Systematic analysis of potential targets of the curcumin analog pentagamavunon-1 (PGV-1) in overcoming resistance of glioblastoma cells to bevacizumab

BACKGROUND: Glioblastoma is one of the most aggressive and deadliest malignant tumors. Acquired resistance decreases the effectiveness of bevacizumab in glioblastoma treatment and thus increases the mortality rate in patients with glioblastoma. In this study, the potential targets of pentagamavunone-1 (PGV-1), a curcumin analog, were explored as a complementary treatment to bevacizumab in glioblastoma therapy. METHODS: Target prediction, data collection, and analysis were conducted using the similarity ensemble approach (SEA), SwissTargetPrediction, STRING DB, and Gene Expression Omnibus (GEO) datasets. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted using Webgestalt and DAVID, respectively. Hub genes were selected based on the highest degree scores using the CytoHubba. Analysis of genetic alterations and gene expression as well as Kaplan–Meier survival analysis of selected genes were conducted with cBioportal and GEPIA. Immune infiltration correlations between selected genes and immune cells were analyzed with database TIMER 2.0. RESULTS: We found 374 targets of PGV-1, 1139 differentially expressed genes (DEGs) from bevacizumab-resistant-glioblastoma cells. A Venn diagram analysis using these two sets of data resulted in 21 genes that were identified as potential targets of PGV-1 against bevacizumab resistance (PBR). PBR regulated the metabolism of xenobiotics by cytochrome P450. Seven potential therapeutic PBR, namely GSTM1, AKR1C3, AKR1C4, PTGS2, ADAM10, AKR1B1, and HSD17B110 were found to have genetic alterations in 1.2%–30% of patients with glioblastoma. Analysis using the GEPIA database showed that the mRNA expression of ADAM10, AKR1B1, and HSD17B10 was significantly upregulated in glioblastoma patients. Kaplan–Meier survival analysis showed that only patients with low mRNA expression of AKR1B1 had significantly better overall survival than the patients in the high mRNA group. We also found a correlation between PBR and immune cells and thus revealed the potential of PGV-1 as an immunotherapeutic agent via targeting of PBR. CONCLUSION: This study highlighted seven PBR, namely, GSTM1, AKR1C3, AKR1C4, PTGS2, ADAM10, AKR1B1, and HSD17B110. This study also emphasized the potential of PBR as a target for immunotherapy with PGV-1. Further validation of the results of this study is required for the development of PGV-1 as an adjunct to immunotherapy for glioblastoma to counteract bevacizumab resistance.