Hermawan Adam, Putri Herwandhani
Laboratory of Macromolecular Engineering, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada Sekip Utara II, 55281 Yogyakarta, Indonesia.
Cancer Chemoprevention Research Center, Faculty of Pharmacy, Universitas Gadjah Mada Sekip Utara II, 55281 Yogyakarta, Indonesia.
Saudi Pharm J. 2021 Nov;29(11):1289-1302. doi: 10.1016/j.jsps.2021.09.015. Epub 2021 Oct 5.
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.
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.
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 , , and was significantly upregulated in glioblastoma patients. Kaplan-Meier survival analysis showed that only patients with low mRNA expression of 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.
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.
胶质母细胞瘤是最具侵袭性和致命性的恶性肿瘤之一。获得性耐药降低了贝伐单抗在胶质母细胞瘤治疗中的有效性，从而增加了胶质母细胞瘤患者的死亡率。在本研究中，探索了姜黄素类似物五戊烯酮-1（PGV-1）的潜在靶点，作为胶质母细胞瘤治疗中贝伐单抗的补充治疗方法。
使用相似性整合方法（SEA）、瑞士靶点预测、STRING数据库和基因表达综合数据库（GEO）数据集进行靶点预测、数据收集和分析。分别使用Webgestalt和DAVID进行基因本体论和京都基因与基因组百科全书（KEGG）通路富集分析。使用CytoHubba根据最高度得分选择枢纽基因。使用cBioportal和GEPIA进行选定基因的基因改变和基因表达分析以及Kaplan-Meier生存分析。使用数据库TIMER 2.0分析选定基因与免疫细胞之间的免疫浸润相关性。
我们发现了PGV-1的374个靶点，以及来自贝伐单抗耐药胶质母细胞瘤细胞的1139个差异表达基因（DEG）。使用这两组数据进行的维恩图分析得出21个基因，这些基因被确定为PGV-1对抗贝伐单抗耐药性（PBR）的潜在靶点。PBR通过细胞色素P450调节外源性物质的代谢。发现七个潜在的治疗性PBR，即谷胱甘肽S-转移酶M1（GSTM1）、醛酮还原酶1C3（AKR1C3）、醛酮还原酶1C4（AKR1C4）、环氧合酶2（PTGS2）、解聚素和金属蛋白酶10（ADAM10）、醛酮还原酶1B1（AKR1B1）和17β-羟类固醇脱氢酶11（HSD17B11）在1.2%-30%的胶质母细胞瘤患者中存在基因改变。使用GEPIA数据库分析表明，在胶质母细胞瘤患者中，GSTM1、AKR1C3和AKR1C4的mRNA表达显著上调。Kaplan-Meier生存分析表明，只有GSTM1 mRNA表达低的患者总体生存率明显高于高mRNA组的患者。我们还发现PBR与免疫细胞之间存在相关性，从而揭示了PGV-1通过靶向PBR作为免疫治疗药物的潜力。
本研究突出了七个PBR，即GSTM1、AKR1C3、AKR1C4、PTGS2、ADAM10、AKR1B1和HSD17B11。本研究还强调了PBR作为PGV-1免疫治疗靶点的潜力。为了将PGV-1开发为胶质母细胞瘤免疫治疗的辅助药物以对抗贝伐单抗耐药性，需要对本研究结果进行进一步验证。
