Abstract
Abstract
Intrinsic and acquired resistance to temozolomide (TMZ), the standard chemotherapeutic agent for glioblastoma (GBM), is highly common and results in poor clinical outcomes. This review highlights the emerging dual role of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein (Cas) technologies in addressing this challenge. First, it examines genome-wide CRISPR screens that revealed DNA damage repair networks, stress adaptations, stemness maintenance, and tumor heterogeneity as key drivers of resistance to TMZ. Second, it examines CRISPR/Cas-based strategies, including targeted gene disruption and epigenetic silencing of O6-methylguanine-DNA methyltransferase (MGMT), to restore TMZ sensitivity. Finally, it explores CRISPR/Cas-engineered brain tumor models. Alongside these approaches, CRISPR/Cas technologies highlight the value of decoding the multifactorial basis of TMZ resistance and guiding rational therapeutic strategies. Continued refinement of CRISPR/Cas tools may ultimately contribute to more effective treatments for GBM.
Graphical Abstract

Supplementary Information
The online version contains supplementary material available at 10.1007/s40291-026-00864-3.
Key Points
| CRISPR/Cas-based screening technologies have successfully transitioned (GBM) research from descriptive sequencing to functional genomic mapping, highlighting DNA damage repair, stress adaptation, stemness maintenance, and tumor heterogeneity as key drivers of TMZ resistance and revealing pharmacologically actionable targets for rational combination therapy. |
| Emerging CRISPR/Cas therapeutic strategies, including targeted gene disruption and epigenetic MGMT silencing, demonstrate preclinical efficacy in reversing both MGMT-dependent and MGMT-independent TMZ chemoresistance. |
| CRISPR-engineered brain tumor models provide genetically precise, immunocompetent, and cell-type-specific platforms that more faithfully recapitulate microenvironmental complexity and treatment-relevant resistance phenotypes, representing an important step toward translationally relevant preclinical validation of novel therapeutic strategies. |
Current Challenges in Temozolomide Therapy and Opportunities for CRISPR/Cas Systems
Brain tumors of the central nervous system represent the 19th most common cancer worldwide, yet they rank as the 12th leading cause of cancer-related mortality, highlighting their disproportionate lethality [1]. Among them, glioblastoma (GBM), a grade 4 adult-type diffuse glioma, is the most prevalent and aggressive primary brain tumor in adults, with a median overall survival of only 12–15 months [2, 3]. Its poor prognosis is driven by marked intratumoral heterogeneity, highly invasive growth, and the challenge of delivering therapeutic agents across the blood–brain barrier (BBB), all of which limit the effectiveness of both existing and emerging treatments [4, 5]. Despite decades of research, the current standard-of-care therapy, termed the Stüpp protocol, which includes surgical resection, followed by radiotherapy and the chemotherapeutic agent temozolomide (TMZ), has remained largely unchanged for nearly 20 years [6–8]. However, more than half of patients with GBM exhibit intrinsic or acquired resistance to TMZ, driven by complex and multifactorial molecular mechanisms that lead to tumor persistence, recurrence, and treatment failure [9]. Accordingly, strategies to understand and overcome TMZ resistance remain a central research priority in GBM [10].
The 2020 Nobel Prize-winning Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein (Cas) has rapidly become one of the most powerful genetic engineering tools available [11]. Essentially, a programmable guide RNA (gRNA) directs the Cas9 nuclease to a specific DNA sequence, enabling precise DNA double-strand breaks at targeted locations (Fig. S1 of the Electronic Supplementary Material [ESM]). Following cleavage, the cell can repair the break via non-homologous end joining, often leading to insertion-deletion mutations that disrupt the gene, or via homology-directed repair, in which a supplied DNA template guides accurate genome editing [12, 13].
More recently, next-generation CRISPR/Cas systems have expanded the scope of genome manipulation, allowing epigenetic regulation and transcriptional control. In the context of brain tumors, CRISPR/Cas technologies have been applied not only as therapeutic tools but also as innovative research platforms to uncover mechanisms of TMZ resistance and to develop CRISPR/Cas-based co-treatment strategies to restore drug sensitivity. Importantly, although several alternative approaches have also been investigated for overcoming TMZ resistance, including small-molecule inhibitors and RNA interference, this review specifically prioritizes the unique contributions of programmable CRISPR/Cas-based platforms [14–18]. This emphasis reflects their ability to support both mechanistic discovery and targeted intervention at scale. Additionally, the limited availability of physiologically relevant brain tumor models has prompted the use of CRISPR/Cas to engineer biomimetic tumor models that better recapitulate human disease [19]. Notably, despite extensive research, the contribution of CRISPR/Cas technologies to mapping, modulating, and modeling TMZ resistance has not yet been systematically reviewed. Therefore, this review addresses three approaches: (i) CRISPR/Cas-based screens to identify TMZ resistance mechanisms; (ii) CRISPR/Cas-mediated strategies to enhance TMZ sensitivity; and (iii) CRISPR/Cas-engineered tumor models that show translational relevance.
Methods
A targeted literature search was performed on 18 May, 2026, on PubMed and Scopus databases. The following search equation was applied: (“Organoids” OR “Disease Models, Animal” OR “Temozolomide”) AND “CRISPR/Cas Systems” AND “Brain Neoplasms”. Medical Subject Heading (MeSH) terms were used in PubMed to ensure precision. To capture recent advances, only English-language studies were selected to examine the evolving functions of CRISPR/Cas systems. This initial search identified 74 publications. After removing duplicates, 44 records were screened according to predefined inclusion and exclusion criteria (Table S1 of the ESM), resulting in 20 eligible publications. Reference lists of the included studies were also examined, identifying three additional relevant publications; one record was excluded because of inaccessibility to the full text. In total, 22 papers were included in this review and grouped in three sections: decoding TMZ resistance (n = 10), restoring TMZ sensitivity (n = 6), and CRISPR/Cas-based brain tumor models (n = 6). The study selection process is illustrated in Fig. S2 of the ESM (PRISMA flow diagram).
Temozolomide: Mechanism and Resistance
Temozolomide, also known as 3-methyl-4-oxoimidazo[5,1-d][1,2,3,5]tetrazine-8-carboxamide and Temodal®, is an oral alkylating agent approved for the treatment of GBM and other cancers [20, 21]. Its lipophilic nature allows TMZ to readily cross the BBB and enter tumor cells. Under physiological pH, TMZ is spontaneously converted into monomethyl triazeno imidazole carboxamide (MTIC, 5-(3-methyltriazen-1-yl) imidazole-4-carboxamide), which subsequently decomposes to release AIC (5-aminoimidazole-4-carboxamide) and the methyldiazonium cation (MC). The latter represents a highly reactive metabolite that methylates DNA bases, primarily at N7 or O6 of guanine and N3 of adenine, generating mismatches during DNA replication [9].
Cells counteract these errors through DNA repair pathways: O6-methylguanine-DNA methyltransferase (MGMT) directly removes O6-methyl groups from guanine, restoring accurate base pairing, while the base excision repair system recognizes N7-methylguanine and N3-methyladenine lesions and replaces them with the correct bases. If mutations persist, the mismatch repair (MMR) system detects mispaired nucleotides, excises the newly synthesized DNA strand, and triggers cell-cycle arrest and apoptosis [7, 22]. Figure 1 represents an overview of the TMZ mechanism and MGMT-mediated and base excision repair-mediated resistance.
Fig. 1.

Overview of the temozolomide (TMZ) mechanism and O6-methylguanine-DNA methyltransferase (MGMT)-mediated resistance. (A) In tumor cells, TMZ is converted to the intermediate monomethyl triazenoimidazole carboxamide (MTIC), which rapidly decomposes into an inactive compound, releasing 5-aminoimidazole-4-carboxamide (AIC) and methyldiazonium cation (MC). (B) The reactive ion methylates DNA, specifically at the N7 or O6 of guanine and N3 of adenine. The resulting lesions are recognized by the mismatch repair machinery, triggering DNA strand breaks and ultimately leading to apoptosis. However, the DNA repair enzymes base excision repair (BER) and MGMT can remove the methyl group from methyladenine and methylguanine, counteracting the cytotoxic effect of TMZ and promoting tumor cell survival and proliferation. Created with ChemDraw and BioRender.com
While MGMT overexpression remains the best-characterized mechanism of TMZ resistance, MGMT-independent pathways also limit drug efficacy. These include enhanced drug efflux, activation of survival autophagy, dysregulation of microRNAs, particularly overexpression of oncogenic microRNAs and downregulation of tumor-suppressor microRNAs, as well as, enhanced extracellular vesicular secretion, and the persistence of glioma stem cells (GSCs) [9, 22, 23]. Clinically, approximately 50% of patients with GBM are unresponsive to TMZ therapy, yet no robust predictive biomarkers of resistance have been validated beyond MGMT promoter methylation status, which regulates MGMT expression levels. However, MGMT testing lacks methodological standardization and cut-off thresholds, which results in inconsistent patient stratification and variability in the implementation of the Stupp protocol [24, 25]. Furthermore, resistance can be either intrinsic, reflecting inherent tumor properties, or acquired after initial exposure to TMZ, further complicating prognosis and treatment planning [7]. As such, the next sections focus on deepening the understanding of TMZ resistance using CRISPR/Cas-based screens.
Decoding TMZ Resistance
Beyond targeted gene editing, CRISPR/Cas systems have become powerful platforms for mapping the complex molecular networks that shape TMZ response. Across the studies reviewed, genome-wide CRISPR knockout (CRISPR-KO), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) screens, alongside targeted CRISPR/Cas9 gene KO and Cas13a messenger RNA degradation, have been systematically employed to investigate mechanisms driving TMZ sensitivity and TMZ resistance.
Typically, functional genomic CRISPR screens involve engineering target cells to stably express the Cas endonuclease, followed by transduction with a pooled lentiviral gRNA library. Following infection, antibiotic selection isolates successfully transduced cells, ensuring stable expression of the CRISPR/Cas system. The resulting cell population is then exposed to sub-lethal concentrations of the drug of interest to reveal genes whose loss or activation modulates treatment response. Identified hits are subsequently validated and mechanistically characterized with complementary assays [26, 27].
However, simple loss-of-function approaches fail to capture the full spectrum of transcriptional mechanisms that govern TMZ chemoresistance. To address this limitation, CRISPRi has been used to silence gene expression without altering the DNA sequence. By employing a deactivated Cas9 (dCas9) fused to the KRAB repressor, CRISPRi achieves targeted transcriptional knockdown [26, 27]. Conversely, complementary CRISPRa screens offer insights into gain-of-function mechanisms of resistance by using a dCas9 fused to transcriptional activators, such as VP64 and P65, to upregulate gene expression [26]. In addition to DNA-directed manipulation, RNA-targeting Cas13a platforms expand the CRISPR/Cas toolkit by enabling the direct post-transcriptional degradation of messenger RNA transcripts without risk of permanent genomic disruption (Fig. 2) [28].
Fig. 2.

Comparison of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/-associated protein (Cas) systems used in decoding temozolomide (TMZ) resistance and O6-methylguanine-DNA methyltransferase (MGMT) epigenetic silencing. In CRISPR/Cas9 knockout (KO), guide RNA (gRNA) directs Cas9 to a complementary DNA sequence, creating a double-strand break that results in gene KO. Similarly, gRNA directs Cas13a to target RNA transcripts, leading to RNA degradation. CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) employ deactivated Cas9 (dCas9) fused to the KRAB repressor or transcriptional activators VP64/P65 to silence or activate gene expression, respectively. Regarding MGMT epigenetic silencing, gRNA directs dCas9-methyltransferase to the MGMT promoter, inducing DNA methylation and resulting in gene silencing (left). The CRISPRoff system operates similarly, but dCas9-methyltransferase is also fused to the KRAB repressor, achieving more durable gene repression (right). Created with BioRender.com
Cumulatively, the literature search identified ten CRISPR/Cas studies aimed at decoding TMZ resistance. Despite using diverse screening strategies and identifying distinct genes, these studies converge on interconnected biological processes. Taken together, these functional studies reveal DNA damage repair networks, multi-genetic co-mutations, cellular stress adaptation, intracellular trafficking, and stemness-associated tumor heterogeneity as key determinants of TMZ response (Table 1).
Table 1.
Summary and key findings of studies employing CRISPR/Cas technology to study TMZ sensitivity in brain tumors
| Biological pathway | Tumor | CRISPR/Cas system | Strategy | Key outcomes | Ref. |
|---|---|---|---|---|---|
| DNA damage response | Glioma | Targeted CRISPR/Cas9 KO | Gene loss-of-function |
ATRX stabilizes PARP1 and enhances DNA damage repair, increasing TMZ resistance Combined PARP1 inhibitor (olaparib) and TMZ improves therapeutic response in glioma-bearing mice |
[29] |
| DNA damage response | Glioma | CRISPR/Cas13a | RNA knockdown |
TMZ-induced upregulation of RAD51AP1 contributes to resistance in MGMT-methylated tumors Combined RAD51AP1 knockdown and TMZ prolonged the survival of glioma-bearing mice RAD51AP1 may serve as a prognostic biomarker in MGMT-methylated glioma |
[28, 30] |
| Cell-cycle checkpoint regulation | Glioma | Genome-wide CRISPR/Cas9 KO screen | Gene loss-of-function |
Myt1 kinase promotes TMZ-induced DNA-damage cell-cycle arrest, increasing TMZ resistance Combined Myt1 inhibitor and TMZ improves survival in glioma-bearing mice |
[31] |
| Gene alterations (mutations) | GBM | In vivo AAV-CRISPR/Cas9 screen | Gene loss-of-function | Co-mutation of Zc3h13 or Pten with Rb1 promoted TMZ resistance in mouse models | [32] |
| Metabolic stress adaptation | GBM | CRISPRi screen (dCas9-KRAB) | Transcriptional repression |
PGK1 suppression reduces tumor growth but induces compensatory survival responses associated with TMZ resistance PGK1 may serve as a predictive biomarker for TMZ response |
[27] |
| Oxidative stress adaptation | GBM | CRISPR/Cas9 KO | Gene loss-of-function | PAX6 suppression increases proliferation and alters oxidative stress responses, resulting in increased TMZ sensitivity | [33] |
| Intracellular trafficking and drug efflux | GBM | Genome-wide CRISPR/Cas9 KO screen | Gene loss-of-function |
Loss of RASGRP1 and VPS28 reduces exosome-mediated drug efflux, increasing intracellular TMZ accumulation and sensitizing cells to treatment Combined dual silencing of RASGRP1 and VPS28, TMZ, and EPIC-0412 (RAS pathway inhibitor) reduces tumor burden in GBM-bearing mice |
[34] |
| Intracellular trafficking | Glioma | Genome-wide CRISPR/Cas9 KO screen | Gene loss-of-function |
TMZ exposure increases ARF4-dependent retrograde trafficking of resistance-associated proteins into the nucleus ARF4 inhibition enhances TMZ antitumor efficacy in glioma-bearing mice |
[35] |
| Stemness maintenance and proteotoxic stress adaptation | GBM | Genome-wide CRISPR/Cas9 KO screen and targeted validation | Gene loss-of-function |
SOX2, SOX9, DOT1L, and SOCS3 were identified as universal dependencies for GSC proliferation and stemness maintenance SOCS3 ablation directly impairs cell growth Protein UFMylation and ERAD pathways are critical stress-response mechanisms required for GSC survival following TMZ exposure |
[36] |
| Circadian regulation and signaling | GBM | CRISPR/Cas9 KO and CRISPRa screens | Gene loss-of-function and gene upregulation |
NRF2 and CLCA2 suppression enhances TMZ response FZD6 and CTNNB1 overexpression decrease TMZ sensitivity and increase invasiveness NRF2 may serve as a predictive biomarker of TMZ response Circadian rhythm regulators influence TMZ efficacy, suggesting potential value for chronochemotherapy |
[26] |
ARF4 ADP-ribosylation factor 4, ATRX alpha thalassemia/mental retardation X-linked, CRISPR/Cas clustered regularly interspaced short palindromic repeats-associated proteins, ERAD endoplasmic reticulum-associated degradation, dCas9 deactivated Cas9, DOT1l disruptor of telomerase silencing 1-type, GBM glioblastoma, GSC glioblastoma stem cells, KO knockout, MGMT O6-methylguanine-DNA methyltransferase, Myt1 myelin transcription factor 1, PARP1 poly(ADP-ribose) polymerase 1, PGK1 phosphoglycerate kinase 1, RAD51AP1 RAD51-associated protein 1, RASGRP1 RAS guanyl nucleotide-releasing protein 1, SOX2 sex determining region Y--box transcription factor 2, TMZ temozolomide, VSP28 vacuolar protein sorting-associated protein 28
DNA Damage Repair
Beyond MGMT-mediated repair, alternative DNA damage response pathways have emerged as important determinants of TMZ sensitivity. For instance, by KO Alpha Thalassemia/mental Retardation X-linked (ATRX), a chromatin remodeler frequently upregulated in TMZ-resistant glioma cells, Han et al. (2020) revealed that ATRX stabilizes poly(ADP-ribose) polymerase 1 (PARP1) to enhance DNA repair in these glioma cells. Consequently, combining TMZ and the PARP inhibitor olaparib successfully re-sensitized resistant cells, underscoring the therapeutic relevance of the ATRX-PARP1 signaling axis [29].
Additionally, Zhou et al. (2023) used RNA-directed Cas13a to knockdown RAD51-associated protein 1 (RAD51AP1), a facilitator of homologous recombination repair that is upregulated following TMZ exposure. RAD51AP1 suppression accelerated the accumulation of lethal DNA lesions and successfully restored TMZ sensitivity in MGMT-methylated glioma. This is particularly significant because, although MGMT-methylated gliomas lack MGMT-mediated repair, they develop resistance through compensatory repair pathways. Accordingly, elevated RAD51AP1 expression correlated with shortened patient survival, positioning it as a viable prognostic biomarker in MGMT-methylated glioma [28, 30]. Furthermore, looking at cell-cycle checkpoints, Lang et al. (2024) identified myelin transcription factor 1 (Myt1) kinase, a G2/M checkpoint regulator, as a protective factor during TMZ-induced DNA damage. Pharmacological inhibition of Myt1 disrupted checkpoint arrest and sensitized cells to TMZ [31].
Crucially, mapping therapeutic vulnerabilities requires looking beyond single-gene alterations to capture complex genetic contexts within physiological environments. To achieve this direct in vivo validation, Chow et al. deployed an AAV-mediated CRISPR screen directly within the brains of living mouse models [32]. The screen revealed that while a stand-alone Rb1 mutation does not alter therapeutic sensitivity, the CRISPR-driven co-mutation of either Zc3h13 or Pten alongside Rb1 promotes robust in vivo TMZ resistance [32]. This highlights how complex multigenetic interactions drive chemoresistance, emphasizing that enhanced DNA repair capacity and genetic context are major co-dependent drivers of clinical drug resistance. Importantly, several pathways identified already have pharmacological inhibitors available, including PARP inhibitors such as olaparib and cell-cycle checkpoint inhibitors targeting Myt1, supporting the potential for rapid clinical translation of these findings [29, 31].
Cellular Stress Adaptation
Tumor cells also exploit metabolic and microenvironmental adaptation strategies to survive the physiological stress induced by alkylating agents. Li and colleagues (2025) uncovered the dual role of the glycolytic enzyme phosphoglycerate kinase 1 (PGK1) in GBM. While CRISPRi-mediated PGK1 knockdown reduced basal tumor growth, prolonged TMZ treatment paradoxically triggered metabolic stress, forcing the cells to activate compensatory survival pathways that ultimately fostered chemoresistance. Conversely, elevated PGK1 levels closely correlated with improved TMZ sensitivity, positioning PGK1 as a potential predictive biomarker of TMZ response [27].
Similarly, Hegge et al. identified the paradoxical role of the tumor suppressor PAX6 in modulating TMZ sensitivity. CRISPR/Cas9-mediated PAX6 KO increased tumor cell proliferation and altered resistance to oxidative stress [33]. Interestingly, the enhanced proliferative phenotype was associated with increased TMZ sensitivity, potentially because rapidly dividing cells are more susceptible to accumulation of TMZ-induced DNA damage during replication [33]. Altogether, these findings suggest that adaptive responses to metabolic and oxidative stress further contribute to TMZ resistance.
Intracellular Trafficking and Drug Availability
An equally critical determinant of therapeutic efficacy is the drug’s physical concentration at its intracellular site of action, a variable tightly regulated by active transport and vesicle trafficking pathways. Through a genome-wide CRISPR-KO screen, Zhao et al. identified RAS guanyl nucleotide-releasing protein 1 (RASGRP1) and Vacuolar Protein Sorting-Associated Protein 28 (VPS28) as pivotal mediators of resistance. RASGRP1 and VPS28 KO sensitized cells to TMZ by disrupting exosome-mediated drug efflux, thereby promoting intracellular drug accumulation [34]. Complementing this, another comprehensive screen identified ADP-ribosylation factor 4 (ARF4), a regulator of retrograde trafficking, as facilitating the nuclear import of pro-survival factors following TMZ exposure. Repeated TMZ treatment progressively upregulated ARF4 expression, amplifying resistance, whereas pharmacological inhibition of the ARF4 pathway restored TMZ sensitivity in vivo [35]. As just demonstrated, CRISPR-KO screening can also reveal targets for rational TMZ-combined therapies. Overall, these studies identify intracellular trafficking pathways as regulators of intracellular drug availability and adaptive survival responses, suggesting a potential combination of TMZ with targeted transport inhibitors to bypass drug clearance mechanisms.
Stemness and Tumor Heterogeneity
Ultimately, the clinical management of GBM is profoundly complicated by patient-specific genetic landscapes and the persistence of GSCs, which drive tumor recurrence. To map these dependencies across clinically relevant, patient-derived models, MacLeod et al. conducted scalable genome-wide CRISPR-KO screens paired with targeted validation across ten distinct patient-derived GSC lines [36]. This multi-line screening approach successfully isolated core genetic dependencies from confounding background heterogeneity. The screen identified transcription factors Sex Determining Region Y-Box Transcription Factor 2 (SOX2) and SOX9, the histone methyltransferase Disruptor of Telomere Silencing 1-Like (DOT1L), and the cytokine signaling regulator SOCS3 as universal requirements for GSC self-renewal and stemness, which indirectly contribute to TMZ resistance. Moreover, components of the cellular UFMylation pathway and the endoplasmic reticulum-associated degradation (ERAD) system, both involved in proteostasis regulation, were identified as critical for GSC survival under TMZ-induced proteotoxic stress. Genetic disruption of these pathways effectively sensitized these highly resistant stem cell populations to TMZ treatment [36].
Taking advantage of another layer of cellular heterogeneity, Rocha et al. deployed a genome-wide CRISPRa activation screen, identifying FZD6 and CTNNB1 as genes whose overexpression decreased TMZ sensitivity and enhanced tumor invasiveness. The study also showed that NRF2 overexpression was associated with reduced TMZ response, suggesting its predictive value. Most notably, the same study found that KO of circadian clock genes also increased TMZ resistance, indicating that disruption of the circadian rhythm may promote chemoresistance. Although further research is required to fully confirm this finding, the results suggest that temporal coordination of TMZ treatment with circadian timing, termed chronochemotherapy, may maximize treatment efficacy [26].
The persistence of stem cell programs and context-dependent genetic interactions further demonstrates that TMZ resistance emerges from tumor heterogeneity rather than single-gene alterations. Given this profound inter-patient diversity, it is unlikely that uniform monotherapy will ever achieve universal clinical efficacy [36].
Generally, these findings illustrate the versatility of CRISPR/Cas technologies in mapping molecular factors dictating TMZ response. Importantly, the variation in candidate genes across different studies highlights the profound influence of cellular context and tumor heterogeneity. This variation emphasizes the need for improved GBM models that more accurately recapitulate the tumor microenvironment and the multifactorial nature of TMZ resistance, a point that will be addressed later in Sect. 6. It also reinforces the importance of validating CRISPR screen hits in patient-derived cells and clinically relevant systems to ensure translational relevance.
Nonetheless, despite variations in screening platforms, cell models, and glioma subtypes, the reviewed literature converges on a highly consistent set of biological vulnerabilities. DNA damage tolerance emerges as the dominant and most reproducibly identified driver, with independent studies implicating MGMT stabilization, PARP-dependent repair, and cell-cycle checkpoint evasion as mechanistically distinct yet functionally complementary axes. Alongside this, adaptive metabolic, oxidative, and proteotoxic stress responses further shield tumor cells from alkylating damage, as well as intracellular trafficking networks, which modulate drug availability and stemness maintenance.
Notably, several resistance pathways identified through CRISPR screening have corresponding pharmacological inhibitors, facilitating the future rational design of combination therapies [26, 29, 31]. For instance, the PARP inhibitor olaparib, which is already approved for BRCA-mutant cancers, is currently being investigated in GBM clinical trials (NCT05463848) in combination with TMZ and immunotherapy [37, 38]. Similarly, Myt1 kinase and NRF2 inhibitors are under active investigation, with the natural compound brutasol already demonstrating promising activity as an NRF2 inhibitor in HER2-positive breast cancers [39–42].
Finally, these discoveries demonstrate that TMZ resistance is not driven by a single molecular event but rather arises from a dynamic context-dependent survival network, underscoring the need for multi-target combinatorial treatments to overcome chemoresistance in patients. Accordingly, CRISPR/Cas systems are now being investigated not only as discovery tools but as direct therapeutic modulators of TMZ response, particularly through epigenetic silencing of MGMT expression, which will be discussed in the following section.
Restoring Temozolomide Sensitivity: Epigenetic Silencing of MGMT and Knockdown of Midkine
Being the most recognized mechanism of TMZ resistance in GBM, numerous studies have targeted MGMT using substrate analogs and enzymatic inhibitors; however, these approaches have shown limited efficacy and caused considerable hematologic adverse effects, hindering their clinical use [22, 43]. Gene-editing approaches targeting MGMT KO have also been explored, while more recently, epigenetic editing strategies have emerged as a promising, potentially safer alternative.
The methylation status of the MGMT promoter remains a key predictor of TMZ response, as an unmethylated promoter, present in approximately 60% of patients with GBM, is associated with elevated MGMT expression and poor prognosis [44, 45]. From the literature search, five studies employed a dCas9 fused to DNA methyltransferases as an epigenetic strategy to enhance TMZ sensitivity. Table 2 summarizes the key findings. In these systems, gRNAs were designed to target CpG islands within the MGMT promoter and/or enhancer regions, directing dCas9 to induce site-specific methylation. An overview of the strategy is presented in Fig. 2. Four studies served primarily as proof-of-concept, demonstrating that dCas9-mediated methylation of MGMT effectively suppressed MGMT expression and restored TMZ sensitivity across multiple TMZ-resistant GBM cell lines [44–47].
Table 2.
Summary and key findings of studies employing CRISPR/Cas technology to enhance TMZ sensitivity in GBM via epigenetic modulation and MDK KO
| Tumor | CRISPR/Cas system | Delivery system | Model | Key outcomes | Ref. |
|---|---|---|---|---|---|
| GBM | dCas9-methyltransferase | Plasmid | GBM cell line (HEK293T) |
MGMT promoter/enhancer methylation decreased MGMT mRNA ~7-fold TMZ IC50 reduced 9-fold |
[44] |
| GBM | CRISPRoff | Plasmid | GBM cell lines (LN18 and T-325) |
MGMT promoter methylation decreased MGMT protein levels Not all promoter methylation sites silence MGMT equally, so the most effective region for MGMT suppression should be identified |
[45] |
| GBM | CRISPRoff | Plasmid | GBM cell lines (LN18, T98G, and U138MG) |
MGMT promoter methylation suppressed MGMT expression TMZ IC50 reduced by 78% No off-target effects detected |
[46] |
| Glioma | dCas9-methyltransferase | Lentivirus | Glioma cell line (LN18) |
High-density MGMT promoter/enhancer methylation downregulated MGMT expression and sensitized cells to TMZ Minimal off-target effects detected |
[47] |
| GBM | CRISPRoff |
Lipid nanoparticles + electroporation (in vitro) |
GBM cell lines (LN18, T98G, and SF7996) |
MGMT promoter methylation decreased 97% MGMT transcript levels with loss of MGMT protein Site-specific DNA methylation and low incidence of off-target effects Sustained MGMT silencing up to 8 months 100- to 762-fold increase in TMZ sensitivity Superior sensitization of CRISPRoff compared with Cas9-mediated MGMT deletion |
[48] |
| Patient-derived GBM cultures | Complete MGMT loss and TMZ sensitization | ||||
| Orthotopic GBM xenografts | Full tumor regression after TMZ treatment (oral gavage) | ||||
| GBM | CRISPR/Cas9 RNP | Plofsome | GBM cell lines (LN229R and GL261R) and patient-derived GBM cells | ROS-triggered polymeric de-capping converted the liposome to a fusogenic state, enabling cell membrane fusion and cargo release | [55] |
| Orthotopic GBM xenografts |
Tumor-responsive cargo delivery across the BBB with safe release restricted to the ROS-rich tumor site (tail vein administration) RNP-mediated MDK silencing No off-target editing detected in normal brain, kidney, or liver Plofsome@RNP + TMZ significantly inhibited tumor growth and prolonged survival compared with TMZ monotherapy |
CRISPR/Cas clustered regularly interspaced short palindromic repeats-associated protein, dCas9 deactivated Cas9, GBM glioblastoma, IC50 half-maximal inhibitory concentration, KO knockout, MDK midkine. MGMT O6-methylguanine-DNA methyltransferase, mRNA messenger RNA, Plofsome polymer-locking fusogenic liposome, RNP ribonucleoprotein, ROS reactive oxygen species, TMZ temozolomide
Building on these findings, Lin et al. developed a more advanced system using CRISPRoff, in which dCas9 is fused not only to methyltransferases but also to the KRAB transcriptional repressor, enabling durable and heritable gene silencing (Fig. 2) [48]. Compared with conventional dCas9-methyltransferase systems, CRISPRoff provides greater repression through synergistic KRAB-mediated chromatin remodeling. Additionally, in contrast to earlier plasmid and lentivirus-based delivery systems, CRISPRoff messenger RNA was encapsulated in lipid nanoparticles and delivered via electroporation to enhance in vitro uptake. This system achieved stable MGMT silencing for up to 8 months in continuously passaged GBM clones, confirming the long-term stability of CRISPRoff-mediated repression. Furthermore, Lin and colleagues verified this multiplexed strategy in patient-derived GBM cultures and orthotopic mouse models, where CRISPRoff-treated TMZ-sensitive animals exhibited complete tumor regression [48]. However, to fully assess CRISPRoff efficacy, future studies should evaluate this system in truly TMZ-resistant tumors, rather than previously sensitized models used for xenograft generation.
In contrast to CRISPR/Cas-mediated gene editing, CRISPR/Cas-based epigenetic modulation offers a reversible yet durable strategy to regulate gene expression, bypassing permanent gene editing and its associated unpredictability and off-target risks [49]. Notably, targeted epigenetic modulation alone proved sufficient to enhance TMZ response, eliminating the need for irreversible gene disruption. Nevertheless, gRNA design requires careful optimization to ensure on-target specificity and minimize unintended epigenetic changes, with combinatorial gRNA strategies often yielding higher efficiency. Delivery systems also remain a major translational barrier, requiring optimization to overcome current challenges in biodistribution, BBB penetration, tumor-specific targeting, and efficient intratumoral delivery [50–52].
Importantly, MGMT expression is regulated by multiple pathways, and MGMT methylation alone might be insufficient to fully suppress protein levels [46]. Moreover, as previously discussed, TMZ resistance in GBM is inherently multifactorial, involving a complex interplay of DNA repair, apoptosis, autophagy, and signaling pathways beyond MGMT itself, reinforcing the need for using combinatorial therapies [9, 22].
Beyond MGMT, the literature search identified one additional study addressing CRISPR/Cas-based approaches to reverse TMZ resistance through an MGMT-independent mechanism (Table 2). Midkine (MDK) is a heparin-binding growth factor overexpressed in several malignancies, including GBM, where it drives tumor progression and TMZ resistance by sustaining GSCs stemness [53, 54]. To exploit this pathway, Zhao and colleagues engineered a smart polymer-locking fusogenic liposome (Plofsome) designed to deliver nucleic acid cargo systemically [55]. Structurally, the Plofsome is shielded by a protective polymer capping during blood circulation and BBB crossing, hindering premature cargo release. Within the oxidative tumor microenvironment, elevated reactive oxygen species (ROS) levels trigger detachment of the polymer shield, thereby rendering the liposome fusogenic. With this tumor-responsive platform, the authors demonstrated that encapsulating either CRISPR/Cas9 ribonucleoprotein (RNP) complex for permanent genomic KO or small interfering RNA (siRNA) for transient post-transcriptional knockdown successfully silenced MDK. By disrupting MDK-CD109 signaling and downstream STAT3 phosphorylation, Plofsome@RNP or @siRNA effectively restored TMZ sensitivity in resistant GBM cells and significantly extended survival in orthotopic mouse models. Importantly, gene editing and MDK silencing were tumor specific, with no off-target editing detected in normal brain, kidney, or liver tissue, attributable to the ROS-gated activation mechanism [55].
The CRISPR/Cas-based approaches reviewed here exist within a broader landscape of strategies investigated to overcome TMZ resistance, many of which preceded the CRISPR era and encountered significant translational barriers. Pharmacological MGMT inhibitors, including O6-benzylguanine and lomeguatrib, which act as false MGMT substrates, were among the earliest clinical strategies but were reported to have limited therapeutic benefit and substantial hematological toxicity, namely neutropenia and thrombocytopenia, in clinical trials [17, 18, 43]. Beyond MGMT-mediated resistance, other pharmacological strategies have targeted complementary resistance pathways, including PARP inhibitors such as olaparib, Wnt signaling inhibitors (celecoxib), histone deacetylase inhibitors, and ATM kinase inhibitors, all of which have demonstrated the capacity to restore TMZ sensitivity in preclinical GBM [14, 15, 56, 57]. At the post-transcriptional level, RNA interference and inhibitors of miR-21, which are frequently overexpressed in TMZ-resistant GBM, have also effectively suppressed the expression of resistance-associated genes and enhanced TMZ responsiveness [16, 58]. However, RNA-based strategies are often limited by poor BBB penetration and transient biological activity, hindering sustained therapeutic efficacy [59]. Compared with these modalities, CRISPR/Cas platforms offer several complementary advantages, including permanent gene disruption or durable epigenetic regulation, as well as the ability to simultaneously target multiple resistance pathways. However, challenges related to delivery, tumor specificity, and potential off-target editing remain current barriers to clinical translation. Consequently, continued optimization of CRISPR/Cas delivery systems and editing precision will be essential for the development of safe and effective therapeutic applications in GBM.
Overall, these findings demonstrate that CRISPR/Cas-based strategies, whether targeting MGMT through epigenetic silencing or disrupting MGMT-independent resistance drivers such as MDK, can effectively restore TMZ sensitivity, highlighting the therapeutic versatility of programmable gene regulation in overcoming the multifactorial nature of GBM chemoresistance. Interestingly, although several promising targets were identified in the previous decoding section, including ATRX, Myt1, and ARF4, none has yet been directly explored through CRISPR/Cas-targeted therapeutic modulation. Nonetheless, more physiologically relevant tumor models are required to evaluate these strategies within the complex microenvironment of brain tumors and to accelerate the translation of therapeutic discoveries.
CRISPR/Cas-Engineered Brain Tumor Models
Current preclinical brain tumor models, including established cell lines (i.e., U87, U251, T98G, and LN229 cells), patient-derived organoids, three-dimensional bioprinting systems, organ-on-a-chip platforms, and animal models, each recapitulate only selected aspects of tumor biology [60]. Critically for the study of TMZ resistance, many fail to adequately capture the intratumoral heterogeneity, tumor-microenvironment interactions, immune landscape, and invasive behavior that collectively shape therapeutic response [61, 62]. Although genetically engineered mouse models remain valuable for modeling tumor initiation and progression in vivo, conventional genetically engineered mouse model generation is laborious and time consuming, with limited scalability and experimental flexibility, which hinders systematic interrogation of resistance mechanisms [63–65]. Mostly, these limitations contribute to high failure rates when promising preclinical therapies progress to clinical trials [66].
CRISPR/Cas technologies have increasingly been employed to generate genetically engineered tumor models across cancer types, including liver, lung, and pancreas cancers [67–69]. The development of early CRISPR/Cas9 gene editing protocols by Ran et al., established a foundation for rapid and flexible somatic editing that accelerated in vivo tumor modeling [70]. Building on these advances, CRISPR/Cas-based brain tumor models are now being explored to generate more genetically precise and physiologically relevant systems for investigating gliomagenesis, tumor heterogeneity, chemoresistance, and therapeutic response in immunocompetent settings. The literature search identified six studies, most of which were published in the last 2 years, that employed CRISPR/Cas9 approaches for this purpose; these studies are summarized in Table 3.
Table 3.
Summary and key features of CRISPR/Cas-based brain tumor models
| Cancer | Model | CRISPR/Cas system | Target gene(s) | Strategy | Key features | Ref. |
|---|---|---|---|---|---|---|
| DMG | RCAS/tv-a transgenic mouse | CRISPR/Cas9 - RCAS/tv-a | Atm, Cdkn2a, Pten, Trp53 | Synergistic combination of RCAS/tv-a retroviral delivery and CRISPR/Cas9 to introduce tumor-driver mutations in neural stem cells |
Rapid tumor formation (~3–4 weeks) Enables cell-type-specific and spatially controlled mutagenesis Reproducible tumor induction Recapitulates molecular and histopathological features of human DMG |
[19] |
| GBM | Immunocompetent mouse | CRISPR/Cas9 | Nf1, Pten, Trp53 | Somatic KO of tumor suppressor genes |
High tumor penetrance with multiplex gene targeting Longer tumor latency (~6–14 weeks) compared with SHH MB models |
[65] |
| SHH MB | Immunocompetent mouse | CRISPR/Cas9 | Ptch1 | Somatic KO of the SHH pathway gene |
High tumor penetrance Rapid tumor formation (~5 weeks) in Trp53-deficient mice Recapitulates molecular and histopathological features of human SHH MB No detectable off-target effects reported |
[65] |
| SHH MB | Zebrafish | CRISPR/Cas9 | Ptch1, tp53 | Targeted KO of the SHH pathway and tumor suppressor genes |
Recapitulates genetic and histological features of human SHH MB TP53 loss increases tumor aggressiveness Compatible with high-throughput functional and drug screening studies |
[71] |
| Glioma | Immunocompetent mouse | CRISPR/Cas9 | Nf1, Pten, Trp53 | Somatic KO of tumor suppressor genes in neural stem cells of the developing cortex |
Recapitulates tumor-neuron interactions and peritumoral hyperexcitability Preserves native immune microenvironment Suitable for investigating tumor-associated seizure mechanisms |
[72] |
| GBM | Immunocompetent mouse | CRISPR/Cas9, PiggyBac transposon, gDAM | Nf, Pten, Trp53, EGFRvIII | CRISPR/Cas9-mediated somatic KO combined with ectopic EGFRvIII expression |
Enables astrocyte-specific DNA delivery Suitable for studying gliomagenesis and early progression of astrocyte-derived GBM Rapid tumor formation (-1 month) Recapitulates hallmark GBM features, including hemorrhage, aneuploidy, and necrosis Tumor-derived cells formed tumor-sphere-like structures within 14 days |
[73] |
| GBM | Syngeneic mouse | CRISPR/Cas9 | Mlh1 | Somatic KO to generate MMR deficiency |
Recapitulates TMZ resistance associated with MMR loss Suitable for evaluating alkylating agents in immunocompetent settings |
[75] |
CRISPR/Cas clustered regularly interspaced short palindromic repeats-associated protein, DMG diffuse midline glioma, EGFR epidermal growth factor receptor, GBM glioblastoma , gDAM gene delivery approach admitted by small metabolites, KO knockout, MMR mismatch repair, RCAS/tv-a replication-competent avian sarcoma-leukosis virus/tumor virus A system, SHH MB sonic hedgehog medulloblastoma
One of the earliest demonstrations of CRISPR/Cas9-mediated brain tumor modeling was reported by Zuckermann et al., who used somatic KO of tumor suppressor genes to generate mouse models of medulloblastoma (MB) and GBM [65]. Specifically, KO of Ptch1 induced Sonic hedgehog (SHH)-driven MB, whereas simultaneous disruption of Nf1, Pten, and Trp53 promoted GBM formation. Both models exhibited high tumor penetrance and recapitulated key molecular and histological features observed in human tumors, with no detectable off-target effects, establishing a proof of concept for using somatic CRISPR/Cas editing to generate immunocompetent brain tumor models [65]. Building on this, Casey et al. developed a scalable CRISPR/Cas9-engineered zebrafish model of SHH MB through disruption of Ptch1 and tp53 [71]. Beyond reproducing key genetic and histological features of human SHH MB, the model’s rapid tumor onset and large clutch size facilitate high-throughput drug screening, which is particularly relevant for the systematic evaluation of chemotherapeutic agents and resistance-modulating strategies across large experimental cohorts [71].
Subsequent studies have extended CRISPR/Cas9-mediated somatic gene editing to establish immunocompetent glioma and GBM mouse models through the disruption of tumor suppressor pathways [19, 72, 73]. For instance, Hatcher et al. generated de novo gliomas through KO of Nf1, Pten, and Trp53 in neural stem cells of the developing cortex to investigate tumor-associated cortical hyperexcitability and seizure development [72]. Importantly, this model preserved tumor-neuron interactions and the native immune microenvironment, addressing the clinically relevant observation that up to 80% of adult patients with glioma experience seizures [72]. More recently, Zhou et al. combined CRISPR/Cas9-mediated KO of the same tumor suppressor genes with ectopic expression of the EGFRvIII oncogene, the most common tumor-specific mutation in GBM that directly drives accelerated proliferation, enhanced survival, and robust angiogenic potential [73, 74]. Using a metabolite-assisted gene delivery strategy (gDAM), this platform enabled astrocyte-targeted DNA delivery and the rapid generation of astrocyte-derived GBM models that display hallmark pathological features, including necrosis, hemorrhage, and aneuploidy. The authors proposed that this delivery platform may facilitate the investigation of gliomagenesis and early tumor progression in a cell-type-specific manner [73].
The incorporation of clinically relevant driver mutations has further refined the translation of these models. Wu et al. combined CRISPR/Cas9 with the RCAS/tv-a retroviral system to introduce diffuse midline glioma-associated mutations into neural stem cells, enabling spatially and cell-type-specific tumor generation directed by gRNA design [19].
Finally, CRISPR/Cas technologies have additionally been applied to model therapeutic resistance under clinically relevant selective pressures. Bhatt and colleagues generated syngeneic murine GBM models with MMR deficiency via somatic KO of Mhl1 to investigate TMZ resistance and therapeutic responses to alkylating agents [75]. As previously discussed, loss of MMR function is a well-established mechanism of acquired TMZ resistance in patients with GBM, and these models reproduced key features of MMR-deficient TMZ-resistant tumors observed clinically [75].
Altogether, CRISPR/Cas-based approaches have expanded the experimental flexibility of brain tumor modeling by enabling rapid disruption of tumor suppressor genes, introduction of clinically relevant driver mutations, oncogene activation, and the modeling of resistance under therapeutic selective pressure. The use of immunocompetent systems is a particular strength, allowing tumor-immune interactions and treatment response to be investigated within a native microenvironment. While no single model perfectly recapitulates the complexity of human brain tumors, CRISPR/Cas-engineered platforms represent a meaningful step toward genetically precise, translationally relevant preclinical models to decode and ultimately overcome TMZ resistance.
Translational Challenges and Future Perspectives
Since its discovery in 2012, the CRISPR/Cas9 system has transformed biomedical research through its simplicity, programmability, and broad applicability [12, 13]. Beyond its initial application in genome editing, the CRISPR/Cas toolkit now encompasses a diverse range of modulatory platforms, including CRISPRi and CRISPRa for gene regulation, CRISPRoff for stable epigenetic silencing, and RNA-targeting systems such as Cas13 (Fig. 2) [76]. These developments have expanded CRISPR/Cas from a tool for altering DNA sequence to a much more versatile platform [77–79]. This evolution is particularly significant in oncology, where the ability to manipulate gene expression reversibly, permanently, or transiently within the same experimental framework has opened new avenues for both mechanistic investigation and therapeutic intervention [33, 80, 81].
In the context of brain tumors, CRISPR/Cas systems have been applied for functional investigation of tumor biology and screening to decode TMZ resistance mechanisms, therapeutic gene and epigenetic editing, and tumor model engineering [82–84]. Notably, although the literature search targeted brain tumors broadly, most of the identified studies focused on GBM, reflecting both its clinical prevalence and the pressing need for improved treatment strategies in this highly aggressive cancer [74, 85, 86].
Although significant findings have been made in other areas, the present review specifically focused on three areas: CRISPR/Cas-based screens to uncover TMZ resistance, CRISPR/Cas-based strategies to modulate TMZ response, and CRISPR/Cas-based approaches to brain tumor modeling. To integrate these findings, Fig. 3 highlights how CRISPR/Cas platforms converge across the three interconnected applications discussed.
Fig. 3.

Conceptual framework illustrating the multifunctional role of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated proteins (Cas) systems in enhancing temozolomide (TMZ)-based therapy for brain tumors. CRISPR/Cas technologies provide a versatile platform for: (i) generating engineered brain tumor models that more accurately reflect tumor heterogeneity; (ii) uncovering mechanisms of TMZ resistance by identifying genes and pathways involved in metabolism, epigenetic regulation, DNA repair, intracellular trafficking, and circadian signaling; and (iii) restoring TMZ sensitivity through epigenetic repression of MGMT. These interconnected applications facilitate the discovery of predictive and prognostic biomarkers, supporting treatment stratification, identify novel therapeutic targets, and provide improved drug-testing platforms, ultimately enhancing brain tumor therapy. CRISPRa CRISPRactivation, CRISPRi CRISPR interference. Created with BioRender.com
CRISPR/Cas-based screening strategies have emphasized the complexity and multifactorial nature of TMZ resistance, implicating DNA damage repair mechanisms, adaptive stress responses, stemness maintenance, and tumor heterogeneity, among others [29, 31, 35]. Importantly, many resistance-associated genes identified in screens already have pharmacological inhibitors in clinical use, suggesting an opportunity for accelerated translation through rational drug repurposing [31, 40, 41]. Additionally, several predictive and prognostic biomarker candidates have emerged, which could support patient stratification into treatment-responsive subgroups and guide more tailored clinical decision making [27, 30, 85].
Despite the identification of target candidates, CRISPR/Cas-based therapeutic approaches aimed at reversing TMZ resistance have largely focused on modulating MGMT expression, particularly through targeted epigenetic editing with dCas9-methyltransferase and CRISPRoff systems [45, 48]. These studies demonstrate that CRISPR/Cas-mediated epigenetic editing can achieve stable durable repression of MGMT, thereby restoring TMZ sensitivity. Beyond MGMT, the Plofsome-delivered CRISPR/Cas9 RNP system targeting MDK represents an important proof-of-concept for CRISPR-based reversal of MGMT-independent resistance, demonstrating that tumor-responsive ROS-gated delivery can achieve therapeutically relevant gene disruption with tumor-restricted specificity [55]. However, clinical translation will require progress in three independent challenges. First, delivery systems must be capable of crossing the BBB efficiently while achieving adequate intratumoral distribution [5, 86]. Second, gRNA design must be optimized to minimize off-target editing and unintended epigenetic remodeling [87]. Finally, MGMT silencing alone is unlikely to be sufficient given the multifactorial nature of TMZ resistance, as discussed throughout the review [9, 86]. Combination strategies targeting MGMT alongside compensatory repair or stress-adaptation pathways will almost certainly be required, and a uniform approach is unlikely to prove effective across the heterogeneous GBM patient population [36, 88].
The CRISPR/Cas-based tumor models offer a complementary path toward bridging this translational gap by enabling more genetically precise and physiologically relevant preclinical systems [82, 89]. The studies reviewed demonstrate that CRISPR/Cas enables rapid tumor generation in immunocompetent hosts, cell-type-specific and spatially directed modeling, and scalable platforms compatible with high-throughput drug screening [19, 71, 73]. The generation of MMR-deficient syngeneic models through somatic Mlh1 KO represents a particularly relevant advance for chemoresistance research, providing immunocompetent systems in which TMZ resistance can be studied under conditions that recapitulate the clinical selective pressure of alkylating agent treatment [75]. Nevertheless, no single model fully recapitulates the cellular heterogeneity, immune landscape, and microenvironmental complexity of human GBM. Integration of CRISPR-engineered models with patient-derived organoids, spatial transcriptomics, and single-cell lineage tracing is likely to represent the next critical step toward improving physiological relevance and predictive validity for therapeutic evaluation [61, 90, 91].
Looking ahead, overcoming TMZ resistance will require a deeper understanding of the interconnected molecular networks that drive chemoresistance, the identification of robust predictive biomarkers for patient stratification, and the development of personalized combination therapies [24, 92–94]. Advances in CRISPR/Cas technologies, physiologically relevant tumor models, and next-generation delivery systems may facilitate the translation of these discoveries into clinically effective interventions [5, 55, 73, 75]. Furthermore, integration with emerging imaging technologies, multi-omics approaches, and artificial intelligence-based analytical tools may improve treatment selection and accelerate therapeutic development [85, 94–96]. As CRISPR/Cas tools continue to expand, their strategic application may shift the landscape of GBM research from descriptive observation to mechanistically informed, patient-specific therapeutic design.
Conclusions
The CRISPR/Cas technologies have become valuable tools in advancing brain tumor research beyond traditional gene editing. Their applications in functional genomic screening, epigenetic modulation of TMZ response, and the development of genetically precise tumor models have deepened the understanding of treatment resistance and highlighted new therapeutic opportunities. Nonetheless, significant challenges remain, particularly regarding efficient brain-targeted delivery, tumor heterogeneity, and translation of preclinical findings into clinical benefits. Despite these limitations, CRISPR/Cas-based strategies continue to refine drug discovery pipelines and hold promise for overcoming TMZ resistance. As these platforms evolve, they may ultimately contribute to more effective, personalized, and durable therapeutic approaches, thereby improving survival outcomes for patients with GBM. As research advances, CRISPR/Cas systems may shift TMZ therapy from a uniform standard of care to a stratified, mechanism-guided, and patient-specific approach.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgments
The authors acknowledge funding from the Coimbra Chemistry Centre—Institute of Molecular Sciences (CCC-IMS), which is supported by the Fundação para a Ciência e a Tecnologia (FCT), Portuguese Agency for Scientific Research. CCC is funded by FCT through projects UID/PRR/00313/2025 (10.54499/UID/PRR/00313/2025) and UID/00313/2025 (10.54499/UID/00313/2025) and IMS through special complementary funds provided by FCT (project LA/P/0056/2020).
Funding
Open access funding provided by FCT|FCCN (b-on).
Declarations
Funding
The authors also acknowledge Fundação para a Ciência e a Tecnologia (FCT) for funding project 2022.06174.PTDC. The figures were created with BioRender.com.
Conflicts of Interest
Bárbara S. Marques, Maria Mendes, José Luís Alves, Alberto Pais, and Carla Vitorino have no conflicts of interest that are directly relevant to the content of this article.
Ethics Approval
Not applicable.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Availability of Data and Material
Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.
Code Availability
Not applicable.
Authors’ Contributions
BSM contributed to conceptualization, methodology, formal analysis, investigation, and writing of the original draft. MM and CV contributed to conceptualization and formal analysis, reviewed and edited the manuscript, and supervised the study. JLA and AP reviewed and edited the manuscript. All authors have read and approved the final version of the manuscript.
Contributor Information
Maria Mendes, Email: mmendes@ff.uc.pt.
Carla Vitorino, Email: csvitorino@ff.uc.pt.
References
- 1.Ferlay J, Ervik M, Lam F, Laversanne M, Colombet M, Mery L, et al. Global Cancer Observatory: cancer today. Lyon, France: International Agency for Research on Cancer; 2024. Available from: https://gco.iarc.who.int/today. [Accessed 13 Aug 2025].
- 2.Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. 2021;23:1231–51. 10.1093/neuonc/noab106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Stupp R, Brada M, van den Bent MJ, Tonn JC, Pentheroudakis G. High-grade glioma: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2014;25:93–101. 10.1093/annonc/mdu050. [DOI] [PubMed] [Google Scholar]
- 4.Mendes M, Nunes S, Cova T, Branco F, Dyrks M, Koksch B, et al. Charge-switchable cell-penetrating peptides for rerouting nanoparticles to glioblastoma treatment. Colloids Surf B Biointerfaces. 2024:1–18. 10.1016/j.colsurfb.2024.113983. [DOI] [PubMed] [Google Scholar]
- 5.Branco F, Cunha J, Mendes M, Vitorino C, Sousa JJ. Peptide-hitchhiking for the development of nanosystems in glioblastoma. ACS Nano. 2024;18:16359–94. 10.1021/acsnano.4c01790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Stupp R, Mason WP, Van Den Bent MJ, Weller M, Fisher B, Taphoorn MJB, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005;352:987–96. 10.1056/NEJMoa043330. [DOI] [PubMed] [Google Scholar]
- 7.Singh N, Miner A, Hennis L, Mittal S. Mechanisms of temozolomide resistance in glioblastoma: a comprehensive review. Cancer Drug Resist. 2021;4:17–43. 10.20517/cdr.2020.79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kotecha R, Odia Y, Khosla AA, Ahluwalia MS. Key clinical principles in the management of glioblastoma. JCO Oncol Pract. 2023;19:180–9. 10.1200/OP.22. [DOI] [PubMed] [Google Scholar]
- 9.White J, White MPJ, Wickremesekera A, Peng L, Gray C. The tumour microenvironment, treatment resistance and recurrence in glioblastoma. J Transl Med. 2024:1–14. 10.1186/s12967-024-05301-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Tang Q, Ren T, Bai P, Wang X, Zhao L, Zhong R, et al. Novel strategies to overcome chemoresistance in human glioblastoma. Biochem Pharmacol. 2024:1–26. 10.1016/j.bcp.2024.116588. [DOI] [PubMed] [Google Scholar]
- 11.The Nobel Prize. The Nobel Prize in chemistry 2020. 2020. Available from: https://www.nobelprize.org/prizes/chemistry/2020/popular-information/ [Accessed 26 May 2024].
- 12.Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, Charpentier E. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science. 1979;2012:1–7. 10.1126/science.1225829. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Doudna JA, Charpentier E. The new frontier of genome engineering with CRISPR-Cas9. Science. 2014;346:1258096. 10.1126/science.1258096. [DOI] [PubMed] [Google Scholar]
- 14.Yelton CJ, Ray SK. Histone deacetylase enzymes and selective histone deacetylase inhibitors for antitumor effects and enhancement of antitumor immunity in glioblastoma. Neuroimmunol Neuroinflamm. 2018;5(46):1–18. 10.20517/2347-8659.2018.58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Lin CJ, Lee CC, Shih YL, Lin TY, Wang SH, Lin YF, et al. Resveratrol enhances the therapeutic effect of temozolomide against malignant glioma in vitro and in vivo by inhibiting autophagy. Free Radic Biol Med. 2012;52:377–91. 10.1016/J.FREERADBIOMED.2011.10.487. [DOI] [PubMed] [Google Scholar]
- 16.Gan J, Wang F, Mu D, Qu Y, Luo R, Wang Q. RNA interference targeting Aurora-A sensitizes glioblastoma cells to temozolomide chemotherapy. Oncol Lett. 2016;12:4515–23. 10.3892/OL.2016.5261. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Yu W, Zhang L, Wei Q, Shao A. O6-methylguanine-DNA methyltransferase (MGMT): challenges and new opportunities in glioma chemotherapy. Front Oncol. 2020;9:1–11. 10.3389/FONC.2019.01547. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bai P, Fan T, Wang X, Zhao L, Zhong R, Sun G. Modulating MGMT expression through interfering with cell signaling pathways. Biochem Pharmacol. 2023;215:1–18. 10.1016/j.bcp.2023.115726. [DOI] [PubMed] [Google Scholar]
- 19.Wu SR, Sharpe J, Tolliver J, Groth AJ, Chen R, Guerra García ME, et al. Combining the RCAS/tv-a retrovirus and CRISPR/Cas9 gene editing systems to generate primary mouse models of diffuse midline glioma. Neoplasia. 2025;62:1–10. 10.1016/j.neo.2025.101139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.National Center for Biotechnology Information. Temozolomide: compound summary 2025. https://pubchem.ncbi.nlm.nih.gov/compound/temozolomide [Accessed 17 Aug 2025].
- 21.European Medicines Agency. Temodal: summary of product characteristics. 2024. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/temodal. [Accessed 17 Aug 2025].
- 22.Tomar MS, Kumar A, Srivastava C, Shrivastava A. Elucidating the mechanisms of temozolomide resistance in gliomas and the strategies to overcome the resistance. Biochim Biophys Acta Rev Cancer. 2021;1876:1–15. 10.1016/j.bbcan.2021.188616. [DOI] [PubMed] [Google Scholar]
- 23.Miranda A, Blanco-Prieto M, Sousa J, Pais A, Vitorino C. Breaching barriers in glioblastoma. Part I: molecular pathways and novel treatment approaches. Int J Pharm. 2017;531:372–88. 10.1016/j.ijpharm.2017.07.056. [DOI] [PubMed] [Google Scholar]
- 24.Wick W, Weller M, Van Den Bent M, Sanson M, Weiler M, Von Deimling A, et al. MGMT testing: the challenges for biomarker-based glioma treatment. Nat Rev Neurol. 2014;10:372–85. 10.1038/nrneurol.2014.100. [DOI] [PubMed] [Google Scholar]
- 25.Malmström A, Łysiak M, Kristensen BW, Hovey E, Henriksson R, Söderkvist P. Do we really know who has an MGMT methylated glioma? Results of an international survey regarding use of MGMT analyses for glioma. Neuro-oncol Pract. 2020;7:68–76. 10.1093/nop/npz039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Rocha CRR, Rocha AR, Silva MM, Gomes LR, Latancia MT, Tomaz MA, et al. Revealing temozolomide resistance mechanisms via genome-wide crispr libraries. Cells. 2020;9(2573):1–17. 10.3390/cells9122573. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Li X, Zhang W, Fang Y, Sun T, Chen J, Tian R. Large-scale CRISPRi screens link metabolic stress to glioblastoma chemoresistance. J Transl Med. 2025;23(289):1–18. 10.1186/s12967-025-06261-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Zhou J, Tong F, Zhao J, Cui X, Wang Y, Wang G, et al. Identification of the E2F1-RAD51AP1 axis as a key factor in MGMT-methylated GBM TMZ resistance. Cancer Biol Med. 2023;20:385–400. 10.20892/j.issn.2095-3941.2023.0011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Han B, Meng X, Wu P, Li Z, Li S, Zhang Y, et al. ATRX/EZH2 complex epigenetically regulates FADD/PARP1 axis, contributing to TMZ resistance in glioma. Theranostics. 2020;10:3351–65. 10.7150/thno.41219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Wang Q, Liu X, Zhou J, Yang C, Wang G, Tan Y, et al. The CRISPR-Cas13a gene-editing system induces collateral cleavage of RNA in glioma cells. Adv Sci. 2019;6:1–7. 10.1002/advs.201901299. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Lang F, Cornwell JA, Kaur K, Elmogazy O, Zhang W, Zhang M, et al. Abrogation of the G2/M checkpoint as a chemosensitization approach for alkylating agents. Neuro Oncol. 2024;26:1083–96. 10.1093/neuonc/noad252. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Chow RD, Guzman CD, Wang G, Schmidt F, Youngblood MW, Ye L, et al. AAV-mediated direct in vivo CRISPR screen identifies functional suppressors in glioblastoma. Nat Neurosci. 2017;20:1329–41. 10.1038/nn.4620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hegge B, Sjøttem E, Mikkola I. Generation of a PAX6 knockout glioblastoma cell line with changes in cell cycle distribution and sensitivity to oxidative stress. BMC Cancer. 2018;18(496):1–19. 10.1186/s12885-018-4394-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Zhao J, Cui X, Zhan Q, Zhang K, Su D, Yang S, et al. CRISPR-Cas9 library screening combined with an exosome-targeted delivery system addresses tumorigenesis/TMZ resistance in the mesenchymal subtype of glioblastoma. Theranostics. 2024;14:2835–55. 10.7150/thno.92703. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Budhiraja S, McManus G, Baisiwala S, Perrault EN, Cho S, Saathoff M, et al. ARF4-mediated retrograde trafficking as a driver of chemoresistance in glioblastoma. Neuro Oncol. 2024;26:1421–37. 10.1093/neuonc/noae059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.MacLeod G, Bozek DA, Rajakulendran N, Monteiro V, Ahmadi M, Steinhart Z, et al. Genome-wide CRISPR-Cas9 screens expose genetic vulnerabilities and mechanisms of temozolomide sensitivity in glioblastoma stem cells. Cell Rep. 2019;27:971-86.e9. 10.1016/j.celrep.2019.03.047. [DOI] [PubMed] [Google Scholar]
- 37.European Medicines Agency. Lynparza. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/lynparza. [Accessed 30 May 2026].
- 38.NCT05463848: surgical pembro +/- olaparib w TMZ for rGBM. Available from: https://clinicaltrials.gov/study/NCT05463848?cond=Glioblastoma&intr=Olaparib&viewType=Card&rank=1/ [Accessed 30 May 2026].
- 39.Lang F, Kaur K, Zaheer J, Ribeiro DL, Yang C. Myt1kKinase: an emerging cell-cycle regulator for cancer therapeutics. Clin Cancer Res. 2025;31:960–4. 10.1158/1078-0432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Tomović Pavlović K, Kocić G, Šmelcerović A. Myt1 kinase inhibitors: insight into structural features, offering potential frameworks. Chem Biol Interact. 2024:1–9. 10.1016/j.cbi.2024.110901. [DOI] [PubMed] [Google Scholar]
- 41.Yang Y, Tian Z, Guo R, Ren F. Nrf2 inhibitor, brusatol in combination with trastuzumab exerts synergistic antitumor activity in HER2-positive cancers by inhibiting Nrf2/HO-1 and HER2-AKT/ERK1/2 pathways. Oxid Med Cell Longev. 2020;2020:1–14. 10.1155/2020/9867595. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Harder B, Tian W, La Clair JJ, Tan AC, Ooi A, Chapman E, et al. Brusatol overcomes chemoresistance through inhibition of protein translation. Mol Carcinog. 2017;56:1493–500. 10.1002/MC.22609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Quinn JA, Jiang SX, Reardon DA, Desjardins A, Vredenburgh JJ, Rich JN, et al. Phase II trial of temozolomide plus O6-benzylguanine in adults with recurrent, temozolomide-resistant malignant glioma. J Clin Oncol. 2009;27:1262–7. 10.1200/JCO.2008.18.8417. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Yousefi Y, Nejati R, Eslahi A, Alizadeh F, Farrokhi S, Asoodeh A, et al. Enhancing temozolomide (TMZ) chemosensitivity using CRISPR-dCas9-mediated downregulation of O6-methylguanine DNA methyltransferase (MGMT). J Neurooncol. 2024;169:129–35. 10.1007/s11060-024-04708-0. [DOI] [PubMed] [Google Scholar]
- 45.Weber R, Weller M, Reifenberger G, Vasella F. Epigenetic modification and characterization of the MGMT promoter region using CRISPRoff in glioblastoma cells. Front Oncol. 2024:1–7. 10.3389/fonc.2024.1342114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Han X, Abdallah MOE, Breuer P, Stahl F, Bakhit Y, Potthoff AL, et al. Downregulation of MGMT expression by targeted editing of DNA methylation enhances temozolomide sensitivity in glioblastoma. Neoplasia. 2023;44:1–10. 10.1016/j.neo.2023.100929. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Zapanta Rinonos S, Li T, Pianka ST, Prins TJ, Eldred BSC, Kevan BM, et al. dCas9/CRISPR-based methylation of O-6-methylguanine-DNA methyltransferase enhances chemosensitivity to temozolomide in malignant glioma. J Neurooncol. 2024;166:129–42. 10.1007/s11060-023-04531-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Lin K, Zou C, Hubbard A, Sengelmann S, Goudy L, Wang I-C, et al. Multiplexed epigenetic memory editing using CRISPRoff sensitizes glioblastoma to chemotherapy. Neuro Oncol. 2025;27:1443–57. 10.1093/neuonc/noaf055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Nuñez JK, Chen J, Pommier GC, Cogan JZ, Replogle JM, Adriaens C, et al. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell. 2021;184:2503–19. 10.1016/j.cell.2021.03.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Seijas A, Cora D, Novo M, Al-Soufi W, Sánchez L, Arana ÁJ. CRISPR/Cas9 delivery systems to enhance gene editing efficiency. Int J Mol Sci. 2025;26:4420. 10.3390/IJMS26094420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Lino CA, Harper JC, Carney JP, Timlin JA. Delivering CRISPR: a review of the challenges and approaches. Drug Deliv. 2018;25:1234–57. 10.1080/10717544.2018.1474964. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Du J, Wu Q, Liu C, Wang N, Gong C. CRISPR delivery systems for organ-specific targeting: advances and challenges. Precis Med Eng. 2025;2(4):100048. 10.1016/J.PREME.2025.100048. [Google Scholar]
- 53.Yu X, Zhou Z, Tang S, Zhang K, Peng X, Zhou P, et al. MDK induces temozolomide resistance in glioblastoma by promoting cancer stem-like properties. Am J Cancer Res. 2022;12(10):4825–39. [PMC free article] [PubMed] [Google Scholar]
- 54.Xi X, Ding X, Wang Q, Liu N, Wang B, Wang G, et al. Targeting the MDK/c-Myc complex to overcome temozolomide resistance in glioma. Clin Transl Med. 2025:1–25. 10.1002/CTM2.70359. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Zhao Y, Qin J, Yu D, Liu Y, Song D, Tian K, et al. Polymer-locking fusogenic liposomes for glioblastoma-targeted siRNA delivery and CRISPR–Cas gene editing. Nat Nanotechnol. 2024;19:1869–79. 10.1038/s41565-024-01769-0. [DOI] [PubMed] [Google Scholar]
- 56.Agnihotri S, Burrell K, Buczkowicz P, Remke M, Golbourn B, Chornenkyy Y, et al. ATM regulates 3-methylpurine-DNA glycosylase and promotes therapeutic resistance to alkylating agents. Cancer Discov. 2014;4:1198–213. 10.1158/2159-8290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Wickström M, Dyberg C, Milosevic J, Einvik C, Calero R, Sveinbjörnsson B, et al. Wnt/β-catenin pathway regulates MGMT gene expression in cancer and inhibition of Wnt signalling prevents chemoresistance. Nat Commun. 2015;6:1–10. 10.1038/NCOMMS9904. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Zhang S, Wan Y, Pan T, Gu X, Qian C, Sun G, et al. MicroRNA-21 inhibitor sensitizes human glioblastoma U251 stem cells to chemotherapeutic drug temozolomide. J Mol Neurosci. 2012;47:346–56. 10.1007/S12031-012-9759-8. [DOI] [PubMed] [Google Scholar]
- 59.Lozada-Delgado EL, Grafals-Ruiz N, Vivas-Mejía PE. RNA interference for glioblastoma therapy: innovation ladder from the bench to clinical trials. Life Sci. 2017;188:26–36. 10.1016/J.LFS.2017.08.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Branco F, Cunha J, Mendes M, Sousa JJ, Vitorino C. 3D bioprinting models for glioblastoma: from scaffold design to therapeutic application. Adv Mater. 2025;37:1–39. 10.1002/ADMA.202501994. [DOI] [PubMed] [Google Scholar]
- 61.Liu P, Griffiths S, Veljanoski D, Vaughn-Beaucaire P, Speirs V, Brüning-Richardson A. Preclinical models of glioblastoma: limitations of current models and the promise of new developments. Expert Rev Mol Med. 2021. 10.1017/ERM.2021.20. [DOI] [PubMed] [Google Scholar]
- 62.Pagliaro A, Andreatta F, Finger R, Artegiani B, Hendriks D. Generation of human fetal brain organoids and their CRISPR engineering for brain tumor modeling. Nat Protoc. 2025;20:1846–83. 10.1038/s41596-024-01107-7. [DOI] [PubMed] [Google Scholar]
- 63.Antonica F, Aiello G, Soldano A, Abballe L, Miele E, Tiberi L. Modeling brain tumors: a perspective overview of in vivo and organoid models. Front Mol Neurosci. 2022;15:1–19. 10.3389/fnmol.2022.818696. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Kersten K, de Visser KE, van Miltenburg MH, Jonkers J. Genetically engineered mouse models in oncology research and cancer medicine. EMBO Mol Med. 2016;9:137:53. 10.15252/EMMM.201606857. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Zuckermann M, Hovestadt V, Knobbe-Thomsen CB, Zapatka M, Northcott PA, Schramm K, et al. Somatic CRISPR/Cas9-mediated tumour suppressor disruption enables versatile brain tumour modelling. Nat Commun. 2015;6:1–9. 10.1038/ncomms8391. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Aldape K, Brindle KM, Chesler L, Chopra R, Gajjar A, Gilbert MR, et al. Challenges to curing primary brain tumours. Nat Rev Clin Oncol. 2019;16:509–20. 10.1038/s41571-019-0177-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Platt RJ, Chen S, Zhou Y, Yim MJ, Swiech L, Kempton HR, et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell. 2014;159:440–55. 10.1016/j.cell.2014.09.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Xue W, Chen S, Yin H, Tammela T, Papagiannakopoulos T, Joshi NS, et al. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature. 2014;514:380–5. 10.1038/NATURE13589. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Chiou SH, Winters IP, Wang J, Naranjo S, Dudgeon C, Tamburini FB, et al. Pancreatic cancer modeling using retrograde viral vector delivery and in vivo CRISPR/Cas9-mediated somatic genome editing. Genes Dev. 2015;29:1576–85. 10.1101/GAD.264861.115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Ran FA, Hsu PD, Wright J, Agarwala V, Scott DA, Zhang F. Genome engineering using the CRISPR-Cas9 system. Nat Protoc. 2013;8:2281–308. 10.1038/nprot.2013.143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Casey MJ, Chan PP, Li Q, Zu JF, Jette CA, Kohler M, et al. A simple and scalable zebrafish model of Sonic hedgehog medulloblastoma. Cell Rep. 2024;43:1–21. 10.1016/j.celrep.2024.114559. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Hatcher A, Yu K, Meyer J, Aiba I, Deneen B, Noebels JL. Pathogenesis of peritumoral hyperexcitability in an immunocompetent CRISPR-based glioblastoma model. J Clin Invest. 2020;130:2286–300. 10.1172/JCI133316. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Zhou H, Dai J, Li D, Wang L, Ye M, Hu X, et al. Efficient gene delivery admitted by small metabolites specifically targeting astrocytes in the mouse brain. Mol Ther. 2025;33:1166–79. 10.1016/j.ymthe.2025.01.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Vincent CA, Nissen I, Dakhel S, Hörnblad A, Remeseiro S. Epigenomic perturbation of novel EGFR enhancers reduces the proliferative and invasive capacity of glioblastoma and increases sensitivity to temozolomide. BMC Cancer. 2023;23(945):1–14. 10.1186/s12885-023-11418-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.Bhatt D, Sundaram RK, López KSL, Lee T, Gueble SE, Vasquez JC. Development of syngeneic murine glioma models with somatic mismatch repair deficiency to study therapeutic responses to alkylating agents and immunotherapy. Curr Protoc. 2025. 10.1002/cpz1.70097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Yang X, Zhang B. A review on CRISPR/Cas: a versatile tool for cancer screening, diagnosis, and clinic treatment. Funct Integr Genom. 2023. 10.1007/S10142-023-01117-W. [DOI] [PubMed] [Google Scholar]
- 77.Makarova KS, Shmakov SA, Wolf YI, Mutz P, Altae-Tran H, Beisel CL, et al. An updated evolutionary classification of CRISPR-Cas systems including rare variants. Nat Microbiol. 2025;10:3346–61. 10.1038/s41564-025-02180-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Aliciaslan M, Erbasan E, Erendor F, Sanlioglu S. Advances in CRISPR base editing: from molecular evolution to therapeutic applications in genomic medicine. J Cell Mol Med. 2026:1–39. 10.1111/JCMM.71159. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Vats P, Baweja B, Saini C, Kushwah AS, Kumar A, Srivastava SK, et al. An overview of CRISPR-artificial intelligence theranostics: current and emerging applications. Biomater Transl. 2025;7:79–120. 10.12336/BMT.25.00106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80.Han H, Sun X, Guo X, Wen J, Zhao X, Zhou W. CRISPR/Cas9 technology in tumor research and drug development application progress and future prospects. Front Pharmacol. 2025;16:1–24. 10.3389/FPHAR.2025.1552741/FULL. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Wang KC, Zheng T, Hubbard BP. CRISPR/Cas technologies for cancer drug discovery and treatment. Trends Pharmacol Sci. 2025;46:437–52. 10.1016/j.tips.2025.02.009. [DOI] [PubMed] [Google Scholar]
- 82.Mao X-Y, Dai J-X, Zhou H-H, Liu Z-Q, Jin W-L. Brain tumor modeling using the CRISPR/Cas9 system: state of the art and view to the future. Oncotarget. 2016;7:1–71. 10.18632/oncotarget.8075. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Ferri A, Stagni V, Barilà D. Targeting the DNA damage response to overcome cancer drug resistance in hlioblastoma. Int J Mol Sci. 2020;21(4910):1–18. 10.3390/IJMS21144910. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Li Q, Zhang Z, Wu X, Zhao Y, Liu Y. Cascade-responsive nanoparticles for efficient CRISPR/Cas9-based glioblastoma gene therapy. ACS Appl Mater Interfaces. 2025;17:4480–9. 10.1021/ACSAMI.4C15671. [DOI] [PubMed] [Google Scholar]
- 85.Ciafarone A, Palumbo P, Tai P. The evolution of chemotherapy in brain tumors: from historical milestones to precision medicine in glioblastoma. Explor Target Antitumor Ther. 2026;7:1-21. 10.37349/etat.2026.1002374. [DOI] [PMC free article] [PubMed]
- 86.Biomedicine M, Sung J-Y, Hwang K. Glioblastoma: epidemiology, molecular pathogenesis, diagnosis, management, and therapeutic resistance. Mol Biomed. 2026;7:63. 10.1186/s43556-026-00467-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Xu Y, Li Z. CRISPR-Cas systems: overview, innovations and applications in human disease research and gene therapy. Comput Struct Biotechnol J. 2020;18:2401–15. 10.1016/j.csbj.2020.08.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Renee Parker N, Khong P, Fergus Parkinson J, Maarika Howell V, Ruth Wheeler H, Leanne McDonald K, et al. Molecular heterogeneity in glioblastoma: potential clinical implications. Front Oncol. 2015;5:1–9. 10.3389/fonc.2015.00055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Antonica F, Aiello G, Soldano A, Abballe L, Miele E, Tiberi L. Modeling brain tumors: a perspective overview of in vivo and organoid models. Front Mol Neurosci. 2022;15:818696. 10.3389/FNMOL.2022.818696/FULL. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Köpke K, Zuhorn IS, Kruyt FAE. The biomechanics of glioblastoma: why glioblastoma models and clinical reality diverge highlights: what are the main findings? Cells. 2026;15:1–24. 10.3390/cells15100876. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Sabnis NA, Cooksey LC, Jayakumar H, Mendez MM, Mathew E, Petty RM, et al. Evolving landscape of glioblastoma research: integrating therapeutic advances and diagnostic frontiers. Brain Sci. 2026;16:1–46. 10.3390/brainsci16050487. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.Shih T, Hodeify R, Kaur J, Alnuaimi M, Aboud O. Machine learning-driven metabolomic biomarker discovery in glioblastoma: advances, challenges, and future directions. Int J Mol Sci. 2026;27:1–19. 10.3390/IJMS27093842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Tanner G, Barrow R, Ajaib S, Al-Jabri M, Ahmed N, Pollock S, et al. IDHwt glioblastomas can be stratified by their transcriptional response to standard treatment, with implications for targeted therapy. Genome Biol. 2024;25(24):1–29. 10.1186/s13059-024-03172-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94.Dai Y, Shi C, Zhao K, Tie J, Lian K, Li W, et al. Integrating computational pathology and multi-transcriptomics to characterize glioblastoma heterogeneity and identify prognostic biomarkers. Hum Pathol. 2025;166:1–13. 10.1016/j.humpath.2025.105982. [DOI] [PubMed] [Google Scholar]
- 95.Li J, Zhang L, Yu Z, Bao Z, Li D, Wang L. The impact of AI on modern oncology from early detection to personalized cancer treatment. NPJ Precis Oncol. 2026;10(69):1–18. 10.1038/s41698-026-01276-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96.Zhao Z, Zhang KN, Wang Q, Li G, Zeng F, Zhang Y, et al. Chinese Glioma Genome Atlas (CGGA): a comprehensive resource with functional genomic data from Chinese glioma patients. Genom Proteomics Bioinform. 2021;19:1–12. 10.1016/j.gpb.2020.10.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
