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Mekler AA, Schwartz DR, Savelieva OE. Genetic Discrimination of Grade 3 and Grade 4 Gliomas by Artificial Neural Network. Cell Mol Neurobiol 2023; 44:13. [PMID: 38150033 DOI: 10.1007/s10571-023-01448-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 12/16/2023] [Indexed: 12/28/2023]
Abstract
Gliomas, including anaplastic gliomas (AG; grade 3) and glioblastomas (GBM; grade 4), are malignant brain tumors associated with poor prognosis and low survival rates. Current classification systems based on histopathology have limitations due to intratumoral heterogeneity. The treatment and prognosis are distinctly different between grade 3 and grade 4 gliomas patients. Therefore, there is a need for molecular markers to differentiate these tumors accurately. In this study, we aimed to identify a gene expression signature using an artificial neural network (ANN) in application to microarray and serial analysis of gene expression (SAGE) data for grade 3 (AG) and grade 4 (GBM) gliomas discrimination. We acquired gene expression data from publicly available datasets on glial tumors of grades 3 and 4-a total of 93 grade 3 gliomas and 224 grade 4 gliomas. To select genes for classification, we implemented an artificial neural network-based method using a combination of self-organized maps (SOM) and perceptron. In general, we implemented a multi-stage procedure that involved multiple runs of a genetic algorithm to identify genes that provided optimal clusterization on the SOM. We performed this procedure multiple times, resulting in different sets of genes each time. Eventually, we selected several genes that appeared most frequently in the reduced sets and performed classification using them. Our analysis identified a set of seven genes (BCAS4, GLUD2, KCNJ10, KCND2, AKR7A2, FOLR1, and KIAA0319). The classification accuracy using this gene set was 87.5%. These findings suggest the potential of this gene set as a molecular marker for distinguishing grade 3 (AG) from grade 4 (GBM) gliomas.
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Affiliation(s)
- Aleksei A Mekler
- Department for Innovations and Analytics, St. Petersburg State Pediatric Medical University, Saint Petersburg, 194100, Russia.
| | - Dmitry R Schwartz
- Institute of Computer Science and Technologies, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, 195251, Russia
| | - Olga E Savelieva
- Research Center and Department of Biological Chemistry, St. Petersburg State Pediatric Medical University, Saint Petersburg, 194100, Russia
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Kalita O, Sporikova Z, Hajduch M, Megova Houdova M, Slavkovsky R, Hrabalek L, Halaj M, Klementova Y, Dolezel M, Drabek J, Tuckova L, Ehrmann J, Vrbkova J, Trojanec R, Vaverka M. The Influence of Gene Aberrations on Survival in Resected IDH Wildtype Glioblastoma Patients: A Single-Institution Study. ACTA ACUST UNITED AC 2021; 28:1280-1293. [PMID: 33801093 PMCID: PMC8025822 DOI: 10.3390/curroncol28020122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 03/17/2021] [Indexed: 12/18/2022]
Abstract
This prospective population-based study on a group of 132 resected IDH-wildtype (IDH-wt) glioblastoma (GBM) patients assesses the prognostic and predictive value of selected genetic biomarkers and clinical factors for GBM as well as the dependence of these values on the applied therapeutic modalities. The patients were treated in our hospital between June 2006 and June 2015. Clinical data and tumor samples were analyzed to determine the frequencies of TP53, MDM2, EGFR, RB1, BCR, and CCND1 gene aberrations and the duplication/deletion statuses of the 9p21.3, 1p36.3, 19q13.32, and 10p11.1 chromosome regions. Cut-off values distinguishing low (LCN) and high (HCN) copy number status for each marker were defined. Additionally, MGMT promoter methylation and IDH1/2 mutation status were investigated retrospectively. Young age, female gender, Karnofsky scores (KS) above 80, chemoradiotherapy, TP53 HCN, and CCND1 HCN were identified as positive prognostic factors, and smoking was identified as a negative prognostic factor. Cox proportional regression models of the chemoradiotherapy patient group revealed TP53 HCN and CCND1 HCN to be positive prognostic factors for both progression-free survival and overall survival. These results confirmed the influence of key clinical factors (age, KS, adjuvant oncotherapy, and smoking) on survival in GBM IDH-wt patients and demonstrated the prognostic and/or predictive importance of CCND1, MDM2, and 22q12.2 aberrations.
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Affiliation(s)
- Ondrej Kalita
- Department of Neurosurgery, University Hospital Olomouc, I.P. Pavlova 6, 779 00 Olomouc, Czech Republic
| | - Zuzana Sporikova
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Marian Hajduch
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Magdalena Megova Houdova
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Rastislav Slavkovsky
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Lumir Hrabalek
- Department of Neurosurgery, University Hospital Olomouc, I.P. Pavlova 6, 779 00 Olomouc, Czech Republic
| | - Matej Halaj
- Department of Neurosurgery, University Hospital Olomouc, I.P. Pavlova 6, 779 00 Olomouc, Czech Republic
| | - Yvona Klementova
- Department of Oncology, University Hospital Olomouc, I.P. Pavlova 6, 779 00 Olomouc, Czech Republic
| | - Martin Dolezel
- Department of Oncology, University Hospital Olomouc, I.P. Pavlova 6, 779 00 Olomouc, Czech Republic
| | - Jiri Drabek
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Lucie Tuckova
- Department of Pathology and Laboratory of Molecular Pathology, University Hospital Olomouc, Hnevotinska 3, 779 00 Olomouc, Czech Republic
| | - Jiri Ehrmann
- Department of Pathology and Laboratory of Molecular Pathology, University Hospital Olomouc, Hnevotinska 3, 779 00 Olomouc, Czech Republic
| | - Jana Vrbkova
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Radek Trojanec
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc, Hnevotinska 5, 779 00 Olomouc, Czech Republic
| | - Miroslav Vaverka
- Department of Neurosurgery, University Hospital Olomouc, I.P. Pavlova 6, 779 00 Olomouc, Czech Republic
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