wang
1   Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
,
Zhaohua Fang
2   Department of Neurosurgery, Chongren County People's Hospital, Fuzhou, Jiangxi, China
,
Yongping Gui
3   Department of Neurosurgery, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
4   Department of Neurosurgery, Xiangya Hospital Jiangxi Hospital, Central South University, Nanchang, Jiangxi, China
,
Bin Xi
3   Department of Neurosurgery, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
4   Department of Neurosurgery, Xiangya Hospital Jiangxi Hospital, Central South University, Nanchang, Jiangxi, China
,
Zhiping Xie
3   Department of Neurosurgery, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
4   Department of Neurosurgery, Xiangya Hospital Jiangxi Hospital, Central South University, Nanchang, Jiangxi, China
› Author Affiliations Funding This research was supported by the Scientific Research initial foundation of Jiangxi Provincial People's Hospital.
› Further Information
Also available at
    Permissions and Reprints

Abstract

Background Glioblastoma multiforme (GBM) is a highly aggressive form of brain cancer. This study investigated the clinical predictive value of heat shock protein β1 (HSPB1) in patients with GBM.

Methods A correlation was established between HSPB1 expression and GBM progression using data from The Cancer Genome Atlas (TCGA) dataset, Chinese Glioma Genome Atlas dataset, Gene Expression Omnibus dataset, and Human Protein Atlas database. A survival analysis was conducted and an HSPB1-based nomogram was constructed to evaluate the prognostic value of HSPB1 in patients with GBM.

Results Based on TCGA data mining, we discovered that HSPB1 was significantly elevated in patients with GBM and may reflect their response to immunotherapy. In survival analysis, it appeared to have a predictive role in the prognosis of patients with GBM. Five signaling pathways were significantly enriched in the high HSPB1 expression phenotype according to the gene set enrichment analysis. In addition, a significant association was found between HSPB1 expression and immune checkpoints, tumor immune infiltration, tumor immune microenvironment, and immune cell markers in glioma. Overall, our results suggest that HSPB1 may regulate the function of immune cells, serve as a new immunotherapy target, and predict the response to immunotherapy in patients with GBM.

Conclusion HSPB1 appears to serve as a potential predictor of the clinical prognosis and response to immunotherapy in patients with GBM. It may be possible to identify patients who are likely to benefit from immunotherapy by assessing the expression level of HSPB1.

Keywords

glioblastoma multiforme - heat shock protein β1 - biomarker - immunity - prognosis

Availability of Data and Material

All data generated or analyzed are included in this article and are available from the corresponding author on reasonable request.


Author Contributions

Z.W. was responsible for the design and concept of the study, analysis and visualization, and writing and revision of the article. Z.F., B.X., and Y.G. contributed to article revising and reviewing. Z.X. contributed to the study design and concept, and article reviewing. All the authors approved the final version of the article.




Publication History

Received: 18 May 2023

Accepted: 24 October 2023

Article published online:
03 July 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Stupp R, Hegi ME, Mason WP. et al; European Organisation for Research and Treatment of Cancer Brain Tumour and Radiation Oncology Groups, National Cancer Institute of Canada Clinical Trials Group. Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol 2009; 10 (05) 459-466
    CrossrefPubMedSearch in Google Scholar
  • 2 Ostrom QT, Gittleman H, Liao P. et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2010-2014. Neuro-oncol 2017; 19 (Suppl. 05) v1-v88
    CrossrefPubMedSearch in Google Scholar
  • 3 Virtuoso A, Giovannoni R, De Luca C. et al. The glioblastoma microenvironment: morphology, metabolism, and molecular signature of glial dynamics to discover metabolic rewiring sequence. Int J Mol Sci 2021; 22 (07) 22
    CrossrefPubMedSearch in Google Scholar
  • 4 Carrasco-Garcia E, Martinez-Lacaci I, Mayor-López L. et al. PDGFR and IGF-1R inhibitors induce a G2/M arrest and subsequent cell death in human glioblastoma cell lines. Cells 2018; 7 (09) 7
    CrossrefPubMedSearch in Google Scholar
  • 5 Cho CF, Farquhar CE, Fadzen CM. et al. A tumor-homing peptide platform enhances drug solubility, improves blood-brain barrier permeability and targets glioblastoma. Cancers (Basel) 2022; 14 (09) 14
    CrossrefPubMedSearch in Google Scholar
  • 6 Lechpammer M, Rao R, Shah S. et al. Advances in immunotherapy for the treatment of adult glioblastoma: overcoming chemical and physical barriers. Cancers (Basel) 2022; 14 (07) 14
    CrossrefPubMedSearch in Google Scholar
  • 7 McGranahan T, Therkelsen KE, Ahmad S, Nagpal S. Current state of immunotherapy for treatment of glioblastoma. Curr Treat Options Oncol 2019; 20 (03) 24
    CrossrefPubMedSearch in Google Scholar
  • 8 Chen Z, Hambardzumyan D. Immune microenvironment in glioblastoma subtypes. Front Immunol 2018; 9: 1004
    CrossrefPubMedSearch in Google Scholar
  • 9 Reardon DA, Brandes AA, Omuro A. et al. Effect of nivolumab vs bevacizumab in patients with recurrent glioblastoma: the CheckMate 143 phase 3 randomized clinical trial. JAMA Oncol 2020; 6 (07) 1003-1010
    CrossrefPubMedSearch in Google Scholar
  • 10 Amoozgar Z, Kloepper J, Ren J. et al. Targeting Treg cells with GITR activation alleviates resistance to immunotherapy in murine glioblastomas. Nat Commun 2021; 12 (01) 2582
    CrossrefPubMedSearch in Google Scholar
  • 11 Pombo Antunes AR, Scheyltjens I, Duerinck J, Neyns B, Movahedi K, Van Ginderachter JA. Understanding the glioblastoma immune microenvironment as basis for the development of new immunotherapeutic strategies. eLife 2020; 9: 9
    CrossrefPubMedSearch in Google Scholar
  • 12 Lianos GD, Alexiou GA, Mangano A. et al. The role of heat shock proteins in cancer. Cancer Lett 2015; 360 (02) 114-118
    CrossrefPubMedSearch in Google Scholar
  • 13 Zhang R, Tremblay TL, McDermid A, Thibault P, Stanimirovic D. Identification of differentially expressed proteins in human glioblastoma cell lines and tumors. Glia 2003; 42 (02) 194-208
    CrossrefPubMedSearch in Google Scholar
  • 14 Wang S, Xiong Y, Zhao L. et al. UCSCXenaShiny: an R/CRAN package for interactive analysis of UCSC xena data. . Bioinformatics 2021
    PubMed
  • 15 Uhlén M, Fagerberg L, Hallström BM. et al. Proteomics. Tissue-based map of the human proteome. Science 2015; 347 (6220) 1260419
    CrossrefPubMedSearch in Google Scholar
  • 16 Szklarczyk D, Morris JH, Cook H. et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 2017; 45 (D1): D362-D368
    CrossrefPubMedSearch in Google Scholar
  • 17 Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 2003; 4: 2
    CrossrefPubMedSearch in Google Scholar
  • 18 Subramanian A, Tamayo P, Mootha VK. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 2005; 102 (43) 15545-15550
    CrossrefPubMedSearch in Google Scholar
  • 19 Zhou Q, Yan X, Liu W. et al. Three immune-associated subtypes of diffuse glioma differ in immune infiltration, immune checkpoint molecules, and prognosis. Front Oncol 2020; 10: 586019
    CrossrefPubMedSearch in Google Scholar
  • 20 Kim JE, Patel MA, Mangraviti A. et al. Combination therapy with anti-PD-1, anti-TIM-3, and focal radiation results in regression of murine gliomas. Clin Cancer Res 2017; 23 (01) 124-136
    CrossrefPubMedSearch in Google Scholar
  • 21 Garg AD, Vandenberk L, Van Woensel M. et al. Preclinical efficacy of immune-checkpoint monotherapy does not recapitulate corresponding biomarkers-based clinical predictions in glioblastoma. OncoImmunology 2017; 6 (04) e1295903
    CrossrefPubMedSearch in Google Scholar
  • 22 Ye W, Luo C, Li C, Liu Z, Liu F. CD161, a promising immune checkpoint, correlates with patient prognosis: a pan-cancer analysis. J Cancer 2021; 12 (21) 6588-6599
    CrossrefPubMedSearch in Google Scholar
  • 23 Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics 2013; 14: 7
    CrossrefPubMedSearch in Google Scholar
  • 24 Bindea G, Mlecnik B, Tosolini M. et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 2013; 39 (04) 782-795
    CrossrefPubMedSearch in Google Scholar
  • 25 Yoshihara K, Shahmoradgoli M, Martínez E. et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun 2013; 4: 2612
    CrossrefPubMedSearch in Google Scholar
  • 26 Ostrom QT, Cioffi G, Gittleman H. et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2012-2016. Neuro-oncol 2019; 21 (Suppl. 05) v1-v100
    CrossrefPubMedSearch in Google Scholar
  • 27 Yaghi NK, Gilbert MR. Immunotherapeutic approaches for glioblastoma treatment. Biomedicines 2022; 10 (02) 10
    CrossrefPubMedSearch in Google Scholar
  • 28 M Gagné L, Boulay K, Topisirovic I, Huot MÉ, Mallette FA. L MG. Oncogenic activities of IDH1/2 mutations: from epigenetics to cellular signaling. Trends Cell Biol 2017; 27 (10) 738-752
    CrossrefPubMedSearch in Google Scholar
  • 29 Wick W, Meisner C, Hentschel B. et al. Prognostic or predictive value of MGMT promoter methylation in gliomas depends on IDH1 mutation. Neurology 2013; 81 (17) 1515-1522
    CrossrefPubMedSearch in Google Scholar
  • 30 Zeng J, See AP, Phallen J. et al. Anti-PD-1 blockade and stereotactic radiation produce long-term survival in mice with intracranial gliomas. Int J Radiat Oncol Biol Phys 2013; 86 (02) 343-349
    CrossrefPubMedSearch in Google Scholar
  • 31 Park J, Kwon M, Kim KH. et al. Immune checkpoint inhibitor-induced reinvigoration of tumor-infiltrating CD8+ T cells is determined by their differentiation status in glioblastoma. Clin Cancer Res 2019; 25 (08) 2549-2559
    CrossrefPubMedSearch in Google Scholar
  • 32 Liang Y, Wang Y, Zhang Y. et al. HSPB1 facilitates chemoresistance through inhibiting ferroptotic cancer cell death and regulating NF-κB signaling pathway in breast cancer. Cell Death Dis 2023; 14 (07) 434
    CrossrefPubMedSearch in Google Scholar
  • 33 Long S, Peng F, Song B, Wang L, Chen J, Shang B. Heat shock protein beta 1 is a prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma. Int J Gen Med 2021; 14: 5483-5492
    CrossrefPubMedSearch in Google Scholar
  • 34 Peng S, Yin Y, Zhang Y, Zhu F, Yang G, Fu Y. FYN/TOPK/HSPB1 axis facilitates the proliferation and metastasis of gastric cancer. J Exp Clin Cancer Res 2023; 42 (01) 80
    CrossrefPubMedSearch in Google Scholar
  • 35 Huang ZC, Li H, Sun ZQ. et al. Distinct prognostic roles of HSPB1 expression in non-small cell lung cancer. Neoplasma 2018; 65 (01) 161-166
    CrossrefPubMedSearch in Google Scholar
  • 36 Okuno M, Adachi S, Kozawa O, Shimizu M, Yasuda I. The clinical significance of phosphorylated heat shock protein 27 (HSPB1) in pancreatic cancer. Int J Mol Sci 2016; 17 (01) 17
    CrossrefPubMedSearch in Google Scholar
  • 37 Deng S, Zheng Y, Mo Y. et al. Ferroptosis suppressive genes correlate with immunosuppression in glioblastoma. World Neurosurg 2021; 152: e436-e448
    CrossrefPubMedSearch in Google Scholar
  • 38 Gimenez M, Marie SKN, Oba-Shinjo S. et al. Quantitative proteomic analysis shows differentially expressed HSPB1 in glioblastoma as a discriminating short from long survival factor and NOVA1 as a differentiation factor between low-grade astrocytoma and oligodendroglioma. BMC Cancer 2015; 15: 481
    CrossrefPubMedSearch in Google Scholar
  • 39 Sabaawy HE, Ryan BM, Khiabanian H, Pine SR. JAK/STAT of all trades: linking inflammation with cancer development, tumor progression and therapy resistance. Carcinogenesis 2021; 42 (12) 1411-1419
    CrossrefPubMedSearch in Google Scholar
  • 40 Ridnour LA, Cheng RY, Switzer CH. et al. Molecular pathways: toll-like receptors in the tumor microenvironment: poor prognosis or new therapeutic opportunity. Clin Cancer Res 2013; 19 (06) 1340-1346
    CrossrefPubMedSearch in Google Scholar
  • 41 Zins K, Sioud M, Aharinejad S, Lucas T, Abraham D. Modulating the tumor microenvironment with RNA interference as a cancer treatment strategy. Methods Mol Biol 2015; 1218: 143-161
    CrossrefPubMedSearch in Google Scholar
  • 42 Moossavi M, Parsamanesh N, Bahrami A, Atkin SL, Sahebkar A. Role of the NLRP3 inflammasome in cancer. Mol Cancer 2018; 17 (01) 158
    CrossrefPubMedSearch in Google Scholar
  • 43 Crisponi L, Buers I, Rutsch F. CRLF1 and CLCF1 in Development, Health and Disease. Int J Mol Sci 2022; 23 (02) 23
    CrossrefPubMedSearch in Google Scholar
  • 44 Kaderbhaï C, Tharin Z, Ghiringhelli F. The role of molecular profiling to predict the response to immune checkpoint inhibitors in lung cancer. Cancers (Basel) 2019; 11 (02) 11
    CrossrefPubMedSearch in Google Scholar
  • 45 Neal JT, Li X, Zhu J. et al. Organoid modeling of the tumor immune microenvironment. Cell 2018; 175 (07) 1972-1988.e16
    CrossrefPubMedSearch in Google Scholar
  • 46 Jiao S, Subudhi SK, Aparicio A. et al. Differences in tumor microenvironment dictate T helper lineage polarization and response to immune checkpoint therapy. Cell 2019; 179 (05) 1177-1190.e13
    CrossrefPubMedSearch in Google Scholar
  • 47 Zhao G, Yu H, Ding L. et al. microRNA-27a-3p delivered by extracellular vesicles from glioblastoma cells induces M2 macrophage polarization via the EZH1/KDM3A/CTGF axis. Cell Death Discov 2022; 8 (01) 260
    CrossrefPubMedSearch in Google Scholar
  • 48 Wu J, Shen S, Liu T. et al. Chemerin enhances mesenchymal features of glioblastoma by establishing autocrine and paracrine networks in a CMKLR1-dependent manner. Oncogene 2022; 41 (21) 3024-3036
    CrossrefPubMedSearch in Google Scholar
  • 49 Chen Y, Song Y, Du W, Gong L, Chang H, Zou Z. Tumor-associated macrophages: an accomplice in solid tumor progression. J Biomed Sci 2019; 26 (01) 78
    CrossrefPubMedSearch in Google Scholar
  • 50 Mellman I, Coukos G, Dranoff G. Cancer immunotherapy comes of age. Nature 2011; 480 (7378) 480-489
    CrossrefPubMedSearch in Google Scholar
  • 51 Gil Del Alcazar CR, Alečković M, Polyak K. Immune escape during breast tumor progression. Cancer Immunol Res 2020; 8 (04) 422-427
    CrossrefPubMedSearch in Google Scholar