Modulating Wnt/β-Catenin Signaling Pathway on U251 and T98G Glioblastoma Cell Lines Using a Combination of Paclitaxel and Temozolomide, A Molecular Docking Simulations and Gene Expression Study

Abstract

One of the most lethal cancers, glioblastoma (GBM), affects 14.5% of all central nervous system (CNS) tumors. Patients diagnosed with GBM have a meager median overall survival (OS) of 15 months. Extensive genetic analysis has shown that many dysregulated pathways, including the Wnt/β-catenin signaling system, contribute to the pathogenicity of GBM. Paclitaxel (PTX) and temozolomide (TMZ) are recognized to have therapeutic potential in several types of cancer, including GBM. This work aimed to examine the impact of PTX and TMZ on the human glioma cell lines U251 and T98G using molecular docking simulations and gene expression profiles in the Wnt/β-catenin signaling pathway. Standard procedure for Molecular Docking simulation, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) cytotoxicity assay, and Flow Cytometry assay was used. Genes implicated in the Wnt/β-catenin signaling pathway, including Dvl, Axin, APC, β-catenin, and glycogen synthase kinase3-β (GSK3β), were subjected to real-time PCR. The estimated parameters for targets revealed that the average binding energy and inhibition constant (Ki) for the DVL, β-Catenin, and GSK3β, when targeted by PTX, were − 5.01 kcal/mol, − 5.4 kcal/mol, and − 9.06 kcal/mol, respectively. This energy range was − 6.34 kcal/mol for DVL, − 5.52 kcal/mol for β-Catenin, and − 5.66 kcal/mol for GSK3β as a result of TMZ’s inhibitory actions. Gene expression analyses indicated that PTX and PTX/TMZ suppressed GSK3β (p < 0.05). GSK3β from the Wnt/β-catenin signaling pathway was significantly targeted by PTX alone, and adding TMZ to PTX may improve the efficacy of glioblastoma treatment. In addition, the GSK3β gene may help GBM therapy strategies as a potential PTX target.

Introduction

Glioblastoma (GBM) is the most frequent primary malignant tumor of the brain and central nervous system (CNS), making up 14.5% of all CNS tumors and 48.6% of all malignant CNS tumors. Patients with GBM have a dismal 15-month median overall survival (OS).¹⁾ Additionally aggressive and heterogeneous, GBM affects therapeutic outcomes.²⁾ Currently, patients with GBM get conventional care that includes radiation and chemotherapy after a maximum surgical resection.³⁾ Numerous deregulated signaling pathways, including WNT signaling, are implicated in the pathogenesis of GBM.^4,5) It has been demonstrated that the WNT signaling pathway is essential for maintaining glioma stem cells, increasing invasion and migration, and causing multidrug resistance.⁶⁾ Paclitaxel (Taxol = PTX) and temozolomide (Temadol = TMZ) have recognized therapeutic uses in various cancers. As a DNA alkylating agent, temozolomide is the most widely used chemotherapeutic drug with low side effects.⁷⁾ PTX, an anti-microtubule medication, effectively treats various malignancies, including GBM.⁸⁾ In addition, it has been demonstrated that TMZ and PTX cause G2/M arrest in GBM cell lines.^9,10) Most GBM patients resist PTX and TMZ, even though early clinical responses are excellent.^9,11) Consequently, the capacity to reduce chemoresistance is crucial for GBM patients. This work aimed to examine the impact of TMZ and PTX on U251 and T98G GBM cell lines at the level of the simulation model and gene expression in the canonical WNT signaling pathway.

Experimental

Molecular Docking Simulation

To investigate the simulation model of the PTX and TMZ with the active site of the genes involved in the Wnt/β-catenin signaling pathway, the chemical structures of PTX (CID: 36314) and TMZ (CID: 5394) were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov). To find out the best PDB id of proteins, including Dishevelled (PDB id:6lca), Axin (4Nm0), beta-catenin (PDB id:2gl7), and glycogen synthase kinase3-β (GSK3β) (PDB id: 5kpm), The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, uniport, and RCSB PDB were applied. And the detection of the protein binding site was performed using PLIP, CASTP, and UniProt bioinformatics servers. The chemical structure characteristics of ligands and protein are shown in Table 1. A site-specific molecular docking study was performed using the Auto Dock Vina program (Lamarckian genetic algorithm, docking runs = 80, population size = 150, mutation rate = 0.02, and cross-over rate = 0.8), and the energy minimization was done by Hyper-Chem software package. The results were analyzed using the Molegro Virtual Docker software to access the protein cavity.¹²⁾

Table 1. Molecular Docking Parameters of Ligand and Receptors Residues in the Current Study

Name	PubChem/PDB ID	Molecular formula			Synonyms	Molecular weight
Paclitaxel	CID:36314	C47H51NO14			Taxol	853.9
Temozolomide	CID:5394	C6H6N6O2			Methazolastone	194.15
					Temodar
					Temodal
Dvl (Dishevelled1)	6LCA	Data snapshot			Human dishevelled1 PDZ domain homotrimer	86.94 kDa
		Resolution	R-value free	R-value Work
		2.40 Å	0.273	0.245
Axin	1QZ7	Data snapshot			Beta-catenin binding domain of axin in complex with beta-catenin	65.97 kDa
		Resolution	R-value Free	R-value Work
		2.20 Å	0.256	0.221
β-Catenin	2GL7	2.60A	0.267	0.221	Beta-catenin/BCL9/Tcf4 complex	142.32 kDa
GSK3β	5KPM	2.69A	0.240	0.175	Kinase 3 beta complexed with BRD3731	95.11 kDa
APC	51Z9	2.93 Å	0.282	0.233	Adenomatous polyposis coli	39.92

Cell Culture and Drugs Preparation

T98G (CRL-1690™) and U251 GBM cell lines were purchased from ATCC (Manassas, VA, U.S.A.) cell bank and cultured in Dulbecco’s modified Eagle’s medium (DMEM) (supplemented with 10% fetal bovine serum (FBS, Gibco by life technologies, South America) and Penicillin G 100 U/mL, Streptomycin 100 µg/mL (Gibco, Thermo Fisher-Germany). All cells were incubated at 37 °C in a humidified atmosphere with 5% CO₂. These adherent cells were sub-cultured every three days.

3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium Bromide (MTT) Cytotoxicity Assay

Referring to the manufacturer’s protocol, in vitro cytotoxicity test on PTX and TMZ was performed using MTT assay¹³⁾ on both T98G and U251 cell lines. Concisely, Confluent cells were isolated for 3–5 min, incubated with 0.25 percent trypsin–ethylenediaminetetraacetic acid (EDTA), and then seeded into the 96-well plates at a density of 6 × 10⁴ cells/mL in DMEM and incubated overnight at 37 °C. Various concentrations of PTX (0.1, 0.5, 1, and 20 µM) and TMZ (0.1, 0.5, 1, and 20 µM) concentrations were used for the treatment of both T98G and U251 cells, either separately or in combination, and the plates were incubated at 37 °C for 24 and 48 h. A 100 µL MTT reagent (Sigma-U.S.A.) was subsequently applied to each well. The supernatant was removed four hours later, and 50 µL of dimethyl sulfoxide (0.1 percent) (Merck, Germany) was applied to each well to dissolve formazan crystals. The optical density (OD) was determined using a spectrophotometer at 570 nm (Milton Roy-Spectronic21D-U.S.A.). Media without samples and untreated cells were used as a blank and negative control, respectively. Each experiment was assessed in triplicate (n = 3).

Flow Cytometry Assay

Annexin V-fluorescein isothiocyanate (FITC) was conducted to determine the mode of cell death according to the manufacturer’s protocol (Annexin V-FITC Apoptosis Detection Kit, Nacalai Tesque, Inc., Japan). 5 × 10⁵ density of cells was seeded in 6-well plates and incubated at 37 °C in a humidified, 5% CO₂ incubator atmosphere for overnight to allow them to attach. After discarding, the culture medium cells were treated with PTX and TMZ separately and in combination at optimum concentrations of 0.5 and 1 µM, respectively. Then cells were detached using trypsin/EDTA and separated by centrifugation for 5 min at 112 × g. Cells were washed with phosphate buffered saline (PBS) and re-suspended in Annexin V binding buffer. The suspension was stained using 5 µL of Annexin V-FITC and 10 µL of Propidium Iodide and was incubated in darkness at room temperature for 20 min. After that, analysis was done using a flow cytometer (FACS-CALIBUR) to monitor treated and control cell death induction.

Quantitative Real-Time PCR

RNA Extraction and cDNA Synthesis

In compliance with the manufacturer’s instructions, total RNAs were collected from T98G and U251 untreated and treated with PTX and TMZ and combined (optimized IC₅₀) using Triazole (YTzol Pure RNA, Sigma-Aldrich), and the purity of RNAs was measured using the Nanodrop spectrophotometer (Milton Roy-Spectronic 21D-U.S.A.). cDNAs were synthesized using QuantiTect reverse transcription kit (Qiagen-U.S.A.) according to the manufacturer’s protocol.

Quantitative (q) PCR Assay

It was done using an applied biosystem PCR detection device. To evaluate the post-transcriptional level of Wnt/β-catenin pathway genes, including Dvl, Axin, APC, β-catenin, and GSK3β primers were designed using Primer3 input version0.4.0 software¹⁴⁾ and the efficiency of primers was assessed using Beacon Designer (http://www.premierbiosoft.com/molecular_beacons/index.html) and M-fold (http://www.unafold.org/) bioinformatics tools. The PCR reaction was performed in a final volume of 25 µL containing 12.5 µL of cyber green (Thunderbird cyber green qPCR mix-Toyobo-Japan), 1 µL of cDNA, 1 µL of each primer 0.2 pmol/µL and 9.5 µL of distilled water. The PCR amplification was carried out in a 45-cycle based on the following procedures: Primary denaturation at 95 kcal for 15 min and later for 15 s, the annealing temperature of each pair’s primers at 60 °C for 1 min, and extension performed at 60 °C for 10 s for each desired gene. These were followed by a melting curve analysis for each PCR amplicon in the temperature ranges from 60 to 95 °C, and gene expression was normalized to GAPDH as an internal control. All experiments were done in triplicate repeats. Table 2 describes Gene location, primers, and PCR conditions in the current research.

Table 2. Gene Location, Primers, PCR Conditions, and Biological Roles and Expression Pattern of Genes Involved in GBM

Gene symbol	Gene location	Primers (5′ to 3′)	Annealing temperature (°C)	Product size (bp)	Pathway/biological role in GBM/Expression pattern in GBM	Reference
DVL	Ch3 (q27.1)	F-TTACCATCCCTAATGCTTTC	60.25	150	Promote clonogenic growth and stem-like characteristics of GBM cells/overexpressed	36)
		R-AGGTGATCTTGTTGACGGTA	60.02
Axin	Ch16 (P13.3)	F-TACTTGAAGTGGGCTGAGTC	59.87	84	Key negative regulator of the Wnt signaling pathway/overexpressed	37)
		R-CTCCTGCTTCAGGAAAGTC	60.10
β-Catenin	Ch3 (P22.1)	F-TCTGTGAACTTGCTCAGGAC	60.10	172	β-catenin expression in GBM is associated with a degree of resection. And the positive β-catenin expression is a significant independent prognostic factor in patients with GBM/overexpressed	38)
		R-GAAAGCCGTTTCTTGTAATC	60.04
GSK-3β	Ch3 (q13.33)	F-ATATTTCCAGGGGATAGTGG	60.15	147	GSK-3β inhibition in glioblastoma multiforme cells induces apoptosis, cell cycle arrest, and changing biomolecular structure/overexpressed	39)
		R-GACCTTAGTCCAAGGATGTG	60.07
APC	Ch5 (q22.2)	F-CCATTCAGTTCTAGCAGCTC	60.10	171	Tumor suppressor/overexpressed in astrocytoma tumors	40)
		R-ATCTCGCTTCTTTGTGTTGT	59.80
GAPDH	Chr4 (q22.1)	F-ACAGCCTCAAGATCATCAGC	59.8	99	Housekeeping	41)
		R-TGAGTCCTTCCACGATACCA	59.7

Gene Interactions Analysis

A biological network integration for dysregulated gene prioritization and predicting gene function analysis was performed using The GeneMANIA prediction server (https://genemania.org) based on A label propagation algorithm for predicting gene function to verify all the potential interactions between dysregulated and target genes.

Data Analysis

All data are expressed as the mean ± standard deviation (S.D.) of three dependent experiments and analyzed using Student’s t-test or one-way ANOVA (Tukey’s honestly significant difference (HSD) test). All data were analyzed using Graf pad Prism version 8 software. p < 0.05 considered statistically significant.

Results

Molecular Docking Simulation

The parameters computed for targets demonstrated that the average binding energy and inhibition constant (Ki) for the DVL, β-catenin and GSK3β were − 5.01 kcal/mol and − 5.4 kcal/mol and − 9.06 kcal/mol, respectively, when targeted by PTX. This energy range was − 6.34 kcal/mol for DVL, − 5.52 kcal/mol for β-catenin, and − 5.66 kcal/mol for GSK3β in inhibitory effects of TMZ. As a result, docking analysis shows that PTX with binding energy − 9.06 kcal/mol could inhibit GSK3β protein CYS199, ASN186, ASP200, LYS183, ASN64, GLY63, VAL135, VAL70, and LEU188 amino acid residues compared to other proteins. In the molecular docking process, No Cavity (ligand-specific binding site) was detected for Axin protein, therefore, omitted from the docking simulation. The results have been presented in Table 3. Molecular docking simulation results between ligands and wnt pathway proteins are shown in Fig. 1.

Table 3. Molecular Docking Parameters, Inhibitory Binding Affinity, and Amino Acid Residues in the Current Simulation Study

Protein–ligand interactions (Docking)		clRMSD	refRMSD	Inhibitory binding affinity (kcal/mol)	Amino acid residues
PTX (CD:36314)	DVL	0	122.4	−5.01	MET256, ASN255, ALA288, LEU254, ARG258, ASP292, HIS259, ALA291
	β-Catenin	0	25.06	−5.4	TYR306, GLN302, ARG342, LYS270, ALA269, LEU264, ILE303
	GSK3β	0	17.28	−9.06	CYS199, ASN186, ASP200, LYS183, ASN64, GLY63, VAL135, VAL70, LEU188
	Axin	No cavity (ligand-specific binding site) was detected
TMZ (CID:5394)	DVL	0	134.34	−6.34	MET256, ASN255, ARG258, GLU257
	β-Catenin	0	33.05	−5.52	LEU262, ALA269, LYS270, MET271, GLY268
	GSK3β	0.2	31.74	−5.66	Glu97, ASP200, LYS85
	Axin	No cavity (ligand-specific binding site) was detected

Fig. 1. Molecular Modeling of PTX and TMZ Inhibition of Wnt/β-Catenin Pathway Genes

Docking simulation was performed between PTX-DVL (a1), PTX-β-catenin (b1), PTX-GSK3β (c1), PTX-APC(d1), TMZ-DVL(e1), TMZ- β-catenin (f1), TMZ- GSK3β (g1) and TMZ-APC (h1). Donor and acceptor bands, PTX-TMZ docked model interactions; alpha and beta sheets interactions with amino acids (a2–h2), and amino acid residues involved in docking have been shown separately for each gene (a3–h3). No ligand-specific binding site was detected for Axin, therefore omitted from the docking process and analysis. A molecular simulation was performed using Autodock4 (version 4.2) software.

In Vitro Cells Viability of PTX and TMZ

The findings of the MTT assay showed that PTX (20 µM) and TMZ (0.5 µM) alone significantly target the T98G cell type 24 h post incubation (p < 0.05) (Figs. 2a, 2c). Furthermore, the MTT assay has also revealed that the U251 cell type was significantly targeted with PTX (0.5 µM) and TMZ (1 µM) alone in the 48 h post-inoculation period (p < 0.05 (Figs. 2b, 2d). The mixture of two PTX and TMZ drugs on both T98G and U251cell lines was tested 24 and 48 h after incubation, and the optimal dosage of the drugs PTX 0.1 µM (24 h) combined with TMZ (0.5 µM, 24 h) was chosen to trace additive effects for both cell lines (Figs. 2e–2h). Furthermore, the results indicated significantly additive effects of coupled drugs compared with drug effects alone. The dose dependence was reduced to 0.1 and 0.5 µM for PTX and TMZ during 24 h post incubation, respectively (p < 0.05). The anti-proliferative effects of PTX and TMZ alone and combined results of both drugs on T98G and U251 cell lines during 24 and 48 h post incubation period have been presented in Fig. 2. Optimal concentrations of combined PTX and TMZ have been shown to have the highest inhibitory and anti-proliferative effects (Figs. 3a, 3b).

Fig. 2. MTT Assay

The anti-proliferative and inhibitory effects of different concentrations of PTX and TMZ on T98G and U251 cell lines during 24 and 48 h post-incubation time (2a–2d). In T98G and U251 cell lines, the IC₅₀ was measured at 20 and 0.5 µM when the cells were incubated for 24 h with PTX and TMZ, respectively. In addition, after 48 h post-incubation, the IC₅₀ for the U251 cell line was 0.5 and 1 µM for PTX and TMZ, respectively. The IC₅₀ for combination drugs was 0.1 PTX and 0.5 TMZ 24 h after incubation (in Fig. 2h, the time has been corrected to 48 h).

Fig. 3. A Diagram of Combined Effects of PTX and TMZ on T98G and U251 Cell Lines during 24 h Post Inoculation Time

The Bar diagram demonstrates that the percentage of the viability of both U251 (3a) and T98G (3b) cell lines was significantly decreased in a combined form of drugs. The results also revealed a significant decrease of T98G cells when exposed to PTX (0.1 µM) alone. The results are represented as the mean ± S.D. of triplicate (** p < 0.02; and * p < 0.05) (3b). The analysis was performed using one-way ANOVA test using graph pad prism version8.0.2 (the column of TMZ has been added).

Additive Effects in Apoptosis Distribution

Flow cytometry was used to assess apoptosis distribution. After 24 h treatment using PTX (20 µM) and TMZ (0.5 µM) alone and combined (optimized concentrations, 0.1 µM PTX +0.5 µM TMZ), T98G and U251 cells significantly underwent early and late stages of apoptosis. When the U251 and T98G cells were exposed to PTX alone, 4.2 and 3.11% went to the Q3 phase (early apoptosis), respectively, which statistically was non-significant (p > 0.05). Whereas under TMZ treatment, 11.2% of U251 cells and 11.6% of T98G cells were in the Q3 stage (early apoptosis), which was not a significant difference between the two drugs (p > 0.05). Furthermore, statistical analysis revealed that combining two drugs increased apoptosis induction in both cell lines. The data revealed that 30.3% of U251cells were in the Q2 (late stage) phase, and 18.965% of T98G cells were in the Q3 (early stage) phase in combination. According to the results, the apoptosis distribution showed the susceptibility of T98G cells compared with U251 when the T98G cells undergo the early stage of apoptosis (p < 0.05). The percentage of apoptotic cells (U251 and T98G) is depicted in Figs. 4a–4h. Due to the short duration of early apoptosis, this result indicated that the T98G cell type was sensitive to the combined form of both PTX and TMZ drugs.

Fig. 4. Apoptosis Distribution of U251 and T98G Cell Lines When Exposed to PTX and TMZ Alone and Combination Forms after 24 h

The number of early apoptosis T98G cells was much higher than U251 cells in a combination treatment form (p ˂ 0.05), demonstrating the sensitivity of T98G cells to the combined form of PTX and TMZ. Q1 = necrosis cells, Q2 = late apoptosis cells, Q3 = early apoptosis cells, Q4 = viable cells. Apoptosis distribution of U251 and T98G cell lines under PTX, TMZ alone, and combination form Fig. (4i). The one-way ANOVA test was performed to detect statistically differences between each stages and normal in both cell lines. The significant p-Value (p < 0.05) has been presented with star shape (Figs. 4 and 5 were merged and error bar added).

Additive Effects of PTX and TMZ on Wnt Pathway Genes Expression

Analysis of the gene expression showed a significantly dysregulated pattern (FC = 0.13, p = 0.02) of the GSK3β gene in the T98G cell line when exposed to 20 µM of PTX (Fig. 5a). The other genes did not have any dysregulated pattern. Furthermore, under 20 µM of PTX, the Wnt pathway genes did not have any change in expression pattern. Although there was no detected expression of genes in both cell lines under TMZ treatment (p > 0.05) (Fig. 5b), the data showed a significant down-regulated pattern of the GSK3β gene (FC = 0.8, p < 0.001) in the T98G cell line when exposed to PTX and TMZ in combination form (optimized concentration) (Fig. 5c) that can confirm the sensitivity of T98G cell line to combination treatment strategy in glioblastoma multiforme. Figure 5 presented the expression pattern of wnt signaling genes under PTX, TMZ, and combination forms of treatment.

Fig. 5. Relative Expression Panel of Wnt Signaling Pathway Genes under PTX (5a), TMZ (5b), and Synergic Effects of PTX and TMZ in Glioblastoma Multiforme Cell Lines (U251 and T98G)

The GSK3β gene was significantly down-regulated in T98G cell lines (p = 0.02) compared to the control group under PTX treatment, and there were no expression changes in both cell lines when exposed to TMZ (5b). Furthermore, a significant down-regulated pattern was observed in the T98G cell line when the cells were exposed to PTX and TMZ in optimized combined form (FC = 0.8, P=<0.001). GAPDH served as a housekeeping gene with expression value = 1. The results are represented as the mean ± S.D. of triplicate (Error bar has been added).

Discussion

The dysregulation of WNT signaling has been related to various cancers, including GBM, the fatal primary brain tumor.^6,15) It has been revealed that WNTs and their downstream effectors regulate proliferation, death, and migration.⁶⁾ Cancers acquire resistance to radiation and chemotherapy in the majority of cases. Multiple investigations have shown that WNT signaling activation induces treatment resistance in ovarian, colon, pancreatic, and GBM cancers.^6,9,16–18) The significant cross talk between different signaling pathways and varied role of GSK3β in these pathways makes it all the more difficult to pinpoint one player. Furthermore, Pharmacological inhibition of GSK3β has been shown to promote cell death via apoptosis signaling pathway.¹⁹⁾

WNT signaling increases resistance to temozolomide, a popular chemotherapeutic therapy for GBM patients.²⁰⁾ In addition, published results indicated that WNT ectopic expression boosted ovarian cancer cell PTX resistance.^14,17) TMZ is the most often utilized anti-glioma medicine since its capacity to penetrate the blood–brain barrier (BBB) has shown minimal adverse effects.²¹⁾ PTX has superior anti-cancer actions, particularly against brain tumors.^22,23) PTX may promote apoptotic cell death in human glioblastoma U87MG cells by controlling the apoptotic activities of p53 and c-Jun N-Terminal Kinase.²⁴⁾

The current study’s findings supported the combination treatment strategy of glioblastoma tumor cell line, particularly T98G with PTX and TMZ, targeting the GSK3β gene in the canonical Wnt signaling pathway. To the best of our knowledge, this is the first report of additive effects of PTX and TMZ on GBM at the canonical Wnt signaling pathway. Additive effects of PTX and TMZ have been tested in some GBM cell lines using different kinds of co-delivery systems. Xu et al. established the synergic anti-cancer and inhibitory effects of PTX and TMZ co-loaded in mPEG-PLGA nanoparticles (NPs) on U87 and C6 glioma cells lines in a study.²⁵⁾ Their data showed significant inhibitory effects of PTX/TMZ-NPs on GBM.²⁵⁾ Furthermore, co-delivery of PTX and TMZ through a photopolymerizable hydrogel system has also been revealed prevention GBM recurrence after surgical resection.²⁶⁾ A previous study has demonstrated the combination of TMZ and PTX has a synergistic inhibitory impact on PTX-resistant U251-glioma cells via glucose metabolism inhibition.¹¹⁾ A research study had shown that when PTX and TMZ were loaded in B19 aptamer (Apt)-conjugated polyamidoamine (PAMAM) G4C12 dendrimer NPs, they dramatically reduced the tumor development of U-87 stem cells by inducing apoptosis via the downregulation of autophagic and multidrug resistance (MDR) genes.²⁷⁾ Ruan et al., PTX inhibits GBM growth and proliferation through the MMP-9-mediated p38/JNK signaling pathway in U251 cells.²⁸⁾ Additionally, our research showed that the T98G glioblastoma cell line might be targeted by PTX alone or combined with TMZ by downregulating the GSK3 gene in the canonical Wnt pathway. Glycogen synthase kinase3-β (GSK3β) is a serine-threonine protein kinase that limits the conversion of glucose to glycogen by phosphorylating and inactivating glycogen synthase. GSK3β is a component of signaling cascades implicated in the process of apoptosis.^28,29) As discussed in the current research, inhibition of GSK3β activity enhances apoptosis in glioblastoma cell lines. In a research study revealed that GSK3 inhibition has a negative effect on the subpopulation of cancer stem cell-like cells, depleting them and pushing into differentiation.^30–32) The significant cross talk between different signaling pathways and varied role of GSK3β in these pathways makes it all the more difficult to pinpoint one player. In the current research, the data from the GENEMANIA bioinformatics tool presented the crucial role of the GSK3β gene in the Wnt signaling pathway. Analysis revealed the physical and genetic interactions with other genes and pathways that have a negative or positive regulation role in the Wnt signaling pathway (Fig. 6). A research study proposed that GSK3β plays an essential role in the astrocytic differentiation of human GBM cells.³³⁾ GSK3β has been studied for its opposing involvement in several human malignancies as either a tumor suppressor or promoter.³⁴⁾ Our data at the molecular level demonstrated that the only T98G cell line was significantly sensitive to PTX (p = 0.02) and the combination form of the PTX-TMZ administration (p = 0.001). Although it is clear that inhibition of GSK3β in GBM improves TMZ sensitivity by modulating Mdm2/P53 and c-Myc/MGMT signaling pathways that upregulate MGMT promoter methylation,³⁵⁾ our data showed that TMZ alone did not affect T98G and U251 cell lines and a resistant phenotype of both cell lines when exposed to TMZ was observed.

Fig. 6. Pathway Analysis of Dysregulated GSK3β Gene

The pathway analysis shows physical and genetic interactions between GSK3β and other genes that have a positive and negative role in regulating the canonical Wnt signaling pathway. The Pink, green, and blue colors indicate physical interactions, genetic interactions, and pathways involved in apoptosis. Pathway analysis was performed using the GENEMANIA bioinformatics tool.

Conclusion

Based on these observations, the current research data suggest that PTX alone and more significantly combined with TMZ can inhibit the growth and proliferation of T98G GBM cells in vitro. Although, based on the results and the molecular docking simulation and laboratory tests, the GSK3β gene may be introduced as a new target of PTX in GBM strategy treatment, the proteomics study and knock the GSK3β gene down were the major limitations in our research that would be highly recommended for future work.

Acknowledgments

We would like to acknowledge Professor Zamberi Sekawi (Universiti Putra Malysia) for chemical support, and Mrs. Marsitah binti Abdul Jalil (Universiti Putra Malaysia) for technical assistance on flow cytometry analyses.

Conflict of Interest

The authors declare no conflict of interest.

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