Glioblastoma (GBM) is one of the most malignant tumors with an extremely poor prognosis (1-4). The currently available treatment methods, including chemotherapy, radiotherapy, and surgery, does not yield significant clinical benefits for GBM patients, offering 2-year survival rate of 10% (5). The malignancy of GBM is attributed to highly heterogeneous tumor microenvironment, which originates from glioma stem cells (GSCs) (6). Therefore, understanding the mechanisms that increase and maintain cancer stem cell-like properties is important for the development of new cancer therapeutics.

Leucine-rich repeat kinase 2 (LRRK2), also known as PARK8, was known for its association with Parkinson’s disease (7). Considering that both neurodegenerative diseases and brain cancer are all age-related, common genetic mutations, including SNCA, PARK2, LRRK2, ATM, p53, PTEN, and MC1R, are present in both pathologies (8, 9). Interestingly, some key genes can function differently in these two pathologies based on their expression within brain tissue. PARK2, whose mutation is responsible for half of the early-onset inherited Parkinson’s disease case, is downregulated in GBM patients (10, 11). While DJ-1, another gene responsible for autosomal recessive Parkinson’s disease, is upregulated in GBM patients (12, 13).

In the context of Parkinson’s disease, the G2019S mutation of LRRK2 is the most common single mutation type associated with an increased risk of the disease (14, 15). Since mutations in the PARK family cause Parkinson’s disease and changes in wild-type expression lead to GBM, we speculated whether a change in the expression level of another PARK gene, LRRK2, is associated with GBM (16). The current relationship between LRRK2 mutation carriers and increased cancer risk was found in non-skin cancer, smoking-related cancers, and hormone-related cancers (17-19). However, the relationship between the expression of wild-type LRRK2 and GBM tumorigenesis has not been questioned. Hence, we deduced that there is a possible co-rrelation between wild-type LRRK2 expression and GBM malignancy.

Here we suggest that LRRK2 acts a strong tumor driver in GBM, regulating stemness. For this reason, we developed thea novel LRRK2 kinase inhibitor DNK72 (20), which has a high affinity for the phosphorylation site and is highly permeable through the blood-brain barrier. DNK72 has been shown to effectively reduce the proliferation rate and stemness factors of LRRK2-positive GBM stem cells in both in vitro and in vivo studies. We propose that further studies targeting cancer stemness should consider LRRK2 as an important target for the successful development of therapeutic methods.

Cells and cell culture conditions

Human GSCs derived from patients who agreed to participate in the research were obtained from Dr. Do-Hyun Nam (Samsung Medical Center, Korea), approved by the Institutional Review Board at Samsung Medical Center, Korea (No. 2005-04-001, 2010-04-004). GSCs were maintained in Dulbecco’s modified Eagle medium/nutrient mixture F-12 (DMEM/F-12) 50/50 supplemented with B27 (Invitrogen), epidermal growth factor (EGF, 10 ng/mL; R&D Systems), basic fibroblast growth factor (bFGF, 5 ng/mL; R&D Systems).

Western blot

Proteins were extracted with RIPA buffer containing complete protease inhibitors (Roche), separated by electrophoresis, transferred to PVDF membranes (Millipore), and blocked with 5% skim milk (BD). Primary antibodies were incubated overnight at 4℃. Immunoreactive bands were visualized using peroxidase-labeled affinity purified secondary antibodies (KPL) and detected with Amersham ECL prime Western blotting detection reagent (GE Healthcare). In every western blot panel, more than three independent experiments were performed, and one representative immunoblot was shown.

In vivo study

All animal work was conducted in accordance with protocols approved by the Institutional Animal Care and Use Committee at the National Cancer Center, Korea (No. NCC-17-402). Republic of Korea. Animals were randomized by body weight before conducting experiments. For the orthotopic mouse model, patient-derived GBM cells were orthotopically transplanted following washing and resuspension in DMEM/F-12 supplemented with B27, EGF (10 ng/mL), and bFGF (5 ng/mL). Survival was analyzed using PRISM software version 7 (GraphPad).

Drug treatment

Patient-derived cancer cells were treated with LRRK2 inhibitors. We examined how the LRRK2 inhibitors function in the cellular signaling mechanism and regulate in phosphorylation residues. DNK72 was administered at 30 minutes, 2, 8, and 16 hours in 448T patient-derived cancer cells for liquid chromatography-mass spectrometry (LC-MS) based proteomics to check the immediate early response and trigger reactions against LRRK2 targeting.

Protein extraction and peptide digestion

PBS-washed cell pellets were solubilized in SDS solubilization buffer (5% SDS, 50mM triethylammonium bicarbonate [TEAB] pH 8.5) using an S220 Focused-ultrasonicator (Covaris). Proteins were digested using S-Trap^TM spin columns (ProtiFi) following the manufacturer’s instructions. The samples were reduced with dithiothreitol and alkylated with iodoacetamide. After quenching the alkylation reaction, additional SDS and phosphoric acid were added to reach final concentration was 5% SDS and 1.2% phosphoric acid. Acidified samples were mixed with 90% methanol in 100 mM TEAB, loaded into the S-Trap micro columns, incubated with mass spec grade Trypsin/Lys-C (Promega) for 3 hours at 47℃. Eluted peptides were evaporated using a vacuum concentrator (Eppendorf) and cleaned up using Peptide Desalting Spin Columns (Thermo Fisher Scientific).

Tandem mass tag labeling

Desalted peptides were reconstituted in 100 mM TEAB pH 8.5 and labeled using tandem mass tag (TMT) label reagents (Thermo Fisher Scientific). Each prepared TMT reagent was transferred to the peptide sample, the mixture was incubated for 1 hour, quenched by the addition of 5 mL of 5% hydroxylamine, and incubated for 15 minutes at room temperature. Differently labeled peptides was pooled and dried using vacuum concentrator.

Peptide fractionation by mid-pH reverse phase liquid chromatography

The pooled TMT-labeled sample was separated using an 1260 Infinity HPLC system (Agilent) with an XBridge C18 analytical column (4.6×250 mm, 130 Å, 5 μm; Waters) and a guard column (4.6×20 mm, 130 Å, 5 μm; Waters). Solvents A and B were 10 mM TEAB in water (pH 7.5) and 10 mM TEAB in 90% acetonitrile (ACN, pH 7.5), respectively. Peptide fractionation was performed using a 120 minutes gradient at a flow rate of 500 mL/min as follows: 0% solvent B for 15 minutes, 0% to 5% solvent B over 10 minutes, from 5% to 35% solvent B over 60 minutes, from 35% to 70% solvent B over 15 minutes, 70% solvent B for 10 minutes, from 70% to 0% solvent B over 10 minutes. A total of 96 fractions were collected every minute from 15 to 110 minutes and were pooled into 24 non-continuous peptide fractions (i.e., #1–#25–#49–#73, #2–#26–#50–#74, …, #24–#48–#72–#96) and dried using a concentrator. For global proteome analysis, 5% of each fraction was aliquoted and dried using a vacuum concentrator. The remaining 95% concatenated fractions were further combined into 12 fractions and dried using a vacuum concentrator for phosphopeptide enrichment.

Phosphopeptide enrichment using immobilized metal affinity chromatography

For phosphopeptide enrichment, Ni-NTA agarose beads (QIAGEN) were washed with deionized water and treated with 100 mM ethylene-diamine-tetraacetic acid (EDTA), pH 8.0 for 30 minutes with end-over-end rotation. The EDTA solution was removed, the beads were washed with deionized water and then treated with 10 mM aqueous FeCl₃ metal ion solution for 30 minutes with end-over-end rotation. After removing excess metal ions, the beads were washed with deionized water, resuspended in a 1：1：1 mixture of ACN/methanol/0.01% acetic acid solution, and aliquoted into microcentrifuge tubes. Fractionated peptide samples were resuspended in resuspension buffer (80% ACN, 0.1% trifluoroacetic acid [TFA]). After washing the aliquoted Fe^3＋-NTA beads with the resuspension buffer, the resuspended peptide sample was added and incubated with end-over-end rotation for 30 minutes. The superna-tant was collected and dried for future reference. The beads were washed with resuspension buffer, and the remaining solution was discarded. The enriched phosphopeptide was eluted with 1：1：1 mixture of ACN/2.5% ammonia water/2 mM phosphate buffer, acidified with 10% TFA solution, and dried using vacuum concentrator.

LC-MS/MS analysis

TMT-labeled peptides prepared for global and phosphoproteome analysis were resuspended in 0.1% formic acid in water and analyzed on a Q Exactive Orbitrap mass spectrometer (Thermo Fisher Scientific) coupled with an Ulti-Mate 3000 RSLCnano system (Thermo Fisher Scientific). The peptides were loaded onto a trap column (75 μm×2 cm) packed with Acclaim PepMap 100 C18 resin and separated on an analytical column (EASY-Spray column, 75 μm×50 cm; Thermo Fisher Scientific), then sprayed into the nano-electrospray ionization source with an electrospray.

Database search

Database searching of all raw data files was performed using Proteome Discoverer 2.5 software (Thermo Fisher Scientific). SEQUEST-HT was used for database searching against the SwissProt human database. Database searches against the corresponding reverse database was also performed to evaluate the false discovery rate (FDR) of peptide identification. The database search parameters included a precursor ion mass tolerance of 10 ppm, a fragment ion mass tolerance of 0.08 Da, a fixed modification for carbamidomethyl cysteine (＋57.021 Da/C), and variable modifications for methionine oxidation (＋15.995 Da/M) and phosphorylation (＋79.966 Da/S, T, Y). We obtained an FDR of less than 1% on the peptide level and filtered with high peptide confidence.

Histology and tissue staining

For observation of histological features, brains were removed, fixed with 4% paraformaldehyde for 24 hours at 4℃, sectioned at a thickness of 4 μm using an essential microtome (Leica RM2125 RTS; Leica Biosystems), and stained with hematoxylin (Dako) and 0.25% eosin (Merck). Tissue sections were then incubated overnight at 4℃ in a humidified chamber with primary antibody, diluted with antibody diluent buffer (IHC World). Tissue sections for DAB staining were developed using 3,3’-diaminobenzidine (DAB; Vector Laboratories) as the chromogen.

Statistics

All data are expressed as mean±SEM from at least three independent experiments. The Kaplan–Meier method was used to plot survival curves. In the case of patients who were alive at the time of last follow-up, survival records were censored in our analysis. The SPSS software (version 16; SPSS Inc.) was used for statistical analysis. In the case of mouse experiments, the results of multiple datasets were compared by ANOVA using the log-rank (Mantel-Cox) test. The results of two-dataset experiments were compared using a two-tailed Student’s t-test. p-values<0.05 were considered statistically significant. The functional networks based on the biological processes (MSigDB) were analyzed using the Enrichment Map Cytoscape plugin.

Phosphorylation site analysis

The LRRK2 phosphorylation sites were evaluated with Microsoft Excel and MeV experiments in the R package. Heatmaps were calculated from the averages of replicate experiments.

Kinase substrate enrichment analysis

Kinase-substrate analysis was done using the online KSEA App (https://casecpb.shinyapps.io/ksea/). KSEA was used to calculate kinase’s activity score based on PhosphoSitePlus and NetworkIN databases. The p-value cut-off (for a plot) and the number of substrates cut-off were set to 0.05.

In order to investigate the link between LRRK2 and malignancy of the brain tumor, we stained for LRRK2 in various brain tumor types: Oligodendroglioma, astrocytoma, and GBM (Fig. 1A). We found that GBM exhibited more intense LRRK2 expression compared to less malignant brain tumor types, including oligodendroglioma and astro-cytoma. To investigate the correlation between LRRK2 expression levels and patients’ survival, we analyzed the survival of patients based on a tissue microarray (TMA) of 161 patients that we had acquired (Supplementary Fig. S1A, S1B). Noticeably, almost 40% of the GBM patients exhibited moderate to high levels of LRRK2 expression, and those with high LRRK2 expression (n=44) had significantly poorer survival times compared to patients with low LRRK2 expression (n=117) (Fig. 1B). This difference was also observed in GBM patients, showing that higher LRRK2 expression significantly reduces survival time (Fig. 1C). Next, we utilized an online database to see if similar observations were prevalent. From REMBRANDT database, we obtained data on 329 gliomas and observed that high LRRK2 expression (n=165) was correlated with poor prognosis in cancer patients (Fig. 1D).

Figure 1. Leucine-rich repeat kinase 2 (LRRK2) is highly expressed in glioblastoma (GBM) and GBM stem cells. (A) LRRK2 staining for various brain tumor types, including oligodendroglioma, astrocytoma, and GBM. GBM showed higher LRRK2 expression than less malignant tumors like oligodendroglioma and astrocytoma. Scale bar=50 μm. (B, C) Kaplan–Meier survival plots for all glioma patients and GBM patients with high and low LRRK2 expression. Patients with high LRRK2 expression had shorter survivals, as demonstrated in the tissue microarray (TMA) data of all 161 glioma and 101 GBM patients. (D) Kaplan–Meier survival plots for all glioma patients with high and low LRRK2 expression. Data were obtained from the REMBRANDT of the National Cancer Institute (log-rank test). High LRRK2 expression in 165 of 329 glioma cases from the REMBRANDT database indicated poor prognosis. (E, F) Upon serum-induced differentiation of 0317 and 448T patient-derived cancer cells, a decrease in phospho-LRRK2 (pLRRK2) and total LRRK2 levels was noted, along with reduced cancer stemness factors (CD133, NESTIN, OLIG2, SOX2), while the differentiation marker glial fibrillary acidic protein (GFAP) increased.

Previous studies have identified that cancer stem cell markers are responsible for developing malignancies in GBM patients. We screened for LRRK2 expression in astrocytes and patient-derived GBM cell lines (Supplementary Fig. S1C). To investigate whether LRRK2 regulates stemness factors in patient-derived cancer cells, we selected the 448T and 0317 cells, which had high levels of phospho-LRRK2 (pLRRK2) and total LRRK2 expression. We then differentiated these cells using serum and observed a gradual decrease in both pLRRK2 and total LRRK2 expression at the mRNA and protein levels (Fig. 1E, 1F, Supplementary Fig. S1D). Additionally, we noted a decrease in cancer stemness factors such as CD133, NESTIN, OLIG2, and SOX2 as the cells underwent serum-induced differentiation. Meanwhile, the differentiation marker glial fibrillary acidic protein (GFAP) increased at both mRNA and protein levels (Fig. 1E, 1F, Supplementary Fig. S1D). Our results suggest that LRRK2 controls the stemness in GSCs, thereby increasing GBM malignancy.

To further validate the functional significance of LRRK2 in maintaining the stemness factor and promoting tumorigenesis, we designed two shRNAs targeting LRRK2. Transduction of shLRRK2 in 0317 and 448T cells has shown decreased pLRRK2 and LRRK2 expression, and stemness factors (CD133, NESTIN, OLIG2, SOX2), while the differentiation marker GFAP was increased (Fig. 2A, 2D). For the 448T cells treated with shLRRK2, one of the clones, specifically 448T-shLRRK2-2, displayed a lesser reduction in LRRK2 expression. Correspondingly, this clone also showed a slightly smaller decrease in cell viability (Fig. 2D). Also, shLRRK2 dramatically reduced stem cell capability and the proliferation of two GSCs (Fig. 2B, 2C, 2E, 2F). Orthotopic mouse models using shLRRK2 448T cells were developed. The shLRRK2 treated mouse models showed a dramatic decrease in tumor size and increase in overall survival (Fig. 2G, 2I). Immunohistochemical experiments have shown a dramatic decrease in the expression of LRRK2 and stemness factors, and increased differentiation marker in shLRRK2 models (Fig. 2H).

Figure 2. Leucine-rich repeat kinase 2 (LRRK2) regulates the stemness and tumorigenesis of glioma stem cells (GSCs). (A) Representative western blot images of phospho-LRRK2 (pLRRK2), LRRK2, stemness factors (CD133, NESTIN, OLIG2, SOX2), and differentiation marker glial fibrillary acidic protein (GFAP) in control 0317 cells (1, 0317-shControl), and two different LRRK2-knockdown 0317 cell lines (2, 0317-shLRRK2-1; 3, 0317-shLRRK2-2). (B) Limiting dilution assays (LDAs) performed using 0317-shControl, 0317-shLRRK2-1, and 0317-shLRRK2-2 cells (**p<0.01, t-test). (C) Cell proliferation assays performed using 0317-shControl, 0317-shLRRK2-1, and 0317-shLRRK2-2 cells. All error bars represent mean±SEM (n=3). **p<0.01, t-test. (D) Representative western blot images of pLRRK2, LRRK2, stemness factors (CD133, NESTIN, OLIG2, SOX2), and differentiation marker GFAP in control 448T cells (1, 448T-shControl), and two different LRRK2-knockdown 448T cell lines (2, 448T-shLRRK2-1; 3, 448T-shLRRK2-2). (E) LDAs performed using 448T-shControl, 448T-shLRRK2-1, and 448T-shLRRK2-2 cells (**p<0.01, t-test). (F) Cell proliferation assays performed using 448T-shControl, 448T-shLRRK2-1, and 448T-shLRRK2-2 cells. All error bars represent mean±SEM (n=3). **p<0.01, t-test. (G) Magnetic resonance imaging images of the whole brains from mice implanted with 448T-shControl, 448T-shLRRK2-1, or 448T-shLRRK2-2 cells. (H) H&E staining of the whole brains from mice implanted with 448T-shControl, 448T-shLRRK2-1, or 448T-shLRRK2-2 cells. Scale bars=100 μm. (I) Kaplan–Meier survival plots for the orthotopic xenograft mouse model (log-rank test). The shLRRK2 treated orthotopic mouse models showed dramatically decrease of tumor size and increase of overall survivals.

In order to test the potential significance of LRRK2 as a therapeutic target, we designed a novel drug, DNK72, which targets the phosphorylation of LRRK2 (Supplementary Fig. S2). We selected 0317 and 448T cells to investigate the function of LRRK2 as they exhibit the highest LRRK2 expression (Fig. 1C). We tested the dose-dependent effect of DNK72 on 0317 and 448T cells, identifying a gradual decrease in pLRRK2 levels as the concentration of DNK72 increased (Fig. 3A, 3B), which led to a significant decrease in cell proliferation (Fig. 3C, 3D). Next, we compared the effect of DNK72 with LRRK2 targeting drugs in clinical trials for Parkinson’s disease treatment, such as PF-06447475, GNE7915, MLi-2, and LRRK2-IN-1, on the inhibition of pLRRK2 levels. We observed that treatment of 1,000 nM of these compounds resulted in similar pLRRK2 inhibition capabilities (Fig. 3E, 3F), while DNK72 slightly outperformed the other compounds in reducing cell proliferation (Fig. 3G, 3H). Since LRRK2 is associated with stemness factors prevalent in tumor microenvironment, we made orthotopic mouse models using 448T cell and treated them with serial doses of DNK72. We observed that the increasing DNK72 up to 60 mg/kg dramatically decreased tumor mass and increased the survival time of the mice. In the orthotopic in vivo model using LRRK2 inhibitors, DNK72 provided the most significant increase in survival time and decrease in tumor volume (Fig. 3I, 3J). DNK72 was administrated at dose of either 10 or 60 mg/kg to the orthotopic mouse models using 448T cells. Here, we noted a decrease in tumor volume with increased DNK72 dosage. LRRK2 and stemness factor expression were decreased, and GFAP was increased as a result of DNK72 treatment (Fig. 4).

Figure 3. The effect of phospho-leucine-rich repeat kinase 2 (pLRRK2) targeting drugs including DNK72 in 0317, 448T glioma stem cells (GSCs) and orthotopic mouse models. (A, B) Representative western blot images of pLRRK2, LRRK2 in two GSCs with different concentrations of DNK72. The pLRRK2 level gradually decreased as the concentration of DNK72 increased. (C, D) Cell proliferation assays performed using two GSCs with different concentrations of DNK72. All error bars represent mean±SEM (n=3). **p<0.01, t-test. (E, F) Representative western blot images of pLRRK2, LRRK2 in two GSCs with different inhibitors of pLRRK2. pLRRK2 targeting drugs in a clinical trial for Parkinson’s disease treatment, PF-06447475, GNE7915, MLi-2, and LRRK2-IN-1, and we compared the effect of these drugs with DNK72 for the inhibition of pLRRK2 level. (G, H) Cell proliferation assays performed using two GSCs with different inhibitors of pLRRK2. All error bars represent mean±SEM (n=3). **p<0.01, t-test. The treatment of 1,000 nM of these compounds gave similar pLRRK2 inhibition capability (E, F), while DNK72 reduced cell proliferation slightly better than other compounds (G, H). (I) Kaplan–Meier survival plots for the orthotopic xenograft mouse model (log-rank test). The shLRRK2 treated orthotopic mouse models showed dramatically decrease of tumor size and increase of overall survivals. (J) H&E staining of the whole brains from mice implanted with 448 cells with different inhibitors of pLRRK2. Scale bars=1 mm.

Figure 4. The immunohistochemical experiment has shown a dramatic decrease in the expression of leucine-rich repeat kinase 2 (LRRK2) and ste-mness factors and increased differentiation marker glial fibrillary acidic protein (GFAP) in DNK72 treated orthotopic mouse models. Scale bars=100 μm.

We performed a GSEA Enrichment assay using LC-MS based global proteome expression data. We found that in LRRK2 positive 448T cells treated with DNK72, LRRK2 protein expression was positively correlated with cancer and cell cycle pathway, RNA-processing associated pathway, and mitochondria-associated pathway. Conversely, LRRK2 protein expression was negatively correlated with FGFR/TP53 pathway (Fig. 5A, Supplementary Table S1). A protein pathway analysis using LC-MS based phosphoproteome data revealed that in LRRK2 positive 448T cells treated with DNK72, phosphosites related to protein localization, cytoskeleton, central nervous system (CNS) development, immune response, cell growth, RNA binding and Ras signaling were significantly reduced. These results suggest that LRRK2 might be involved in regulating stemness through multiple pathways (Fig. 5B, Supplementary Table S2).

Figure 5. Analysis of changes in the proteome and phosphoproteome according to DNK72 treatment in patient derived glioblastoma cells. (A) In the GSEA EnrichmentMap, leucine-rich repeat kinase 2 (LRRK2) protein expression was positively correlated with the cancer and cell cycle pathway, the RNA-processing associated pathway, and the mitochondria-associated pathway. On the other hand, LRRK2 protein expression was negatively correlated with the FGFR/TP53 pathway. (B) The protein pathway analysis showed that treatment of LRRK2-positive 448T cells with DNK72 resulted in a significant decrease in phosphorylation sites involved in various cellular functions, suggesting that LRRK2 may play a role in regulation stemness through multiple pathways. FDR: false discovery rate, NES: normalized enrichment score, CNS: central nervous system.

Our study has shown that LRRK2 was highly expressed in almost 40% of glioma patients, and its expression was directly correlated with the malignancy of the tumor. Unlike mutations in LRRK2, which acts as a direct cause of late-onset Parkinson’s disease, the expression of wild-type LRRK2 functions as a master regulator of stemness in glioma, consequently increasing tumor malignancy and leading to poor patient prognosis.

GBM has long been considered one of the most malignant and incurable tumor types due to its highly complex microenvironment, caused by various stemness factors that orchestrate to form a highly heterogeneous tumor environment. The role of GSCs is a central element in understanding the complexity and treatment resistance of this pathology. GSCs possess self-renewal and differentiation abilities and are known to drive tumor heterogeneity and recurrence within GBM. These cells exhibit significant resistance to traditional therapies, complicating the treatment of GBM. The importance of GSCs in GBM stems from the characteristics exhibited by this cell population. GSCs have high resistance to treatment, often cited as the main cause of relapse after standard therapies. Therefore, targeting GSCs in GBM could be a vital strategy to reduce recurrence and improve overall survival rates.

Furthermore, GSCs interact with the tumor microenvi-ronment to promote tumor growth and invasion. This interaction affects tumor progression and treatment resistance, making the understanding of the interplay between GSCs and the tumor microenvironment crucial for developing GBM treatment strategies. Thus, a deep understanding of the role of GSCs in GBM is essential for improving the management of this disease and developing more effective treatments. Research on GSCs can elucidate the pathological features of GBM and identify potential therapeutic targets. Thus, ongoing research on GSCs in GBM will be key to improving treatment outcomes for this brain tumor.

However, no single treatment has shown a better therapeutic effect compared to conventional temozolomide and radiation therapy. This suggests that therapeutics targeting the master regulator of stemness factors are necessary for the effective treatment of GBM patients. Our results have shown that inhibition of LRRK2 with DNK72 or shRNA transduction successfully decreased LRRK2 expression and stemness factors, suggesting that LRRK2 controls the expression of stemness factors at the upstream level. Furthermore, decreased LRRK2 expression resulted in reduced stem cell capability and proliferation in high LRRK2-ex-pressing GSCs. Orthotopic in vivo models further implied that LRRK2 inhibition in high LRRK2-expressing tumor models was effective not only in decreasing tumor volume and increasing survival time but also in reducing stemness factors, which in turn decreased the malignancy of the tumor. Although similar LRRK2-targeting drugs are available in the market, previous drugs were not suitable for the treatment of GBM due to their low blood-brain barrier penetration. In contrast, our novel DNK72 has shown a better therapeutic effect compared to other LRRK2 inhibitors, thanks to its high blood-brain barrier permeability, making it much more suitable for the treating high LRRK2-expressing GBM.

LRRK2 signaling pathway has acquired significant attention in neurodegenerative disease research, particularly in the Parkinson’s disease. However, recent studies have begun to reveal the role of LRRK2 in cancer biology, reported indications its involvement in GBM as well. LRRK2 overexpression can contribute to increased cell proliferation and resistance to apoptosis, highlighting its impor-tance in GBM pathophysiology (21). Given the aggressive nature of GBM and the limited efficacy of current treatment options, understanding the molecular mechanisms underlying LRRK2’s role in GBM could lead to the development of novel therapeutic strategies. Targeting the LRRK2 signaling pathway in GBM may provide new avenues for treatment, underscoring the need for comprehensive research to explore the full spectrum of LRRK2’s biological functions and its potential as a therapeutic target in GBM.

Unfortunately, this study was not able to identify any other master stemness regulators that control stem cell capability and malignancy in tumor types with low to no LRRK2 expression. Further study is needed to identify the genetic regulations in LRRK2 negative tumor types to better understand the tumor microenvironment in GBM patients.

Our study suggests that in clinical trials, the LRRK2 expression level in glioma patients should be identified, and LRRK2 inhibitors that can penetrate the blood-brain barrier should be administrated to patients with high LRRK2 expression instead of conventional therapeutics to provide a better therapeutic opportunity.

Supplementary data including two tables and two figures can be found with this article online at https://doi.org/10.15283/ijsc24032

There is no potential conflict of interest to declare.

Conceptualization: HGC, JBP, BDL. Data curation: SP, KHK, YHB. Formal analysis: SP, KHK, YHB, YTO, HS, HJK, CIK, SSK. Funding acquisition: JBP. Investigation: SP, KHK, YHB. Methodology: SP, KHK, YHB, YTO, HS, HJK, CIK, SSK. Project administration: HGC, JBP, BDL. Resources: BDL. Software: SP, YTO, KHK, HS. Supervision: HGC, JBP, BDL. Validation: SP, YTO, HJK, CIK, SSK. Visualization: SP, KHK, HS. Writing – original draft: SP, KHK, YHB. Writing – review and editing: HGC, JBP, BDL.

This work was supported by grants NRF-2021R1A2C30 13315, NRF-2021M3F7A1083230 from National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. This work was also supported by the research fund of National Cancer Center Graduate School of Cancer Science and Policy (202100020014).