Braf and Ras Mutations in Vietnamese Patients With Ameloblastoma

Braf and Ras Mutations in Vietnamese Patients With Ameloblastoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Braf and Ras Mutations in Vietnamese Patients With Ameloblastoma Kien Ai Hoang, Chi Thi Kim Nguyen, Chuong Quoc Ho, Tram Bich Duong, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7773170/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Apr, 2026 Read the published version in BMC Oral Health → Version 1 posted 13 You are reading this latest preprint version Abstract Background Ameloblastoma is a benign but locally aggressive odontogenic tumor. Genetic mutations in the mitogen-activated protein kinase (MAPK) signaling pathway, particularly those in BRAF and RAS , have been increasingly implicated in its pathogenesis, but remain underreported in Vietnamese patients. Methods Ninety-six formalin-fixed paraffin-embedded (FFPE) ameloblastoma samples from Vietnamese patients were retrospectively analyzed. Targeted exons of BRAF and RAS genes were amplified by PCR and sequenced using Sanger sequencing on an ABI 3500 Genetic Analyzer. Mutation frequencies, the prevalence of BRAF V600E , and their associations with clinical, radiographic, and histopathological features were evaluated. Results MAPK pathway mutations were identified in 63.5% of cases. BRAF V600E was the most frequent alteration, detected in 52.1% (50/96) of tumors. BRAF V600E mutations were significantly associated with radiographic radiolucent patterns, and were more common in female than in male patients (pA (p.V8M) (HRAS V8M ), was identified in this study, which has not been previously reported in ameloblastoma or in mutation databases. Conclusions BRAF and RAS mutations are prevalent in Vietnamese patients with ameloblastoma, with BRAF V600E mutation accounting for more than half of the cases. The significant association with BRAF V600E with distinct radiographic features and female gender supports its potential value as a biomarker. In addition, the identification of a novel HRAS mutation, warranting the need for further investigation. Trial registration Not applicable Clinical trial number Not applicable Ameloblastoma BRAF mutation RAS mutation BRAF V600E MAPK pathway Vietnam Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Ameloblastoma is one of the most common odontogenic tumors; however, its reported prevalence varies widely across studies from different countries, ranging from 25.3% to 75.9% [ 1 – 4 ]. In Vietnam, ameloblastoma accounts for 57.3% of odontogenic tumors [ 5 ]. Delayed clinical presentation leads to progressive facial deformity, marked osteolysis with cortical perforation of the mandibular or maxillary periosteum, and subsequent invasion into contiguous anatomical structures. In cases of large tumors, patients may develop marked facial disfigurement, impaired mastication, swallowing, and speech, and in rare instances, ameloblastoma can even be life-threatening [ 6 ]. Surgery remains the mainstay of treatment; however, it is often accompanied by significant osseous defects, and in children or elderly patients with comorbidities, surgery may not represent the optimal therapeutic option. Advancements in sequencing technologies following the Human Genome Project have made genomic analysis more efficient, thereby facilitating investigation of genetic susceptibility and tumor pathogenesis [ 7 ]. From 2014 onwards, several molecular investigations in ameloblastoma have been published, offering new insights into its pathogenesis and management. These studies have highlighted cellular signaling pathways involved in tumorigenesis, among which the MAPK (Mitogen-Activated Protein Kinase) pathway plays a crucial role [ 8 , 9 ]. Mutations in BRAF and RAS , which activate the MAPK cascade, have been consistently reported. Of particular note, BRAF mutations in exon 15 are the most frequent in ameloblastoma, with the substitution of valine by glutamic acid at codon 600 ( BRAF V600E ) in the activation loop accounting for approximately 90% of all BRAF mutations [ 10 ]. Reported frequencies of BRAF V600E mutation vary geographically: 43% in the United States [ 11 ], 72.5% in Thailand [ 12 ], 82% in Brazil [ 13 ], and up to 90% in Korea [ 14 ]. In contrast, RAS mutations in ameloblastoma occur at lower frequencies, with an estimated prevalence of around 20% [ 15 ]. Several studies in different countries have investigated BRAF and RAS mutations in the MAPK signaling pathway, especially BRAF V600E , and demonstrated their pivotal role in the pathogenesis of ameloblastoma. However, the reported frequencies and mutation patterns exhibit substantial variation across populations. In addition, evidence on the occurrence of these mutations and their association with patient demographics, clinicopathological features, and radiological characteristics remains inconsistent. Therefore, we conducted this study to determine the frequency of BRAF and RAS mutations in Vietnamese patients with ameloblastoma and analyze their association with clinical, histopathological, and radiological features. These results will contribute to a more comprehensive understanding of the molecular characteristics of ameloblastoma and expand the existing genetic data on this tumor type in Vietnam. Methods Study design This descriptive cross-sectional study investigated BRAF and RAS mutations in ameloblastomas, and assessed their associations with clinical, radiographic and histopathological features. The study including patients diagnosed with ameloblastoma who were examined and treated at the Department of Oral and Maxillofacial Surgery, Ho Chi Minh City Hospital of Odonto-Stomatology, from January 2021 to January 2025. Inclusion criteria: Histopathologically confirmed diagnosis of ameloblastoma; availability of complete medical records; availability of FFPE tissue blocks, and informed consent to participate in the study. Exclusion criteria: No additional exclusion criteria were applied. The minimum sample size was calculated using the formula for estimating a proportion: n ≥ (Z(1-α/2)/d) 2 .p.(1-p). With α = 0.05 (95% confidence level), Z(1-α/2) = 1.96, p estimated from previous studies, and d = 0.1. Based on published data, the mutation frequency of BRAF in ameloblastoma was 46% (Sweeney, 2014) and that of RAS was 20% (Brown, 2014) [ 15 ]. The corresponding minimum sample size required was 96 cases for BRAF and 62 cases for RAS . Therefore, the larger value (96) was adopted as the target sample size for this study. Data collection Clinical variables (age, sex, and tumor status: primary or recurrent) were retrieved from medical records. Primary status was defined as newly diagnosed ameloblastoma at first presentation, whereas recurrence status referred to patients presenting with a recurrent ameloblastoma after previous surgery, not recurrence observed during prospective follow-up. Radiographic characteristics were evaluated on panoramic radiographs obtained with a Planmeca ProMax 3D unit (Planmeca Oy, Helsinki, Finland) and on computed tomography (CT) scans acquired using a Toshiba Aquilion 640 or Canon Aquilion ONE PRISM 640 system (Canon Medical Systems, Japan), with images reviewed on the integrated Vitrea portable viewer. Radiographic features were recorded according to standardized criteria described by tumor location (Hong [ 16 ]); lesion margin (well-defined with sclerosis, well-defined without sclerosis, or ill-defined) (Li [ 17 ]); radiolucent pattern (unilocular, soap-bubble, honeycomb), cortical bone status (expansion, perforation), type of root resorption (knife-edge, spike, or multiplanar type), and association with impacted teeth (Langlais [ 18 ]). Histopathological data were reviewed on hematoxylin and eosin (H&E) stained-slides, and ameloblastomas were classified according to the 2017 WHO Classification of Head and Neck Tumors. Histopathological subtypes included luminal, mural, mixed, plexiform, follicular, acanthomatous, and desmoplastic variants. All radiographs and histopathological slides were independently evaluated by two investigators. Inter-observer agreement was assessed using Cohen's κ statistic, and discrepancies were resolved by consensus review. Mutation data were proceeded in the following steps: Primer design for PCR and sequencing Reference sequences of BRAF (NG_007873, NM_004333), KRAS (NG_007524, NM_004985), NRAS (NG_007572, NM_002524), and HRAS (NG_007666, NM_005343) were retrieved from the GenBank database (NCBI). Primer pairs targeting frequently mutated regions were designed using CLC Main Workbench v5.5. The primer physical properties were evaluated with Oligo Analyzer 3.1 (Integrated DNA Technologies). Synthesized primers were purchased from Integrated DNA Technologies (IDT, USA). The primer sequences are listed in Table 1 . After primer design, annealing temperatures between 54°C to 62°C were evaluated. PCR reactions were performed for each primer pair to identify the optimal annealing temperature that produced specific and efficient amplification. Table 1 Primer sequences used for amplification of target gene regions Gene Exon Primer name Primer sequence (5’ – 3’) Annealing temperature ( 0 C) Product size (bp) BRAF 11 BRAF-g11F2 TTTCTGTTTGGCTTGACTTG 56 273 BRAF-g11R GTTTATTGATGCGAACAGTG 15 BRAF-600F ACTCTTCATAATGCTTGCTC 55 184 BRAF-600R CCACAAAATGGATCCAGACA KRAS 2 KRAS-E2F AGGCCTGCTGAAAATGACTGAATA 55 178 KRAS-E2R CTGTATCAAAGAATGGTCCTGCAC 3 KRAS-61F TTCTCAGGATTCCTACAGGA 56 194 KRAS-61R AAACCCACCTATAATGGTGA NRAS 2 NRAS-1F GATGTGGCTCGCCAATTAAC 55 232 NRAS-1R GGTAAAGATGATCCGACAAGTG 3 NRAS-61F ACCCCCAGGATTCTTACAGA 197 NRAS-61R CTCCTAGTACCTGTAGAGGT HRAS 2 HRAS-2F CAGGAGACCCTGTAGGAGGA 58 139 HRAS-2R TCGTCCACAAAATGGTTCTG 3 HRAS-3F ATTCCTACCGGAAGCAGGTG 156 HRAS-3R AAGACTTGGTGTTGTTGATG DNA extraction from FFPE tissue Genomic DNA was extracted from FFPE tissue blocks using the ReliaPrep™ FFPE gDNA Miniprep System (Promega, USA) according to the manufacturer’s instructions, yielding 50 µL of gDNA solution. DNA purity was measured with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). Extracted DNA was stored at − 20°C until further use. PCR amplification Target regions of the selected genes were amplified using specifically designed primer pairs. The reaction mixture (15 µL total volume) consisted of 1.5 µL 10× PCR buffer, 1.5 µL dNTPs (2.5 mM), 0.75 µL forward primer (10 µM), 0.75 µL reverse primer (10 µM), 0.1 µL TaKaRa Taq HS polymerase (Takara Bio, Japan), 9.4 µL nuclease-free water, and 1 µL gDNA template. Thermal cycling conditions were optimized for each primer set. The hot-start property of Taq polymerase, achieved by binding a monoclonal antibody, minimized nonspecific priming and reduced primer–dimer formation. Amplification success was confirmed when a clear single band of the expected size was obtained without nonspecific amplification. Gel electrophoresis PCR products were separated on 1% agarose gels prepared in 0.5× TBE buffer, alongside a 1 kb Plus DNA ladder (Thermo Fisher Scientific, USA) as a size reference. Electrophoresis was performed at 100 Volt for 30 minutes. PCR product purification Amplified products were purified using the ExoSAP-IT® PCR Product Cleanup Reagent (Applied Biosystems, USA). Each reaction contained 5 µL PCR product, 1 µL ExoSAP-IT, and 1 µL nuclease-free water. Samples were incubated at 37°C for 15 minutes, followed by enzyme inactivation at 80°C for 15 minutes. Sequencing reactions Purified PCR products were sequenced using the BigDye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, USA) with either forward or reverse primers. Each 9.5 µL reaction contained 0.5 µL BigDye Terminator v3.1 (2.5×), 1.5 µL sequencing buffer (5×), 2 µL primer (1.6 µM), 1 µL purified PCR product, and 4.5 µL nuclease-free water. Cycling conditions consisted of initial denaturation at 96°C for 1 min; 30 cycles of 96°C for 10 s, 50°C for 5 s, and 60°C for 4 min; and a final hold at 4°C. Sequencing primers were manually designed in CLC Main Workbench v5.5 (CLC bio, Denmark) based on validated PCR products. Sequencing product precipitation Sequencing products were precipitated with ammonium acetate and ethanol prior to electrophoresis. Briefly, 12 µL of 5 M NH 4 OAc and 60 µL of 100% ethanol were added to each sample, mixed thoroughly, and transferred to 1.5 mL microcentrifuge tubes. Samples were centrifuged at 14,600 rpm for 20 minutes at 4°C, and the supernatant was discarded. The pellet was washed with 400 µL of 70% ethanol and centrifuged again at 14,600 rpm for 25 minutes at 4°C. After vacuum drying at 48°C, the pellet was resuspended in 17 µL Hi-Di formamide (Applied Biosystems, USA), vortexed, and briefly centrifuged. Samples were then denatured at 96°C for 2 minutes, cooled on ice, and stored at − 30°C for 5 minutes before loading into a 96 well sequencing plate.. Sequencing and data analysis Capillary electrophoresis was performed on an ABI 3500 Genetic Analyzer (Applied Biosystems, USA). Raw sequence data were analyzed with CLC Main Workbench v5.5. Consensus sequences were aligned with reference sequences of BRAF, KRAS, NRAS, and HRAS obtained from GenBank (NCBI) to identify mutations. Statistical analysis Data were entered and analyzed using SPSS version 22.0, and ODAS software. Categorical variables (sex, age groups, radiographic features, histological types) were summarized as frequencies and percentages. Continuous variables were expressed as mean ± standard deviation (SD) for normally distributed data or as median and interquartile range (IQR) for non-normally distributed data. Associations between gene mutations and clinicopathological parameters were assessed using the Chi-square test. Fisher’s exact test was applied when more than 20% of expected cell counts were < 5 or when any expected count was < 1. A p-value < 0.05 was considered statistically significant. Results Clinicopathological characteristics of the study cohort A total of 96 patients with ameloblastoma were included, comprising 42 males and 54 females (male-to-female ratio = 0.78:1). The mean age at diagnosis was 32.2 years (SD 16.3; range 8–69 years) with the most common age group being 20–39 years (44.8%). The mandible was the most frequently affected site (89.6%). Most tumors were primary lesions, whereas only five cases (5.2%) represented recurrences. Conventional ameloblastomas accounted for a greater proportion than the unicystic variant (79.2% vs. 20.8%). The distribution of clinical and gross features according to histological type is presented in Table 2 , with no statistically significant differences were observed. Table 2 Distribution of ameloblastoma cases by clinicopathological features Characteristic Total Unicystic type Conventional type p- value N = 96 N = 20 N = 76 Age group 0–19 years 26 (27.1) 7 (26.9) 19 (73.1) 0.399 a 20–39 years 43 (44.8) 8 (18.6) 35 (81.4) 40–59 years 19 (19.8) 5 (26.3) 14 (73.7) ≥ 60 years 8 (8.3) 0 (0.0) 8 (100.0) Sex Female 54 (56.3) 14 (25.9) 40 (74.1) 0.164 b Male 42 (43.8) 6 (14.3) 36 (85.7) Tumor status Primary 91 (94.8) 18 (19.8) 73 (80.2) 0.278 a Recurrent 5 (5.2) 2 (40.0) 3 (60.0) Tumor location Maxilla 10 (10.4) 3 (30.0) 7 (70.0) 0.430 a Mandible 86 (89.6) 17 (19.8) 69 (80.2) a Fisher’s exact test b Chi-square test Frequency and mutation patterns of BRAF and RAS genes in the MAPK pathway Amplification of the target regions of BRAF and RAS genes was performed using specifically designed primer pairs, and the resulting PCR products were subsequently resolved by electrophoresis on 1% agarose gels (Fig. 1). Figure 1. Gel electrophoresis of PCR products from BRAF and RAS genes. Wells 1: BRAF exon 11; Wells 3: BRAF exon 15; Wells 5: KRAS exon 2; Wells 7: KRAS exon 3; Wells 9: NRAS exon 2; Wells 11: NRAS exon 3; Wells 13: HRAS exon 2; Wells 15: HRAS exon 3. H₂O (negative control): wells 2, 4, 6, 8, 10, 12, 14, and 16. Mutations in the MAPK pathway were identified in 61 of 96 cases (63.5%). Alterations in the BRAF gene were found in 55 cases (57.3%), whereas RAS mutations were detected in 6 cases (6.3%). A total of nine distinct mutation types were identified. Most alterations occurred as single mutations, with the BRAF V600E substitution being predominant, detected in 50 cases (52.1%) and representing 90.9% of all BRAF mutations (Table 3 ). Table 3 Frequency and mutation patterns of BRAF and RAS genes in the MAPK pathway Mutation type Frequency (N = 96) Percentage (%) MAPK pathway mutations 61 63.5 BRAF mutations 55 53.7 Exon 11: c.1333G > A (D445N), c.1375G > A (K459M), c.1397 G > A (G466E) 3 3.1 Exon 15: c.1789G > A (V600M), c.1828T > C (F610L) 2 2.1 Exon 15: c.1799T > A (V600E) 50 52.1 RAS mutations 6 6.3 KRAS (exon 2): c.35G > T (G12C), c.50G > A (S17N) 2 2.1 NRAS (exon 2): c.34G > A (G12S) 1 1 HRAS (exon 2): c.31G > A (A11T), c.22G > A (V8M) 2 2.1 HRAS (exon 3): c.205G > A (D69N) 1 1 The BRAF V600E mutation identified in the study is a point mutation in which thymine (T) at nucleotide position 1799 is replaced by adenine (A) (c.1799T > A) (Fig. 2). In addition, a novel HRAS mutation, c.22G > A (p.V8M), was identified in case 3, characterized by a soap-bubble radiolucent lesion with well-defined, non-sclerotic margins and an acanthomatous histological pattern (Fig. 3). Figure 2. Mutation c.1799T > A (p.Val600Glu) in exon 15 codon 600 of BRAF gene ( BRAF V600E ) (50/96 cases) Figure 3 . Mandibular ameloblastoma with HRAS V8M mutation (case 3): (a) Mutation c.22G > A (p.Val8Met) in exon 2 codon 8 of HRAS , (b) Radiograph showing a soap-bubble radiolucent lesion with well-defined, non-sclerotic margins, and (c) Acanthomatous histological pattern (×40). Association between BRAF and RAS mutations in the MAPK pathway and clinicopathological and radiographic features Table 4 Mean age of patients according to mutation status Mean age (years) Standard deviation (SD) p-value MAPK pathway mutations Absent 33.2 18 0.635 Present 31.6 15.4 BRAF V600E mutation Absent 31.6 17.3 0.745 Present 32.7 15.5 Independent samples t-test assuming equal variances The mean age in mutation-positive and mutation-negative groups ranged from 31 to 34 years, with no statistically significant difference between them (Table 4 ). Table 5. Association between gene mutations and clinicopathological features a Fisher’s exact test b Chi-square test The highest frequency of MAPK pathway mutations was observed in the 40–59 year age group (68.4%). Mutation rates were higher in recurrent tumors compared with primary tumors for both overall MAPK pathway mutations and specifically for BRAF V600E (80% vs. 60%, respectively), although these differences were not statistically significant. Female patients exhibited a significant higher prevalence of BRAF V600E mutations compared with males (61.1% vs. 40.5%) (Fisher’s exact test, p = 0.045) (Table 5 ). Table 6. Association between gene mutations and radiographic features a Fisher’s exact test b Chi-square test. In the MAPK pathway, mutations were more frequent in mandibular than in maxillary tumors (65.1% vs. 50.0%). Within the mandible, the highest frequency occurred in the symphysis–body region (66.7%). Mutations tended to be more common in ameloblastomas exhibiting a soap-bubble pattern, well-defined without sclerotic margins, absence of impacted teeth, spike type root resorption, and cortical expansion; however, these associations did not reach statistical significance. BRAF V600E mutations were also more prevalent in mandibular than in maxillary tumors (54.7% vs. 30.0%), with the highest prevalence in the angle–ramus region (59.3%). Notably, BRAF V600E mutations were significantly associated with radiolucent patterns (soap-bubble and unilocular) (p = 0.040). (Table 6 ; Fig. 4). Figure 4 . Radiographic features of mandibular ameloblastomas with different BRAF mutations. (a) Case 83: BRAF V600E mutation, soap-bubble radiolucency with well-defined, without sclerotic margins in the left mandibular body. (b) Case 21: BRAF D445N mutation, honeycomb radiolucency with ill-defined margins in the symphysis region. (c) Case 58: BRAF V600E mutation, unilocular radiolucency with well-defined and sclerotic margins in the left mandibular ramus Table 7 . Association between gene mutations and histopathological features a Chi-square test b Fisher’s exact test MAPK pathway mutations, including BRAF V600E , were more frequent in unicystic than conventional ameloblastomas (75% vs. 60.5% and 70% vs. 47.4%, respectively). By histological subtype, MAPK mutations were highest in the luminal subtype (80%), while BRAF V600E occurred most often in mural and luminal subtypes (70%). In conventional tumors, the acanthomatous subtype showed the highest MAPK mutation rate (66.7%), and the plexiform subtype exhibited the highest BRAF V600E frequency (58.8%). However, none of these correlation were statistically significant (Table 7 ). Discussion Since 2014, several studies have established the MAPK signaling pathway as the main pathogenic mechanism in ameloblastoma [ 10 , 15 , 19 , 20 ]. The RAS family ( KRAS , NRAS , HRAS ) and BRAF genes are positioned upstream in the cascade and initiate the entire RAS–BRAF–MEK–ERK signaling pathway. Mutations in these genes are sufficient to constitutively activate MAPK signaling, leading to abnormal proliferation and tumor formation [ 9 , 21 ]. Other genes in the MAPK pathway, such as MEK and ERK, have not yet been clinically validated. Therefore, in the present study, we focused on BRAF and RAS mutations, which are the most biologically and clinically relevant and ensure feasibility. In our study, the mean patient age was 32.2 years (± 16.3), ranging from 8 to 69 years, with the most common age group being 20–39 years (44.8%). These demographic findings are consistent with previous reports [ 22 – 25 ]. Ameloblastoma showed no sex predilection in earlier studies [ 23 – 25 ], whereas in our series female patients were slightly more common (male-to-female ratio 0.78:1). Mandibular lesions predominated (89.6%), and the conventional type was more frequent than the unicystic type (79.2% vs. 20.8%), consistent with the literature [ 24 , 26 , 27 ]. These findings support the representativeness of our cohort. RAS mutations in ameloblastoma typically occur in exons 2 and 3 [ 15 , 28 ], while BRAF mutations are most frequently identified in exons 11 and 15 [ 29 ]. Interestingly, mutations in these two genes appear to be mutually exclusive, rarely occurring together [ 11 , 15 , 20 ]. Therefore, in this study, we sequenced BRAF exons 11 and 15 first, and in negative cases we proceeded to RAS sequencing ( NRAS , HRAS , KRAS in exons 2 and 3). Among 96 paraffin-embedded samples, MAPK pathway mutations were identified in 61 cases (63.5%), including 55 BRAF mutations (57.3%) and six RAS mutations (6.3%). The RAS mutation rate was lower than that reported by Brown and Sweeney, who found a prevalence of approximately 20% [ 11 , 15 ]. A systematic review by Guimarães also confirmed that RAS mutations in odontogenic tumors, including ameloblastomas, are uncommon [ 9 ]. This supports the conclusion that BRAF mutations are the main driver in the MAPK pathway, while RAS mutations play a minor role. We detected BRAF V600E mutations in 50 of 96 cases (52.1%). This prevalence is lower than reported in Asian countries such as Korea (90%) [ 14 ], Thailand (72.5%) [ 12 ], Japan, and China (> 70%), but comparable to reports in Europe and the United States (40–65%) [ 30 ]. Ethnic and population differences may partly explain this variability. Moreover, differences in methodology, such as the use of immunohistochemistry (which may yield false positives) versus PCR-based sequencing (which may miss novel variants), may also influence reported frequencies. Nevertheless, most studies consistently report BRAF V600E mutations in more than 50% of cases. In 2020, González et al. reviewed 19 studies involving 611 ameloblastomas and reported a pooled BRAF V600E prevalence of 60% (366/611). In that analysis, single BRAF V600E mutations without co-occurring variants accounted for 93.7% of positive cases, while multiple mutations were present in only 6.3%. This finding explains why targeted therapies directed against BRAF V600E , such as vemurafenib or dabrafenib, may be effective [ 31 ]. In our cohort, 12 MAPK pathway mutations were identified, predominantly as isolated events. All six BRAF variants detected were RAS-independent [ 32 ], with BRAF V600E accounting for 90.9% of all BRAF -mutant cases, consistent with previous reports [ 29 ]. Six RAS variants were identified across NRAS , HRAS , and KRAS in this cohort. Among them, a novel HRAS mutation, c.22G > A (p.Val8Met) (HRAS V8M ) , was detected. The novel mutation occurred in case 3, a 36-year-old female patient with ameloblastoma of the mandibular ramus. The tumor presented as a conventional type with acanthomatous histological pattern, showing a soap-bubble radiolucency, well-defined, non-sclerotic margins, and cortical perforation (Fig. 3). To the best of our knowledge, this variant has not been previously reported in mutation databases. HRAS alterations are generally rare in odontogenic tumors, with most molecular studies documenting only sporadic cases at codons 12, 13, or 61[ 33 ]. The identification of HRAS V8M therefore expands the mutational spectrum of HRAS and provides further evidence of the genetic heterogeneity underlying this neoplasm. Although the biological significance of this substitution remains to be determined, its location within the N-terminal region of HRAS suggests a potential role in altering protein conformation and driving aberrant activation of the MAPK/ERK signaling cascade. Similar early-codon RAS variants have been implicated in oncogenesis in other tumor types [ 34 ], supporting the hypothesis that this mutation may also act as an activating event. Future functional studies are warranted to establish its oncogenic potential and to clarify whether it influences sensitivity or resistance to targeted inhibitors currently under investigation for RAS/MAPK-driven tumors. Overall, the identification of this novel HRAS mutation highlights the importance of comprehensive genetic profiling in ameloblastoma and underscores the need for larger, multicenter studies to clarify its prevalence and clinical relevance. The mean age of patients with and without MAPK mutations was similar (31–34 years). The 40–59-year group had the highest frequency of mutations (68.4%), but this difference was not statistically significant. This finding differs from Bonacina and Kelppe, who reported lower mean ages in BRAF V600E -positive cases [ 35 , 36 ]. Most previous studies found no sex-related difference in BRAF V600E prevalence [ 30 , 36 , 37 ]. However, in our series, females had a significantly higher frequency of BRAF V600E mutations compared with males (61.1% vs. 40.5%, Fisher’s exact test, p = 0.045). This unexpected finding contradicts most of the published literature and raises questions about potential biological or population-specific factors underlying the observed disparity. One plausible hypothesis is the influence of sex hormones on MAPK pathway activity. Experimental studies in breast and thyroid cancer cells have demonstrated that estrogen can activate RAF–MEK–ERK signaling [ 38 , 39 ]. In addition, investigations in thyroid cancer [ 40 ] and cancer in general [ 41 ] have also reported a link between estrogen and MAPK pathway activation. These findings suggest that hormonal influences may partly explain the higher frequency of BRAF V600E mutations observed in females in our cohort. Alternatively, this difference may be related to genetic or epigenetic characteristics specific to the Vietnamese population, which could modify susceptibility to mutation. Three of the five recurrent cases harbored the BRAF V600E mutation and one carried a RAS mutation. The overall mutation frequency in the recurrent group was higher than in the primary group (80% for MAPK pathway mutations and 60% for BRAF V600E ), although the difference did not reach statistical significance. Given the small number of recurrent cases, meaningful comparison with other studies was limited, and previous reports have also shown no significant difference in recurrence risk between BRAF V600E -mutant and wild-type cases [ 35 , 36 , 42 ]. Nevertheless, the trend toward higher mutation frequency in recurrent tumors observed in our cohort suggests a potential role of MAPK pathway activation in disease persistence and progression. BRAF V600E -positive clones may have enhanced proliferative capacity or resistance to conventional treatment, thereby contributing to recurrence. Clinically, these findings highlight the need for vigilant longterm follow-up in patients with MAPK pathway–mutant ameloblastomas, particularly those harboring BRAF V600E . Moreover, the potential application of BRAF inhibitors or combined targeted approaches in recurrent or refractory cases deserves consideration, in light of emerging evidence of therapeutic benefit in other BRAF V600E -driven tumors. In this study, MAPK pathway mutations were more frequent in mandibular than maxillary tumors, with the symphysis–body region showing the highest prevalence, whereas BRAF V600E mutations were most frequent in the angle-ramus region. Consistent with our findings, previous studies have also reported that BRAF mutations predominate in the mandible, while RAS mutations are more frequently detected in the maxilla [ 20 ]. There is currently limited research on the association between BRAF and RAS mutations and the radiographic features of ameloblastoma. Therefore, we investigated this relationship across several parameters, including radiolucent pattern, leision margin characteristics, presence of impacted teeth within the lesion, root resorption, and cortical bone alterations [ 17 , 18 , 43 ]. Our findings revealed that ameloblastomas with a unilocular or soap-bubble radiolucent pattern had a significantly higher frequency of BRAF V600E mutations compared with other patterns (Fisher’s exact test, p = 0.04). This observation suggests that specific radiographic features may reflect underlying molecular alterations and could serve as useful markers for prognostication. Nevertheless, radiographic appearance is not determined solely by genetic background but may also be influenced by the timing of clinical presentation. Given the slow growing and often asymptomatic nature of ameloblastoma, many patients present only when the tumor has enlarged, which results in more advanced imaging features such as multilocularity, cortical perforation, or extensive root resorption [ 44 – 46 ]. Thus, part of the association between BRAF V600E mutations and distinct radiographic patterns in our cohort may have been confounded by symptom duration at diagnosis. Future studies with larger cohorts should adjust for both disease duration and tumor size to validate imaging–genotype correlations and clarify the biological mechanisms by which BRAF V600E mutations contribute to bone resorption. MAPK pathway mutations and BRAF V600E mutations were more common in unicystic than conventional ameloblastomas (75% vs. 70%). These findings are consistent with Guimarães [ 9 ], González [ 31 ], Bonacina [ 35 ], and Kelppe [ 36 ]. Among histological subtypes, the plexiform subtype showed the highest BRAF V600E prevalence (58.8%), consistent with the findings of Shirsat [ 47 ]. These parallels suggest possible biological differences among histopathological variants. Notably, the higher frequency of mutations in unicystic ameloblastomas may partly explain their more indolent clinical behavior and responsiveness to targeted therapy compared with conventional forms. Furthermore, the predominance of BRAF V600E in the plexiform pattern raises the possibility that distinct molecular mechanisms drive tumor architecture. Taken together, these results support the hypothesis that genetic alterations not only influence tumor initiation but may also contribute to the histopathological phenotype and clinical course of ameloblastomas. In summary, this study is strengthened by its relatively large sample size, the application of reliable gene sequencing methods, and comprehensive analyses integrating clinical, radiographic, and histopathological features. However, certain limitations should be acknowledged, including its single-center design in Ho Chi Minh City, the descriptive cross-sectional nature, and the absence of long-term follow-up data on recurrence. Conclusions BRAF V600E mutation was the most prevalent genetic alteration in Vietnamese patients with ameloblastoma, occurring in more than half of cases, whereas RAS mutations were rare, with one novel variant detected. Furthermore, BRAF V600E mutaion was significantly associated with sex and radiographic features, being more common in females and correlated with distinct radiolucent patterns. These findings highlight the pivotal role of MAPK signaling pathway alterations in ameloblastoma and warrant further studies to elucidate their pathogenesis and therapeutic implication. Abbreviations CT Computed tomography H &E Hematoxylin and Eosin MAPK Mitogen-Activated Protein Kinase FFPE Formalin-fixed paraffin-embedded SD Standard deviation IQR interquartile range Declarations Ethics approval and consent to participate This study was reviewed and approved by the Ethics Committee in Biomedical Research, University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam (Approval No. 272/HĐĐĐ-ĐHYD, dated March 9, 2023). Written informed consent was obtained from all participants. Retrospective patients provided written consent during follow-up visits and prospective patients provided written consent during treatment. Clinical trial number: not applicable. Consent for publication Not applicable. Availability of data and materials The nucleotide sequence corresponding to the novel HRAS variant (c.22G>A; p.V8M) identified in this study has been deposited in the GenBank repository (Submission ID: 3012939). The permanent accession number will be provided upon release by GenBank and updated in both the manuscript and the editorial system. All other genetic variants analyzed in this study are previously reported and have corresponding stable public database identifiers (ClinVar, COSMIC, dbSNP). Stable database identifiers for non-novel variants: BRAF c.1375G>A (p.Val459Met, V459M): COSMIC COSM10284879 BRAF c.1333G>A (p.Asp445Asn, D445N): ClinVar RCV00044227; dbSNP rs752429313 BRAF c.1397G>A (p.Gly466Glu, G466E): ClinVar RCV000442274; COSMIC COSM453 BRAF c.1828T>C (p.Phe610Leu, F610L): dbSNP rs2128998190 BRAF c.1798G>A (p.Val600Met, V600M): ClinVar RCV000429286; COSMIC COSM1130 BRAF c.1799T>A (p.Val600Glu, V600E): ClinVar RCV000067669; COSMIC COSM476 KRAS c.35G>T (p.Gly12Val, G12V): COSMIC COSM520; ClinVar RCV000154262 KRAS c.50G>A (p.Ser17Asn, S17N): ClinVar RCV002292309; COSMIC COSM51382 NRAS c.34G>A (p.Gly12Ser, G12S): ClinVar RCV000421327; COSMIC COSM563 HRAS c.31G>A (p.Ala11Thr, A11T): COSMIC COSM4193616 HRAS c.205G>A (p.Asp69Asn, D69N): COSMIC COSM6009011 Competing interests The authors declare that they have no competing interests. Funding This research was funded by the University of Medicine and Pharmacy at Ho Chi Minh City under contract number 263/2023 /HĐ-ĐHYD, dated 17/10/2023. Authors’ contributions KAH conceived and designed the study, collected and analyzed the data, and drafted the manuscript. CQH, TBD, TTTL, and TTTB assisted with laboratory procedures, pathology review, and data interpretation. NCNH revised the manuscript to correct formatting inconsistencies and typographical errors. TDV, CTKN contributed to manuscript revision prior to submission. TDV, CTKN, and VAH supervised the project and provided scientific guidance. All authors contributed to the critical revision of the manuscript and approved the final version. Acknowledgements The authors thank the Odonto-Maxillo-Facial Hospital of Ho Chi Minh City and the Center for Molecular Biomedicine, University of Medicine and Pharmacy at Ho Chi Minh City, for supporting this study. 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Cite Share Download PDF Status: Published Journal Publication published 13 Apr, 2026 Read the published version in BMC Oral Health → Version 1 posted Editorial decision: Revision requested 01 Jan, 2026 Reviews received at journal 31 Dec, 2025 Reviews received at journal 24 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviewers agreed at journal 21 Dec, 2025 Reviewers agreed at journal 20 Dec, 2025 Reviewers agreed at journal 18 Dec, 2025 Reviewers agreed at journal 18 Dec, 2025 Reviewers invited by journal 18 Dec, 2025 Editor invited by journal 09 Dec, 2025 Editor assigned by journal 14 Oct, 2025 Submission checks completed at journal 14 Oct, 2025 First submitted to journal 14 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":1000754,"visible":true,"origin":"","legend":"\u003cp\u003eGel electrophoresis of PCR products from \u003cem\u003eBRAF\u003c/em\u003eand \u003cem\u003eRAS \u003c/em\u003egenes. Wells 1: \u003cem\u003eBRAF \u003c/em\u003eexon 11; Wells 3: \u003cem\u003eBRAF\u003c/em\u003e exon 15; Wells 5: \u003cem\u003eKRAS\u003c/em\u003e exon 2; Wells 7: \u003cem\u003eKRAS\u003c/em\u003e exon 3; Wells 9: \u003cem\u003eNRAS\u003c/em\u003e exon 2; Wells 11: \u003cem\u003eNRAS\u003c/em\u003e exon 3; Wells 13: \u003cem\u003eHRAS\u003c/em\u003e exon 2; Wells 15: \u003cem\u003eHRAS\u003c/em\u003e exon 3. H₂O (negative control): wells 2, 4, 6, 8, 10, 12, 14, and 16.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7773170/v1/ed919be8a686422721a5ac1c.png"},{"id":98820954,"identity":"79d1d073-9ca0-40b6-bd78-feb348ccb009","added_by":"auto","created_at":"2025-12-22 17:19:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":716925,"visible":true,"origin":"","legend":"\u003cp\u003eMutation c.1799T\u0026gt;A (p.Val600Glu) in exon 15 codon 600 of \u003cem\u003eBRAF \u003c/em\u003egene (\u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e) (50/96 cases)\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7773170/v1/422232fbe9251c2576269f50.png"},{"id":99307303,"identity":"a46e0515-8775-437d-9900-20b823f92f0a","added_by":"auto","created_at":"2025-12-31 16:05:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2084914,"visible":true,"origin":"","legend":"\u003cp\u003eMandibular ameloblastoma \u003cem\u003ewith HRAS\u003c/em\u003e\u003csup\u003eV8M\u003c/sup\u003e mutation (case 3): (a) Mutation c.22G\u0026gt;A (p.Val8Met) in exon 2 codon 8 of \u003cem\u003eHRAS\u003c/em\u003e, (b) Radiograph showing a soap-bubble \u0026nbsp;radiolucent lesion with well-defined, non-sclerotic margins, and (c) Acanthomatous histological pattern \u0026nbsp;(×40).\u003c/p\u003e","description":"","filename":"Figure3ac.png","url":"https://assets-eu.researchsquare.com/files/rs-7773170/v1/870d94430ddc7a05e76395bc.png"},{"id":99307368,"identity":"840b1ec3-ad0d-4838-b520-f71e3a4a93bc","added_by":"auto","created_at":"2025-12-31 16:06:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2383451,"visible":true,"origin":"","legend":"\u003cp\u003eRadiographic features of mandibular ameloblastomas with different \u003cem\u003eBRAF\u003c/em\u003e mutations. (a) Case 83: \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e\u003cem\u003e \u003c/em\u003emutation, soap-bubble radiolucency with well-defined, without sclerotic margins in the left mandibular body. (b) Case 21: \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eD445N\u003c/sup\u003e\u003cem\u003e \u003c/em\u003emutation, honeycomb radiolucency with ill-defined margins in the symphysis region. (c) Case 58: \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e\u003cem\u003e \u003c/em\u003emutation, unilocular radiolucency with well-defined and sclerotic margins in the left mandibular ramus\u003c/p\u003e","description":"","filename":"Figure4ac.png","url":"https://assets-eu.researchsquare.com/files/rs-7773170/v1/55a04980cacf817e8a692643.png"},{"id":107351162,"identity":"b368ea58-2b52-4b0e-90fb-c2866d2e0a6c","added_by":"auto","created_at":"2026-04-20 16:09:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7002795,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7773170/v1/b97eec17-20f7-44bb-9ce6-3bd5647eba36.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBraf and Ras Mutations in Vietnamese Patients With Ameloblastoma\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eAmeloblastoma is one of the most common odontogenic tumors; however, its reported prevalence varies widely across studies from different countries, ranging from 25.3% to 75.9% [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In Vietnam, ameloblastoma accounts for 57.3% of odontogenic tumors [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Delayed clinical presentation leads to progressive facial deformity, marked osteolysis with cortical perforation of the mandibular or maxillary periosteum, and subsequent invasion into contiguous anatomical structures. In cases of large tumors, patients may develop marked facial disfigurement, impaired mastication, swallowing, and speech, and in rare instances, ameloblastoma can even be life-threatening [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Surgery remains the mainstay of treatment; however, it is often accompanied by significant osseous defects, and in children or elderly patients with comorbidities, surgery may not represent the optimal therapeutic option.\u003c/p\u003e \u003cp\u003eAdvancements in sequencing technologies following the Human Genome Project have made genomic analysis more efficient, thereby facilitating investigation of genetic susceptibility and tumor pathogenesis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. From 2014 onwards, several molecular investigations in ameloblastoma have been published, offering new insights into its pathogenesis and management. These studies have highlighted cellular signaling pathways involved in tumorigenesis, among which the MAPK (Mitogen-Activated Protein Kinase) pathway plays a crucial role [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Mutations in \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e, which activate the MAPK cascade, have been consistently reported. Of particular note, \u003cem\u003eBRAF\u003c/em\u003e mutations in exon 15 are the most frequent in ameloblastoma, with the substitution of valine by glutamic acid at codon 600 (\u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e) in the activation loop accounting for approximately 90% of all \u003cem\u003eBRAF\u003c/em\u003e mutations [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Reported frequencies of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation vary geographically: 43% in the United States [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], 72.5% in Thailand [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], 82% in Brazil [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and up to 90% in Korea [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In contrast, \u003cem\u003eRAS\u003c/em\u003e mutations in ameloblastoma occur at lower frequencies, with an estimated prevalence of around 20% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies in different countries have investigated \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e mutations in the MAPK signaling pathway, especially \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e, and demonstrated their pivotal role in the pathogenesis of ameloblastoma. However, the reported frequencies and mutation patterns exhibit substantial variation across populations. In addition, evidence on the occurrence of these mutations and their association with patient demographics, clinicopathological features, and radiological characteristics remains inconsistent. Therefore, we conducted this study to determine the frequency of \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e mutations in Vietnamese patients with ameloblastoma and analyze their association with clinical, histopathological, and radiological features. These results will contribute to a more comprehensive understanding of the molecular characteristics of ameloblastoma and expand the existing genetic data on this tumor type in Vietnam.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis descriptive cross-sectional study investigated BRAF and RAS mutations in ameloblastomas, and assessed their associations with clinical, radiographic and histopathological features.\u003c/p\u003e \u003cp\u003e The study including patients diagnosed with ameloblastoma who were examined and treated at the Department of Oral and Maxillofacial Surgery, Ho Chi Minh City Hospital of Odonto-Stomatology, from January 2021 to January 2025.\u003c/p\u003e \u003cp\u003eInclusion criteria: Histopathologically confirmed diagnosis of ameloblastoma; availability of complete medical records; availability of FFPE tissue blocks, and informed consent to participate in the study.\u003c/p\u003e \u003cp\u003e Exclusion criteria: No additional exclusion criteria were applied.\u003c/p\u003e \u003cp\u003eThe minimum sample size was calculated using the formula for estimating a proportion:\u003c/p\u003e \u003cp\u003en \u0026ge; (Z(1-α/2)/d)\u003csup\u003e2\u003c/sup\u003e.p.(1-p). With α\u0026thinsp;=\u0026thinsp;0.05 (95% confidence level), Z(1-α/2)\u0026thinsp;=\u0026thinsp;1.96, p estimated from previous studies, and d\u0026thinsp;=\u0026thinsp;0.1.\u003c/p\u003e \u003cp\u003eBased on published data, the mutation frequency of \u003cem\u003eBRAF\u003c/em\u003e in ameloblastoma was 46% (Sweeney, 2014) and that of \u003cem\u003eRAS\u003c/em\u003e was 20% (Brown, 2014) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The corresponding minimum sample size required was 96 cases for \u003cem\u003eBRAF\u003c/em\u003e and 62 cases for \u003cem\u003eRAS\u003c/em\u003e. Therefore, the larger value (96) was adopted as the target sample size for this study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eClinical variables (age, sex, and tumor status: primary or recurrent) were retrieved from medical records. Primary status was defined as newly diagnosed ameloblastoma at first presentation, whereas recurrence status referred to patients presenting with a recurrent ameloblastoma after previous surgery, not recurrence observed during prospective follow-up. Radiographic characteristics were evaluated on panoramic radiographs obtained with a Planmeca ProMax 3D unit (Planmeca Oy, Helsinki, Finland) and on computed tomography (CT) scans acquired using a Toshiba Aquilion 640 or Canon Aquilion ONE PRISM 640 system (Canon Medical Systems, Japan), with images reviewed on the integrated Vitrea portable viewer. Radiographic features were recorded according to standardized criteria described by tumor location (Hong [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]); lesion margin (well-defined with sclerosis, well-defined without sclerosis, or ill-defined) (Li [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]); radiolucent pattern (unilocular, soap-bubble, honeycomb), cortical bone status (expansion, perforation), type of root resorption (knife-edge, spike, or multiplanar type), and association with impacted teeth (Langlais [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]). Histopathological data were reviewed on hematoxylin and eosin (H\u0026amp;E) stained-slides, and ameloblastomas were classified according to the 2017 WHO Classification of Head and Neck Tumors. Histopathological subtypes included luminal, mural, mixed, plexiform, follicular, acanthomatous, and desmoplastic variants.\u003c/p\u003e \u003cp\u003eAll radiographs and histopathological slides were independently evaluated by two investigators. Inter-observer agreement was assessed using Cohen's κ statistic, and discrepancies were resolved by consensus review.\u003c/p\u003e \u003cp\u003eMutation data were proceeded in the following steps:\u003c/p\u003e\n\u003ch3\u003ePrimer design for PCR and sequencing\u003c/h3\u003e\n\u003cp\u003eReference sequences of \u003cem\u003eBRAF\u003c/em\u003e (NG_007873, NM_004333), \u003cem\u003eKRAS\u003c/em\u003e (NG_007524, NM_004985), \u003cem\u003eNRAS\u003c/em\u003e (NG_007572, NM_002524), and \u003cem\u003eHRAS\u003c/em\u003e (NG_007666, NM_005343) were retrieved from the GenBank database (NCBI). Primer pairs targeting frequently mutated regions were designed using CLC Main Workbench v5.5. The primer physical properties were evaluated with Oligo Analyzer 3.1 (Integrated DNA Technologies). Synthesized primers were purchased from Integrated DNA Technologies (IDT, USA). The primer sequences are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. After primer design, annealing temperatures between 54\u0026deg;C to 62\u0026deg;C were evaluated. PCR reactions were performed for each primer pair to identify the optimal annealing temperature that produced specific and efficient amplification.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer sequences used for amplification of target gene regions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrimer name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimer sequence\u003c/p\u003e \u003cp\u003e(5\u0026rsquo; \u0026ndash; 3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnnealing temperature (\u003csup\u003e0\u003c/sup\u003eC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProduct size (bp)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBRAF-g11F2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTTTCTGTTTGGCTTGACTTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBRAF-g11R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGTTTATTGATGCGAACAGTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBRAF-600F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eACTCTTCATAATGCTTGCTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBRAF-600R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCACAAAATGGATCCAGACA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKRAS-E2F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAGGCCTGCTGAAAATGACTGAATA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKRAS-E2R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTGTATCAAAGAATGGTCCTGCAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKRAS-61F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTTCTCAGGATTCCTACAGGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKRAS-61R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAACCCACCTATAATGGTGA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNRAS-1F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGATGTGGCTCGCCAATTAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNRAS-1R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGGTAAAGATGATCCGACAAGTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNRAS-61F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eACCCCCAGGATTCTTACAGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNRAS-61R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTCCTAGTACCTGTAGAGGT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eHRAS\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHRAS-2F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCAGGAGACCCTGTAGGAGGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHRAS-2R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTCGTCCACAAAATGGTTCTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHRAS-3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATTCCTACCGGAAGCAGGTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHRAS-3R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAGACTTGGTGTTGTTGATG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eDNA extraction from FFPE tissue\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted from FFPE tissue blocks using the ReliaPrep\u0026trade; FFPE gDNA Miniprep System (Promega, USA) according to the manufacturer\u0026rsquo;s instructions, yielding 50 \u0026micro;L of gDNA solution. DNA purity was measured with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). Extracted DNA was stored at \u0026minus;\u0026thinsp;20\u0026deg;C until further use.\u003c/p\u003e\n\u003ch3\u003ePCR amplification\u003c/h3\u003e\n\u003cp\u003eTarget regions of the selected genes were amplified using specifically designed primer pairs. The reaction mixture (15 \u0026micro;L total volume) consisted of 1.5 \u0026micro;L 10\u0026times; PCR buffer, 1.5 \u0026micro;L dNTPs (2.5 mM), 0.75 \u0026micro;L forward primer (10 \u0026micro;M), 0.75 \u0026micro;L reverse primer (10 \u0026micro;M), 0.1 \u0026micro;L TaKaRa Taq HS polymerase (Takara Bio, Japan), 9.4 \u0026micro;L nuclease-free water, and 1 \u0026micro;L gDNA template. Thermal cycling conditions were optimized for each primer set. The hot-start property of Taq polymerase, achieved by binding a monoclonal antibody, minimized nonspecific priming and reduced primer\u0026ndash;dimer formation. Amplification success was confirmed when a clear single band of the expected size was obtained without nonspecific amplification.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGel electrophoresis\u003c/h2\u003e \u003cp\u003ePCR products were separated on 1% agarose gels prepared in 0.5\u0026times; TBE buffer, alongside a 1 kb Plus DNA ladder (Thermo Fisher Scientific, USA) as a size reference. Electrophoresis was performed at 100 Volt for 30 minutes.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePCR product purification\u003c/h3\u003e\n\u003cp\u003eAmplified products were purified using the ExoSAP-IT\u0026reg; PCR Product Cleanup Reagent (Applied Biosystems, USA). Each reaction contained 5 \u0026micro;L PCR product, 1 \u0026micro;L ExoSAP-IT, and 1 \u0026micro;L nuclease-free water. Samples were incubated at 37\u0026deg;C for 15 minutes, followed by enzyme inactivation at 80\u0026deg;C for 15 minutes.\u003c/p\u003e\n\u003ch3\u003eSequencing reactions\u003c/h3\u003e\n\u003cp\u003ePurified PCR products were sequenced using the BigDye\u0026reg; Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, USA) with either forward or reverse primers. Each 9.5 \u0026micro;L reaction contained 0.5 \u0026micro;L BigDye Terminator v3.1 (2.5\u0026times;), 1.5 \u0026micro;L sequencing buffer (5\u0026times;), 2 \u0026micro;L primer (1.6 \u0026micro;M), 1 \u0026micro;L purified PCR product, and 4.5 \u0026micro;L nuclease-free water. Cycling conditions consisted of initial denaturation at 96\u0026deg;C for 1 min; 30 cycles of 96\u0026deg;C for 10 s, 50\u0026deg;C for 5 s, and 60\u0026deg;C for 4 min; and a final hold at 4\u0026deg;C. Sequencing primers were manually designed in CLC Main Workbench v5.5 (CLC bio, Denmark) based on validated PCR products.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSequencing product precipitation\u003c/h2\u003e \u003cp\u003eSequencing products were precipitated with ammonium acetate and ethanol prior to electrophoresis. Briefly, 12 \u0026micro;L of 5 M NH\u003csub\u003e4\u003c/sub\u003eOAc and 60 \u0026micro;L of 100% ethanol were added to each sample, mixed thoroughly, and transferred to 1.5 mL microcentrifuge tubes. Samples were centrifuged at 14,600 rpm for 20 minutes at 4\u0026deg;C, and the supernatant was discarded. The pellet was washed with 400 \u0026micro;L of 70% ethanol and centrifuged again at 14,600 rpm for 25 minutes at 4\u0026deg;C. After vacuum drying at 48\u0026deg;C, the pellet was resuspended in 17 \u0026micro;L Hi-Di formamide (Applied Biosystems, USA), vortexed, and briefly centrifuged. Samples were then denatured at 96\u0026deg;C for 2 minutes, cooled on ice, and stored at \u0026minus;\u0026thinsp;30\u0026deg;C for 5 minutes before loading into a 96 well sequencing plate..\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSequencing and data analysis\u003c/h2\u003e \u003cp\u003eCapillary electrophoresis was performed on an ABI 3500 Genetic Analyzer (Applied Biosystems, USA). Raw sequence data were analyzed with CLC Main Workbench v5.5. Consensus sequences were aligned with reference sequences of \u003cem\u003eBRAF, KRAS, NRAS, and HRAS\u003c/em\u003e obtained from GenBank (NCBI) to identify mutations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were entered and analyzed using SPSS version 22.0, and ODAS software. Categorical variables (sex, age groups, radiographic features, histological types) were summarized as frequencies and percentages. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for normally distributed data or as median and interquartile range (IQR) for non-normally distributed data.\u003c/p\u003e \u003cp\u003eAssociations between gene mutations and clinicopathological parameters were assessed using the Chi-square test. Fisher\u0026rsquo;s exact test was applied when more than 20% of expected cell counts were \u0026lt;\u0026thinsp;5 or when any expected count was \u0026lt;\u0026thinsp;1. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eClinicopathological characteristics of the study cohort\u003c/h2\u003e\n \u003cp\u003eA total of 96 patients with ameloblastoma were included, comprising 42 males and 54 females (male-to-female ratio\u0026thinsp;=\u0026thinsp;0.78:1). The mean age at diagnosis was 32.2 years (SD 16.3; range 8\u0026ndash;69 years) with the most common age group being 20\u0026ndash;39 years (44.8%). The mandible was the most frequently affected site (89.6%). Most tumors were primary lesions, whereas only five cases (5.2%) represented recurrences. Conventional ameloblastomas accounted for a greater proportion than the unicystic variant (79.2% vs. 20.8%). The distribution of clinical and gross features according to histological type is presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, with no statistically significant differences were observed.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDistribution of ameloblastoma cases by clinicopathological features\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnicystic type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConventional type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ep- value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;96\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;20\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;76\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;19 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.399\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026ndash;39 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35 (81.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14 (73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge; 60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 (74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.164\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36 (85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91 (94.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.278\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaxilla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.430\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMandible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e Fisher\u0026rsquo;s exact test\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003e Chi-square test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eFrequency and mutation patterns of BRAF and RAS genes in the MAPK pathway\u003c/h2\u003e\n \u003cp\u003eAmplification of the target regions of \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e genes was performed using specifically designed primer pairs, and the resulting PCR products were subsequently resolved by electrophoresis on 1% agarose gels (Fig. 1).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure 1.\u003c/strong\u003e Gel electrophoresis of PCR products from \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e genes. Wells 1: \u003cem\u003eBRAF\u003c/em\u003e exon 11; Wells 3: \u003cem\u003eBRAF\u003c/em\u003e exon 15; Wells 5: \u003cem\u003eKRAS\u003c/em\u003e exon 2; Wells 7: \u003cem\u003eKRAS\u003c/em\u003e exon 3; Wells 9: \u003cem\u003eNRAS\u003c/em\u003e exon 2; Wells 11: \u003cem\u003eNRAS\u003c/em\u003e exon 3; Wells 13: \u003cem\u003eHRAS\u003c/em\u003e exon 2; Wells 15: \u003cem\u003eHRAS\u003c/em\u003e exon 3. H₂O (negative control): wells 2, 4, 6, 8, 10, 12, 14, and 16.\u003c/p\u003e\n \u003cp\u003eMutations in the MAPK pathway were identified in 61 of 96 cases (63.5%). Alterations in the \u003cem\u003eBRAF\u003c/em\u003e gene were found in 55 cases (57.3%), whereas \u003cem\u003eRAS\u003c/em\u003e mutations were detected in 6 cases (6.3%). A total of nine distinct mutation types were identified. Most alterations occurred as single mutations, with the \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e substitution being predominant, detected in 50 cases (52.1%) and representing 90.9% of all \u003cem\u003eBRAF\u003c/em\u003e mutations (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFrequency and mutation patterns of \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e genes in the MAPK pathway\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMutation type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMAPK pathway mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExon 11: c.1333G\u0026thinsp;\u0026gt;\u0026thinsp;A (D445N), c.1375G\u0026thinsp;\u0026gt;\u0026thinsp;A (K459M), c.1397 G\u0026thinsp;\u0026gt;\u0026thinsp;A (G466E)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExon 15: c.1789G\u0026thinsp;\u0026gt;\u0026thinsp;A (V600M), c.1828T\u0026thinsp;\u0026gt;\u0026thinsp;C (F610L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExon 15: c.1799T\u0026thinsp;\u0026gt;\u0026thinsp;A (V600E)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eRAS\u003c/em\u003e mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e (exon 2): c.35G\u0026thinsp;\u0026gt;\u0026thinsp;T (G12C), c.50G\u0026thinsp;\u0026gt;\u0026thinsp;A (S17N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e (exon 2): c.34G\u0026thinsp;\u0026gt;\u0026thinsp;A (G12S)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHRAS\u003c/em\u003e (exon 2): c.31G\u0026thinsp;\u0026gt;\u0026thinsp;A (A11T), c.22G\u0026thinsp;\u0026gt;\u0026thinsp;A (V8M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHRAS\u003c/em\u003e (exon 3): c.205G\u0026thinsp;\u0026gt;\u0026thinsp;A (D69N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation identified in the study is a point mutation in which thymine (T) at nucleotide position 1799 is replaced by adenine (A) (c.1799T\u0026thinsp;\u0026gt;\u0026thinsp;A) (Fig. 2).\u003c/p\u003e\n \u003cp\u003eIn addition, a novel \u003cem\u003eHRAS\u003c/em\u003e mutation, c.22G\u0026thinsp;\u0026gt;\u0026thinsp;A (p.V8M), was identified in case 3, characterized by a soap-bubble radiolucent lesion with well-defined, non-sclerotic margins and an acanthomatous histological pattern (Fig. 3).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure 2.\u003c/strong\u003e Mutation c.1799T\u0026thinsp;\u0026gt;\u0026thinsp;A (p.Val600Glu) in exon 15 codon 600 of \u003cem\u003eBRAF\u003c/em\u003e gene (\u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e) (50/96 cases)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure 3\u003c/strong\u003e. Mandibular ameloblastoma \u003cem\u003ewith HRAS\u003c/em\u003e\u003csup\u003eV8M\u003c/sup\u003e mutation (case 3): (a) Mutation c.22G\u0026thinsp;\u0026gt;\u0026thinsp;A (p.Val8Met) in exon 2 codon 8 of \u003cem\u003eHRAS\u003c/em\u003e, (b) Radiograph showing a soap-bubble radiolucent lesion with well-defined, non-sclerotic margins, and (c) Acanthomatous histological pattern (\u0026times;40).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eAssociation between BRAF and RAS mutations in the MAPK pathway and clinicopathological and radiographic features\u003c/h2\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean age of patients according to mutation status\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean age (years)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard deviation (SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAPK pathway mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eIndependent samples t-test assuming equal variances\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe mean age in mutation-positive and mutation-negative groups ranged from 31 to 34 years, with no statistically significant difference between them (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eAssociation between gene mutations and clinicopathological features\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Chi-square test\u003c/p\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003eThe highest frequency of MAPK pathway mutations was observed in the 40\u0026ndash;59 year age group (68.4%). Mutation rates were higher in recurrent tumors compared with primary tumors for both overall MAPK pathway mutations and specifically for \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e (80% vs. 60%, respectively), although these differences were not statistically significant. Female patients exhibited a significant higher prevalence of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations compared with males (61.1% vs. 40.5%) (Fisher\u0026rsquo;s exact test, p\u0026thinsp;=\u0026thinsp;0.045) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003eAssociation between gene mutations and radiographic features\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n 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\"\u003e\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Chi-square test.\u003c/p\u003e\n \u003cp\u003eIn the MAPK pathway, mutations were more frequent in mandibular than in maxillary tumors (65.1% vs. 50.0%). Within the mandible, the highest frequency occurred in the symphysis\u0026ndash;body region (66.7%). Mutations tended to be more common in ameloblastomas exhibiting a soap-bubble pattern, well-defined without sclerotic margins, absence of impacted teeth, spike type root resorption, and cortical expansion; however, these associations did not reach statistical significance.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e \u003csup\u003eV600E\u003c/sup\u003e mutations were also more prevalent in mandibular than in maxillary tumors (54.7% vs. 30.0%), with the highest prevalence in the angle\u0026ndash;ramus region (59.3%). Notably, \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations were significantly associated with radiolucent patterns (soap-bubble and unilocular) (p\u0026thinsp;=\u0026thinsp;0.040). (Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e; Fig.\u0026nbsp;4).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure 4\u003c/strong\u003e. Radiographic features of mandibular ameloblastomas with different \u003cem\u003eBRAF\u003c/em\u003e mutations. (a) Case 83: \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation, soap-bubble radiolucency with well-defined, without sclerotic margins in the left mandibular body. (b) Case 21: \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eD445N\u003c/sup\u003e mutation, honeycomb radiolucency with ill-defined margins in the symphysis region. (c) Case 58: \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation, unilocular radiolucency with well-defined and sclerotic margins in the left mandibular ramus\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 7\u003c/strong\u003e. Association between gene mutations and histopathological features\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cdiv align=\"center\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Chi-square test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003cp\u003eMAPK pathway mutations, including \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e, were more frequent in unicystic than conventional ameloblastomas (75% vs. 60.5% and 70% vs. 47.4%, respectively). By histological subtype, MAPK mutations were highest in the luminal subtype (80%), while \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e occurred most often in mural and luminal subtypes (70%). In conventional tumors, the acanthomatous subtype showed the highest MAPK mutation rate (66.7%), and the plexiform subtype exhibited the highest \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e frequency (58.8%). However, none of these correlation were statistically significant (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSince 2014, several studies have established the MAPK signaling pathway as the main pathogenic mechanism in ameloblastoma [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The \u003cem\u003eRAS\u003c/em\u003e family (\u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, \u003cem\u003eHRAS\u003c/em\u003e) and \u003cem\u003eBRAF\u003c/em\u003e genes are positioned upstream in the cascade and initiate the entire RAS\u0026ndash;BRAF\u0026ndash;MEK\u0026ndash;ERK signaling pathway. Mutations in these genes are sufficient to constitutively activate MAPK signaling, leading to abnormal proliferation and tumor formation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Other genes in the MAPK pathway, such as MEK and ERK, have not yet been clinically validated. Therefore, in the present study, we focused on \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e mutations, which are the most biologically and clinically relevant and ensure feasibility.\u003c/p\u003e \u003cp\u003eIn our study, the mean patient age was 32.2 years (\u0026plusmn;\u0026thinsp;16.3), ranging from 8 to 69 years, with the most common age group being 20\u0026ndash;39 years (44.8%). These demographic findings are consistent with previous reports [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Ameloblastoma showed no sex predilection in earlier studies [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], whereas in our series female patients were slightly more common (male-to-female ratio 0.78:1). Mandibular lesions predominated (89.6%), and the conventional type was more frequent than the unicystic type (79.2% vs. 20.8%), consistent with the literature [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These findings support the representativeness of our cohort.\u003c/p\u003e \u003cp\u003e \u003cem\u003eRAS\u003c/em\u003e mutations in ameloblastoma typically occur in exons 2 and 3 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], while \u003cem\u003eBRAF\u003c/em\u003e mutations are most frequently identified in exons 11 and 15 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Interestingly, mutations in these two genes appear to be mutually exclusive, rarely occurring together [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, in this study, we sequenced \u003cem\u003eBRAF\u003c/em\u003e exons 11 and 15 first, and in negative cases we proceeded to \u003cem\u003eRAS\u003c/em\u003e sequencing (\u003cem\u003eNRAS\u003c/em\u003e, \u003cem\u003eHRAS\u003c/em\u003e, \u003cem\u003eKRAS\u003c/em\u003e in exons 2 and 3). Among 96 paraffin-embedded samples, MAPK pathway mutations were identified in 61 cases (63.5%), including 55 \u003cem\u003eBRAF\u003c/em\u003e mutations (57.3%) and six \u003cem\u003eRAS\u003c/em\u003e mutations (6.3%). The \u003cem\u003eRAS\u003c/em\u003e mutation rate was lower than that reported by Brown and Sweeney, who found a prevalence of approximately 20% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A systematic review by Guimar\u0026atilde;es also confirmed that \u003cem\u003eRAS\u003c/em\u003e mutations in odontogenic tumors, including ameloblastomas, are uncommon [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This supports the conclusion that \u003cem\u003eBRAF\u003c/em\u003e mutations are the main driver in the MAPK pathway, while \u003cem\u003eRAS\u003c/em\u003e mutations play a minor role.\u003c/p\u003e \u003cp\u003eWe detected \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations in 50 of 96 cases (52.1%). This prevalence is lower than reported in Asian countries such as Korea (90%) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Thailand (72.5%) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], Japan, and China (\u0026gt;\u0026thinsp;70%), but comparable to reports in Europe and the United States (40\u0026ndash;65%) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Ethnic and population differences may partly explain this variability. Moreover, differences in methodology, such as the use of immunohistochemistry (which may yield false positives) versus PCR-based sequencing (which may miss novel variants), may also influence reported frequencies. Nevertheless, most studies consistently report \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations in more than 50% of cases. In 2020, Gonz\u0026aacute;lez et al. reviewed 19 studies involving 611 ameloblastomas and reported a pooled \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e prevalence of 60% (366/611). In that analysis, single \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations without co-occurring variants accounted for 93.7% of positive cases, while multiple mutations were present in only 6.3%. This finding explains why targeted therapies directed against \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e, such as vemurafenib or dabrafenib, may be effective [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In our cohort, 12 MAPK pathway mutations were identified, predominantly as isolated events. All six \u003cem\u003eBRAF\u003c/em\u003e variants detected were RAS-independent [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], with \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e accounting for 90.9% of all \u003cem\u003eBRAF\u003c/em\u003e-mutant cases, consistent with previous reports [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Six \u003cem\u003eRAS\u003c/em\u003e variants were identified across \u003cem\u003eNRAS\u003c/em\u003e, \u003cem\u003eHRAS\u003c/em\u003e, and \u003cem\u003eKRAS\u003c/em\u003e in this cohort. Among them, a novel \u003cem\u003eHRAS\u003c/em\u003e mutation, c.22G\u0026thinsp;\u0026gt;\u0026thinsp;A (p.Val8Met) \u003cem\u003e(HRAS\u003c/em\u003e \u003csup\u003eV8M\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e, was detected. The novel mutation occurred in case 3, a 36-year-old female patient with ameloblastoma of the mandibular ramus. The tumor presented as a conventional type with acanthomatous histological pattern, showing a soap-bubble radiolucency, well-defined, non-sclerotic margins, and cortical perforation (Fig.\u0026nbsp;3). To the best of our knowledge, this variant has not been previously reported in mutation databases. \u003cem\u003eHRAS\u003c/em\u003e alterations are generally rare in odontogenic tumors, with most molecular studies documenting only sporadic cases at codons 12, 13, or 61[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The identification of \u003cem\u003eHRAS\u003c/em\u003e\u003csup\u003eV8M\u003c/sup\u003e therefore expands the mutational spectrum of \u003cem\u003eHRAS\u003c/em\u003e and provides further evidence of the genetic heterogeneity underlying this neoplasm. Although the biological significance of this substitution remains to be determined, its location within the N-terminal region of \u003cem\u003eHRAS\u003c/em\u003e suggests a potential role in altering protein conformation and driving aberrant activation of the MAPK/ERK signaling cascade. Similar early-codon \u003cem\u003eRAS\u003c/em\u003e variants have been implicated in oncogenesis in other tumor types [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], supporting the hypothesis that this mutation may also act as an activating event. Future functional studies are warranted to establish its oncogenic potential and to clarify whether it influences sensitivity or resistance to targeted inhibitors currently under investigation for RAS/MAPK-driven tumors. Overall, the identification of this novel \u003cem\u003eHRAS\u003c/em\u003e mutation highlights the importance of comprehensive genetic profiling in ameloblastoma and underscores the need for larger, multicenter studies to clarify its prevalence and clinical relevance.\u003c/p\u003e \u003cp\u003eThe mean age of patients with and without MAPK mutations was similar (31\u0026ndash;34 years). The 40\u0026ndash;59-year group had the highest frequency of mutations (68.4%), but this difference was not statistically significant. This finding differs from Bonacina and Kelppe, who reported lower mean ages in \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e-positive cases [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMost previous studies found no sex-related difference in \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e prevalence [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, in our series, females had a significantly higher frequency of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations compared with males (61.1% vs. 40.5%, Fisher\u0026rsquo;s exact test, p\u0026thinsp;=\u0026thinsp;0.045). This unexpected finding contradicts most of the published literature and raises questions about potential biological or population-specific factors underlying the observed disparity. One plausible hypothesis is the influence of sex hormones on MAPK pathway activity. Experimental studies in breast and thyroid cancer cells have demonstrated that estrogen can activate RAF\u0026ndash;MEK\u0026ndash;ERK signaling [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In addition, investigations in thyroid cancer [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and cancer in general [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] have also reported a link between estrogen and MAPK pathway activation. These findings suggest that hormonal influences may partly explain the higher frequency of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations observed in females in our cohort. Alternatively, this difference may be related to genetic or epigenetic characteristics specific to the Vietnamese population, which could modify susceptibility to mutation. Three of the five recurrent cases harbored the \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation and one carried a \u003cem\u003eRAS\u003c/em\u003e mutation. The overall mutation frequency in the recurrent group was higher than in the primary group (80% for MAPK pathway mutations and 60% for \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e), although the difference did not reach statistical significance. Given the small number of recurrent cases, meaningful comparison with other studies was limited, and previous reports have also shown no significant difference in recurrence risk between \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e-mutant and wild-type cases [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Nevertheless, the trend toward higher mutation frequency in recurrent tumors observed in our cohort suggests a potential role of MAPK pathway activation in disease persistence and progression. \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e-positive clones may have enhanced proliferative capacity or resistance to conventional treatment, thereby contributing to recurrence. Clinically, these findings highlight the need for vigilant longterm follow-up in patients with MAPK pathway\u0026ndash;mutant ameloblastomas, particularly those harboring \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e. Moreover, the potential application of \u003cem\u003eBRAF\u003c/em\u003e inhibitors or combined targeted approaches in recurrent or refractory cases deserves consideration, in light of emerging evidence of therapeutic benefit in other \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e-driven tumors.\u003c/p\u003e \u003cp\u003eIn this study, MAPK pathway mutations were more frequent in mandibular than maxillary tumors, with the symphysis\u0026ndash;body region showing the highest prevalence, whereas \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations were most frequent in the angle-ramus region. Consistent with our findings, previous studies have also reported that \u003cem\u003eBRAF\u003c/em\u003e mutations predominate in the mandible, while \u003cem\u003eRAS\u003c/em\u003e mutations are more frequently detected in the maxilla [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is currently limited research on the association between \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e mutations and the radiographic features of ameloblastoma. Therefore, we investigated this relationship across several parameters, including radiolucent pattern, leision margin characteristics, presence of impacted teeth within the lesion, root resorption, and cortical bone alterations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Our findings revealed that ameloblastomas with a unilocular or soap-bubble radiolucent pattern had a significantly higher frequency of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations compared with other patterns (Fisher\u0026rsquo;s exact test, p\u0026thinsp;=\u0026thinsp;0.04). This observation suggests that specific radiographic features may reflect underlying molecular alterations and could serve as useful markers for prognostication. Nevertheless, radiographic appearance is not determined solely by genetic background but may also be influenced by the timing of clinical presentation. Given the slow growing and often asymptomatic nature of ameloblastoma, many patients present only when the tumor has enlarged, which results in more advanced imaging features such as multilocularity, cortical perforation, or extensive root resorption [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Thus, part of the association between \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations and distinct radiographic patterns in our cohort may have been confounded by symptom duration at diagnosis. Future studies with larger cohorts should adjust for both disease duration and tumor size to validate imaging\u0026ndash;genotype correlations and clarify the biological mechanisms by which \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations contribute to bone resorption.\u003c/p\u003e \u003cp\u003eMAPK pathway mutations and \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations were more common in unicystic than conventional ameloblastomas (75% vs. 70%). These findings are consistent with Guimar\u0026atilde;es [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], Gonz\u0026aacute;lez [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], Bonacina [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and Kelppe [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Among histological subtypes, the plexiform subtype showed the highest \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e prevalence (58.8%), consistent with the findings of Shirsat [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. These parallels suggest possible biological differences among histopathological variants. Notably, the higher frequency of mutations in unicystic ameloblastomas may partly explain their more indolent clinical behavior and responsiveness to targeted therapy compared with conventional forms. Furthermore, the predominance of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e in the plexiform pattern raises the possibility that distinct molecular mechanisms drive tumor architecture. Taken together, these results support the hypothesis that genetic alterations not only influence tumor initiation but may also contribute to the histopathological phenotype and clinical course of ameloblastomas.\u003c/p\u003e \u003cp\u003e In summary, this study is strengthened by its relatively large sample size, the application of reliable gene sequencing methods, and comprehensive analyses integrating clinical, radiographic, and histopathological features. However, certain limitations should be acknowledged, including its single-center design in Ho Chi Minh City, the descriptive cross-sectional nature, and the absence of long-term follow-up data on recurrence.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cem\u003eBRAF\u003c/em\u003e \u003csup\u003eV600E\u003c/sup\u003e mutation was the most prevalent genetic alteration in Vietnamese patients with ameloblastoma, occurring in more than half of cases, whereas RAS mutations were rare, with one novel variant detected. Furthermore, \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutaion was significantly associated with sex and radiographic features, being more common in females and correlated with distinct radiolucent patterns. These findings highlight the pivotal role of MAPK signaling pathway alterations in ameloblastoma and warrant further studies to elucidate their pathogenesis and therapeutic implication.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComputed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eH \u0026amp;E\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHematoxylin and Eosin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAPK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMitogen-Activated Protein Kinase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFFPE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFormalin-fixed paraffin-embedded\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Ethics Committee in Biomedical Research, University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam (Approval No. 272/HĐĐĐ-ĐHYD, dated March 9, 2023). Written informed consent was obtained from all participants. Retrospective patients provided written consent during follow-up visits and prospective patients provided written consent during treatment.\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe nucleotide sequence corresponding to the novel \u003cem\u003eHRAS\u003c/em\u003e variant (c.22G\u0026gt;A; p.V8M) identified in this study has been deposited in the GenBank repository (Submission ID: 3012939). The permanent accession number will be provided upon release by GenBank and updated in both the manuscript and the editorial system. All other genetic variants analyzed in this study are previously reported and have corresponding stable public database identifiers (ClinVar, COSMIC, dbSNP).\u003c/p\u003e\n\u003cp\u003eStable database identifiers for non-novel variants:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e c.1375G\u0026gt;A (p.Val459Met, V459M): COSMIC COSM10284879\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e c.1333G\u0026gt;A (p.Asp445Asn, D445N): ClinVar RCV00044227; dbSNP rs752429313\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e c.1397G\u0026gt;A (p.Gly466Glu, G466E): ClinVar RCV000442274; COSMIC COSM453\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e c.1828T\u0026gt;C (p.Phe610Leu, F610L): dbSNP rs2128998190\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e c.1798G\u0026gt;A (p.Val600Met, V600M): ClinVar RCV000429286; COSMIC COSM1130\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e c.1799T\u0026gt;A (p.Val600Glu, V600E): ClinVar RCV000067669; COSMIC COSM476\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e c.35G\u0026gt;T (p.Gly12Val, G12V): COSMIC COSM520; ClinVar RCV000154262\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e c.50G\u0026gt;A (p.Ser17Asn, S17N): ClinVar RCV002292309; COSMIC COSM51382\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e c.34G\u0026gt;A (p.Gly12Ser, G12S): ClinVar RCV000421327; COSMIC COSM563\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHRAS\u003c/em\u003e c.31G\u0026gt;A (p.Ala11Thr, A11T): COSMIC COSM4193616\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHRAS\u003c/em\u003e c.205G\u0026gt;A (p.Asp69Asn, D69N): COSMIC COSM6009011\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the University of Medicine and Pharmacy at Ho Chi Minh City under contract number 263/2023 /HĐ-ĐHYD, dated 17/10/2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors’ contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKAH conceived and designed the study, collected and analyzed the data, and drafted the manuscript. CQH, TBD, TTTL, and TTTB assisted with laboratory procedures, pathology review, and data interpretation. NCNH revised the manuscript to correct formatting inconsistencies and typographical errors. TDV, CTKN contributed to manuscript revision prior to submission. TDV, CTKN, and VAH supervised the project and \u0026nbsp;provided scientific guidance. All authors contributed to the critical revision of the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Odonto-Maxillo-Facial Hospital of Ho Chi Minh City and the Center for Molecular Biomedicine, University of Medicine and Pharmacy at Ho Chi Minh City, for supporting this study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTamme T, Soots M, Kulla A, Karu K, Hanstein S, Sokk A, et al. 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Mechanism of 17\u0026beta;-estradiol-induced Erk1/2 activation in breast cancer cells. J Biol Chem. 2002;277(25):22558-65.\u003c/li\u003e\n\u003cli\u003eKim M, Kim S, Ha S, Oh S, Kim D, Park J, et al. \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation enhances estrogen-induced metastatic potential in thyroid cancer by regulating the expression of estrogen receptors. Endocrinol Metab (Seoul). 2022; 37(6):879-890.\u003c/li\u003e\n\u003cli\u003eŚmiech M, Leszczynski P, Kono H, Wardell C, Tanguchi H. Emerging \u003cem\u003eBRAF\u003c/em\u003e mutations in cancer progression and their effects on estrogen-responsive genes. Genes (Basel); 2020;11(11):1342.\u003c/li\u003e\n\u003cli\u003eHeikinheimo K, Huhtala J, Thiel A, Heikinheimo H, Kurppa KJ, Heikinheimo H, et al. The mutational profile of unicystic ameloblastoma. J Dent Res. 2019;98(1):54\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eKoseki T, Kakimoto N, Hashimoto K, Ariji Y, Tsuchimochi M, Toyama M, et al. Computed tomography of odontogenic myxoma. Dentomaxillofac Radiol. 2003;32(3):160\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eMerbold L, Smit C, Ker-Fox J, Uys A. The radiologic progression of ameloblastoma. SA J Radiol. 2023; 27(1): e2668.\u003c/li\u003e\n\u003cli\u003eMariz B, Andrade B, Agostini M, Almeida O, Romanach M, Jr J, et al. Radiographic estimation of the growth rate of initially underdiagnosed ameloblastomas. Med Oral Patol Oral Cir Bucal. 2019;24(4):e468-e472.\u003c/li\u003e\n\u003cli\u003eSmit C, Robinson L, Ker-Fox J, Fonsea F, Heerden W, Uys A. Clinicoradiologic features of ameloblastomas. J Oral Pathol Med. 2024;53(2):133-41.\u003c/li\u003e\n\u003cli\u003eShirsat PK, Bansal S, Prasad P, Desai RS. Low frequency of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e immunoexpression in mandibular ameloblastomas: An institutional study. J Oral Maxillofac Pathol. 2018;22(3):353-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ameloblastoma, BRAF mutation, RAS mutation, BRAF V600E, MAPK pathway, Vietnam","lastPublishedDoi":"10.21203/rs.3.rs-7773170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7773170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003cbr\u003e\n\u003c/strong\u003eAmeloblastoma is a benign but locally aggressive odontogenic tumor. Genetic mutations in the mitogen-activated protein kinase (MAPK) signaling pathway, particularly those in \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e, have been increasingly implicated in its pathogenesis, but remain underreported in Vietnamese patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e\u003cbr\u003e\n\u003c/strong\u003e\u003c/em\u003eNinety-six formalin-fixed paraffin-embedded (FFPE) ameloblastoma samples from Vietnamese patients were retrospectively analyzed. Targeted exons of \u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e genes were amplified by PCR and sequenced using Sanger sequencing on an ABI 3500 Genetic Analyzer. Mutation frequencies, the prevalence of \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e, and their associations with clinical, radiographic, and histopathological features were evaluated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003cbr\u003e\n\u003c/strong\u003eMAPK pathway mutations were identified in 63.5% of cases. \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e was the most frequent alteration, detected in 52.1% (50/96) of tumors. \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutations were significantly associated with radiographic radiolucent patterns, and were more common in female than in male patients (p\u0026lt; 0.05). Notably, a novel \u003cem\u003eHRAS \u003c/em\u003emutation, c.22G\u0026gt;A (p.V8M)\u003cem\u003e (HRAS\u003c/em\u003e\u003csup\u003eV8M\u003c/sup\u003e\u003cem\u003e),\u003c/em\u003e was identified in this study, which has not been previously reported in ameloblastoma or in mutation databases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003cbr\u003e\n\u003c/strong\u003e\u003cem\u003eBRAF\u003c/em\u003e and \u003cem\u003eRAS\u003c/em\u003e mutations are prevalent in Vietnamese patients with ameloblastoma, with \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e mutation accounting for more than half of the cases. The significant association with \u003cem\u003eBRAF\u003c/em\u003e\u003csup\u003eV600E\u003c/sup\u003e with distinct radiographic features and female gender supports its potential value as a biomarker. In addition, the identification of a novel \u003cem\u003eHRAS\u003c/em\u003e mutation, warranting the need for further investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e","manuscriptTitle":"Braf and Ras Mutations in Vietnamese Patients With Ameloblastoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 17:19:22","doi":"10.21203/rs.3.rs-7773170/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-01T08:37:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T15:53:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-25T03:15:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T13:21:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291693972317152086282048568567606107195","date":"2025-12-21T12:05:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183014077819641478492430170104246121874","date":"2025-12-21T00:52:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"192819454195702101594596458717343199736","date":"2025-12-19T03:35:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173715696358356477344518400652520824913","date":"2025-12-19T00:08:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-18T14:53:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T08:52:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T17:41:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-14T15:17:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2025-10-14T15:13:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b356cba9-7d30-47a4-b172-23ff13d0bbfc","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T16:07:30+00:00","versionOfRecord":{"articleIdentity":"rs-7773170","link":"https://doi.org/10.1186/s12903-026-08325-3","journal":{"identity":"bmc-oral-health","isVorOnly":false,"title":"BMC Oral Health"},"publishedOn":"2026-04-13 15:58:18","publishedOnDateReadable":"April 13th, 2026"},"versionCreatedAt":"2025-12-22 17:19:22","video":"","vorDoi":"10.1186/s12903-026-08325-3","vorDoiUrl":"https://doi.org/10.1186/s12903-026-08325-3","workflowStages":[]},"version":"v1","identity":"rs-7773170","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7773170","identity":"rs-7773170","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}