ORIGINAL ARTICLE
Molecular classification of glioblastoma based on immunohistochemical expression of EGFR, PDGFRA, NF1, IDH1, p53 and PTEN proteins
1
Department of Pathology, Pomeranian Medical University, Szczecin, Poland
2
Department of Neurology, Pomeranian Medical University, Szczecin, Poland
3
Department of Neurosurgery, Pomeranian Medical University, Szczecin, Poland
Submission date: 2020-12-04
Final revision date: 2021-04-25
Acceptance date: 2021-05-26
Publication date: 2021-05-31
Pol J Pathol 2021;72(1):1-10
KEYWORDS
TOPICS
ABSTRACT
Glioblastoma (GBM) is the most common and most aggressive primary tumor of the central nervous system. Current GBM treatments have low effectiveness. This is mainly due to the high degree of heterogeneity of GBM tumors. Despite similarities in the classic microscopic image, these tumors differ significantly in molecular terms. The aim of the study was to classify GBM tumors into one of four molecular types based on the immunohistochemical expression of EGFR, PDGFRA, NF1, IDH1, p53 and PTEN proteins and find the association between individual glioma molecular types and prognostic clinical and morphological parameters. From the group of 162 patients the classical molecular type of tumor was observed in 17 (10%) patients, in 23 (14%) the tumor was mesenchymal, in 32 (20%) proneural, and in 90 (56%) neural. No significant relationship was observed between the molecular type of GBM tumors and the studied clinical and morphological parameters of prognostic significance. There were also no statistically significant correlations between the GBM tumor molecular type and survival, both in terms of overall survival and relapse-free survival. Analyzing the impact of all prognostic variables and molecular type of GBM on the probability of overall survival, statistically significant relationships were found.
REFERENCES (33)
1.
Velásquez C, Mansouri S, Mora C, et al. Molecular and clinical insights into the invasive capacity of glioblastoma cells. J Oncol 2019; 1: 740-763.
2.
Batash R, Asna N, Schaffer P, et al. Glioblastoma multiforme, diagnosis and treatment; recent literature review. Curr Med Chem 2017; 24: 3002-3009.
3.
Zhou W, Wahl DR. Metabolic abnormalities in glioblastoma and metabolic strategies to overcome treatment resistance. Cancers 2019; 11: 1231.
4.
Gately L, McLachlan SA, Philip J, et al. Molecular profile of long-term survivors of glioblastoma: a scoping review of the literature. Clin Neurosci 2019; 68: 1-8.
5.
Noch EK, Ramakrishna R, Magge R. Challenges in the treatment of glioblastoma: multisystem mechanisms of therapeutic resistance. World Neurosurg 2018; 116: 505-517.
6.
Verhaak RG, Hoadley KA, Purdom E, et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR and NF1. Cancer Cell 2010; 17: 98-110.
7.
Cancer Genome Atlas Research Network, Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008; 455: 1061-1068.
8.
Brennan CW, Verhaak RG, McKenna A, et al. The somatic genomic landscape of glioblastoma. Cell 2013; 155: 462-477.
9.
Le Mercier M, Hastir D, Lopez XM, et al. A simplified approach for the molecular classification of glioblastomas. PLoS One 2012; 7: e45475.
10.
Chaurasia A, Park SH, Seo JW, et al. Immunohistochemical analysis of ATRX, IDH1 and p53 in glioblastoma and their correlations with patient survival. J Korean Med Sci 2016; 31: 1208-1214.
11.
Nagy Á, Garzuly F, Padányi G, et al. Molecular subgroups of glioblastoma – an assessment by immunohistochemical markers. Pathol Oncol Res 2019; 25: 21-31.
12.
Jovčevska I. Genetic secrets of long-term glioblastoma survivors. Bosn J Basic Med Sci 2019; 19: 116-124.
13.
Wesseling P, Capper D. WHO 2016 Classification of gliomas. Neuropathol Appl Neurobiol 2018; 44: 139-150.
14.
Jakovlevs A, Vanags A, Gardovskis J, et al. Molecular classification of diffuse gliomas. Pol J Pathol 2019; 70: 246-258.
15.
Steed TC, Treiber JM, Patel K, et al. Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis. Oncotarget 2016; 7: 24899-24907.
16.
Aubry M, de Tayrac M, Etcheverry A, et al. From the core to beyond the margin: a genomic picture of glioblastoma intratumor heterogeneity. Oncotarget 2015; 6: 12094-12109.
17.
McKeever PE, Dennis TR, Burgess AC, et al. Chromosome break point at 17q11.2 andinsertion of DNA from three different chromosomes in a glioblastoma with exceptional glial fibrillary acidic protein expression. Cancer Genet Cytogenet 1996; 87: 41-47.
18.
Vandenbroucke I, Van Oostveldt P, Coene E, et al. Neurofibromin is actively transported to the nucleus. FEBS Lett 2004; 560: 98-102.
19.
Felsberg J, Hentschel B, Kaulich K, et al. Epidermal Growth Factor Receptor Variant III (EGFRvIII) Positivity in EGFR-amplified glioblastomas: prognostic role and comparison between primary and recurrent tumors. Clin Cancer Res 2017; 23: 6846-6855.
20.
Karnam S, Kottu R, Chowhan AK, et al. Expression of p53 & epidermal growth factor receptor in glioblastoma. Indian.
22.
Lee E, Yong RL, Paddison P, et al. Comparison of glioblastoma (GBM) molecular classification methods. Semin Cancer Biol 2018; 53: 201-211.
23.
Noushmehr H, Weisenberger DJ, Diefes K, et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 2010; 17: 510-522.
24.
He ZC, Ping YF, Xu SL, et al. Fetal lower MGMT expression predicts better prognosis in proneural-like glioblastoma. Int.
26.
Myung JK, Jin Cho H, Kim H, et al. Prognosis of glioblastoma with oligodendroglioma component is associated with the IDH1 mutation and MGMT methylation status. Transl Oncol 2014; 7: 712-719.
27.
Sottoriva A, Spiteri I, Piccirillo SG, et al. Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics. Proc Natl Acad Sci U S A 2013; 110: 4009-4014.
28.
Johnson BE, Mazor T, Hong C, et al. Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science 2014; 343: 189-193.
29.
Kalkan R. Glioblastoma stem cells as a new therapeutic target for glioblastoma. Clin Med Insights Oncol 2015; 9: 95-103.
30.
Lan X, Jörg DJ, Cavalli FMG, et al., Fate mapping of human glioblastoma reveals an invariant stem cell hierarchy. Nature 2017; 549: 227-232.
31.
Eder K, Kalman B. Molecular heterogeneity of glioblastoma and its clinical relevance. Pathol Oncol Res 2014; 20: 777-787.
32.
Severson B, Li E, Pignon JC, et al. Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biol 2016; 17: 174.
33.
Huang B, Zhang H, Gu L, et al. Advances in immunotherapy for glioblastoma multiforme. J Immunol Res 2017; 3: 597-613.
Share
RELATED ARTICLE
| eISSN: | 2084-9869 |
| ISSN: | 1233-9687 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
