Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach

Amir Barzegar Behrooz; Hamid Latifi-Navid; Simone C da Silva Rosa; Maciej Swiat; Emilia Wiechec; Carla Vitorino; Rui Vitorino; Zahra Jamalpoor; Saeid Ghavami

doi:10.3390/cancers15123158

Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach

Cancers (Basel). 2023 Jun 12;15(12):3158. doi: 10.3390/cancers15123158.

Authors

Amir Barzegar Behrooz¹, Hamid Latifi-Navid², Simone C da Silva Rosa³, Maciej Swiat⁴, Emilia Wiechec⁵, Carla Vitorino^{6

7}, Rui Vitorino^{8

9}, Zahra Jamalpoor¹, Saeid Ghavami^{3

4

10

11}

Affiliations

¹ Trauma Research Center, Aja University of Medical Sciences, Tehran 14117-18541, Iran.
² Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology, Tehran 14977-16316, Iran.
³ Department of Human Anatomy and Cell Science, University of Manitoba College of Medicine, Winnipeg, MB R3E 3P5, Canada.
⁴ Faculty of Medicine in Zabrze, University of Technology in Katowice, 41-800 Zabrze, Poland.
⁵ Division of Cell Biology, Department of Biomedical and Clinical Sciences, Linköping University, 58185 Linköping, Sweden.
⁶ Coimbra Chemistry Coimbra, Institute of Molecular Sciences-IMS, Department of Chemistry, University of Coimbra, 3000-456 Coimbra, Portugal.
⁷ Faculty of Pharmacy, University of Coimbra, 3000-456 Coimbra, Portugal.
⁸ Department of Medical Sciences, Institute of Biomedicine iBiMED, University of Aveiro, 3810-193 Aveiro, Portugal.
⁹ UnIC, Department of Surgery and Physiology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal.
¹⁰ Biology of Breathing Theme, Children Hospital Research Institute of Manitoba, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.
¹¹ Research Institute of Oncology and Hematology, Cancer Care Manitoba-University of Manitoba, Winnipeg, MB R3T 2N2, Canada.

Abstract

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maximally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7560 proteins related to GBM disease and 3860 proteins associated with signaling pathways involved in GBM. By integrating the results of the analyses mentioned above and again performing centrality analysis, eleven key genes involved in GBM disease were identified. ProteomicsDB and Gliovis databases were used for determining the gene expression in normal and tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of identified genes, miRNAs, and metabolites associated with GBM disease was performed using ExpressAnalyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was performed using pathway, joint pathway, and network analyses. The results of this study allowed us to identify 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, and hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose, and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in GBM disease development. The identified top genes, miRNAs, and metabolite signatures can be targeted to establish early diagnostic methods and plan personalized GBM treatment strategies.

Keywords: autophagy; biomarker selection; glioblastoma; inflammationomics; metabolomics; network analysis; pathway analysis; personalized therapy.

Grants and funding

This research was funded by the Portuguese Foundation for Science and Technology (FCT), European Union, QREN, FEDER, COMPETE and PIDDAC for funding the iBiMED (UIDB/04501/2020, POCI-01-0145-FEDER-007628), Unidade de Investigação Cardiovascular (UID/IC/00051/2019), the projects LAQV-REQUIMTE (UIDB/50006/2020), CENTRO-01-0145-FEDER-03075 and the Coimbra Chemistry Center, CQC (UID/QUI/00313/2020). Moreover, Simone C. da Silva Rosa was funded by the Canadian Institutes of Health and Research (CIHR) Postdoctoral Fellowship. Furthermore, Coimbra Chemistry Centre (CCC) is supported by Fundação para a Ciência e a Tecnologia through the Project UID/QUI/00313/2020.