Photodynamic Therapy in Glioblastoma: Current Insights and Emerging Molecular Targets

Photodynamic Therapy in Glioblastoma: Current Insights and Emerging Molecular Targets

Nazar Vasyliv *1, Oleksandr Tverdokhlib 2, Philip Boughton 3

 

1. Centre for Clinical Brain Sciences, University of Edinburgh, University of Glasgow Affiliate, WWCRC, Scientific CEO, Global Alliance for Neurosurgical & Brain Cancer Research Innovations, Edinburgh, United Kingdom.

2. Research Data Analyst, CFO, Global Alliance for Neurosurgical & Brain Cancer Research Innovations, Edinburgh, United Kingdom.

3. GSI-Lab Head, Sydney Spine Institute, Pharmacy Project Lead Engineer & Research Affiliate, Faculty of Medicine & Health, The University of Sydney, Australia.

 

*Correspondence to: Mr Nazar Vasyliv, MD, MSc, PhD.  N.Vasyliv@sms.ed.ac.uk.


Copyright

© 2025 Mr Nazar Vasyliv, This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: 28 Apr 2025

Published: 02 May 2025

DOI: https://doi.org/10.5281/zenodo.15688054

Abstract

Glioblastoma (GBM), a highly aggressive and treatment-refractory tumour of the central nervous system, remains one of the most difficult cancers to treat. Despite significant advancements in surgery, radiation therapy, and chemotherapy, GBM's inherent resistance mechanisms result in poor prognosis and high recurrence rates. Photodynamic therapy (PDT), a promising treatment strategy based on the activation of photosensitizers with light to generate reactive oxygen species (ROS), offers a potential alternative to conventional therapies. However, its clinical application is constrained by limited light penetration, tumour heterogeneity, and resistance mechanisms. Recent insights into the molecular biology of GBM, particularly the role of ubiquitination and deubiquitination in regulating cellular responses to PDT, have opened new avenues for optimizing treatment efficacy. This review examines the mechanisms underlying PDT-induced cell death, the role of ubiquitination in modulating PDT responses, and the potential for enhancing PDT through novel molecular targets and combination approaches.


Photodynamic Therapy in Glioblastoma: Current Insights and Emerging Molecular Targets

Introduction

Glioblastoma represents one of the most formidable healthcare challenges globally, accounting for approximately 15% of all primary brain tumours and affecting over 200,000 patients annually [1]. Despite advances in understanding the molecular biology of GBM, therapeutic options remain limited, with a median survival of just 12–18 months post-diagnosis. This survival rate has remained largely unchanged for decades, underscoring the urgent need for innovative treatments. Financial investment in GBM research is significantly lower than for other cancers, limiting the ability to develop novel and effective therapies [2]. PDT presents a promising avenue, but several factors, including the blood-brain barrier (BBB), tumour microenvironment, and tumour heterogeneity, hinder its widespread clinical adoption.

Although GBM predominantly affects adults, paediatric GBM presents distinct molecular and clinical features. Paediatric gliomas often exhibit mutations in the p53, IDH1, and H3F3A genes, contributing to their differential response to treatment [3]. Moreover, the tumour microenvironment in paediatric cases is more immunosuppressive, requiring tailored therapeutic approaches. In keeping with pediatric therapeutic best practices and ethical constraints, the PDT approach must be compatible with minimally invasive strategies and avoid leading to serious short-term or long-term complications.

Like photosynthesis, PDT involves the use of light to induce singlet oxygen formation. This singlet oxygen can then lead to the formation of ROS. This photochemical reaction occurs in the presence of porphyrins, vitamins, and other organic and inorganic molecules or agents (Tanaka and Nakamura, 2021).

PDT using porphyrin photosensitizers has demonstrated quantified targeted effectiveness against a range of infective species: bacterial, fungal, biofilm, and cancer cells [4].

PDT has also shown promise in paediatric gliomas due to its ability to specifically target tumour cells with minimal systemic toxicity, but further research is needed to elucidate the unique metabolic and molecular features of paediatric GBM that influence PDT outcomes [5].

PDT offers a targeted approach to GBM by utilizing photosensitizers that preferentially accumulate in tumour cells. Upon light activation, these photosensitizers generate ROS that can induce direct tumour cell death through apoptosis, necrosis, or autophagy [6]. The selective uptake of photosensitizers by tumour cells is influenced by several factors, including the tumour microenvironment, the expression of specific transporters, and metabolic activity [7].

The intrinsic molecular pathways governing PDT-induced tumour cell death are complex, involving not only ROS generation but also a variety of intracellular signalling pathways.

Recent studies have revealed that PDT-induced stress responses are closely linked to the regulation of protein stability via the ubiquitin-proteasome system (UPS) [8]. Ubiquitination, the process by which ubiquitin molecules are covalently attached to target proteins, regulates various cellular processes including cell cycle progression, apoptosis, and DNA repair [9]. In the context of PDT, ubiquitination plays a crucial role in modulating cellular responses to oxidative stress by regulating the degradation of key proteins involved in stress response and cell death pathways.

Ubiquitin-proteasome system dysregulation can affect tumour cell sensitivity to PDT, as certain anti-apoptotic proteins may evade degradation, promoting tumour survival even after PDT-induced damage.

Deubiquitinating enzymes (DUBs), which remove ubiquitin chains from target proteins, also modulate the cellular response to PDT. DUBs such as USP7 and USP9X have been shown to stabilize pro-survival proteins like p53 and Bcl-2, thereby enhancing resistance to PDT-induced cell death [10]. These findings highlight the potential for targeting the UPS and DUBs to enhance PDT efficacy and overcome resistance mechanisms in GBM.

 

Table 1. PDT Photosensitizers and Selectivity Enhancement

Photosensitizer

Mechanism of Selectivity

Target Tumour Cell Type

Challenges

References

5-Aminolevulinic Acid (5-ALA)

Metabolized to protoporphyrin IX (PpIX) in tumour cells, preferentially accumulating in GBM cells

Tumour cells with high metabolic activity and altered porphyrin biosynthesis

Limited depth of light penetration in solid tumours

Dougherty et al., 1998 [10]; Stummer et al., 2000 [11]

Photofrin

Accumulates in tumour vasculature, leading to vascular disruption and tumour necrosis

Tumour vasculature and endothelial cells

Suboptimal distribution in deeper tumour regions

Kessel et al., 2008 [12]; Ribeiro et al., 2015 [13]

Verteporfin

Targets tumour endothelial cells and macrophages, causing vascular damage

Endothelial cells and macrophages in the tumour microenvironment

Limited BBB penetration, requires specific light delivery systems

Nishimura et al., 2008 [14]; Baginski et al., 2014 [15]

Talaporfin  Sodium

Selectively accumulates in hypoxic regions of tumours, including GBM

Hypoxic regions of GBM

Requires optimization for hypoxic targeting

Watanabe et al., 2015 [16]; Nakajima et al., 2014 [17]

 

In Vitro, In Silico, and Preclinical Models for PDT Evaluation in Glioblastoma

The development and refinement of PDT for GBM demand comprehensive preclinical and clinical evaluation. In vitro, in silico, and preclinical animal models are essential for understanding the molecular mechanisms underlying PDT-induced cell death, identifying predictive biomarkers, and optimizing therapeutic strategies. These models allow for investigation into how PDT interacts with the complex molecular machinery of GBM cells, particularly the role of the ubiquitin-proteasome system (UPS) and deubiquitinating enzymes (DUBs), which regulate essential cell survival and death pathways. By targeting these mechanisms, it is possible to sensitize GBM cells to PDT and improve therapeutic outcomes.

In Vitro Models for PDT Evaluation in GBM

In vitro cell culture models, particularly using GBM cell lines such as U87MG and T98G, provide controlled environments to study PDT at the molecular level. These models allow for detailed investigation of PDT-induced cytotoxicity, the generation of ROS, and the subsequent activation of key intracellular signaling pathways, such as apoptosis, autophagy, and necroptosis.

 

Molecular Mechanisms of PDT in GBM

PDT relies on the accumulation of photosensitizers within tumour cells and their activation by light to generate ROS. These ROS cause cellular damage by modifying key macromolecules, including lipids, proteins, and DNA. At the molecular level, PDT-induced oxidative stress triggers several key pathways, including:

 

Table 2. Key Molecular Targets Influencing PDT Efficacy in GBM

Molecular Target

Role in PDT Response

Regulatory Mechanism

Potential Therapeutic Strategy

References

p53

Apoptosis regulation

Ubiquitination by MDM2

MDM2 inhibitors (e.g., Nutlin-3) to restore p53 function

[18], [31]

Bcl-2

Anti-apoptotic protein

Stabilized by USP9X

USP9X inhibitors to destabilize Bcl-2

[9], [24]

RIPK1/RIPK3

Necroptosis activation

Ubiquitinated and regulated by DUBs

Promote necroptosis via DUB inhibition

[21], [37]

ATM/ATR

DNA damage response

Ubiquitin-modulated activity

UPS inhibitors to impair DDR and enhance PDT

[20], [32]

c-Myc

Cell proliferation and survival

Regulated by SCF^βTrCP E3 ligase

Inhibit SCF^βTrCP or enhance degradation

[22]


Apoptosis: ROS activate the intrinsic mitochondrial pathway, leading to the release of pro-apoptotic factors like cytochrome c and the activation of caspases. A central regulator of apoptosis is p53, a tumour suppressor protein that is frequently mutated in GBM. Ubiquitination of p53 plays a critical role in its stability and function. Upon PDT, the UPS can facilitate the degradation of mutated or damaged p53, contributing to tumour resistance. Inhibition of E3 ubiquitin ligases such as MDM2, which promote p53 degradation, could enhance p53-mediated apoptosis in GBM cells post-PDT [18]. Disruption of p53's ubiquitination could help overcome PDT resistance mechanisms in GBM.

Autophagy: In response to ROS, GBM cells may initiate autophagy as a protective mechanism. Autophagy is regulated by several key molecular pathways, including the mTOR pathway, and involves the degradation of cellular components in lysosomes. Ubiquitination plays a role in tagging autophagic substrates for degradation. Proteins such as p62/SQSTM1 are often stabilized by ubiquitination during PDT, facilitating autophagy in GBM cells. This survival mechanism can be targeted to sensitize GBM cells to PDT-induced death [19]. Ubiquitin-protein conjugates can be manipulated to optimize autophagic flux and enhance PDT efficacy.

DNA Repair: ROS generated during PDT induce DNA damage, which triggers the DNA damage response (DDR). Proteins such as ATM, ATR, and DNA-PKcs are regulated by ubiquitination to modulate their stability and activity. In GBM, inhibiting DDR pathways could enhance PDT efficacy by preventing the repair of PDT-induced DNA lesions. DUBs such as USP1 and USP7 regulate the stability of DDR proteins, influencing their ability to repair PDT-induced DNA damage [20]. Targeting the UPS to prevent the degradation of DDR proteins could potentiate the efficacy of PDT.

Necroptosis: PDT can trigger necroptosis, a form of programmed necrosis regulated by the RIPK1/RIPK3/MLKL pathway. The role of ubiquitination in necroptosis regulation is becoming increasingly significant. RIPK1undergoes ubiquitination by various E3 ligases, which modulate its interaction with downstream signaling molecules such as RIPK3 and MLKL. Inhibition of DUBs, which remove ubiquitin chains, can enhance necroptosis and promote GBM cell death following PDT [21]. Manipulating ubiquitin conjugation pathways offers a novel strategy to enhance PDT efficacy in GBM treatment.

These molecular insights emphasize the central role of ubiquitination and DUBs in modulating the cellular response to PDT. Targeting these pathways can optimize PDT efficacy in GBM by overcoming resistance mechanisms and enhancing therapeutic outcomes.

 

In Silico Models for PDT Evaluation in GBM

In silico models, which use computational simulations to predict tumour responses to PDT, have become critical in optimizing treatment parameters and predicting therapeutic outcomes. These models incorporate the complexities of light penetration, photosensitizer distribution, and the cellular molecular responses to PDT.

 

Modeling PDT-Induced Molecular Pathways

Computational models enable researchers to simulate interactions between PDT-induced ROS and the molecular machinery of GBM cells. Specifically, these models simulate how the ubiquitin-proteasome system (UPS) regulates the degradation of proteins involved in cell cycle progression, DNA repair, and apoptosis. In the context of PDT, computational approaches can predict how changes in ubiquitin ligase activity, such as inhibition of MDM2 or SCFβTrCP, may influence the stability of proteins like p53 and c-Myc, which play critical roles in GBM cell survival [22]. By incorporating these molecular dynamics, in silico models help identify treatment strategies that enhance PDT's efficacy.

Additionally, these computational models can simulate the effects of DUB inhibition on GBM cell survival post-PDT. For example, inhibiting USP7, a DUB that stabilizes pro-survival proteins such as p53 and MDM2, could enhance PDT efficacy by promoting the degradation of these proteins [23]. These models provide a rationale for combining PDT with inhibitors targeting the UPS and DUBs to improve therapeutic outcomes in clinical settings.

 

Preclinical Animal Models for PDT Evaluation in GBM

Preclinical animal models, particularly orthotopic GBM mouse models, are essential for evaluating the in vivo efficacy of PDT. These models closely replicate the complex tumour microenvironment of GBM, including the blood-brain barrier (BBB), tumour vasculature, and hypoxic regions, all of which influence PDT treatment outcomes.

 

Role of the UPS and DUBs in Preclinical Models

In preclinical animal studies, the role of the UPS and DUBs in modulating PDT responses is increasingly recognized. For example, animal models have shown that proteasome inhibition with agents like bortezomib can increase tumour cell sensitivity to PDT by preventing the degradation of pro-apoptotic proteins. Conversely, targeting DUBs such as USP9X, which stabilize anti-apoptotic proteins like Bcl-2, can sensitize GBM cells to PDT-induced death by promoting the degradation of survival proteins [24].

Table 3. Overview of Deubiquitinating Enzymes (DUBs) in PDT Resistance

DUB

Target Protein(s)

Function in PDT

Inhibition Outcome

References

USP7

p53, MDM2

Stabilizes pro-survival proteins

Enhances PDT-induced apoptosis

[9], [23]

USP9X

Bcl-2

Promotes resistance to apoptosis

Sensitizes GBM cells to PDT

[9], [24]

USP1

DNA repair proteins

Maintains DDR signaling

Increases DNA damage post-PDT

[20]

CYLD

RIPK1

Regulates necroptosis threshold

Promotes necroptosis

[21]

 

In preclinical models, light delivery systems are optimized to overcome the challenge of light penetration in deep-seated tumours. Advanced techniques, such as fiber-optic probes and endoscopic systems, allow for precise delivery of light to the tumour site, ensuring adequate ROS generation to induce tumour cell death. Combining PDT with UPS-targeting agents may enhance therapeutic responses by promoting apoptosis and autophagy in GBM cells [25, 26]. Moreover, nanoparticle-based drug delivery systems are being explored to overcome the BBB, improving photosensitizer accumulation in GBM and enhancing PDT efficacy [27, 28].

 

Selective Illumination and the Physics of PDT Application

Efficient light delivery is a key factor in the success of PDT, particularly for tumours located in deep-seated brain regions. The limited penetration of light in tissues, especially for deeply located GBM tumours, requires innovative approaches in light delivery. The use of fiber-optic probes, endoscopic systems, and implantable devices can help overcome this limitation [29]. Furthermore, optimizing the wavelength of light is essential for ensuring that the photosensitizers are effectively activated. Near-infrared (NIR) light, which penetrates more deeply into tissues, has been shown to be particularly effective for PDT in deep-seated brain tumours [30].

The role of the UPS in regulating PDT-induced tumour cell death is increasingly recognized. Proteins involved in DNA repair, apoptosis, and oxidative stress response are tightly controlled by ubiquitination. For example, the stabilization of the tumour suppressor p53 through inhibition of its ubiquitination can enhance the apoptotic response to PDT [31]. Additionally, the removal of ubiquitin chains by DUBs can prevent the degradation of key pro-survival proteins, leading to increased resistance to PDT. Therefore, targeting the UPS and DUBs in combination with PDT could improve treatment outcomes by preventing resistance mechanisms and enhancing the tumour’s susceptibility to oxidative stress [32].

 

Optimizing PDT Dose and Delivery

The optimization of PDT involves carefully balancing light dose, photosensitizer concentration, and treatment timing to maximize tumour cell death while minimizing damage to healthy tissue. Advances in PDT optimization include the use of fractionated doses of light or photosensitizers, as well as the timing of light exposure relative to circadian rhythms, which influence the cellular response to PDT [33]. Furthermore, combining PDT with inhibitors of the UPS, such as proteasome inhibitors or DUB inhibitors, can help sensitize tumour cells to PDT-induced cell death by modulating protein degradation and apoptosis pathways [34].


Table 4. Wavelength-Dependent Optimization of Light Delivery in PDT for Glioblastoma

Wavelength Range (nm)

Light Type

Tissue Penetration Depth

Compatible Photosensitizers

Clinical Advantages

Limitations

References

400–450

Violet–Blue

<1 mm

None widely used for deep tumors

Strong PS activation

Limited penetration

[29]

630–635

Red (standard PDT)

2–5 mm

Photofrin, 5-ALA (PpIX)

Widely used, FDA-approved for other cancers

Suboptimal for deep brain tumors

[11], [12], [30]

650–690

Deep Red

5–10 mm

Talaporfin sodium, Verteporfin

Better depth, used in Japan for GBM trials

Requires precise light dosing

[14], [16], [17]

700–800

Near-Infrared (NIR-I)

Up to 20 mm

Indocyanine green, NIR dyes

Excellent depth, minimal scattering

Lower energy photons, lower ROS generation

[30], [27], [29]

800–900

Near-Infrared (NIR-II)

20–30 mm

Experimental NIR-II PSs

Potential for non-invasive deep brain access

Mostly preclinical, unapproved PSs

[30], emerging data

 

The circadian regulation of the UPS and cell cycle is particularly relevant in optimizing PDT. Studies have shown that the cellular response to PDT, including DNA repair and apoptosis, is influenced by the time of day [35]. By synchronizing PDT treatment with the natural circadian rhythm, it may be possible to enhance the efficacy of PDT and improve clinical outcomes [36].

 

Targeting Necroptosis and mediated cell-death pathways in GBM Post-PDT

Necroptosis, a regulated form of cell death, is emerging as a critical pathway in GBM’s response to PDT. Unlike apoptosis, necroptosis is initiated when apoptosis is blocked, and is often driven by receptor-interacting protein kinases (RIPKs), particularly RIPK1, RIPK3, and MLKL (Nazar Vasyliv, 2024, MAR). Ubiquitination plays a central role in regulating necroptosis, with RIPK1 and RIPK3 being substrates for ubiquitination and deubiquitination. By inhibiting DUBs such as USP7, which stabilize anti-apoptotic proteins, it may be possible to promote necroptosis in GBM stem cells and enhance the effectiveness of PDT [37]. This approach could provide an alternative form of cell death when apoptosis pathways are compromised in GBM.

Despite promising results from in vitro, in silico, and preclinical models, the clinical translation of PDT for GBM remains challenging. Key issues include limited light penetration in solid tumours and the heterogeneity of the tumour microenvironment. The BBB also presents a major obstacle for delivering photosensitizers to GBM cells. Recent advances in nanoparticle-based delivery systems are addressing these barriers by improving photosensitizer uptake in GBM cells.

Understanding the role of circadian rhythms in regulating cellular responses to PDT is another emerging area of interest. In vivo studies have shown that the timing of PDT can influence its efficacy, as circadian regulation of the UPS affects cellular sensitivity to ROS. Targeting the circadian clock and its influence on the UPS could synchronize treatment with peak tumour cell sensitivity, thus enhancing PDT outcomes [38].

 

Research Ethics and Conflict of Interest Statement

The authors affirm that the research was conducted in accordance with the highest ethical standards and institutional guidelines. No conflicts of interest, financial or otherwise, are declared by any of the authors. All authors contributed independently and impartially to the conception, design, and execution of the study.

 

References

1. Ostrom, Q. T., Cioffi, G., Gittleman, H., & Liao, P. (2019). The epidemiology of glioblastoma. In: Glioblastoma: Molecular Mechanisms of Resistance and Therapy. Springer, Cham.

2. Reardon, D. A., & Wen, P. Y. (2016). Glioblastoma: molecular mechanisms of resistance and therapy. Seminars in Oncology, 43(1), 29-39.

3. Penas-Prado, M., & Macdonald, D. R. (2016). Pediatric gliomas: molecular and clinical features. Journal of Clinical Oncology, 34(10), 2173-2181.

4. Poon, W., & Chuang, S. (2019). Pediatric gliomas and photodynamic therapy: Insights into targeted therapeutic approaches. Journal of Neurosurgery Pediatrics, 24(2), 120-127.

5. Dougherty, T. J., Gomer, C. J., Henderson, B. W., et al. (1998). Photodynamic therapy. Journal of the National Cancer Institute, 90(12), 889-905.

6. Hamblin, M. R., & Hasan, T. (2004). Photodynamic therapy: a new antimicrobial approach to infectious disease. Photochemistry and Photobiology, 80(4), 727-739.

7. Tanaka, T., & Nakamura, T. (2021). Molecular mechanisms and regulation of PDT-induced oxidative stress in glioblastoma cells. Cell Death and Disease, 12(1), 47.

8. Clague, M. J., & Urbé, S. (2010). Ubiquitin and ubiquitin-like proteins as regulators of cell signalling. Nature Reviews Molecular Cell Biology, 11(9), 621-633.

 

9. Suresh, S., & Gandhi, S. (2018). The role of deubiquitinating enzymes in photodynamic therapy response. Oncogene, 37(22), 2891-2901.

10. Ghosh, D., & Zhao, Z. (2020). The impact of ubiquitination on cellular survival pathways following PDT in glioblastoma. Journal of Cancer Research and Clinical Oncology, 146(4), 1017-1026.

11. Xu, Y., & Zhao, J. (2017). Deubiquitinating enzymes: molecular regulation and role in the response to oxidative stress in glioblastoma. Cellular and Molecular Life Sciences, 74(15), 2679-2689.

12. He, F., & Chiu, J. (2019). Proteasomal regulation of glioblastoma cell responses to PDT-induced oxidative stress. Frontiers in Neuroscience, 13, 667.

13. Zhu, L., & Zhang, H. (2019). Autophagy as a modulator of photodynamic therapy response in glioblastoma. Cell Death and Disease, 10(6), 341.

14. Lee, H., & Liao, Y. (2019). Ubiquitination of pro-apoptotic proteins in photodynamic therapy and their relevance to glioblastoma treatment. Journal of Biomedical Science, 26(1), 59.

15. Lee, M., & Lee, S. (2018). Autophagy in the regulation of cell death in response to photodynamic therapy. Journal of Cancer Research and Therapy, 14(4), 789-794.

16. Mueller, W. M., & Kihara, Y. (2020). Ubiquitin-proteasome system in photodynamic therapy. Oncology Reports, 43(4), 1150-1158.

17. Schmitz, M., & Bhat, N. (2021). Inhibition of the UPS enhances the sensitivity of glioblastoma cells to PDT. Journal of Experimental & Clinical Cancer Research, 40(1), 133.

18. Lee, Y., & Cheung, S. (2022). PDT-induced ubiquitination and its role in resistance mechanisms in GBM. Cancer Letters, 513, 56-64.

19. Biswas, D., & Khatun, A. (2020). The role of autophagy in photodynamic therapy in glioblastoma. Autophagy, 16(5), 945-959.

20. Zou, L., & Wang, C. (2021). DNA damage and repair mechanisms in glioblastoma: implications for PDT treatment. Nature Reviews Neurology, 17(1), 12-23.

21. Salas, E., & Deng, J. (2021). Necroptosis as a form of regulated cell death following PDT in glioblastoma. Cellular and Molecular Life Sciences, 78(14), 589-597.

22. Brown, T., & Lin, X. (2020). Computational modeling of PDT-induced molecular mechanisms in glioblastoma cells. Journal of Theoretical Biology, 497, 110280.

23. Oh, S., & Wang, Z. (2022). Targeting USP7 to enhance PDT efficacy in glioblastoma. Frontiers in Oncology, 12, 734328.

24. Patel, S., & Dagar, R. (2020). Targeting deubiquitinating enzymes to overcome resistance in glioblastoma photodynamic therapy. Cell Death & Disease, 11(4), 342.

25. Liao, L., & Pan, Y. (2019). Nanoparticle-based delivery systems for photodynamic therapy in glioblastoma treatment. Biomaterials Science, 7(5), 1589-1603.

26. Fang, X., & He, J. (2020). Overcoming the blood-brain barrier with nanoparticles to improve PDT in glioblastoma. Journal of Nanobiotechnology, 18(1), 65.

27. Yang, Z., & Li, W. (2021). Preclinical evaluation of photodynamic therapy in glioblastoma using orthotopic mouse models. Neuro-Oncology, 23(3), 379-389.

28. Xu, X., & Fu, Z. (2022). Proteasome inhibitors as adjuncts to photodynamic therapy for glioblastoma in preclinical models. Oncology Research, 30(7), 519-531.

29. Lee, A., & Kim, K. (2020). Strategies to enhance light delivery in PDT for glioblastoma. Photochemotherapy, 45(6), 1173-1181.

30. Mody, S., & Gupta, N. (2020). Near-infrared light as a promising approach for PDT in glioblastoma treatment. Journal of Neurosurgery, 133(4), 987-993.

31. Geng, W., & Liu, C. (2021). Targeting p53 in glioblastoma through proteasomal regulation for enhanced PDT efficacy. Oncotarget, 12(7), 680-694.

32. Zhang, H., & Wang, X. (2022). Enhancing PDT response in glioblastoma by inhibiting deubiquitinating enzymes. Cancer Research and Therapy, 33(4), 225-234.

33. Zhang, L., & Liu, M. (2019). Optimization of photodynamic therapy by adjusting light dose and timing. Journal of Experimental & Clinical Cancer Research, 38(1), 195.

34. Wang, J., & Zhang, X. (2021). Combination of PDT with proteasome and deubiquitinating enzyme inhibitors for glioblastoma treatment. Molecular Cancer Therapy, 20(3), 642-651.

35. Chen, X., & Zhao, H. (2021). Circadian rhythm in glioblastoma and its impact on PDT response. Photobiology and Photomedicine, 28(2), 143-155.

36. Zhao, Y., & Zhou, X. (2022). Circadian regulation of PDT-induced oxidative stress in glioblastoma cells. Journal of Biological Rhythms, 37(2), 167-176.

37. Vasyliv, N. (2024). Targeting Glioblastoma: Inducing Necroptosis Molecular Pathway Post-Photodynamic Therapy for Enhanced Neurosurgical and Therapeutic Outcomes /MAR/ https://doi.org/10.13140/RG.2.2.28609.98400

38. Gong, S., & Chen, Y. (2021). Targeting necroptosis to enhance the efficacy of PDT in glioblastoma. Cancer Cell International, 21(1), 105.

antarmuka fokus mahjong daya pengguna aktifaws grid serasi mahjong dasar tahapan terjagaaws jejak mekanisme mahjong arah fase lanjutanaws kajian wild berantai mahjong interaktif analitisaws kesesuaian persentase layanan mahjong seluler lanceraws pendalaman persentase mahjong gerak wild mutakhircorak langka mahjong tumbuh perlahan berubahgerak mahjong adaptasi mekanisme pemakai sekarangnalar scatter mahjong malam putaran ekstratempo mahjong kaitan mekanisme keadaan terkinialur permainan mahjong cepat scatter wilddalam hitungan detik scatter wild mahjongmenyatukan naluri pola scatter hitam mahjongmomen mahjong permainan berbalik arahmomen singkat mahjong dinamika permainanperpaduan insting pola scatter hitam momentperubahan drastis mahjong ways scatter wildscatter wild mahjong datang polasekejap berubah scatter wild mahjong wayssensasi baru mahjong lebih scatter wildenergi scatter emas irama reel mahjongevolusi reel mahjong balutan mistisintervensi cepat emas momentum lamakemunculan mendadak naga emas mahjongketika scatter naga emas aktif mahjongnaga emas muncul arah spin mahjongnaga emas ritme mahjong ways berubahrahasia rtp tinggi balik scatter hitamsaat scatter naga emas alih irama reelscatter hitam kunci lonjakan rtp mahjonge5 scatter wild memberikan sentuhan baru di setiap spin mahjong ways 2e5 scatter wild menghidupkan suasana permainan mahjong ways 2e5 scatter wild mengubah pola permainan mahjong ways 2 secara signifikane5 setiap putaran mahjong ways 2 terasa berbeda dengan scatter wilde5 strategi adaptif berbasis analisis rtp hariane5 strategi berbasis data dan algoritma untuk analisis momentume5 strategi berkembang berkat data rtp hariane5 strategi memahami algoritma untuk mengidentifikasi momentum ideale5 strategi membaca pola algoritma demi menangkap momentum optimale5 strategi modern mengandalkan evaluasi rtp hariane5 strategi responsif dengan dukungan evaluasi rtp hariane5 strategi terukur dengan analisis rtp hariane5 struktur scatter dan wild terlihat jelas berkat analisis sistem moderne5 tanpa disadari kombinasi ini sering mengarah ke scatter di mahjong wins 3e5 teknik evaluasi algoritma untuk mendapatkan momentum yang tepate5 teknik observasi sistem untuk analisis momentum yang lebih presisie5 terungkap formasi ini sering jadi awal munculnya scatter di mahjong wins 3e5 transformasi digital rtp live berkat artificial intelligence inovatife5 transformasi ritme mahjong ways 2 dipicu oleh kekuatan scatter wilde5 wajib tahu pola tersembunyi ini sering menghasilkan scattere5 applee5 bananae5 candye5 doge5 eaglee5 falcone5 geminie5 horsee5 indiae5 japananalisa pola mahjong ways rutinanalisis kinerja heuristik variansi gameanalisis pola mahjong ways hariananalisis pola mahjong ways kebiasaanera baru mahjong wins bonus optimalgebrakan bonus mahjong wins mekanisme efisieninsight pola mahjong ways rutinkajian pola mahjong ways rutinkomparasi heuristik variansi game digitalledakan bonus mahjong wins sistem efektifmahjong wins bonus sistem generasi baruobservasi pola mahjong ways harianpendekatan algoritma heuristik variansi gameperbandingan model heuristik variansi gamerahasia bonus mahjong wins sistem cerdasrangkuman pola mahjong ways harianringkasan pola mahjong ways harianstudi pola mahjong ways hariantinjauan heuristik variansi game digitaltinjauan pola mahjong ways harianalur sombol mahjong kemunculan scatterdari rtp mahjong bermain lebih efektifjejak scatter mahjong putaran tenangkejutan scatter wild simbol mahjong arahkemunculan simbol ganda membuat mahjongketika grid mahjong scatter semakin dekatketika rtp mahjong pola mulai lebih jelasketika scatter wild ritme simbol mahjongketika scatter wild titik sesi mahjong waysketika susunan simbol mahjong ritme scattermemahami rtp mahjong cara bermain lebihpergerakan simbol mahjong scatter wildpergeseran mahjong ketika scatter hadirsaat rtp mahjong terbaca baik strategisaat scatter hadir simbol mahjong bergeserscatter wild dinamika simbol mahjongstabilitas putaran mahjong pola scattersusunan baru reel mahjong scatter emassusunan mahjong wins mengandung scattersusunan simbol mahjong diam pola scatterrm menguak keunikan mahjong wins sudut pandang teknisrm cara memahami pergerakan mahjong ways tenaga ekstrarm mahjong wins standar baru industri hiburan digitalrm rahasia ketahanan mahjong ways eksis gempuran gamerm pentingnya memahami transisi level mahjong wins mendalamrm strategi mengatur tempo mahjong ways kendali permainanrm peran kecerdasan buatan mekanisme mahjong wins adilrm alasan keberhasilan mahjong ways mencuri perhatian analisrm mempelajari struktur dasar mahjong wins efisiensi putaranrm inovasi desain mahjong ways kesan bermain responsifrm teknik observasi mahjong wins jarang dibahas dampakrm cara mempertahankan fokus dinamika mahjong ways cepatrm eksplorasi fitur tersembunyi mahjong wins ritme terbaikrm mahjong ways integrasi teknologi modern keamanan nyamanrm analisis faktor pendukung mahjong wins digemari generasirm langkah efektif menyesuaikan perubahan sistem mahjong waysrm mengintip proses pengembangan mahjong wins kualitas penggunarm analisis data membantu membaca arah mahjong waysrm menemukan titik temu insting logika mahjong winsrm transformasi besar mahjong ways menghadirkan tantangan menarikmengungkap simbol langka nasib drastismisteri besar kombinasi simbol langkamisteri simbol langka keberuntungan besarsimbol langka misterius ubah hiduprahasia simbol langka nasib cepattransformasi bonus mahjong wins sistem efektifmahjong wins suguhkan bonus sistem modernsuguhan bonus efisien mahjong winsefektivitas sistem bonus mahjong winsmahjong wins hadirkan bonus sistem optimaloke76cincinbetaqua365slot gacorstc76samurai76TOBA1131samurai76 login