1. Introduction
Glioblastoma (GBM) is the most common, primary brain tumor that is considered as one of the most aggressive malignant human tumors. Despite maximal safe resection followed by radiation with adjuvant chemotherapy, the average survival is 15 months after diagnosis as more aggressive tumors recur typically within 6 months after therapy [
1]. Temozolomide (TMZ) is an alkylating drug widely used as a first-choice chemotherapeutic agent in GBM [
2], however, 50% of patients develop the resistance to TMZ, which restricts an effective treatment. The O
6-methylguanine-DNA methyltransferase (MGMT) is responsible for removing the methyl group from O
6-methylguanine in DNA thereby diminishing the overall efficacy of TMZ. MGMT expression, determined by a CpG methylation status of the
MGMT gene promoter, is an important factor in predicting the response to TMZ treatment [
3,
4]. Hypermethylation of the
MGMT promoter results in decreased expression of the MGMT protein and has been shown to correlate with prolonged survival of GBM patients. In contrast, tumors with unmethylated
MGMT (with increased MGMT activity) commonly exhibit resistance to TMZ. The epigenetic status of
MGMT became a crucial predicting factor of TMZ effectiveness [
5,
6]. Nevertheless, many other molecular mechanisms can contribute to TMZ resistance, such as other DNA repair systems, epigenetic modifications, aberrant signaling pathways or molecular- and cellular heterogeneity in malignant glioma [
7,
8]. Therefore, there is an urgent need to discover a novel approach to increase the glioma cell sensitivity to TMZ and other drugs.
Anthracycline antibiotic doxorubicin (DOX) is one of the most common chemotherapeutics used in the treatment of various solid and blood cancers [
9,
10]. Previous studies have shown the DOX-related toxicity to cultured glioma cells [
11]. Moreover, DOX was an effective anti-glioma agent in animal models of malignant gliomas [
12,
13]. Unfortunately, DOX has a low penetration of blood brain barrier (BBB), and causes side effects in healthy tissues, including dose-limiting cardiotoxicity. Various formulations such as nanoparticles, liposomes, exosomes and polymer conjugates were developed to improve transport of DOX through BBB and achieve the desired concentration of the drug within tumors [
14,
15,
16,
17,
18]. Additionally, complementary approaches including combinatory treatment and/or intra-tumoral delivery of DOX to GBM, had been used in GBM therapy to reduce cytotoxicity in normal tissue [
15,
17,
19].
GBM is characterized by high inter- and intra-patient heterogeneity. Integrated genomic and transcriptomic analyses identified clinically relevant subtypes of GBMs, referred to as: classical (CL), mesenchymal (MES), neural (NE), and proneural (PN). These subtypes are tightly associated with genomic abnormalities. Platelet-derived growth factor receptor alpha (
PDGFRA) amplifications and isocitrate dehydrogenase 1 (
IDH1) as well as Tumor protein 53 (
TP53) gene mutations were most frequently found in the PN group. The epithelial growth factor receptor (EGFR) alterations were found in the CL group, and neurofibromin 1 (
NF1) gene abnormalities were preferentially grouped in MES GBMs. Moreover, the response to aggressive therapy differs by a subtype, with the greatest benefits in the CL subtype and no benefits in the PN subtype [
20]. These subtypes also vary within the same tumor specimen, as multi-region tumor sampling has shown co-existence of multiple subtypes in different regions of the same tumor. These subtypes can change over time and through therapy. Single-cell RNA-sequencing (scRNA-seq) indicated that distinct cells in the same tumor recapitulate programs from distinct subtypes [
21,
22,
23]. Studies by Patel et al. [
22] showed that cells from the same tumor had variable ‘stemness’ and expressed different receptor tyrosine kinases (RTKs). Markedly, several studies indicated the presence of different cells, including glioma stem cells (GSCs) (also called tumor-initiating cells), within a tumor and their contribution to tumor growth, recurrence, and resistance to radio- and chemotherapies [
24,
25,
26,
27].
Receptor tyrosine kinases (RTKs) are the most commonly altered genes in adult GBMs (67%) [
28]. The amplifications and mutations of
EGFR are detected in about half of GBM tumors and in 95% of CL-GBMs [
28,
29,
30]. Amplification of
EGFR is often accompanied by the appearance of a EGFR variant III (EGFRvIII), which lacks the extracellular domain, causing a ligand-independent constitutive activity [
31,
32]. EGFR and its downstream signaling networks contribute to GBM cell proliferation and diffused invasion [
33]. Due to frequency of
EGFR aberrations, many EGFR-targeting therapies are in development or in clinical trials for many different types of tumors, including GBMs [
34,
35]. Although EGFR kinase inhibitors had shown initial success in other tumors (e.g non-small lung cancer) [
36], EGFR inhibitors, such as gefitinib and erlotinib, failed to assist in GBM therapy, demonstrating insignificant outcome in clinical trials [
37,
38,
39]. Among mechanisms of therapy resistance to EGFR inhibitors are:
PTEN (phosphatase and tensin homolog) alterations, deregulated PI3K (phosphatidylinositol 3-kinase) pathway [
38,
40], compensatory signaling pathways, tumor heterogeneity and ineffective BBB penetration [
41]. A better understanding of the EGFR signaling network and its interrelations with other pathways is essential to improve drug activity, clarify the mechanisms of resistance, and develop better therapeutic agents. EGFR and its constitutively activated variant EGFRvIII transduce signals via classical RTK pathways: the RAS/mitogen activated protein kinase (MAPK)/extracellular signal–regulated kinase (ERK, the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB/AKT), the Janus kinas (JAK)/STAT, and the protein kinase C (PKC) [
35].
Signal transducer and activator of transcription 3 (STAT3) is an oncogenic transcription factor [
42] regulating the transcription of several genes involved in cell cycle progression, resistance to apoptosis, angiogenesis, invasiveness and immune escape [
43,
44,
45]. GBM patients with high levels of activated (phosphorylated) STAT3 have more aggressive disease and poorer clinical outcomes [
46]. Interestingly, activated STAT3 is abundant in patient-derived GSC [
47,
48]. Inhibition of STAT3 phosphorylation or STAT3 knockdown decreased viability of glioma cells, including GSCs and slowed disease progression of GSC orthotopic xenografts in mice [
49,
50,
51,
52]. Constitutively activated STAT3 is frequently co-expressed with EGFR in high-grade gliomas and targeting STAT3 sensitizes glioma cells to anti-EGFR (Iressa/gefitinib) and alkylating agents [
53]. Concurrent inhibition of EGFR and JAK2/STAT3, with afatinib and pacritinib, abrogated elevated STAT3 signaling detected upon EGFR inhibition in patient-derived GSCs. Combinatorial treatment was highly effective in a panel of molecularly heterogeneous GSC and in orthotopic
EGFRvIII GSC xenografts [
54]. Afatinib (a second generation of EGFR-inhibitor) combined with TMZ synergistically inhibited cell proliferation, clonogenicity, invasion and motility of cultured glioma cells expressing
EGFRvIII and prevented progression of intracranially implanted U87-MG
EGFRvIII cells [
55]. Cetuximab (an anti-EGFR antibody) augmented radiation and chemotherapy effects in GBM cells
in vitro and
in vivo [
56,
57]. TMZ and cetuximab were tested in a phase I/II clinical trial of primary GBMs [
58]. Depatuxizumab mafodotin (ABT-414), an EGFR-targeting antibody–drug conjugate [
59], selectively killed tumor cells overexpressing wild-type or mutant forms of EGFR and provided significant therapeutic benefit in a GBM xenograft model [
60].
DOX conjugated with ultrasmall nanoparticle shows a significant efficacy in patient-derived xenografts harboring EGFR mutations and/or amplification after intravenous administration [
19]. The anti-EGFR-doxorubicin-loaded immunoliposomes (ILs-DOX) displayed highly efficient binding and internalization in a panel of EGFR and EGFRvIII overexpressing cells [
61,
62]. Recently, a small trial with anti-EGFR ILs-DOX on relapsed GBMs with
EGFR amplification showed positive response in one patient [
63].
The lack of effective conventional GBM therapy encourages researchers to search for new therapeutic strategies based upon the combination of repurposed drugs. We investigated the effectiveness of an EGFR inhibitor AG1478 in combination with TMZ or DOX using molecularly diverse patient-derived cell cultures, especially with a different status of MGMT. We established a quick and reliable method for generating patient-derived primary glioma cell cultures from fresh-resected glioma tissues and performed their molecular characterization. Our study demonstrated that targeting EGFR signaling together with TMZ or DOX decreased cell viability and induced apoptosis of GBM-derived cells with methylated or intermediate status of MGMT. Mechanistic studies revealed that although AG1478 inhibits phosphorylation of STAT3 in patient-derived cells, it was not sufficient to sensitize primary cells with the unmethylated MGMT promoter. These data defines cell-type specific responses to the EGFR inhibitor in combination with TMZ or DOX and indicates a role of the MGMT promoter methylation in predicting cell responses to chemotherapeutics.
2. Materials and Methods
2.1. Cell cultures and treatments
WG0, WG1, WG3, WG4, WG5, WG6, WG9, WG10, WG13, WG14, WG15, WG16, WG16, WG17, WG18, WG19 primary glioma cultures originated from surgically resected glioblastoma samples (grade 4, according to WHO 2016 classification) [
64]. The use of tissues was approved by the Research Ethics Board at Institute of Psychiatry and Neurology in Warsaw, Poland and informed consents were obtained from the patients. All methods were carried out in accordance with the relevant guidelines and regulations. Freshly resected tumor tissues were washed in Hank’s balanced sodium solution (HBSS; Gibco Invitrogen, Switzerland) and subjected to mechanical and enzymatic dissociation using Neural Tissue Dissociation Kit (Miltenyi Biotec, Germany) according to the manufacturer’s instructions. Some samples were processed without enzymatic digestion, in favor of accurate tissue cutting in DMEM/F12 medium until a smooth milky single cell suspension was achieved. To remove undissociated pieces and debris cell suspension was filtered through a 100 and 40 micron cell strainer. The blood cells were discarded during serial passage and medium exchange, instead of using Lympholyte-M [
65]. Tumor cells were re-suspended in DMEM/F-12 medium (Gibco Invitrogen, Switzerland) supplemented with 10% fetal bovine serum for adherent cultures, or DMEM/F-12 serum-free medium for sphere cultures, and plated at a density of 1–2 × 10
6 cells/T75 flask. 50% of the fresh medium was replaced every 4 days.
The L0125, and L0627 GBM GSC lines were provided by Dr Rossella Galli (San Raffaele Scientific Institute, Milan, Italy) [
66]. L0125 and L0627 were expanded
in vitro in serum-free medium for sphere culture.
Normal human astrocytes (NHA) were purchased from Lonza (Walkersville,, USA) and cultured in ABM Basal Medium (Lonza) supplemented with 3% fetal bovine serum, 1% L-glutamine, 0.1% ascorbic acid, 0.1% human EGF, 0.1% gentamicin, and 0.0025% recombinant human insulin.
NTERA-2 cl.D1 were purchased from ATCC (Manassas, USA) and cultured in DMEM with GlutaMax-1 and supplemented with 10% fetal bovine serum.
All cell cultures were grown in a humidified atmosphere of CO2/air (5%/95%) at 37 °C.
2.2. Sphere cultures and material collection
For sphere cultures, cells were seeded at a low density (3000 viable cells/cm2) onto non-adherent plates and cultured in serum-free DMEM/F-12 medium, supplemented with 2% B27 (Gibco Invitrogen, Switzerland), 20 ng/mL recombinant human bFGF (Miltenyi Biotec, Germany), 20 ng/mL recombinant human EGF (StemCell Technologies, Canada), 0.0002% heparin (StemCell Technologies, Canada) and antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin, Gibco Invitrogen, Switzerland). 25% of the medium was replaced every 3 days. After 7-14 days of culturing, the spheres were collected by centrifugation at 110 × g and lysed in Qiagen RLT lysis buffer for RNA isolation or lysed in buffer supplemented with complete protease inhibitor cocktail (Roche Applied Science, USA) for blotting.
2.3. Cell treatments
Temozolomide (TMZ), doxorubicin (DOX) and AG1478 (AG) were dissolved in DMSO. Cells were treated with single drugs: TMZ (1 mM) for 72 h, DOX (50-1000 nM) for 48 h and AG (10 µM) for 6 h, or with combination of TMZ+AG (1 mM + 10 µM) for 72 h, and DOX+AG (500 nM + 10 µM) for 48 h. DMSO was added at respective concentrations and served as a control condition.
2.4. Cell viability assays
Cell viability was evaluated using MTT metabolism test, as described previously [
67]. Briefly, 1.5-2 x10
4 cells were seeded onto 24-well plates and the MTT solution (0.5 mg/mL; Sigma-Aldrich, Germany) was added after 24, 48, 72 and 96 h after cell seeding. After 1 h of incubation at 37 °C, water-insoluble formazan was dissolved in DMSO and optical densities were measured at 570 nm and 620 nm using a scanning multi-well spectrophotometer. Cell viability after AG, DOX or TMZ treatments was evaluated using the PrestoBlue Cell Viability Reagent (Invitrogen, USA). Diluted PrestoBlue reagent was added to each well for 1.5 h at 37 °C. After collecting samples fluorescence was measured at 570 nm and 620 nm using a multi-well spectrophotometer.
2.5. Immunoblotting
Whole cell lysates were prepared in a buffer containing phosphatase and protease inhibitors, separated by SDS-PAGE and transferred onto nitrocellulose membranes as described [
68]. After blocking with 5% nonfat milk in a blocking buffer, the membranes were incubated overnight with primary antibodies and then with the appropriate secondary antibodies for 1 h. Immunocomplexes were visualized using an enhanced chemiluminescence detection system (SuperSignal West Pico PLUS; ThermoFisher Scientific, USA). Blots were visualized with a Chemidoc imaging system (Bio-Rad, USA). The molecular weight of proteins was estimated with prestained protein markers (Sigma-Aldrich, USA).
2.6. Immunofluorescence
Cells were seeded onto glass coverslip at a density of 2-3x10
4 cells. After 24 h cells were fixed with 4% PFA pH 7.2, washed, permeabilized with 0.1% Triton-X100 and blocked in a mix of 2% donkey serum and 1.5% fetal bovine serum, followed by overnight incubation with primary antibodies diluted in PBS containing 1% bovine serum albumin (BSA) and 0.1% Triton X-100. Cells were then washed in PBS, incubated with Alexa Fluor A555 secondary antibodies diluted in PBS for 2 h, counterstained with DAPI and mounted. For reagent specifications, catalogue numbers, and concentrations, see
Supplementary Table S1.
2.7. Scratch-wound assay
Cells were seeded onto 60-mm culture dishes at a density of 8×104 cells, in duplicates. When cells reached 80% confluency, a scratch was gently made using a p200 pipette tip. The pictures of the area were taken immediately after a wound was inflicted to the cells (0 h) and after 18 h. Migration rate was estimated from the distance that the cells moved, as determined microscopically. The area between the edges of the wound was measured by using Image J software. The six measurements were taken for each experimental condition. A mobility rate is expressed as percentage of wound closure as compared to 0 h time point. Migration rates were calculated using the following equation: (initial distance-final distance/initial distance) × 100%.
2.8. Bisulfite DNA conversion and methylation-specific polymerase chain reaction (MS-PCR)
DNA was extracted using standard phenol/chloroform methods. A purity and concentration of DNA were estimated by measuring absorbance at 260/280 nm. DNA (2 μg) was treated with bisulfite (EpiTect Bisulfite Kit, Qiagen, Germany). The modified DNA was amplified using primers specific for the methylated or unmethylated
MGMT gene promoter, as listed in
Supplementary Table S1. Each PCR mixture contained 1 μL of DNA, 500 nM of primers, 1x reaction buffer containing 1.5 mM MgCl
2, and 1 U HotStarTaq DNA Polymerase and 250 mM dNTPs (Promega, USA). PCR was performed with thermal conditions as follows: 95 °C for 10 min, 45 cycles of 95 °C for 30 s, 57 °C for 30 s and 72 °C for 30 s with a final extension of 72 °C for 10 min. PCR products were visualized using Agilent TapeStation system (Agilent Technologies, USA) yielding a band of 81 bp for a methylated product and 93 bp for an unmethylated product. Positive methylated and positive unmethylated controls (EpiTect PCR Control DNA Set Qiagen, Germany) were included.
2.9. Quantitative RT-PCR Analysis
Total RNA was extracted using an RNeasy Mini kit (Qiagen, Germany) and purified using RNeasy columns. An integrity of RNA was determined using an Agilent 2100 Bioanalyzer. For qRT-PCR, total RNA from cells was used to synthesize cDNA by extension of oligo (dT)
15 primers with SuperScript reverse transcriptase (Thermo Fisher Scientific, USA). Real Time PCR experiments were performed in duplicates using a cDNA equivalent of 22.5 ng RNA in a 10-μl reaction volume containing 2x SYBR Green Fast PCR Master Mix (Applied Biosystems, Germany) and a set of primers. Sequences of the primers are listed in
Table S1. Data were analyzed by the relative quantification method using StepOne Software (Applied Biosystems, Germany). The expression of each product was normalized to 18S rRNA and presented as a dCt value.
2.10. mRNA library preparation and sequencing
Quality and quantity of isolated nucleic acids were determined by Nanodrop (Thermo Fisher Scientific, Waltham, MA, USA). mRNA libraries were prepared using KAPA Stranded mRNAseq Kit (Roche, Switzerland/Kapa Biosystems, USA) according to manufacturer’s protocol. Briefly, mRNAs were enriched from 500 ng total RNAs using poly-T oligo-attached magnetic beads (Kapa Biosystems, USA). Enriched mRNA was fragmented, then the first and second strand of cDNA were synthesized. Adapters were ligated and the loop structure of each adapter was cut by USER enzyme (NEB, USA). Finally, the amplification of obtained dsDNA fragments that contained a specific adapter sequence was performed using NEB starters. Quality control of final libraries was performed using Agilent Bioanalyzer High Sensitivity dsDNA Kit (Agilent Technologies, USA). Concentration of the final libraries was measured using Quantus Fluorometer and QuantiFluor ONE Double Stranded DNA System (Promega, USA). Libraries were sequenced on HiSeq 1500 (Illumina, USA) on the rapid run flow cell with a paired-end settings (2x76bp).
2.11. RNA-seq data alignment, processing, and analysis
Data analysis: RNA sequencing reads were aligned to the human genome reference with the STAR algorithm [
69], a fast gap-aware mapper. Then, gene counts were obtained by featurecounts [
70] using human transcriptomic annotations. The counts were then imported to R and processed by DESeq2 [
71]. The counts were normalized for gene length and library size.
TCGA public data analysis: TCGA level 3 RNAseq data (aligned by STAR and gene expression counted by HTseq) were uploaded to R. Data from TCGA GBM (glioblastoma, WHO grade 4) and LGG (lower-grade gliomas, WHO grades 2/3) repositories were uploaded. Gene expression values as FPKM (fragments per kilobase of exon per million) were used for further analysis. The curated sets of genes characteristic for each GBM subtype, categorized originally by Verhaak et al. [
20], were downloaded from the Molecular Signatures Database v7.5.1. The analysis for the following gene sets was performed VERHAAK_GLIOBLASTOMA_PRONEURAL, VERHAAK_GLIOBLASTOMA_NEURAL, VERHAAK_GLIOBLASTOMA_CLASSICAL, VERHAAK_GLIOBLASTOMA_MESENCHYMAL.
2.12. Statistical analysis
All biological experiments were performed on 3-4 independent cell passages. Results are expressed as means ± standard deviation (SD). P-values were calculated using two-tailed t test or one-way ANOVA followed by appropriate post-hoc test using GraphPad Prism v6 (GraphPad Software, USA). Differences were considered statistically significant for p values < 0.05.
The effect size, Cohen’s ‘d’ and Hedge’s ‘g’, were calculated as follows: , . - mean of the group, - error mean square, - sample size.
4. Discussion
Glioblastomas are the most malignant tumor types of central nervous system (CNS) that remain incurable with the standard therapies [
87,
88], therefore new therapeutic approaches are needed. Due to slow pace and high costs of a new drug discovery, repurposing of Food and Drug Administration (FDA)-approved drugs becomes an attractive strategy [
89,
90]. Currently, several active agents, such as chlorpromazine (antipsychotic agent), imipramine (antidepressant), chloroquine (anti-malarial drug), metformin (anti-diabetic drug) or disulfiram (alcohol-abuse drug) are being investigated for their effects on GBM cells [
91,
92,
93,
94,
95,
96]. Moreover, better superior outcomes may be achieved by combining different targeted therapies [
97].
GBM is currently treated with the Stupp protocol, which combines surgery followed by radiotherapy and chemotherapy with TMZ [
98]. However, at least 50% of patients do not respond to the treatment, which ultimately leads to tumor recurrence [
99]. MGMT, an endogenous DNA repair enzyme, is often considered as the most important contributor in TMZ resistance due to it’s direct role in counteracting of DNA alkylation damage [
100]. Moreover, the deregulation of specific molecular pathways, including EGFR pathway, may contribute to TMZ/drug resistance. EGFR pathway has been extensively studied in GBM, due to common mutation and amplification of
EGFR gene [
28,
29,
30]. Several strategies were proposed to inhibit EGFR or its mutant EGFRvIII including small-molecule tyrosine kinase inhibitors, monoclonal antibodies and anti-tumor vaccines. Unfortunately, anti-EGFR therapies have shown negligible efficacy in clinical trials [
97].
We sought to investigate the effectiveness of EGFR inhibitor AG1478 in combination with TMZ or with anthracycline, DOX, which is one of the most widely used chemotherapeutic drug against many cancers. We used molecularly diverse patients-derived primary GBM cell cultures, characterized by a different status of MGMT promoter methylation.
While established cell lines have failed to demonstrate accurate genomic representations of the original tumors, patient-derived tumor cells or xenografts accurately reflect the molecular characteristics of the patient’s tumor and offer possibility of testing the response to a large number of compounds in multiple doses, or in combination with other drugs [
101].
The development and maintenance of a patient-derived glioma cell culture is challenging and time consuming [
65,
102]. We introduced a simplified and modified procedure to culture both adherent cells growing in a medium containing serum and GSCs growing in a serum-free medium supplemented with growth factors. The blood cells were removed during serial passages and medium exchanges. We generated 13 adherent cell cultures out of 16 GBM specimens, including sphere cultures, enriched in GSCs. The analysis of selected stem and differentiation marker expression could explain the low efficiency of obtaining sphere cultures. We found that only WG4 and WG14 cells had high expression of pluripotency markers such as
PROM1,
OLIG2,
SOX2 and
NESTIN (a marker of neural precursors), which are responsible for self-renewal of GSCs [
103,
104]. Expression of astrocytic (
GFAP,
S100) and neuronal (
MAP2,
TUBB3) markers was found in the same cells, suggesting that glioma cells undergone aberrant differentiation. Our data indicate that GBM-derived spheres represent a lineage-restricted progeny that expressed neural stem and precursor markers (NESTIN, SOX2 and OLIG2), but without expression of NANOG and OCT4A, an essential transcription factors that regulate self-renewal and pluripotency of embryonic stem cells [
78], which is in agreement with recent findings [
24,
80,
105]. Interestingly, we generated two cell lines from a WHO grade 1 tumor, and two cell lines from a grade WHO 2/3 tumor [
106]. Creating patient-derived models of lower-grade gliomas (LGG) is challenging [
107]. Virtually all LGG cell lines generated to date from adult patients represent oligodendroglioma WHO grade 3 [
108,
109,
110,
111], thus impeding
in vitro studies of LGGs.
It has been shown that GSCs closely mirror the phenotype and genotype of primary tumors, rather than serum-cultured cell lines [
112]. However, due to the low number of obtained neurosphere cultures from fresh GBM samples, we decided to analyze serum-cultured cells at the lowest passages. Passaging the cells as little as possible prevents genetic or epigenetic alterations keeping them close to the original tumor [
113]. Markedly, primary GBM-derived cell cultures we developed were more similar to high grade gliomas from TCGA than to LGG in terms of transcriptional profiles (data not shown).
Our comprehensive analysis of gene expression profiles and protein levels, revealed high intertumoral heterogeneity among GBM-derived cell cultures. We found that most of the patient-derived cell cultures represented mixed subtypes, without dominant gene expression signature. While a MES subtype was the dominant subtype in WG13 and WG17 cells, WG4 and WG14 cells were characterized by PN and CL signatures. Interestingly, hierarchical clustering revealed that WG4, WG14 and WG9 cell cultures were very similar to each other. CL and PN subtypes had a profile characteristic of highly proliferative cells [
20,
114] and indeed WG4, WG9, WG14 cells had a high proliferation index.
Transcriptional analysis is not routinely feasible in clinical setting, therefore a simplified method based on the IHC expression of some proteins was proposed [
75,
76,
115,
116]. In this study, we evaluated seven proteins (EGFR, PDGFRa, IDH1
R132H, TP53, CHI3L1/YKL40, CD44 and phSTAT3) as molecular markers for GBM subtyping. More than a half of the cultures had high levels of EGFR (CL markers) and phosphorylated/active form of EGFR was found in WG4, WG9 and WG14 cells. The correlation between EGFR mutation and phosphorylation of tyrosine 845 or 1068 has been previously shown in cancer cells [
117]. WG4, WG14 and WG17 cells were positive for the mutant IDH
R132H, therefore they would be assigned as grade 4 astrocytoma according to the current WHO classification published in 2021 [
118]. The anti-IDH1
R132H-specific monoclonal antibody is more sensitive than direct DNA sequencing [
119]. Increased TP53 protein level in WG4, WG14 and WG17 cells suggests non-functional TP53, as wild-type TP53 is rapidly degraded and mutant forms are stabilized in tumor cells [
120]. This is consistent with recent reports [
20,
28], showing that gliomas grade 4 with
IDH1 hotspot mutations harbor concurrent
TP53 mutations. High expression of TP53 and mutant IDH1 mutation did not correlate with high level of PDGFRa, elevated in a half of tumor cell cultures. High expression of CHI3L1/YKL40 (a MES marker) was found only in WG4 and WG14 cells. MES GBMs or MES subtype of GSCs express CD44 [
121,
122] and we confirmed elevated expression of CD44, as well as VIMENTIN in majority of cultures. N-CADHERIN (a hallmark of EMT) was expressed to varying extents in cell cultures. High expression of SNAIL was found in WG4, WG9 and WG13 cells, while the expression of SLUG was uniformly high in studied cell cultures. STAT3 has been implicated into EMT as an inducer of EMT genes such as
SNAIL,
SLUG, and
TWIST [
123,
124,
125] and consistently higher levels of active STAT3 were found in WG9, WG14 and WG4 cells.
We conclude that tested patient-derived cell cultures recapitulate the known molecular heterogeneity of GBM, although gene expression was not fully recapitulated at protein levels. Indeed, Brennan et al. found that a targeted proteomic profile showed that the impact of specific genomic alterations on downstream pathway signaling is not linear and not always concordant with a genotype [
28]. Moreover, the machine-learning approach that designed an immunohistochemical (IHC)-based classification of GBM revealed 79.5% concordance with the transcriptional-based classification, with the highest accuracy (90%) reached in the MES subgroup [
126]. MES and CL subgroups were well segregated, while PN GBM more frequently shared overlapping features with both groups.
The classification of GBM has implications in selecting target therapy strategies. The CL GBMs are more responsive to the radiation and chemotherapy, because the TP53 DNA damage response is intact in this group of patients. The MES subtype is the most aggressive and strongly associated with a poor prognosis compared to PN subtype [
127], in addition, a shift from PN to MES subtype can occur in patients following radiotherapy and chemotherapy [
105].
Based on the above, WG4, WG14 and WG9 cells were classified as a CL/PN subtype, highly expressing phosphorylated/active EGFR. Proteomic data from Reverse Phase Protein Array (RPPA) showed that EGFR and its phosphorylated variants (pY992, pY1068, and pY1173) are significantly enriched in the CL subtypes [
128]. Since
EGFR is among the most frequently mutated genes in human adult gliomas, and mostly found in the CL subtypes, EGFR-targeted therapy has attracted much attention as an alternative therapeutic strategy to treat malignant gliomas. A specific EGFR inhibitor AG1478 [N-(3-chlorophenyl)- 6,7-dimethoxyquinazolin-4-amine] competitively binds to the ATP pocket of EGFR and inhibits its activity [
129,
130]. Previous data showed anti-proliferative effects of AG1478 and enhancement of the sensitivity to cytotoxic drugs, such as cisplatin, etoposide and DOX in different cancer cells [
131,
132]. AG1478 inhibited the growth of A431 tumors
in vivo [
133] and human glioma cells which overexpress a mutant EGFR (EGFRvIII) [
134,
135,
136]. AG1478 was used in EGFRvIII-related murine gliomas and advanced to clinical studies [
137].
We determined the effect of AG1478 on GBM-derived cells treated with TMZ or DOX, but in the context of methylated
MGMT. We found that AG-treated cells with methylated
MGMT promoter or with intermediate status were more sensitive to DOX than cells with the unmethylated
MGMT and AG1478+TMZ resulted in the strongest accumulation of apoptosis markers in WG4 and WG14 cells. Our data suggests that
MGMT promoter methylation could predict the response to other drugs, not only for TMZ [
138,
139]. A recent systematic review and meta-analysis confirmed a
MGMT methylation status as a clinical biomarker in GBM patients, showing association with better overall and progression free survival in patients treated with alkylating agents [
140]. Interestingly, the survival benefits were also observed in GBM patients irrespective of treatment [
141]. A subgroup of patients treated with tyrosine kinase inhibitors (with or without alkylating agent in combination) showed a significant association of the
MGMT methylation with overall survival.
We found reduced levels of the phophorylated EGFR in AG1478-treated cells, including EGFR
high GSCs [
66], while downstream PI3K-AKT and ERK signaling pathways were not affected. Interestingly, the levels of active, phoshoprylated STAT3 were reduced. These data suggest that EGFR-STAT3 pathway is an important signaling rout for the response of tumor cells to AG1478. Lack of the effects on PI3K-AKT pathway could result from PTEN alterations, mutations within the gene encoding the p110 catalytic subunit of PI3K (
PIK3CA),
AKT amplification [
142] or activation via PDGFRs [
143,
144,
145]. We demonstrated that pharmacological inhibition of EGFR reduces phospho-STAT3 levels and increases the sensitivity of GBM derived cells cultures to TMZ or DOX. This evidence supports the notion of using drug combination to improve clinical outcome.
DOX is an anthracycline topoisomerase II inhibitor, used in many cancers but a low penetration of BBB and serious side effects, including cardiotoxicity restrict its use in GBM therapy. To overcome this obstacle various formulations with nanoparticles, liposomes, have been employed to deliver DOX to glioblastomas [
14,
15,
16,
17,
18,
19]. Interestingly, co-delivery of DOX and EGFR siRNA in intracranial U87MG xenografts prolonged the life span of the glioma-bearing mice and induced apoptosis in gliomas [
15]. Other strategies assisting improvement of drug delivery and disruption the peritumoral BBB are focused ultrasound (FUS) and interstitial thermal therapy (LITT). Indeed, the accumulation of DOX in GBM-bearing mice following FUS-induced BBB disruption was significantly higher than that in the control tumor [
18]. Butt et al. recently demonstrated that LITT combined with low-dose DOX results in longer survival recurrent GBM patients. Low dose of DOX was safe for patients, even with extended (>6 weeks) dosing [
146]. Promising results were also observed in phase I trial (GBM-LIPO trial) in which patients with relapsed glioblastoma harboring an
EGFR amplification were treated with anti-EGFR doxorubicin-loaded immunoliposomes (anti-EGFR ILs-dox) [
63].
Figure 1.
Characterization of glioma patients cohort and transcriptomic and protein-based subtyping of patient-derived primary cell cultures (A-B) Graphical representation of sex (A) and age (B) of patients in the analyzed glioma cohort. Red line represents the mean age. (C) The proliferation capacity of glioblastoma patient-derived primary cell cultures and normal human astrocytes (NHA) determined by MTT metabolism assay, n=3, mean ± SD. (D) Doubling time of primary glioma cell cultures and NHA as a non-malignant control. (E) RNAseq of patient-derived cell cultures represented at the heatmap with Verhaak signatures (MES, CL, PN and NE) for glioblastoma subtypes. (F) Representative immunoblots illustrating the markers of glioblastoma subtypes: IDH1 R132H, CHI3L1, pSTAT3, STAT3 (MES); EGFR (CL); PDGFRα, TP53 (PN) in cultures of human glioma cells, NHA and NTERA-2 cells (NTERA). (G) Quantification of immunoblots. The level of a protein of interest in NHA cells equals 1 and is marked by a solid black line. β-actin was used as a loading control. NHA serves as a non-malignant control, whereas NTERA as a positive control for stemness properties, n=2, mean ± SD.
Figure 1.
Characterization of glioma patients cohort and transcriptomic and protein-based subtyping of patient-derived primary cell cultures (A-B) Graphical representation of sex (A) and age (B) of patients in the analyzed glioma cohort. Red line represents the mean age. (C) The proliferation capacity of glioblastoma patient-derived primary cell cultures and normal human astrocytes (NHA) determined by MTT metabolism assay, n=3, mean ± SD. (D) Doubling time of primary glioma cell cultures and NHA as a non-malignant control. (E) RNAseq of patient-derived cell cultures represented at the heatmap with Verhaak signatures (MES, CL, PN and NE) for glioblastoma subtypes. (F) Representative immunoblots illustrating the markers of glioblastoma subtypes: IDH1 R132H, CHI3L1, pSTAT3, STAT3 (MES); EGFR (CL); PDGFRα, TP53 (PN) in cultures of human glioma cells, NHA and NTERA-2 cells (NTERA). (G) Quantification of immunoblots. The level of a protein of interest in NHA cells equals 1 and is marked by a solid black line. β-actin was used as a loading control. NHA serves as a non-malignant control, whereas NTERA as a positive control for stemness properties, n=2, mean ± SD.

Figure 2.
Stemness and differentiation markers across primary cell cultures. (A) RNAseq of primary cell cultures represented as heatmap with stemness (indicated by blue color) and differentiation (red color) related genes. (B) Expression of selected differentiation (GFAP, TUBBIII) and stemness (SOX2, NESTIN) related genes in human patient-derived primary cultures and NHA as a control. The RT-qPCR data are shown as delta Ct values relative to the 18S expression. (C) Representative immunoblots showing GFAP, β-TUB III and SOX2 levels in glioma primary cultures, NHA and NTERA cells. (D) Quantification of immunoblots. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-actin was used as a loading control. NHA serves as a non-malignant control, whereas NTERA as a positive control with stemness properties. Statistical analysis was performed using one way ANOVA with Dunnett’s post hoc test to NHA cells (*p<0.05, **p<0.01, ***p<0.001), n=2, mean ± SD (E) Representative immunofluorescent staining of WG4, WG13, WG14 and WG17 cells displaying the stemness properties, toward the stemness (NESTIN, SOX2) and differentiation (GFAP, β-TUB III, MAP2) markers. White arrows indicate positive nuclear staining. Scale bar: 100 µm.
Figure 2.
Stemness and differentiation markers across primary cell cultures. (A) RNAseq of primary cell cultures represented as heatmap with stemness (indicated by blue color) and differentiation (red color) related genes. (B) Expression of selected differentiation (GFAP, TUBBIII) and stemness (SOX2, NESTIN) related genes in human patient-derived primary cultures and NHA as a control. The RT-qPCR data are shown as delta Ct values relative to the 18S expression. (C) Representative immunoblots showing GFAP, β-TUB III and SOX2 levels in glioma primary cultures, NHA and NTERA cells. (D) Quantification of immunoblots. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-actin was used as a loading control. NHA serves as a non-malignant control, whereas NTERA as a positive control with stemness properties. Statistical analysis was performed using one way ANOVA with Dunnett’s post hoc test to NHA cells (*p<0.05, **p<0.01, ***p<0.001), n=2, mean ± SD (E) Representative immunofluorescent staining of WG4, WG13, WG14 and WG17 cells displaying the stemness properties, toward the stemness (NESTIN, SOX2) and differentiation (GFAP, β-TUB III, MAP2) markers. White arrows indicate positive nuclear staining. Scale bar: 100 µm.

Figure 3.
Characterization of stemness properties of GBM-derived sphere and adherent cell cultures. (A) Morphology of WG14 and L0125 cells in the presence of serum containing media (marked as FBS) or in the growth factors containing media (marked as sph). L0125 serves as a control cell line with stemness properties. (B) Representative immunoblots showing levels of GFAP, β-TUB III (differentiation markers) and OLIG2, SOX2, NANOG, OCT4 (stemness markers) in glioma primary cell cultures, NHA, NTERA, L0125 and L0627 cells. (C) Quantification of immunoblots. The level of a protein of interest in NHA equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical analysis was performed using t-test comparing values in sph and FBS groups (*p<0.05, **p<0.01, ***p<0.001), n≥2, ±SD. (D) Expression of chosen differentiation (GFAP, TUBBIII) and stemness (OLIG2, SOX2, NESTIN) related genes in WG14 human patient-derived primary cells, L0125 and L0627 cells, cultured with FBS or with defined media (sph). The RT-qPCR data are shown as delta Ct values relative to the 18S expression. Statistical analysis was performed using t-test (*p<0.05, **p<0.01, ***p<0.001), n≥2, mean ± SD.
Figure 3.
Characterization of stemness properties of GBM-derived sphere and adherent cell cultures. (A) Morphology of WG14 and L0125 cells in the presence of serum containing media (marked as FBS) or in the growth factors containing media (marked as sph). L0125 serves as a control cell line with stemness properties. (B) Representative immunoblots showing levels of GFAP, β-TUB III (differentiation markers) and OLIG2, SOX2, NANOG, OCT4 (stemness markers) in glioma primary cell cultures, NHA, NTERA, L0125 and L0627 cells. (C) Quantification of immunoblots. The level of a protein of interest in NHA equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical analysis was performed using t-test comparing values in sph and FBS groups (*p<0.05, **p<0.01, ***p<0.001), n≥2, ±SD. (D) Expression of chosen differentiation (GFAP, TUBBIII) and stemness (OLIG2, SOX2, NESTIN) related genes in WG14 human patient-derived primary cells, L0125 and L0627 cells, cultured with FBS or with defined media (sph). The RT-qPCR data are shown as delta Ct values relative to the 18S expression. Statistical analysis was performed using t-test (*p<0.05, **p<0.01, ***p<0.001), n≥2, mean ± SD.

Figure 4.
Epithelial mesenchymal transition (EMT) related genes and proteins in human primary glioma cell cultures (A) Representative immunoblots showing the EMT markers levels in glioma primary cultures, NHA and NTERA cells. (B) Quantification of immunoblots. The level of a protein of interest in NHA cells equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical analysis was performed using one way ANOVA with Dunnett’s post hoc test comparing values obtained in tumor cells to NHA cells (*p<0.05, **p<0.01, ***p<0.001), n=2, mean ± SD. (C) Quantification of glioma cell migration using an in vitro scratch assay. Results are presented as the percentage of scratch coverage after 18 h, n=3, mean ± SD.
Figure 4.
Epithelial mesenchymal transition (EMT) related genes and proteins in human primary glioma cell cultures (A) Representative immunoblots showing the EMT markers levels in glioma primary cultures, NHA and NTERA cells. (B) Quantification of immunoblots. The level of a protein of interest in NHA cells equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical analysis was performed using one way ANOVA with Dunnett’s post hoc test comparing values obtained in tumor cells to NHA cells (*p<0.05, **p<0.01, ***p<0.001), n=2, mean ± SD. (C) Quantification of glioma cell migration using an in vitro scratch assay. Results are presented as the percentage of scratch coverage after 18 h, n=3, mean ± SD.
Figure 5.
MGMT promoter methylation and the impact of TMZ on primary glioma cell cultures. (A) Evaluation of the MGMT promoter methylation in primary glioma cell cultures and (B) a summary table. (C) Microscopic images of WG4, WG14 and WG9 treated with TMZ (1 mM, 72 h). Scale bar: 100 µm. (D) Viability of WG4, WG14 and WG9 cells after TMZ treatment, determined by MTT metabolism test. The viability of untreated cells was set as 100% and marked with a black solid line. Statistical analysis was performed on raw data using t-test in comparison of treated to control groups (*p<0.05, **p<0.01, ***p<0.001), n=5, mean ± SD. (E) Representative immunoblots showing the levels of apoptotic proteins: cleaved caspase 3, cleaved caspase 7 and cleaved PARP (cl. CASP 3, cl. CASP 7, cl. PARP, respectively) in TMZ treated WG4, WG14 and WG9 cells. (F) Quantification of immunoblots. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-actin was used as a loading control. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test in comparison of treated to untreated cells (*p<0.05, **p<0.01, ***p<0.001) or between the cell lines (#p<0.05, ##p<0.01, ###p<0.001), n=3, mean ± SD.
Figure 5.
MGMT promoter methylation and the impact of TMZ on primary glioma cell cultures. (A) Evaluation of the MGMT promoter methylation in primary glioma cell cultures and (B) a summary table. (C) Microscopic images of WG4, WG14 and WG9 treated with TMZ (1 mM, 72 h). Scale bar: 100 µm. (D) Viability of WG4, WG14 and WG9 cells after TMZ treatment, determined by MTT metabolism test. The viability of untreated cells was set as 100% and marked with a black solid line. Statistical analysis was performed on raw data using t-test in comparison of treated to control groups (*p<0.05, **p<0.01, ***p<0.001), n=5, mean ± SD. (E) Representative immunoblots showing the levels of apoptotic proteins: cleaved caspase 3, cleaved caspase 7 and cleaved PARP (cl. CASP 3, cl. CASP 7, cl. PARP, respectively) in TMZ treated WG4, WG14 and WG9 cells. (F) Quantification of immunoblots. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-actin was used as a loading control. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test in comparison of treated to untreated cells (*p<0.05, **p<0.01, ***p<0.001) or between the cell lines (#p<0.05, ##p<0.01, ###p<0.001), n=3, mean ± SD.

Figure 6.
Treatment with the EGFR inhibitor AG1478 modifies sensitivity of glioma cells to TMZ. (A) Representative immunoblots of phosphorylated proteins involved in EGFR signaling pathways in WG4, WG14 and WG9 cells in the presence (6 h) and absence of 10 µM AG1478 (AG). (B) The densitometric quantification. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical significance was determined by t-test in comparison of treated to non-treated cells (*p<0.05, **p<0.01, ***p<0.001), n≥3, mean ± SD. (C) Viability of WG4, WG14 and WG9 cells after 10 µM AG alone or combined with 1 mM TMZ (AG+TMZ) for 72 h was determined with a PrestoBlue test. Viability of the control group was set as 100% and marked by a black solid line. Statistical significance was determined on raw data by one-way ANOVA followed by Dunnett’s post hoc test in comparison of treated to untreated cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or TMZ vs AG+TMZ (#p<0.05, ##p<0.01, ###p<0.001), n=3,mean ± SD. (D) Representative immunoblots detecting the apoptosis markers: cleaved caspase 7 and cleaved PARP (cl. CASP 7, cl. PARP, respectively), and phospho-STAT3 (pSTAT3) and STAT3 of WG4, WG14 and WG9 cells treated with 10 µM AG, 1 mM TMZ or with combination of AG+TMZ for 72 h. (E) Quantification of immunoblots. The level of protein of interest in control cells equals 1 and is marked by a solid black line. β-ACTIN was as a loading control. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test in comparison of treated to untreated control cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or TMZ vs AG+TMZ (#p<0.05, ##p<0.01, ###p<0.001), n≥3, mean ± SD.
Figure 6.
Treatment with the EGFR inhibitor AG1478 modifies sensitivity of glioma cells to TMZ. (A) Representative immunoblots of phosphorylated proteins involved in EGFR signaling pathways in WG4, WG14 and WG9 cells in the presence (6 h) and absence of 10 µM AG1478 (AG). (B) The densitometric quantification. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical significance was determined by t-test in comparison of treated to non-treated cells (*p<0.05, **p<0.01, ***p<0.001), n≥3, mean ± SD. (C) Viability of WG4, WG14 and WG9 cells after 10 µM AG alone or combined with 1 mM TMZ (AG+TMZ) for 72 h was determined with a PrestoBlue test. Viability of the control group was set as 100% and marked by a black solid line. Statistical significance was determined on raw data by one-way ANOVA followed by Dunnett’s post hoc test in comparison of treated to untreated cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or TMZ vs AG+TMZ (#p<0.05, ##p<0.01, ###p<0.001), n=3,mean ± SD. (D) Representative immunoblots detecting the apoptosis markers: cleaved caspase 7 and cleaved PARP (cl. CASP 7, cl. PARP, respectively), and phospho-STAT3 (pSTAT3) and STAT3 of WG4, WG14 and WG9 cells treated with 10 µM AG, 1 mM TMZ or with combination of AG+TMZ for 72 h. (E) Quantification of immunoblots. The level of protein of interest in control cells equals 1 and is marked by a solid black line. β-ACTIN was as a loading control. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test in comparison of treated to untreated control cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or TMZ vs AG+TMZ (#p<0.05, ##p<0.01, ###p<0.001), n≥3, mean ± SD.

Figure 7.
AG1478 enhanced cytotoxicity exerted by DOX in primary glioma cell cultures. (A) Representative immunoblots showing the apoptosis markers: cleaved caspase 7 and cleaved PARP (cl. CASP 7, cl. PARP, respectively) in WG4, WG14 and WG9 cells treated with DOX for 48 h. (B) Densitometric quantification of effects of DOX at the high doses: 0.5 and 1 mM. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test (*p<0.05, **p<0.01, ***p<0.001), n=3, mean ± SD. (C) Cell viability of WG4, WG14 and WG9 cells after 10 µM AG, 0.5 mM DOX or combined, AG+DOX treatment for 48 h, determined by PrestoBlue test. Viability of the control group was set as 100% and marked by a black solid line. Statistical significance was determined on raw data by one-way ANOVA followed by Dunnett’s post hoc test in comparison to untreated control cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or DOX vs AG+DOX (#p<0.05, ##p<0.01, ###p<0.001), n≥3, mean ± SD. (D) Representative immunoblots detecting the apoptosis markers: cleaved caspase 7 and cleaved PARP (cl. CASP 7, cl. PARP, respectively) of WG4, WG14 and WG9 cells treated with 10 µM AG, 0.5 mM DOX or with combination of AG+DOX for 48 h with (E) the densitometric quantification. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test in comparison to untreated control cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or DOX vs AG+DOX (#p<0.05, ##p<0.01, ###p<0.001), n=3, mean ± SD.
Figure 7.
AG1478 enhanced cytotoxicity exerted by DOX in primary glioma cell cultures. (A) Representative immunoblots showing the apoptosis markers: cleaved caspase 7 and cleaved PARP (cl. CASP 7, cl. PARP, respectively) in WG4, WG14 and WG9 cells treated with DOX for 48 h. (B) Densitometric quantification of effects of DOX at the high doses: 0.5 and 1 mM. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. β-ACTIN was used as a loading control. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test (*p<0.05, **p<0.01, ***p<0.001), n=3, mean ± SD. (C) Cell viability of WG4, WG14 and WG9 cells after 10 µM AG, 0.5 mM DOX or combined, AG+DOX treatment for 48 h, determined by PrestoBlue test. Viability of the control group was set as 100% and marked by a black solid line. Statistical significance was determined on raw data by one-way ANOVA followed by Dunnett’s post hoc test in comparison to untreated control cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or DOX vs AG+DOX (#p<0.05, ##p<0.01, ###p<0.001), n≥3, mean ± SD. (D) Representative immunoblots detecting the apoptosis markers: cleaved caspase 7 and cleaved PARP (cl. CASP 7, cl. PARP, respectively) of WG4, WG14 and WG9 cells treated with 10 µM AG, 0.5 mM DOX or with combination of AG+DOX for 48 h with (E) the densitometric quantification. The level of a protein of interest in control cells equals 1 and is marked by a solid black line. Statistical significance was determined by one-way ANOVA followed by Dunnett’s post hoc test in comparison to untreated control cells (*p<0.05, **p<0.01, ***p<0.001) or by one-way ANOVA followed by uncorrected Fisher’s LSD test between the groups: AG or DOX vs AG+DOX (#p<0.05, ##p<0.01, ###p<0.001), n=3, mean ± SD.
