Gliomas represent the most prevalent primary tumors within the central nervous system (CNS), exhibiting an incidence ranging from 1.9 to 9.6 per 100,000 individuals. This incidence variation is contingent upon factors such as age, sex, ethnicity, and geographic location [1]. Historically, tumor classification has relied upon histopathological characteristics and immunohistochemistry (IHC). However, the clinical outcomes and treatment responses of patients with identical morpho logical tumors often diverge due to disparities in the intrinsic genetic characteristics of the tumors. In 2016, the World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS) introduced an integrated diagnostic approach for gliomas, incorporating both pathological and molecular characteristics [2]. Repeated updates to the classification, known as the 5th edition of the 2021 WHO CNS (WHO CNS5), has substantially revolutionized the glioma classification system. This updated version has led to a fundamental change in the classification environment, primarily through the incorporation of numerous molecular biomarkers [3].

Gliomas have been identified to exhibit several genetic alterations that serve as diagnostic, prognostic, predictive, and potentially therapeutic biomarkers. The most frequently reported genetic variations include mutations in genes such as ATRX, BRAF, CDKN2A/B, IDH, NF1, RB1, TP53, telomerase reverse transcriptase promoter (TERTp), and the methylation status of the MGMT promoter. Furthermore, commonly observed genetic features include copy number alterations such as the codeletion of 1p/19q, EGFR amplification, concurrent gain of chromosome 7 along with loss of chromosome 10 (7+/10-), and rearrangements [3].

Depending on the genetic alterations, numerous molecular experimental methods can be used, including Sanger sequencing, quantitative polymerase chain reaction (qPCR) including methylation-specific polymerase chain reaction (MS-PCR), fluorescence in situ hybridization (FISH), and next generation sequencing (NGS) analysis.

NGS technology was designed to enable sequencing of the whole genome, the whole exome, or specific targeted sequences. However, conducting whole genome or exome sequencing is a costly, time-intensive assay, and especially difficult when using small brain biopsy samples, since significant amounts of DNA are required to perform the assay.

Panel-based targeted NGS is designed to sequence specific genes or genetic regions associated with cancer. This approach enables the detection of various genetic alterations, including single nucleotide variants (SNVs), small insertions/deletions (InDels), copy number variations (CNVs), gene fusions, and intragenic deletions. This methodology allows for a rapid turnaround time and is cost-effective. Panel-based targeted NGS provides insights into potentially actionable genetic aberrations, encompassing integrated molecular diagnosis and mutations (SNVs, InDels), CNVs (including gene amplifications), gene fusions, and intragenic deletions [45]. The purpose of this study is to determine the prevalence of genetic alterations and detect actionable target genes through panel-based targeted NGS analysis in glioma patients.

Historically, the diagnosis of CNS tumors has predominantly relied upon light microscopy. The WHO has formulated criteria for the pathological classification and prognostic stratification of gliomas, primarily grounded in the histological characteristics of CNS tumors. Nevertheless, it is important to recognize that tumors with identical morphological appearances may exhibit distinct molecular profiles, which are closely associated with their biological behavior and clinical outcomes. As a consequence, numerous molecular markers have been incorporated into the assessment of CNS tumor diagnoses. These markers are presently instrumental in guiding patient prognosis and dictating suitable treatment approaches.

As clinically relevant molecular alterations increase, the practicality of single gene analysis is decreasing due to the cost efficiency. Therefore, there is a need for high-throughput techniques that can rapidly evaluate various genetic changes in limited neuropathological samples. Currently, there are several restrictions on the use of exome sequencing in neuropathological samples. A large amount of high-quality DNA is required, but this is limited to obtain from FFPE brain biopsy. It also comes with high costs, long turnaround times. Despite the development of diagnosis and treatment procedures, management of glioma samples is still a difficult task.

As a result, NGS technology has garnered increasing attention and developed rapidly. The advantages of this technology include precise analysis of genetic alterations in tumor samples, cost reduction, and swift diagnosis. Utilizing comprehensive panels that employ FFPE samples in both clinical and research domains, various genetic alterations in gliomas can be simultaneously and rapidly identified. This can contribute to the molecular classification of tumors. Applying the advancements of this new technology allows for the identification of established or potential prognostic biomarkers. These biomarkers can contribute to accurate molecular diagnosis and personalized treatment for glioma patients, thereby enhancing clinical outcomes. Our molecular analysis has demonstrated the potential of NGS targeting gliomas to enhance brain tumor classification and aid clinicians in selecting optimal targeted therapies. However, it is noteworthy that our detection panel had limitations, as it did not encompass the detection of MGMT methylation. This particular aspect needs to be assessed separately using alternative methodologies.

In this study, our findings revealed the presence of 301 mutations (SNVs and InDels) in 89.8% of the tumor samples. Among these mutations, TP53, IDH1, TERTp, PIK3CA, EGFR, NF1, PTEN, ATRX, RB1, BRAF, CIC, and PIK3R1 exhibited high incidences in the mutation spectrum, with TP53 being the most prevalent (31.3%). These results were in alignment with those from other studies [6], as the p53 pathway was found to be deregulated in numerous cases. Moreover, the most frequently detected mutations at codon 248 and 273 of the TP53 gene were observed in TP53-positive tumors at comparable frequencies to those reported elsewhere [7]. Additionally, the p.Arg132His variant was present in 97.1% of IDH1 mutant tumors, consistent with findings reported in other studies [8]. Regarding TERTp mutations (23.1%; 34/147), we observed their presence in oligodendrogliomas (62.5%; 10/16), glioblastomas (20.7%, 19/92), and astrocytomas (20.8%, 5/24). These mutations primarily involved the c.-124C>T and c.-146C>T alterations. TERTp mutations occur in 25% to 70% of gliomas, commonly manifesting at two hotspot locations, c.-124C>T and c.-146C>T [910]. The low detection rate of TERTp mutation is attributed to the poor PCR performance on the GC-rich sequence sites of c.-124C>T and c.-146C>T, resulting in a reduction in the hotspot location detection rate. To compensate for the low detection rate as the importance of TERTp mutations in glioma began to be known, the criteria for calling the hotspot position of the TERTp in the analysis algorithm after analysis from 2020 were modified in this study. The revised content made it possible to analyze lower reads, exceptionally even in severe strand biases, and separately monitor the filtering and exclusion of mutations. In this study, all mutations of EGFR were located in at codon 289, codon 598, and codon 108. Common missense mutations identified in EGFR, which are frequently reported in brain cancer, were clustered in the extracellular domain of proteins and included codon 108, codon 289, and codon 598 [11].

In glioma patients, there are associations of the mutational status between mutated genes. IDH1 is often co-mutated with TP53, ATRX, and NOTCH1 [12]. IDH1 mutations were significantly correlated with ATRX, CIC, FUBP1, and NOTCH1 mutant-type in our study (p<0.05). TERTp mutation, mutations in CIC and FUBP1 have been also known as coexisting mutations for the tumorigenesis of oligodendrogliomas [13]. In our study, TERTp mutations were also significantly correlated with CIC and FUBP1 (p<0.05). PIK3CA mutations were found in 13.6% of our study at the same frequency as other report [14]. In our study, PIK3CA mutations were significantly correlated with FGFR1 in diffuse midline glioma and glioblastoma, IDH-wildtype (p<0.05). PIK3CA are commonly mutated genes in H3F3A-mutant in diffuse midline glioma [15]. Diverse cell signaling pathways are implicated in the initiation and progression of gliomas, including those mediated by EGFR/PI3K/AKT/PTEN, which increase capacity to proliferation, invasion, and cell death [16]. In our study, EGFR mutations were correlated in the PTEN mutation type (p<0.05).

We found that the CNV events were detected only in astrocytomas and glioblastomas. Sixty-two out of 147 tumor samples (42.2%) showed evidence of CNV in 25 genes. CNVs were identified most frequently in EGFR (18.4%) followed by PDGFRA (13.6%), CDK4 (10.9%), KIT (9.5%), and MDM4 (6.5%). The amplification of chromosome 7 with EGFR/MET/CDK6 and chromosome 4 with PDGFRA, are commonly detected in gliomas [17]. The identification of CDK4, KIT, MDM4, PDGFRA, and EGFR amplifications is consistent with previous reports as these genetic changes are frequent in glioblastomas [1819]. However EGFR amplification was less detected in our results (28.3%) comparing prevalence (40%–50%) in previous reports of glioblastomas [20]. The low amplification prevalence of other genes, including EGFR amplification, is due to NGS analysis performed at cutoff 6 or higher of CN value. When the cutoff of the CN value is more than 4, the all CNVs of our study are also detected as 83/147 (56.5%), but we significantly detected the cutoff of ≥6 results compared with the tumor cellularity and other IHC results. The cutoff of CN values 4–6 are also detected in all cases and analyzed comprehensively through the validation of the results of the tumor cellularity, chromosome instability, and IHC staining. Also compared to other regions, lower EGFR amplification rates in Asian patients with glioblastoma were recently reported in screening for ILLANCE1 and ILLANCE2 random glioma trials [21].

Associations of CNV status between altered genes were demonstrated in Fig. 4. In our study, the CNV status of EGFR showed a significant correlation with CNV status of MDM4 (p<0.05). The CNV status of CDK4 was correlated with CNV status of KIT, MDM2, and PDGFRA (p<0.05). The type III subfamily of receptor tyrosine kinases, including PDGFRA, KIT, and KDR (VEGFR), has been reported to play important roles in cell survival, proliferation, and angiogenesis [22]. In our study, CNV of PDGFRA were correlated with CNV of KIT and KDR (p<0.05). Similarly, the CNV status of KIT was correlated with KDR (p<0.05).

Twenty-five out of 147 tumor samples (17.0%) showed evidence of gene fusions and intragenic deletion. Intragenic deletion was identified in EGFRvIII (15/147, 10.2%), as same as previous reports [23]. This EGFRvIII was detected in the diagnosis of two subtypes of astrocytoma and glioblastoma. In this study, gene fusions were identified in FGFR3::TACC3, PTPRZ1::MET, ZFTA::RELA, EML4::ALK, CAPZA2::MET, and ST7::MET (10/147, 6.8%). This gene fusions were detected in the diagnosis of 3 types of gliomas: glioblastomas, oligodendroglioma, and supratentorial ependymomas. FGFR::TACC is best described for FGFR fusion in glioblastoma. In glioblastoma, the FGFR2/3::TACC fusion ratio is detected to be about 2.6%–10%, with most estimates in the 3% range [24]. We found three cases of FGFR::TACC3 fusion (3.2%) in glioblastomas. Frattini et al. [25] described that FGFR3::TACC3 fusion can activate oxidative phosphorylation and mitochondrial biosynthesis and induce sensitivity to inhibitors of oxidative metabolic. This finds oncogenic circuits bound by FGFR::TACC fusion in cancer. The MET fusions were limited to high-grade gliomas. The most common gene fusion was PTPRZ1::MET, followed by ST7::MET and CAPZA2::MET, as same as our results [26]. The PTPRZ1::MET fusion is a recently identified gene fusion of glioblastoma. This fusion occurs as a result of intron insertion and tandem duplication between the PTPRZ1 gene located on chromosome 7q31.32 and the closely located MET gene located on chromosome 7q31.2 [27]. The EML4::ALK fusion has been found in lung, breast, and colorectal cancer. High-grade neuroepithelial tumor with EML4::ALK fusion was also reported by Mrowczynski et al. [28]. We found a case of anaplastic oligodendroglioma with EML4::ALK fusion, suggestive of a novel case. This case had IDH1 mutation, 1p/19q codeletion, TERTp mutation, MGMTp methylation, and PIK-3CA mutations. The histopathology of this case shows oligodendroglioma feature with frequent mitosis (8/10 HPF) and microvascular proliferation. EML4::ALK fusion was analyzed as true positive in the review of raw data. However it cannot be ruled out the possibility of false positive, so additional validation is considered necessary. Recurrent ZFTA::RELA fusions were identified in a large fraction (60%–70%) of supratentorial ependymomas [29]. We found two cases (66.7%) of ZFTA::RELA fusion-positive ependymomas in the three cases of supratentorial ependymoma. RELA fusion-positive ependymoma was newly proposed in the WHO CNS, 2016 updated fourth edition. Fusions of zinc finger translocation associated (ZFTA, formerly known as C11orf95) were shown to not only involve RELA, but also other fusion partners, CTNNA2, MAML2/3, NCOA1/2, or MN1. This tumor was then re-classified as supratentorial ependymoma, ZFTA fusion-positive in the WHO CNS 5 [3].

Recognition of potential actionable targets for patients with glioma is very important. The standard treatment of glioblastomas is based on the Stupp protocol following surgical resection, but typically recurs within 6–9 months of diagnosis. The advantage of NGS testing is that it has potential usefulness in detecting clinically relevant genomic changes in various targetable genes for FDA-approved therapy, NCCN guideline therapy, and clinical trials. In our study, 107 patients (72.8% of 147 patients) had alterations on the 11 targetable mutated genes (IDH1, BRAF, NF1, EGFR, TERTp, FGFR, TP53, ATRX, PIK3CA, PIK3R1, and PTEN). Fifty-four patients (36.7% of 147 patients) had alterations on the eight targetable genes (MET, EGFR, PDGFRA, CDK4, KIT, KDR, MDM2, and CDK6). Twenty-three patients (15.6% of 147 patients) had alterations on the three targetable genes (FGFR3::TACC3, EGFRvIII, and MET fusion) with gene fusions and intragenic deletion. These results are consistent with previous evidence in various cohorts of glioma patients reporting rates of actionability ranging between 18% and 55% [30]. In our study, we identified several FDA-approved therapy, NCCN guideline therapy, and ongoing clinical trials investigating targeted therapies for actionable genetic alterations in gliomas and malignant solid tumor filtering by Oncomine Reporter (Tables 5, 6, 7, 8). FDA-approved therapy or NCCN guideline therapy for glioma is targeted for IDH1 and BRAF. A few clinical trials investigating targeted therapies for actionable genetic alterations, such as RAF, EGFR, and FGFR in unspecified solid tumor including gliomas are approved in Ministry of Food and Drug Safety of the Republic of Korea [31]. The targeted therapy of vorasidenib for mutant IDH1 demonstrated very encouraging efficacy and minimal toxicity in a recent, randomized phase III trial in patients with low-grade gliomas [3233]. Successful treatment of gliomas with BRAF V600E-mutation with BRAF/MEK inhibitors has been reported as an objective response rate in high-grade gliomas [34]. Therefore, the BRAF V600E test may recur or change clinical management in progressive glioma. No targeted therapies for TERTp mutations in glioblastoma have been approved for treatment. A variety of approaches targeting TERT activity, including small molecule inhibitors, immunotherapy, and vaccines, are under investigation [35]. A clinical trial (NCT05267106) is ongoing to evaluate the efficacy and safety of pemigatinib, a potent and selective FGFR1-3 inhibitor, in participants previously treated for glioblastoma with FGFR1-3 mutation or fusion (Fight-209) [36]. Paxalisib (GDC-0084) is a small molecule with the ability to penetrate the blood–brain barrier (BBB) and inhibit the PI3K/AKT/Mtor pathway, which is associated with improved overall survival [37]. Evidence of antitumour activity was reported in the Phase 1 Ice-CAP trial (NCT03673787) of ipatasertib and atezolizumab in glioblastoma patients with PTEN mutation [38]. EGFR has been the target of numerous clinical trials in glioblastoma patients, but without positive results. Clinical trials are ongoing evaluating regorafenib for recurrent glioblastoma, as well as EGFR or PDGFR inhibitors, such as erlotinib, lapatinib, and nilotinib, or immunotherapy-based methods for EGFR-overexpressing tumors [394041]. Although these drugs show good anticancer effects in many cases, their use in the treatment of CNS tumor is limited. One of reasons for this is the presence of the BBB which affects drug delivery of drugs to the CNS and inter-patient variability [42]. EGFR inhibitors are not so effective in the treatment of EGFR-amplified glioblastoma patients [4344]. Targetable gene fusions and intragenic deletion involving EGFR, FGFR, or MET represent a promising treatment option for malignant glioma. EGFRvIII intragenic deletion in glioblastoma are frequently targeted by immunotherapy. Autologous chimeric antigen receptor (CAR) T cells targeting EGFRvIII (CAR T-EGFRvIII) has been administrated to treat patients with recurrent glioblastoma [4546]. The identification of FGFR3::TACC3 fusion can help identify diffuse glioma patients who are potentially responsive to targeted therapy with FGFR kinase inhibitors [36]. Clinical trial (NCT05267106) to evaluate the efficacy and safety of pemigatinib, a potent and selective FGFR1-3 inhibitor, in participants with previously treated glioblastoma harboring FGFR1-3 mutation or fusion such as FGFR3::TACC3 (Fight-209) is on-going [47]. A randomized controlled open-label multicenter phase II/III clinical trial (NCT03175224) of a MET inhibitor, bozitinib (synonyms; vebreltinib) targeting PTPRZ1::MET fusion is on-going [48]. A Phase I Study (NCT03598244) of savolitinib in recurrent medulloblastoma, high-grade glioma, diffuse midline glioma, and CNS tumors harboring MET amplification or fusion is on-going [49]. Clinical trial (NCT03993873) of elzovantinib in solid tumors with genetic alterations in MET (SHIELD-1) is on-going [50]. Glumetinib, MET inhibitor, in solid tumors is under development to date (NCT03457532) [51].

In conclusion, we present the results of NGS analysis that detected extensive SNVs, small InDels, CNVs, gene fusions, and intragenic deletions in gliomas detailing the frequency and co-occurrence of genetic alterations in patients with gliomas. We also list genetic alterations with potential therapeutic targets and offer a comprehensive discussion of targeted therapy options. The routine use of multigene NGS analysis, which evaluates multiple relevant markers simultaneously, is an effective way to glioma classification and allows for the identification of a greater number of genetic alterations and rare genomic events, leading to more treatment options for glioma patients. Consequently, NGS analysis is required for diagnosis, prognosis, eligibility for clinical trial enrollment, and treatment decisions in patients with glioma.