Evaluation of salivary and serum exosomal mRNAs as biomarkers for the diagnosis and prognosis of oral squamous cell carcinoma

Evaluation of salivary and serum exosomal mRNAs as biomarkers for the diagnosis and prognosis of oral squamous cell carcinoma | 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 Article Evaluation of salivary and serum exosomal mRNAs as biomarkers for the diagnosis and prognosis of oral squamous cell carcinoma Sarwareddy Kartik Kumar, Neeharika Kanaparthi, Babiola Annes Sesuraj, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6905382/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Minimally-invasive or non-invasive biomarkers from serum and saliva hold significant promise for real-time monitoring of oral squamous cell carcinoma (OSCC). However, the diagnostic potential of exosomes, which carry heterogeneous tumor-derived functional cargo remains largely underexplored. This study aimed to evaluate the diagnostic and prognostic utility of exosomal mRNAs derived from saliva and serum samples of OSCC patients. Exosomes were isolated from paired serum and saliva samples of 40 OSCC patients and 40 healthy controls using commercial kits. Characterization was performed using NTA, TEM, zeta potential, protein/lipid quantification, and western blotting. Expression of nine mRNA markers including cytokines (IL1, IL6, IL8, TNF-α), proliferation markers (OAZ1, SAT, S100P), and metastasis-related molecules (MMP9, Chemerin) was analyzed by qRT-PCR. Diagnostic accuracy was evaluated using ROC curve analysis, and correlations with tumor grade and lymph node metastasis were systematically investigated. Results demonstrated that salivary exosomal MMP9, TNF-α, and OAZ1 exhibited markedly higher diagnostic sensitivity and specificity compared to the top-performing serum exosomal derived markers (MMP9, IL1, and OAZ1). Notably, a two-gene salivary mRNA panel combining TNF-α and OAZ1 demonstrated strong discriminatory power (AUC: 0.89, sensitivity: 80%, specificity: 90%; Youden Index: 0.70). Additionally, salivary exosomal MMP9, IL8, S100P, SAT, and OAZ1 significantly differentiated between grade I and grade III OSCC. Moreover, IL6 expression positively correlated with lymph node metastasis. In contrast, serum exosomal markers lacked clear discriminatory potential. Therefore, salivary exosomal panel of TNF-α and OAZ1 represent promising non-invasive biomarkers for OSCC diagnosis, while MMP9 and IL6 is informative for tumor grading. Biological sciences/Biochemistry Biological sciences/Cancer Biological sciences/Molecular biology Exosomes Saliva Serum Oral cancer Biomarkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Oral cancer is one of the most common types of head and neck malignancy, with oral squamous cell carcinoma (OSCC) accounting for nearly 90% of all oral cancer cases. OSCC typically arises from squamous epithelial cells lining the inner oral mucosa and is known for its aggressive nature. The five-year survival rate varies significantly, ranging from 80–90% when diagnosed at an early stage, but drops to approximately 30% in advanced stages. Although the etiology of OSCC is multifactorial, key risk factors include tobacco use (smoking or chewing), excessive alcohol consumption, and betel nut chewing, with a higher prevalence observed in males 1 , 2 . The global disease burden of OSCC varies geographically, with significantly higher incidence rates reported in Asian countries 3 . A recent national-level report by Akashanand et al. (2024) identified India as a major contributor to the global burden, accounting for nearly one-third of all oral cancer cases worldwide 4 . Clinically, OSCC presents with symptoms such as non-healing ulcers and oral pain in the initial phase, progressing to enlarged oral masses, dysphagia, and odynophagia in more advanced stages. Currently, the gold standard for OSCC diagnosis involves clinical oral examination followed by histopathological evaluation of the tissue obtained through biopsy 5 . However, tissue biopsy methods are invasive, tumour molecular heterogeneity may not be captured, and timely screening and monitoring of the therapeutic response may be challenging. Advances in oral cancer diagnostic research have increasingly focused on the development of minimally invasive or non-invasive molecular biomarker-based liquid biopsies to improve diagnostic accuracy, offer comprehensive insights into tumour biology, and enable real-time monitoring 5 – 7 . Various biological fluids such as serum, saliva, urine, cerebrospinal fluid, and prostatic fluid are being explored for tumour-derived molecule profiling, among which serum and saliva are the most extensively studied and clinically reliable for developing diagnostic platforms for oral cancer 8 , 9 . Serum contains a diverse pool of tumour-derived molecules released into the circulation, including genomic, proteomic, transcriptomic, epigenetic markers, and circulating tumour cells (CTCs), offering a systemic snapshot of tumour dynamics for various cancers including OSCC. In contrast, saliva, owning to its direct contact with the tumour site in OSCC, is enriched with locally derived biomarkers such as RNA, proteins, enzymes, and extracellular vesicles like exosomes 10 , 11 . Recent studies have explored both serum and saliva for OSCC detection, with growing interest in saliva owing to its non-invasive collection and tumour proximity. For instance, Xiaoyuan et al. (2024), Nooshin et al. (2024), and Zhenying et al. (2025) identified serum biomarkers such as chemerin, miR-31-5p, and IL6 12–14 , while Jia et al (2010), Kalpani et al. (2024), and Anu et al. (2021) demonstrated the clinical relevance of DNA, RNA, and protein analysis in saliva 15 – 17 . However, most of these studies were conducted on small cohorts, and there is a lack of population-specific research in India, despite its high OSCC incidence. Exosomes are small extracellular vesicles ranging from 30–200 nm in diameter, known to play key roles in cancer pathophysiology through their cargo, and are stably enclosed within a lipid bilayer, which includes mRNAs, miRNAs, and proteins 18 . In recent years, there has been a growing interest in developing exosome-based platforms for cancer diagnostics and therapeutics owning to their demonstrated efficiency 19 – 22 . Consequently, few studies have focused on identifying exosomal biomarkers in serum and saliva for OSCC due to their high diagnostic sensitivity and specificity. Notably, Natalie et al. (2023) identified salivary exosomal proteins such as AMER3, LOXL2, and AL9A1 as potential OSCC biomarkers, while Ching et al. (2021) demonstrated that serum exosomal miRNAs like miR-155 and miR-21 could serve as diagnostic and prognostic indicators 11 , 23 . However, the diagnostic potential of exosomes in OSCC remains in its infancy, and to the best of our knowledge, no studies have explored exosomal mRNAs in this context. In this study, we aimed to evaluate nine mRNAs including MMP9, IL1, IL6, IL8, TNF-α, Chemerin, OAZ1, SAT, and S100P in both serum and salivary exosomes from histopathologically confirmed OSCC patients, to gain a comprehensive understanding of the tumour microenvironment (TME). These genes were selected to capture molecular features related to cytokine signalling, tumour cell proliferation, and cellular invasion. Our findings demonstrated that salivary exosomal biomarkers possess greater diagnostic potential than those derived from serum, showing significant correlation with tumour grade and lymph node metastasis. Based on this pilot analysis, we propose a salivary exosomal biomarker panel, particularly TNF-α in combination with OAZ1, as a promising molecular diagnostic tool for OSCC, with potential relevance for the Indian population. Materials and Methods Sample Size Estimation: This preliminary study aimed to explore exosome gene panels derived from serum and saliva as potential biomarkers for OSCC, establishing a proof of concept by analyzing expression patterns and correlation trends before conducting large-scale studies. The sample size was estimated based on the standard formula for sensitivity analysis, assuming a 95% confidence interval, expected sensitivity of 98%, specificity of 92.1%, and disease prevalence of 20%. An acceptable margin of error (precision) of 10% (d = 0.10) was considered. Based on this, at least 38 samples were required for the study to achieve statistically meaningful data. Patient Recruitment and Sample Selection: A total of 40 histopathologically confirmed OSCC patients were recruited from the Apollo Cancer Institute, Apollo Hospitals, Jubilee Hills, Hyderabad, between May 2023 and September 2024. Exclusion criteria included patients with recurrent disease, those unwilling to provide informed consent, individuals with a history of other malignancies, and patients with sexually transmitted diseases (STDs). Age-matched healthy controls (40 individuals) were selected following an oral cavity examination by a specialist to confirm the absence of any oral pathological lesions that might influence saliva composition. All participants, including OSCC patients and healthy controls, voluntarily agreed to participate in the study and provided informed consent. Demographic parameters, including age and gender, were recorded during sample collection, whereas clinical data such as tumor grade, site, and lymph node involvement were retrieved from medical records following histopathological evaluation. The study protocol was reviewed and approved by the Institutional Ethics Committee at Apollo Hospitals (IEC No. AHJ-C-S-006/02–25). Participants were informed about the study objectives and the option to withdraw at any time without consequences. All participants provided informed consent, and all serum and saliva samples were anonymized with code labels, ensuring that personal identifiers were not included in the data. Collection of Serum and Saliva Samples: Paired blood and saliva samples were collected from all OSCC patients and healthy controls (HC) enrolled in the study. For each individual, 5 mL of peripheral blood was drawn into blood collection tubes (BD biosciences, USA). After allowing the samples to rest at room temperature for 1 hour, they were centrifuged at 2000 rpm for 10 minutes at 4°C to separate the serum. The resulting supernatant was carefully transferred into 1.5 mL microcentrifuge tubes and subjected to a second centrifugation at 3000 rpm for 10 minutes at 4°C to remove any residual cellular debris. The purified serum was then aliquoted and stored at − 80°C until further use for exosome isolation. In parallel, approximately 1 mL of unstimulated saliva was collected using the Norgen Biotek Saliva Collection and Preservation Kit (Norgenbiotek, Canada). Participants were instructed to refrain from eating or drinking for at least one hour prior to saliva collection to ensure sample consistency. Following collection, saliva samples were centrifuged at 1000 rpm for 10 minutes at 4°C to eliminate any debris. The clarified saliva was then stored at − 80°C until exosome isolation. All samples were processed within 3 hours of collection to preserve their integrity. Notably, blood and saliva were collected from the same individual on the same day to ensure sample comparability. Informed consent was obtained from all participants prior to sample collection, and individuals who were unwilling to provide consent were excluded from the study without prejudice. Isolation of Exosomes from Serum and Saliva: Exosomes were isolated from both serum and saliva samples using commercial Total Exosome Isolation Kits (Thermo Fisher Scientific, USA), following the manufacturer’s protocols. Frozen serum and saliva samples were thawed on ice and centrifuged at 2000 × g for 30 minutes at 25°C to remove any residual cellular debris. The clarified supernatants were then transferred to fresh 1.5 mL microcentrifuge tubes for exosome isolation. For serum exosome isolation, 500 µL of the sample was mixed with 100 µL of the Total Exosome Isolation Reagent for serum (0.2 volume ratio). The mixture was gently vortexed and incubated at 4°C for 30 minutes. For saliva, 250 µL of the sample was first diluted with 250 µL of phosphate-buffered saline (PBS), followed by the addition of 250 µL of the Total Exosome Isolation Reagent for other body fluids (0.5 volume ratio). The mixture was incubated at 4°C for 60 minutes. Following incubation, both serum and saliva mixtures were centrifuged at 10,000 × g for 10 minutes at room temperature to pellet the exosomes. The resulting exosome pellets were resuspended in 1X PBS and stored at − 80°C until further analysis. Identification of Exosomes: Exosomes isolated from serum and saliva were comprehensively characterized using biochemical, biophysical, and molecular methods to evaluate their biochemical composition, size, surface charge, morphology,, and specific protein markers, in accordance with the MISEV2024 guidelines, ensuring their structural integrity and quality 24 . Biochemical Characterization: Biochemical characterization included quantification of total protein and lipid content. The protein concentration of the isolated particles was measured using the Bicinchoninic Acid (BCA) assay, while the sulfo-phospho-vanillin (SPV) assay was employed to estimate the lipid content, following established protocols. From these measurements, the protein-to-lipid ratio was calculated, providing insight into the purity of isolated vesicles 22 . Biophysical Characterization: Nanoparticle Tracking Analysis (NTA) was performed using the ZetaView® x30 system (Particle Metrix, Germany) to determine the size distribution and zeta potential of the particles. This helped confirm that the isolated vesicles were within the expected exosomal size range and exhibited surface charges consistent with stable colloidal particles. Transmission Electron Microscopy (TEM) was used to examine the morphology of the particles. For this, 50 µL of the exosome suspension was loaded onto carbon-coated copper grids and air-dried. The grids were then visualized under the TEM, where the vesicles appeared as round shaped structures, confirming successful exosome isolation 25 . Molecular characterization: Western blotting analysis was performed to analyse the protein expression of exosome specific markers in the isolated particles. In brief, equal amounts of total protein (20 µg) from serum- and saliva-derived exosomes from both OSCC patients and HC were used. The samples were lysed using RIPA buffer, denatured by adding Laemmli buffer, and incubated at 95°C for 10 minutes. Proteins were resolved on a 10% SDS-PAGE gel and transferred onto nitrocellulose membranes. After blocking the membranes with 5% BSA to prevent nonspecific binding, they were incubated overnight at 4°C with primary antibodies against human CD81, TSG101, and HSP70 (Abcam, UK). Following TBST washes, membranes were incubated with HRP-conjugated secondary antibodies for 1 hour at room temperature. Signal detection was performed using a Bio-Rad ECL kit, and the bands were visualized using the ChemiDoc Imaging System 26 . Exosome mRNA Extraction and expression profiling: Total RNA was extracted from isolated exosomes using TRIzol™ Reagent (Invitrogen, USA) in accordance with the manufacturer's protocol. The concentration and purity of the extracted RNA were assessed using a biospectrophotometer, with 1 µL of each sample measured. Subsequently, 500 ng of total RNA was reverse-transcribed into complementary DNA (cDNA) utilizing the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, USA), following the supplier's instructions. For gene expression analysis, nine target genes including IL1, IL6, IL8, TNFα, OAZ1, SAT, S100P, MMP9, and Chemerin, were selected. Specific primers for these genes were procured from Bioserve Biotechnologies (India) PVT. Ltd and their sequences detailed in Supplementary Table 1. To enhance detection sensitivity, 100 ng of cDNA from each sample underwent pre-amplification through 15 PCR cycles using High-Fidelity PCR Master Mix (DXBIDT Laboratories, India) in a thermal cycler (Bio-Rad T100 thermal cycler). The cycling conditions as follows: initial denaturation at 98°C for 30 seconds, denaturation at 98°C for 10 seconds, annealing at 58–62°C (gene-specific) for 30 seconds (Supplementary table 1 ), extension at 72°C for 60 seconds, and final extension at 72°C for 10 minutes. The resulting pre-amplified products were diluted into 1:4 ratio with nuclease-free water. Subsequently, 1 µL of the diluted product was subjected to two-step quantitative real-time PCR (qRT-PCR) over 30 cycles using gene-specific primers and High-Throughput qPCR Master Mix (DXBIDT Laboratories, India) on a Bio-Rad Opus 96 Real-Time PCR System. Detailed PCR conditions are provided in Supplementary Table 1. Gene expression levels were quantified using the comparative Ct (ΔΔCt) method, with B2M serving as the internal control gene 27 , 28 . Statistical Analyses: Statistical analyses were conducted using IBM SPSS Statistics (Version 24, Chicago, USA) and GraphPad Prism (Version 8, Boston, USA). Descriptive statistics, including mean, meadian, and standard deviation (SD), were calculated for continuous variables to summarize the data. Chi squire test was used to study the association between gender and groups. To assess differences between HC and OSCC groups in saliva and serum samples, the non-parametric Mann–Whitney U test was employed, given its suitability for comparing two independent groups without assuming normal distribution, as the data homogeneity has significant deviation. Accordingly, the fold change was represented as the Median with interquartile range (IQR). For evaluating gene expression differences across multiple groups, one-way analysis of variance (ANOVA) was utilized, followed by the Least Significant Difference (LSD) post hoc test to identify specific group differences. In instances where assumptions of normality and homogeneity of variances were not met, the Kruskal–Walli’s test, a non-parametric alternative to ANOVA, was applied. To determine the diagnostic performance of identified gene markers for OSCC, receiver operating characteristic (ROC) curve analyses were performed, calculating the area under the curve (AUC) along with 95% confidence intervals to assess sensitivity and specificity. The diagnostic effectiveness was assessed by Youden index. Furthermore, a combined panel of top-performing individual genes from each category was proposed by computing the cumulative AUC, aiming to enhance diagnostic accuracy using stepwise discriminant function analysis. Throughout the study, a p-value of less than 0.05 was considered statistically significant. Results Demographic and Clinical Profiling of the selected cohort: This study included 80 individuals, comprising 40 patients diagnosed with OSCC and 40 HC. The mean age of OSCC patients was 47.60 ± 11.02 years, while the age-matched control group had a mean age of 42.88 ± 8.33 years. In terms of gender distribution, the OSCC group predominantly consisted of males (92.5%, n = 37), with only 7.5% females (n = 3), reflecting the known higher incidence of OSCC among males. The healthy control group also had a male predominance (72.5%, n = 29), though with a slightly higher proportion of females (27.5%, n = 11) compared to the OSCC group. Tumor localization in the OSCC cohort revealed that the most common sites were the left side of the tongue, right buccal mucosa, and left border of the tongue (n = 3 each). These were followed by the left buccal mucosa, right border of the tongue, left lower alveolus, and middle third mandible (n = 2 each), while the remaining 23 patients presented with lesions at various other intraoral sites, reflecting the heterogeneity of tumor localization in OSCC. Histopathological grading showed that 40% of tumors were classified as grade I (n = 16), another 40% as grade II (n = 16), and 20% as grade III (n = 8), indicating that the majority of patients had moderately to well-differentiated tumors. TNM staging further revealed that 21 patients (52.5%) had evidence of nodal involvement or metastasis, while 19 patients (47.5%) showed no lymph node involvement (Table 1 ). These demographic and clinical characteristics of the selected cohort highlight the diversity in tumor location, histological grade, and metastatic status in OSCC, providing a foundation for the diagnostic investigations. Table 1 Demographic and clinical characteristics of oral cancer patients and HC included in the study. Clinical characteristics OSCC HC P Value Total Number 40 40 Age (Mean + SD) 47.6 + 11.0 42.8 + 8.3 0.033 Sex Male 37 (92.5%) 29 (72.5) 0.019* Female 3 (7.5%) 11 (27.5) Tumour Site left side of tongue 3 - - Right buccal mucosa 3 - - Left border tongue 3 - - Left buccal mucosa 2 - - Right border of tongue 2 - - Left lower alveolus 2 - - Middle third mandible 2 - - Others 23 - - Grade I 16 - - II 16 - - III 8 - - TNM (Tumour node metastasis) Yes 21 - - No 19 - - Exosome Characterization Revealed Successful Isolation and Integrity of Serum and Saliva-Derived Exosomes: Exosomes isolated from serum and saliva of OSCC patients and HC were comprehensively characterized using biochemical, biophysical, and molecular approaches to confirm their integrity and purity (Fig. 1 ). Initial biochemical assessment of the isolated particles from both serum and saliva serum showed the higher levels of total protein in OSCC patients, when compared to HC (Fig. 1 A and B). However, lipid concentration of the serum derived particles was not shown significance between HC and OSCC, while saliva derived particles had a comparable difference with heightened levels in OSCC patients (Fig. 1 B). Additionally, the protein-to-lipid ratio of the vesicles was estimated to be 1–2, supporting the bilayered membrane structure characteristic of exosomes (Fig. 1 C). NTA analysis demonstrated that the isolated particles are in the average size of 150 to 200 in diameter with a negative zeta potential, consistent with the size and surface charge typically associated with exosomes (Fig. 1 D and E). TEM analysis further determined their spherical morphology and most vesicles measured below 100 nm (Fig. 1 F), indicating the confirmation of exosomes. Further, western blot analysis of exosomal lysates revealed the presence of classical exosome-specific protein markers CD81, HSP70, and TSG101 in both serum- and saliva-derived samples (Fig. 1 G), validating the exosomal origin of the isolated particles. These findings confirm the successful isolation and structural integrity of exosomes from both biofluids, supporting their utility for subsequent molecular and diagnostic applications. Salivary Exosomes Exhibit Elevated mRNA Expression in OSCC Patients: As shown in Fig. 2 , all the evaluated genes including, inflammatory cytokines (IL1, IL6, IL8, TNF-α), proliferation/invasion markers (S100P, SAT OAZ1), metastasis related molecules (MMP9, Chemerin) were significantly upregulated in saliva exosoms from OSCC patients compared to HC. Among these, TNF-α demonstrated the highest upregulation of inflammatory cytokines with a 6.0-fold increase (p = 0.0001), while the proliferation genes OAZ1 and S100P showed marked upregulation of 9.7-fold and 6.9-fold, respectively (p = 0.0001). Notably, in the metastatic panel MMP9 showed a heightened expression with 4.5-folds difference (p = 0.0001). The moderate yet statistically significant increases were also observed for Chemerin (2.4-fold; p = 0.0001), IL1 (2.7-fold; p = 0.001), IL6 (2.9-fold), IL8 (3.85-fold; p = 0.002), and SAT (5.79-fold; p = 0.0001). These findings indicate a strong inflammatory response, enhanced cellular proliferation, and invasion potential in OSCC, reflecting the underlying tumor biology and suggesting their relevance as diagnostic indicators. Furthermore, ROC curve analysis (Table 2 ) revealed that TNF-α, MMP9, and OAZ1 individually possess good predictive power for OSCC diagnosis (Fig. 3 ). TNF-α showed 90% sensitivity and 80% specificity (AUC: 0.88), while cell proliferation gene OAZ1 demonstrated a sensitivity of 77.5% and specificity of 87.5% (AUC: 0.87). The invasion/metastasis gene MMP9 achieved a sensitivity of 72% and specificity of 85% (AUC: 0.84). The OSCC-specific gene OAZ1 demonstrated a sensitivity of 77.5% and specificity of 87.5% (AUC: 0.87). Interestingly, combining these markers further improved diagnostic accuracy. The panel TNF-α + OAZ1 + MMP9 yielded a sensitivity of 85% and specificity of 80% (AUC: 0.89), while the combination TNF-α with OAZ1 achieved high discriminate power with 80% sensitivity and 90% specificity (AUC: 0.89) (Table 2 ). These findings underscore the potential of using single or combined salivary biomarkers for the effective diagnosis of OSCC. Table 2 ROC curve characteristics for the significantly upregulated mRNA markers in saliva and serum exosomes and their combined diagnostic potential. Gene Sensitivity Specificity AUC Youden index Saliva IL1 67.5 71.8 0.71 0.39 IL6 80 67.5 0.79 0.47 IL8 60 77.5 0.69 0.37 TNF-α 90 80 0.88 0.70 S100P 92.5 67.5 0.88 0.55 SAT 77.5 77.5 0.82 0.60 OAZ1 77.5 87.5 0.87 0.65 MMP9 72 85 0.84 0.57 Chemerin 80 71.8 0.78 0.51 MMP9 + TNF-α + OAZ1 85 80 0.89 0.65 TNF-α + OAZ1 80 90 0.89 0.70 OAZ1 + SAT + S100P 65 90 0.84 0.55 Serum IL1 87.5 70 0.86 0.57 IL8 50 77.5 0.63 0.27 TNF-α 52.5 92.5 0.75 0.45 SAT 62.5 87.5 0.73 0.50 S100P 72.5 80 0.77 0.52 OAZ1 75 85.5 0.80 0.57 MMP9 82.5 70 0.83 0.52 Chemerin 65 75 0.74 0.40 MMP9 + IL1 + OAZ1 80 85 0.89 0.65 IL1 + OAZ1 75 90 0.89 0.65 OAZ1 + SAT + S100P 80 72.5 0.82 0.52 Increased expression of mRNA biomarkers detected in serum exosomes from OSCC patients: The median gene expression profiles in serum-derived exosomes demonstrated a pattern consistent with that observed in saliva, with eight out of nine genes significantly upregulated in OSCC when compared to HC (Fig. 4 ). When stratified based on expression magnitude, IL1, TNF-α and OAZ1 exhibited the highest fold changes (9.4, 5.8 and 5.0 respectively; p = 0.0001), while S100P, MMP9, SAT and Chemerin showed moderate elevations with median fold changes of 3.1, 2.9, 2.4 and 2.4 (p = 0.0001). Lower, yet statistically significant fold increases were observed for chemerin (2.3; p = 0.0001) and IL8 (1.5; p = 0.032). However, IL6 showed a median fold change of 1.4, but lacked statistical significance (p = 0.240), whereas it was significantly upregulated in saliva (2.92-fold; p = 0.0001) (Fig. 2 ). Although gene expression was elevated in both biofluids, overall mRNA levels were shown higher trend in saliva-derived exosomes, suggesting saliva as a more responsive matrix for capturing tumor-associated molecular changes. Further, ROC curve analysis (Table 2 ) revealed the diagnostic potential of serum exosomal markers. IL1 (Sensitivity: 87.5%, Specificity:70%, AUC: 0.86), OAZ1 (75%, 85.5%, 0.80), and MMP9 (82.5%, 70%, 0.83), and emerged as top-performing individual markers (Fig. 5 ). Importantly, combining these genes enhanced diagnostic power, with the MMP9, IL1, OAZ1 panel achieving 80% sensitivity, 85% specificity, and a higher AUC and Youden index of 0.89 and 0.65 respectively. Similarly, the IL-1 and OAZ1 combination yielded a sensitivity of 75%, specificity of 90%, and an identical AUC of 0.89 with a Youden index of 0.65. These findings further align with results from saliva, where the TNF-α and OAZ1 panel displayed a higher sensitivity (80%) and Youden index (0.70) with comparable specificity and AUC values (Table 2 , Fig. 5 ). Overall, this consistent and parallel upregulation of selected genes in both saliva and serum exosomes underscores their translational value. Notably, the saliva-based panel offers slightly superior discriminatory performance, reinforcing its promise as a robust, non-invasive genomic biomarker set for OSCC diagnosis. Saliva exosomal mRNAs Correlated with OSCC Tumor grade and lymph node metastasis: Beyond their ability to differentiate OSCC patients from HC, saliva-derived exosomal gene markers also demonstrated a significant correlation with tumor progression. A clear trend of increasing gene expression was observed from garde I to grade III in saliva samples (Fig. 6 ), whereas serum-derived exosomal markers did not show any statistically significant association with tumor grades (Supplementary table 2), highlighting the superior discriminatory potential of saliva. Among the identified markers, MMP9 exhibited a marked upregulation, with significantly higher expression from grade II to III (p = 0.001) and between grade I and III (p = 0.001), indicating its strong association with advanced disease. In the cytokine category, IL8 showed a progressive increase with significant differences between grade II and III (p = 0.027) and grade I and III (p = 0.011). Although IL6 demonstrated an increasing trend across grades, the difference between grade I and III did not reach statistical significance (p = 0.066), suggesting a weaker grade-association. Notably, within the proliferation/invasion markers, three out of four S100P, SAT, and OAZ1 displayed significant stage-related elevation. Among them, OAZ1 emerged as the most prominent marker, with substantial upregulation in grade III compared to both grade I and II (p = 0.006). S100P and SAT also followed a similar trend, with expression levels significantly elevated in grade III (p = 0.017, 0.022), supporting their role in tumor progression. However, we did not observe any significant trend changes in the median expression levels of other markers including IL1 (p = 0.72), TNF-α (p = 0.366) Chemerin (p = 0.390) (Fig. 5 ). Collectively, these findings emphasize that saliva-derived exosomal gene signatures, particularly MMP9 not only differentiate OSCC patients from HC but also reflect tumor progression. On other hand, salivary exosomal IL6 levels were significantly higher in lymph node-positive OSCC patients (median = 4.08) compared to lymph node-negative patients (median = 1.83; p = 0.013) (Table 3 ), whereas none of the serum-derived exosome markers correlated with lymph node status (Supplementary Table 3). Overall, this data highlights the role of these markers in the OSCC progression and underscores the clinical potential of saliva exosomes as a non-invasive, grade and lymph node–sensitive biomarker platform for oral cancer diagnostics. Table 3 Association of saliva exosome derived transcripts with lymph node metastasis in OSCC Biomarker LN− (Median) IQR (25%, 75%) LN+ (Median) IQR (25%, 75%) P value IL1 2.97 0.70, 8.12 2.58 1.34, 8.68 0.636 IL6 1.83 1.24, 3.95 4.08 2.11, 9.26 0.013* IL8 4.65 0.84, 18.17 3.77 1.37, 15.44 0.924 TNF-α 5.43 1.54, 57.20 6.75 3.65, 50.58 0.379 S100P 3.98 1.39, 21.19 7.20 2.19, 21.57 0.675 SAT 5.21 1.40, 60.49 6.38 3.18, 13.96 0.735 OAZ1 11.84 2.09, 25.04 6.83 3.73, 17.88 0.731 MMP9 3.52 1.70, 6.9 5.63 1.51–10.38 0.560 Chimerin 2.4 1.47, 5.62 2.51 1.41, 4.80 0.882 Discussion OSCC constitutes the majority of oral cancer cases, with a particularly high prevalence in South Asia, notably in India 4 . Although histopathological evaluation remains the gold standard for OSCC diagnosis, its invasive nature, high cost, and unsuitability for frequent monitoring limits its broad clinical application. This underscores the vital need for non-invasive, cost-effective diagnostic alternatives. Consequently, serum and salivary biomarkers have emerged as potential candidates for early detection and risk stratification of OSCC 29 . Previous studies from the Serbian 29 , Sri Lankan 16 , and Indian 30 cohorts have explored salivary mRNAs and proteins, demonstrating promising diagnostic potential. However, these investigations are largely limited by small sample sizes and lack of validation in large, diverse populations. Given the heterogeneity of OSCC and its multifactorial progression, analyzing multiple biomolecules involved in key oncogenic processes such as inflammation, proliferation, invasion, and metastasis could enhance the diagnostic accuracy, especially when combined into molecular panels 31 . Despite this, the comprehensive evaluation of such multi-marker panels, particularly within exosomes derived from saliva and serum, remains unexplored. To address these gaps, our study aimed to validate the discriminatory potential of nine mRNA transcripts in serum and salivary exosomes for OSCC detection in the Indian population. Exosomes isolated from saliva and serum are generally less complex, more stable and sensitive for disease detection 32 . However, their comprehensive characterization is crucial prior to biomarker analysis. In line with previous OSCC studies, our data revealed elevated total protein and lipid levels in both saliva and serum-derived particles, with notably higher levels observed in saliva 33 , 34 . However, serum exosomes exhibited a higher protein concentration relative to lipids, while the protein-to-lipid ratio was approximately 1 in saliva and around 2 in serum, supporting the lipid bilayer structure of the vesicles 35 . Biophysical analysis confirmed the presence of vesicles with sizes below 200 nm, round shaped morphology, and negative zeta potential, which are hallmarks of exosomes 35 . Further, the presence of membrane protein CD81 supported lipid bilayer integrity, while cytosolic markers HSP70 and TSG101 confirmed vesicle integrity and quality 24 . Overall, these evaluations aligned with the MISEV guidelines and confirming the suitability of these exosomes for downstream diagnostic applications. Notably, our gene expression data revealed that salivary exosomal mRNA panels outperform the serum-derived exosomes, with TNF-α combined with OAZ1 demonstrating the highest diagnostic accuracy. Pro-inflammatory cytokines such as IL1, IL6, IL8, and TNF-α were found to be significantly elevated in salivary exosomes of patients with OSCC. These cytokines, primarily secreted by immune and stromal cells within the tumor microenvironment, are known to promote tumor progression by facilitating cancer cell proliferation, survival, migration, invasion, and immune evasion 36 . Previous studies have similarly reported elevated levels of these cytokines in both serum and saliva 37 – 39 ; however, the choice of biofluid remains debatable. Our comparative analysis indicated higher median expression levels of IL6, IL8, and TNF-α in salivary exosomes, with IL1 as an exception. This finding aligns with the report by Thayalan et al. (2016), who demonstrated 2-3-fold higher IL6 levels in saliva compared to serum 40 , suggesting that saliva is a more optimal diagnostic biofluid. Although cytokines are well-established biomarkers of OSCC and other cancer types, it is important to acknowledge their limited specificity, as their expression can be influenced by other inflammatory conditions. For instance, Yi-Shing et al. (2013) reported elevated IL6 and IL8 levels in chronic periodontitis patients 41 . Therefore, our study extended the analysis to additional molecules directly implicated in tumor cell proliferation, including S100P, SAT, and OAZ1. S100P, a calcium-binding protein, activates key signaling pathways such as NF-κB and MAPKs, thereby promoting cancer cell survival and proliferation 42 . SAT, an enzyme involved in polyamine catabolism, supports uncontrolled tumor growth 43 , whereas OAZ1, a regulator of polyamine synthesis, has been associated with enhanced metastatic potential in OSCC 44 . Despite their biological relevance, these molecules remain underexplored as exosomal biomarkers. Our investigation provided compelling evidence of elevated SAT, S100P, and OAZ1 expression in both salivary and serum exosomes of OSCC patients, with a higher trend observed in saliva. These findings are in agreement with recent observations by Kalpani et al. (2024), who reported the upregulation of these genes in salivary samples from OSCC, OSF, and OLP patients in a Sri Lankan cohort 16 , suggesting their broader applicability across Asian populations. In addition to proliferation-related markers, our study examined invasion markers particularly MMP9, and Chemerin, both of which are critical regulators of tumor metastasis 45 , 46 . MMP9 has been extensively correlated with poor prognosis and increased metastatic potential in OSCC 47 , while Chemerin modulates immune responses and extracellular matrix remodeling to facilitate tumor progression 48 . Our data demonstrated elevated MMP9 expression in both salivary and serum exosomal transcripts from OSCC patients, with higher levels detected in serum, rather than saliva. These observations are consistent with findings from Georgia (2023) and Xiaoyuan et al. (2024), who highlighted the diagnostic relevance of MMP9 and Chemerin in OSCC 12 , 49 . Importantly, our study analysed exosomes derived from paired saliva and serum samples, providing a more comprehensive validation of these biomarkers. Assessing the diagnostic performance of biomarkers requires evaluation of their sensitivity and specificity. To this end, ROC curve analysis identified salivary exosomal TNF-α, OAZ1 and MMP9 as top-performing markers, with AUC values of 0.88, 0.87, and 0.84, respectively, when selecting the most highly expressed molecule from each category (cytokines, proliferation, and invasion). On other hand, serum exosome biomarkers including IL1, OAZ1, and MMP9 were also showed notable performance, with AUC values of 0.86, 0.80, and 0.83, respectively. Consistent with previous studies suggesting that multi-marker panels enhance diagnostic efficiency 50 , 51 , combining TNF-α, OAZ1 and MMP9 improved the AUC to 0.89, with a sensitivity and specificity of 85% and 80%, respectively. However, when excluded MMP9, a two-marker panel of TNF-α and OAZ1 achieved superior specificity of 90% with comparable sensitivity of 80%, an AUC of 0.89, and a Youden index of 0.70. This could be attributed from grade-specific expression of MMP9 52 , which our data showed to be more prominent in advanced OSCC grades (II and III), thus slightly lowering the overall AUC. To this end, Yudan et al 2022 review provide evidence of MMP9 positive correlation with clinical stages of various human cancers 53 . Furthermore, serum exosome panels, particularly IL1 and OAZ1, also demonstrated good diagnostic potential, with a sensitivity and specificity of 75% and 90%, respectively (AUC: 0.89, Youden index: 0.65). However, their overall sensitivity was lower than that of salivary exosome panels. Notably, unlike saliva, serum-derived exosomal MMP9 levels did not show significant variation across OSCC grades (II, II, III), limiting its prognostic applicability. Furthermore, other salivary exosomal markers such as IL8, S100P, SAT, and OAZ1 were also exhibited significant expression differences between early and advanced OSCC grades, providing the first evidence of their potential role in disease staging. Additionally, salivary exosomal IL6 expression showed a positive correlation with lymph node metastasis, a finding that was not observed with serum biomarkers. Although direct evidence linking IL6 to lymph node metastasis in OSCC is limited, similar associations have been reported in bladder cancer and other malignancies. For instance, Jun et al. (2017) reported higher IL-6 immunopositivity in deeply invasive cancer cells 54 , supporting the relevance of our observations. Taken together, these findings underscore the diagnostic and prognostic value of salivary exosomal mRNAs in OSCC. Although several serum-derived exosomal biomarkers were elevated in patients with OSCC, their overall sensitivity and grade-specific discriminatory power were comparatively lower. Therefore, our study highlights salivary exosomal TNF-α, OAZ1, and MMP9 as promising biomarkers for OSCC detection. Despite these promising findings, this study had several limitations. First, the absence of data from benign tumor cases limits the assessment of marker specificity. Second, while the model effectively distinguished OSCC from healthy controls, evaluating the expression of these markers in other cancer types could offer broader insights into their diagnostic utility. Third, increasing the sample size and validating the proposed mRNA panel across diverse cohorts, along with a longitudinal analysis, would help improve the robustness of the model. Lastly, incorporating additional exosomal biomolecules, such as miRNAs, may further strengthen the diagnostic potential and enhance our understanding of OSCC pathophysiology. Future studies are warranted to explore these aspects and advance the development of a more comprehensive and clinically robust diagnostic model. Conclusions Our study highlights that elevated levels of exosomal mRNAs including IL1, IL6, IL8, TNF-α, OAZ1, SAT, S100P, MMP9, and Chemerin in serum and saliva exosomes may serve as biomarkers for OSCC screening. Among these, a salivary exosomal panel comprising TNF-α and OAZ1 has demonstrated strong diagnostic potential with high sensitivity and specificity. Furthermore, salivary markers such as MMP9 and IL6 are relevant for tumor grading and metastasis, suggesting their prognostic value. Therefore, salivary exosomal mRNA profiling could be a valuable, non-invasive, and cost-effective approach for OSCC detection and clinical stratification. Future studies involving large, multicentric cohorts are warranted to validate these findings and enable the development of rapid, clinically applicable diagnostic kits for OSCC. Declarations Conflict of interest: None Funding: This work was supported by Apollo Hospitals Educational and Research Foundation (AHERF), Hyderabad, India. Author Contribution Sarwareddy Kartik Kumar contributed to conceptualization, methodology, sample collection, molecular profiling, data analysis, interpretation, visualization, and manuscript preparation. Neeharika Kanaparthi supported methodology development, data generation, and curation. Babiola Annes Sesuraj, Rajesh V. Bendre, and Nagalla Balakrishna contributed to data analysis and visualization. Saroj Kumar assisted with data visualization. Arsheed Hussain Hakeem provided clinical supervision, coordinated sample collection, supported data interpretation, and reviewed the manuscript. Manda Venkata Sasidhar supervised the project, contributed to strategic planning, funding acquisition, data interpretation, and final manuscript review and editing. All authors reviewed and approved the final manuscript. Acknowledgement We thank our AHERF President, Dr.N.K.Ganguly, Vice president; Ishita Shively, Clinical Director; Dr. Jayanthi Swaminathan for active organizational support Data Availability The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request. References Silva, L. C. et al. The importance of early treatment of oral squamous cell carcinoma: Case report. Oral Oncol. 144 , 106442 (2023). Yang, J. et al. Survival analysis of age-related oral squamous cell carcinoma: A population study based on SEER. 28 , 413 (2023). Ali, K. J. E. B. D. Oral cancer-the fight must go on against all odds. 23 , 1038 (2022). Akashanand et al. Burden of oral cancer and associated risk factors at national and state levels: A systematic analysis from the global burden of disease in India, 1990–2021. Oral Oncol. 159 , 107063 (2024). Pekarek, L. et al. Emerging histological and serological biomarkers in oral squamous cell carcinoma: Applications in diagnosis, prognosis evaluation and personalized therapeutics (Review). Oncology reports 50, (2023). 10.3892/or.2023.8650 Ghallab, N. A. & Shaker, O. G. Serum and salivary levels of chemerin and MMP-9 in oral squamous cell carcinoma and oral premalignant lesions. Clin. Oral Invest. 21 , 937–947. 10.1007/s00784-016-1846-8 (2017). Bastías, D., Maturana, A., Marín, C., Martínez, R. & Niklander, S. E. J. I. J. o. M. S. Salivary biomarkers for oral cancer detection: an exploratory systematic review. 25, 2634 (2024). Manda, S. & Sarvareddy, K. in Beyond the Blueprint - Decoding the Elegance of Gene Expression (ed Morteza Seifi)IntechOpen, (2024). Wang, S., Yang, M., Li, R. & Bai, J. J. E. j. o. m. r. Current advances in noninvasive methods for the diagnosis of oral squamous cell carcinoma: a review. 28 , 53 (2023). Suri, S. et al. Recent advances in minimally invasive biomarkers of OSCC: from generalized to personalized approach. Front. oral health . 5 , 1426507. 10.3389/froh.2024.1426507 (2024). Bozyk, N. et al. Salivary exosomes as biomarkers for early diagnosis of oral squamous cell carcinoma. Oral Oncol. Rep. 6 , 100017 (2023). Hu, X. et al. Prognostic significance of serum Chemerin and neutrophils levels in patients with oral squamous cell carcinoma. Heliyon 10 , e32393 (2024). Mohtasham, N. et al. Serum mir-31-5p is a reliable biomarker in patients with oral squamous cell carcinoma and oral lichen planus. 25 , 77 (2024). Bao, Z. & Yi, B. J. S. R. Analysis of preoperative serum cytokine levels in patients with oral squamous cell carcinoma. 15 , 13537 (2025). Wu, J. Y. et al. Potential biomarkers in saliva for oral squamous cell carcinoma. Oral Oncol. 46 , 226–231 (2010). Senevirathna, K. et al. Diagnostic potential of salivary IL-1β, IL-8, SAT, S100P, and OAZ1 in oral squamous cell carcinoma, oral submucous fibrosis, and oral lichen planus based on findings from a Sri Lankan cohort. 14, 27226 (2024). Jain, A. et al. Identification of potential salivary biomarker panels for oral squamous cell carcinoma. 11 , 3365 (2021). Dai, J. et al. Exosomes: key players in cancer and potential therapeutic strategy. 5, 145 (2020). Maqsood, Q., Sumrin, A., Saleem, Y., Wajid, A. & Mahnoor, M. Exosomes in Cancer: Diagnostic and Therapeutic Applications. Clin. Med. Insights Oncol. 18 , 11795549231215966. 10.1177/11795549231215966 (2024). Wang, F. et al. Identification of blood-derived exosomal tumor RNA signatures as noninvasive diagnostic biomarkers for multi-cancer: a multi-phase, multi-center study. 24 , 60 (2025). Kumar, S. K. & Sasidhar, M. V. J. M. P. Recent trends in the use of small extracellular vesicles as optimal drug delivery vehicles in oncology. 20 , 3829–3842 (2023). Sarwareddy, K. K. et al. Harnessing tomato-derived small extracellular vesicles as drug delivery system for cancer therapy. 11 , 2461956 (2025). Chen, C. M. et al. Exosome-derived microRNAs in oral squamous cell carcinomas impact disease prognosis. Oral Oncol. 120 , 105402 (2021). Welsh, J. A. et al. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches. J. Extracell. vesicles . 13 , e12404. 10.1002/jev2.12404 (2024). De Nunzio, V. et al. Plasma-Derived Exosomes from NAFLD Patients Modulate the Cannabinoid Receptors’ Expression in Cultured HepaRG Cells. 24 , 1739 (2023). Kumar, S. K. & Mani, K. P. J. C. Proinflammatory signaling mechanism of endocan in macrophages: Involvement of TLR2 mediated MAPK-NFkB pathways. 175 , 156482 (2024). Bracht, J. W. et al. Analysis of extracellular vesicle mRNA derived from plasma using the nCounter platform. 11 , 3712 (2021). Kumar, S. K. & Mani, K. P. Endocan alters nitric oxide production in endothelial cells by targeting AKT/eNOS and NFkB/iNOS signaling. Nitric Oxide . 117 , 26–33. https://doi.org/10.1016/j.niox.2021.09.006 (2021). Suri, S. et al. Recent advances in minimally invasive biomarkers of OSCC: from generalized to personalized approach. 5 , 1426507 (2024). Singh, P., Verma, J. K. & Singh, J. K. J. S. r. Validation of salivary markers, IL-1β, IL-8 and Lgals3bp for detection of oral squamous cell carcinoma in an Indian population. 10 , 7365 (2020). Tan, Y. et al. Oral squamous cell carcinomas: state of the field and emerging directions. Int. J. Oral Sci. 15 10.1038/s41368-023-00249-w (2023). Ghosh, S. et al. Harnessing exosomes as cancer biomarkers in clinical oncology. 24 , 278 (2024). Nakamichi, E. et al. Detection of serum/salivary exosomal Alix in patients with oral squamous cell carcinoma. 27 , 439–447 (2021). Zlotogorski-Hurvitz, A. et al. FTIR-based spectrum of salivary exosomes coupled with computational-aided discriminating analysis in the diagnosis of oral cancer. 145 , 685–694 (2019). Osteikoetxea, X. et al. Improved characterization of EV preparations based on protein to lipid ratio and lipid properties. PloS one . 10 , e0121184. 10.1371/journal.pone.0121184 (2015). Babiuch, K. et al. Evaluation of Proinflammatory, NF-kappaB Dependent Cytokines: IL-1α, IL-6, IL-8, and TNF-α in Tissue Specimens and Saliva of Patients with Oral Squamous Cell Carcinoma and Oral Potentially Malignant Disorders. J. Clin. Med. 9 10.3390/jcm9030867 (2020). Sahibzada, H. A. et al. Salivary IL-8, IL-6 and TNF-α as Potential Diagnostic Biomarkers for Oral Cancer. Diagnostics (Basel Switzerland) . 7 10.3390/diagnostics7020021 (2017). St John, M. A. et al. Interleukin 6 and interleukin 8 as potential biomarkers for oral cavity and oropharyngeal squamous cell carcinoma. Archives otolaryngology–head neck Surg. 130 , 929–935. 10.1001/archotol.130.8.929 (2004). Krishnan, R. et al. Association of serum and salivary tumor necrosis factor-α with histological grading in oral cancer and its role in differentiating premalignant and malignant oral disease. Asian Pac. J. cancer prevention: APJCP . 15 , 7141–7148. 10.7314/apjcp.2014.15.17.7141 (2014). Dineshkumar, T. et al. Salivary and Serum Interleukin-6 Levels in Oral Premalignant Disorders and Squamous Cell Carcinoma: Diagnostic Value and Clinicopathologic Correlations. Asian Pac. J. cancer prevention: APJCP . 17 , 4899–4906. 10.22034/apjcp.2016.17.11.4899 (2016). Lisa Cheng, Y. S. et al. Salivary interleukin-6 and‐8 in patients with oral cancer and patients with chronic oral inflammatory diseases. 85 , 956–965 (2014). Hu, Y., Han, Y., He, M., Zhang, Y. & Zou, X. J. O. L. S100 proteins in head and neck squamous cell carcinoma. 26 , 362 (2023). Gibadulinova, A., Tothova, V., Pastorek, J. & Pastorekova, S. J. A. a. Transcriptional regulation and functional implication of S100P in cancer. 41 , 885–892 (2011). Tsuji, T. et al. Ornithine decarboxylase antizyme upregulates DNA-dependent protein kinase and enhances the nonhomologous end-joining repair of DNA double-strand breaks in human oral cancer cells. 46 , 8920–8932 (2007). Barillari, G. The Impact of Matrix Metalloproteinase-9 on the Sequential Steps of the Metastatic Process. Int. J. Mol. Sci. 21 10.3390/ijms21124526 (2020). Sun, X., Guo, Y. & J. I. J. o. E. Chemerin Enhances Migration and Invasion of OC Cells via CMKLR1/RhoA/ROCK-Mediated EMT. 7957018 (2024). (2024). Jose, D. & Mane, D. R. Correlation of matrix metalloproteinase-9 expression with morphometric analysis of mucosal vasculature in oral squamous cell carcinoma, oral epithelial dysplasia, and normal oral mucosa. Int. J. health Sci. 12 , 36–43 (2018). Hu, X. et al. Neutrophils Promote Tumor Progression in Oral Squamous Cell Carcinoma by Regulating EMT and JAK2/STAT3 Signaling Through Chemerin. Front. Oncol. 12 , 812044. 10.3389/fonc.2022.812044 (2022). Benitha, G. et al. Evaluation of Serum Levels of Matrix MetalloProteinase-9 (MMP-9) in Oral Squamous Cell Carcinoma and Its Clinicopathological Correlation. Cureus 15 , e34954. 10.7759/cureus.34954 (2023). Lima, A. R. et al. Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine. Br. J. Cancer . 121 , 857–868. 10.1038/s41416-019-0585-4 (2019). Tang, S. et al. Combination of four serum exosomal MiRNAs as novel diagnostic biomarkers for early-stage gastric cancer. 11 , 237 (2020). Patil, R. et al. Expression of matrix metalloproteinase-9 in histological grades of oral squamous cell carcinoma: An immunohistochemical study. J. oral maxillofacial pathology: JOMFP . 25 , 239–246. 10.4103/0973-029x.325121 (2021). Zeng, Y., Gao, M., Lin, D., Du, G. & Cai, Y. Prognostic and Immunological Roles of MMP-9 in Pan-Cancer. BioMed research international 2592962, (2022). 10.1155/2022/2592962 (2022). Zeng, J., Tang, Z. H., Liu, S. & Guo, S. S. Clinicopathological significance of overexpression of interleukin-6 in colorectal cancer. World J. Gastroenterol. 23 , 1780–1786. 10.3748/wjg.v23.i10.1780 (2017). Additional Declarations No competing interests reported. Supplementary Files Supplimentarydata.pdf NewCompressedzippedFolder.zip NewCompressedzippedFolder.zip Cite Share Download PDF Status: Published Journal Publication published 03 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 22 Jul, 2025 Reviews received at journal 17 Jul, 2025 Reviews received at journal 15 Jul, 2025 Reviewers agreed at journal 09 Jul, 2025 Reviewers agreed at journal 08 Jul, 2025 Reviewers agreed at journal 25 Jun, 2025 Reviewers invited by journal 23 Jun, 2025 Editor assigned by journal 23 Jun, 2025 Submission checks completed at journal 19 Jun, 2025 First submitted to journal 19 Jun, 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6905382","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":475561524,"identity":"6702dad7-28e7-48e1-9e04-016bff57ead0","order_by":0,"name":"Sarwareddy Kartik Kumar","email":"","orcid":"","institution":"Apollo Hospitals Educational and Research Foundation (AHERF), Apollo Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Sarwareddy","middleName":"Kartik","lastName":"Kumar","suffix":""},{"id":475561526,"identity":"1dad3a24-4354-476d-b7e7-cef1d4a1ff3b","order_by":1,"name":"Neeharika Kanaparthi","email":"","orcid":"","institution":"Sephirah innovations Pvt Ltd, Apollo Hospitals Educational and Research Foundation","correspondingAuthor":false,"prefix":"","firstName":"Neeharika","middleName":"","lastName":"Kanaparthi","suffix":""},{"id":475561529,"identity":"535ec04d-eda0-45e6-8a09-173f01c13f59","order_by":2,"name":"Babiola Annes Sesuraj","email":"","orcid":"","institution":"University of Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Babiola","middleName":"Annes","lastName":"Sesuraj","suffix":""},{"id":475561530,"identity":"15d146d7-825c-4eb0-a3e5-319c1fc5e582","order_by":3,"name":"Rajesh V Bendre","email":"","orcid":"","institution":"Apollo Diagnostics","correspondingAuthor":false,"prefix":"","firstName":"Rajesh","middleName":"V","lastName":"Bendre","suffix":""},{"id":475561531,"identity":"91392fa4-6e3b-42cf-b04b-9365868ac360","order_by":4,"name":"Nagalla Balakrishna","email":"","orcid":"","institution":"Apollo Institute of Medical Sciences \u0026 Research","correspondingAuthor":false,"prefix":"","firstName":"Nagalla","middleName":"","lastName":"Balakrishna","suffix":""},{"id":475561534,"identity":"1c931979-7c43-4143-a1d6-8b40935b4d74","order_by":5,"name":"Saroj Kumar","email":"","orcid":"","institution":"All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Saroj","middleName":"","lastName":"Kumar","suffix":""},{"id":475561535,"identity":"9104d3ff-89b7-4345-b76d-085193f49844","order_by":6,"name":"Arsheed Hussain Hakeem","email":"","orcid":"","institution":"Apollo cancer Institute, Apollo Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Arsheed","middleName":"Hussain","lastName":"Hakeem","suffix":""},{"id":475561536,"identity":"0bcd322e-37c0-4aa8-9e16-9a89a5da85ee","order_by":7,"name":"Manda Venkata Sasidhar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYJCCA7wNDAz8DDxApg0pWiQbQFrSgJiNGD0gLQYHiNUi33784YG3O+zyjY+fPfi4IoEhj1++Ab8WgzM5Bgfnnkm23HYmL9nwTAJDsWQbAVsMGHIYDvO2MRuYHcgxk2z8wZC44Rghh/U/fwDUUm9g3P/G/GdDAkPifkJaGG4kGAC1HDYwkMgxYwRp2UDI+wY33gD90nbcQOLGG2PJhgSJxBnHEgg5LP3xh7dt1Qb8/TmGHxsSbBL7mw8QchkqkCBN+SgYBaNgFIwC7AAAHyNGhfg1tL4AAAAASUVORK5CYII=","orcid":"","institution":"Apollo Hospitals Educational and Research Foundation (AHERF), Apollo Hospitals","correspondingAuthor":true,"prefix":"","firstName":"Manda","middleName":"Venkata","lastName":"Sasidhar","suffix":""}],"badges":[],"createdAt":"2025-06-16 12:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6905382/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6905382/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-22246-1","type":"published","date":"2025-11-03T15:57:43+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85616063,"identity":"e53792e1-f54c-490a-86df-b3a9484b8947","added_by":"auto","created_at":"2025-06-29 14:34:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":798870,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of exosomes isolated from serum and saliva of HC and OSCC patients. \u003c/strong\u003e(A) Protein concentrations of serum and saliva derived exosomes quantified using BCA assays from HC and OSCC patients revealed distinct biomolecular profiles. (B) Analysis of lipid levels in serum and saliva derived exosomes using Sulfo-phospho-vanillin assay (SPVA) (C) The protein-to-lipid ratio was approximately 2 for serum exosomes and 1 for salivary exosomes, consistent with the characteristic lipid bilayer structure of exosomes and indicating good sample quality. (D) NTA analysis showed an average particle size of 150-200 nm, representing the overall size distribution of isolated particles. (E) Zeta potential measurements confirmed a net negative surface charge of the particles, supporting their colloidal stability. (F) TEM analysis revealed the round shaped morphology with \u0026lt;100 nm in diameter particles, indicating the presence exosomes. (G) Western blotting detected the expression of classical exosome markers CD81, HSP70, and TSG101 in both serum and saliva derived exosomes from HC and OSCC patients, further validating the successful isolation of exosomes.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/dbe2c37afc5cccc02f26b738.jpg"},{"id":85616065,"identity":"7b0b5029-8492-4567-b1f5-08cae280f60e","added_by":"auto","created_at":"2025-06-29 14:34:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":433051,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential expression of cytokines, proliferation/ invasion, and metastasis-related mRNAs in saliva-derived exosomes of OSCC patients. \u003c/strong\u003e(A) qRT-PCR analysis revealed significantly elevated levels of pro-inflammatory cytokine mRNAs, including IL1, IL6, IL8, and TNF-α, in saliva-derived exosomes from OSCC patients compared to HC. (B) mRNA Expression analysis of proliferation and invasion-associated genes demonstrated upregulation of S100P, SAT, and OAZ1 in OSCC patents. (C) Gene expression of MMP9 and chemerin were significantly increased in OSCC patients. Data are presented as median with IQR from 40 HC and 40 OSCC patients’ saliva derived exosome samples. Statistical significance was assessed using the non-parametric Mann Whitney U test, with ***p \u0026lt; 0.001 and ****p \u0026lt; 0.0001 vs HC, highlighting the markedly elevated exosomal mRNA levels in OSCC patients.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/d64418d31885370e8673c625.jpg"},{"id":85617026,"identity":"28af4c18-4f29-43c8-84a1-d3b51d589552","added_by":"auto","created_at":"2025-06-29 14:42:40","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":887692,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curve analysis of selected salivary exosomal mRNA biomarkers for predicting OSCC using a logistic regression model. \u003c/strong\u003e(A–I) ROC curves depicting the individual diagnostic performance of nine salivary exosomal mRNAs including IL1, IL6, IL8, TNF-α, S100P, SAT, OAZ1, MMP9, and chemerin in discriminating OSCC patients from HC, evaluated for sensitivity and specificity, with an AUC of 0.69 to 0.88. (J) Combined ROC analysis of TNF-α, OAZ1 and MMP9 demonstrated improved diagnostic accuracy compared to individual markers (AUC: 0.89). (K) The combination of TNF-α with OAZ1 yielded superior discriminatory power, indicating a robust predictive model with improved specificity (90%) with good sensitivity (80%) for OSCC detection ((AUC: 0.89). These findings highlight the potential of TNF-α with OAZ1 mRNA panels in diagnosing OSCC, as a non-invasive tool.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/4d563d8f383c5decc64800a9.jpg"},{"id":85616067,"identity":"bcaa6f38-a34e-4a95-acb3-4defd6b96269","added_by":"auto","created_at":"2025-06-29 14:34:40","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":415082,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSerum exosomal mRNA expression profiles of selected cytokines, proliferation/invasion, and metastasis markers in HC (n=40) and OSCC patients (n=40). \u003c/strong\u003e(A) q-RT-PCR analysis of serum-derived exosomal mRNAs revealed significantly elevated levels of IL1, IL8, and TNF-α in OSCC patients compared to HC, whereas IL6 showed an increasing trend without reaching statistical significance. (B) Proliferation and invasion associated genes, including S100P, SAT, and OAZ1, were upregulated in serum exosomes of OSCC patients, normalized against GAPDH. (C) Notable elevation of MMP9 and chemerin transcripts was observed in OSCC serum exosomes. Data were represented as median with IQR and analyzed using the non-parametric Mann-Whitney U test. Statistical significance was denoted as *p \u0026lt; 0.05, ***p \u0026lt; 0.001, and ****p \u0026lt; 0.0001 vs control. Overall, this data indicates upregulation of key mRNA biomarkers in serum exosomes of OSCC patients.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/988da92edd891dd555092f46.jpg"},{"id":85616069,"identity":"8e43f8f0-a18e-4b1c-9464-23194ed44abb","added_by":"auto","created_at":"2025-06-29 14:34:40","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":829096,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Curves of significantly elevated serum exosomal mRNA Signatures for OSCC Detection. \u003c/strong\u003e(A–I) ROC curve analysis of individual serum-derived exosomal mRNA biomarkers IL1, IL6, IL8, TNF-α, S100P, SAT, OAZ1, MMP9, and chemerin for the identification of OSCC, AUC values ranging from 0.63 to 0.86. (J) A combined model comprising three mRNAs IL1, OAZ1 and MMP9 demonstrated improved diagnostic performance, with an AUC of 0.89 and sensitivity and specificity both exceeding 80%. (K) A two-gene panel of IL1 and OAZ1 showed optimal performance, yielding a high sensitivity of 90% and an AUC of 0.89, suggesting its potential as an ideal, minimally invasive biomarker combination for OSCC detection. However, sensitivity of the panel (75%) was comparatively lesser than saliva panel (80%).\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/8221d9c2c8fd9fce95ceb7d5.jpg"},{"id":85617028,"identity":"8d0c70f2-55ab-47dc-9b68-84cd7c9c2970","added_by":"auto","created_at":"2025-06-29 14:42:40","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":584979,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation of salivary exosome-derived mRNA biomarkers with OSCC tumor grade. \u003c/strong\u003eRelative mRNA expression of selected genes IL1, IL6, IL8, TNF-α, S100P, SAT, OAZ1, MMP9, and Chemerin is shown across different tumor grades (A–I). Among these, OAZ1 (G) and MMP9 (H) exhibited a strong positive association with tumor grade, with significantly elevated expression levels observed in G3 compared to G1 and G2 tumors (***p \u0026lt; 0.001), suggesting their potential role in OSCC progression.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/1ffa6c7bf5007aa89614753a.jpg"},{"id":95564070,"identity":"2cc0af45-f3be-463e-bb2c-81d3a5e183d3","added_by":"auto","created_at":"2025-11-10 16:07:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5184324,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/8521e407-cbcf-485a-8ca2-8e9b9e6de7cc.pdf"},{"id":85616072,"identity":"b2aba3b2-70eb-439c-bfbb-4cd4034585a5","added_by":"auto","created_at":"2025-06-29 14:34:41","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":187675,"visible":true,"origin":"","legend":"","description":"","filename":"Supplimentarydata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/5737099c59575ab1b3b150dc.pdf"},{"id":85616076,"identity":"b5f2fdf2-a38d-442b-a821-9b2e6aaa87f7","added_by":"auto","created_at":"2025-06-29 14:34:41","extension":"zip","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2851633,"visible":true,"origin":"","legend":"","description":"","filename":"NewCompressedzippedFolder.zip","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/22e0be04eb207fd064416f7a.zip"},{"id":85619383,"identity":"90767a23-7a2a-4380-8d33-ffd536cb9a33","added_by":"auto","created_at":"2025-06-29 14:58:41","extension":"zip","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2851633,"visible":true,"origin":"","legend":"","description":"","filename":"NewCompressedzippedFolder.zip","url":"https://assets-eu.researchsquare.com/files/rs-6905382/v1/89d70d7665386ddbc3f25e0b.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of salivary and serum exosomal mRNAs as biomarkers for the diagnosis and prognosis of oral squamous cell carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOral cancer is one of the most common types of head and neck malignancy, with oral squamous cell carcinoma (OSCC) accounting for nearly 90% of all oral cancer cases. OSCC typically arises from squamous epithelial cells lining the inner oral mucosa and is known for its aggressive nature. The five-year survival rate varies significantly, ranging from 80\u0026ndash;90% when diagnosed at an early stage, but drops to approximately 30% in advanced stages. Although the etiology of OSCC is multifactorial, key risk factors include tobacco use (smoking or chewing), excessive alcohol consumption, and betel nut chewing, with a higher prevalence observed in males \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The global disease burden of OSCC varies geographically, with significantly higher incidence rates reported in Asian countries \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. A recent national-level report by Akashanand et al. (2024) identified India as a major contributor to the global burden, accounting for nearly one-third of all oral cancer cases worldwide \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Clinically, OSCC presents with symptoms such as non-healing ulcers and oral pain in the initial phase, progressing to enlarged oral masses, dysphagia, and odynophagia in more advanced stages. Currently, the gold standard for OSCC diagnosis involves clinical oral examination followed by histopathological evaluation of the tissue obtained through biopsy \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, tissue biopsy methods are invasive, tumour molecular heterogeneity may not be captured, and timely screening and monitoring of the therapeutic response may be challenging.\u003c/p\u003e \u003cp\u003eAdvances in oral cancer diagnostic research have increasingly focused on the development of minimally invasive or non-invasive molecular biomarker-based liquid biopsies to improve diagnostic accuracy, offer comprehensive insights into tumour biology, and enable real-time monitoring \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Various biological fluids such as serum, saliva, urine, cerebrospinal fluid, and prostatic fluid are being explored for tumour-derived molecule profiling, among which serum and saliva are the most extensively studied and clinically reliable for developing diagnostic platforms for oral cancer \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Serum contains a diverse pool of tumour-derived molecules released into the circulation, including genomic, proteomic, transcriptomic, epigenetic markers, and circulating tumour cells (CTCs), offering a systemic snapshot of tumour dynamics for various cancers including OSCC. In contrast, saliva, owning to its direct contact with the tumour site in OSCC, is enriched with locally derived biomarkers such as RNA, proteins, enzymes, and extracellular vesicles like exosomes \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Recent studies have explored both serum and saliva for OSCC detection, with growing interest in saliva owing to its non-invasive collection and tumour proximity. For instance, Xiaoyuan et al. (2024), Nooshin et al. (2024), and Zhenying et al. (2025) identified serum biomarkers such as chemerin, miR-31-5p, and IL6 \u003csup\u003e12\u0026ndash;14\u003c/sup\u003e, while Jia et al (2010), Kalpani et al. (2024), and Anu et al. (2021) demonstrated the clinical relevance of DNA, RNA, and protein analysis in saliva \u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, most of these studies were conducted on small cohorts, and there is a lack of population-specific research in India, despite its high OSCC incidence.\u003c/p\u003e \u003cp\u003eExosomes are small extracellular vesicles ranging from 30\u0026ndash;200 nm in diameter, known to play key roles in cancer pathophysiology through their cargo, and are stably enclosed within a lipid bilayer, which includes mRNAs, miRNAs, and proteins \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In recent years, there has been a growing interest in developing exosome-based platforms for cancer diagnostics and therapeutics owning to their demonstrated efficiency \u003csup\u003e\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Consequently, few studies have focused on identifying exosomal biomarkers in serum and saliva for OSCC due to their high diagnostic sensitivity and specificity. Notably, Natalie et al. (2023) identified salivary exosomal proteins such as AMER3, LOXL2, and AL9A1 as potential OSCC biomarkers, while Ching et al. (2021) demonstrated that serum exosomal miRNAs like miR-155 and miR-21 could serve as diagnostic and prognostic indicators \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. However, the diagnostic potential of exosomes in OSCC remains in its infancy, and to the best of our knowledge, no studies have explored exosomal mRNAs in this context.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to evaluate nine mRNAs including MMP9, IL1, IL6, IL8, TNF-α, Chemerin, OAZ1, SAT, and S100P in both serum and salivary exosomes from histopathologically confirmed OSCC patients, to gain a comprehensive understanding of the tumour microenvironment (TME). These genes were selected to capture molecular features related to cytokine signalling, tumour cell proliferation, and cellular invasion. Our findings demonstrated that salivary exosomal biomarkers possess greater diagnostic potential than those derived from serum, showing significant correlation with tumour grade and lymph node metastasis. Based on this pilot analysis, we propose a salivary exosomal biomarker panel, particularly TNF-α in combination with OAZ1, as a promising molecular diagnostic tool for OSCC, with potential relevance for the Indian population.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eSample Size Estimation:\u003c/p\u003e \u003cp\u003eThis preliminary study aimed to explore exosome gene panels derived from serum and saliva as potential biomarkers for OSCC, establishing a proof of concept by analyzing expression patterns and correlation trends before conducting large-scale studies. The sample size was estimated based on the standard formula for sensitivity analysis, assuming a 95% confidence interval, expected sensitivity of 98%, specificity of 92.1%, and disease prevalence of 20%. An acceptable margin of error (precision) of 10% (d\u0026thinsp;=\u0026thinsp;0.10) was considered. Based on this, at least 38 samples were required for the study to achieve statistically meaningful data.\u003c/p\u003e \u003cp\u003ePatient Recruitment and Sample Selection:\u003c/p\u003e \u003cp\u003eA total of 40 histopathologically confirmed OSCC patients were recruited from the Apollo Cancer Institute, Apollo Hospitals, Jubilee Hills, Hyderabad, between May 2023 and September 2024. Exclusion criteria included patients with recurrent disease, those unwilling to provide informed consent, individuals with a history of other malignancies, and patients with sexually transmitted diseases (STDs). Age-matched healthy controls (40 individuals) were selected following an oral cavity examination by a specialist to confirm the absence of any oral pathological lesions that might influence saliva composition. All participants, including OSCC patients and healthy controls, voluntarily agreed to participate in the study and provided informed consent. Demographic parameters, including age and gender, were recorded during sample collection, whereas clinical data such as tumor grade, site, and lymph node involvement were retrieved from medical records following histopathological evaluation. The study protocol was reviewed and approved by the Institutional Ethics Committee at Apollo Hospitals (IEC No. AHJ-C-S-006/02\u0026ndash;25). Participants were informed about the study objectives and the option to withdraw at any time without consequences. All participants provided informed consent, and all serum and saliva samples were anonymized with code labels, ensuring that personal identifiers were not included in the data.\u003c/p\u003e \u003cp\u003eCollection of Serum and Saliva Samples:\u003c/p\u003e \u003cp\u003ePaired blood and saliva samples were collected from all OSCC patients and healthy controls (HC) enrolled in the study. For each individual, 5 mL of peripheral blood was drawn into blood collection tubes (BD biosciences, USA). After allowing the samples to rest at room temperature for 1 hour, they were centrifuged at 2000 rpm for 10 minutes at 4\u0026deg;C to separate the serum. The resulting supernatant was carefully transferred into 1.5 mL microcentrifuge tubes and subjected to a second centrifugation at 3000 rpm for 10 minutes at 4\u0026deg;C to remove any residual cellular debris. The purified serum was then aliquoted and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further use for exosome isolation. In parallel, approximately 1 mL of unstimulated saliva was collected using the Norgen Biotek Saliva Collection and Preservation Kit (Norgenbiotek, Canada). Participants were instructed to refrain from eating or drinking for at least one hour prior to saliva collection to ensure sample consistency. Following collection, saliva samples were centrifuged at 1000 rpm for 10 minutes at 4\u0026deg;C to eliminate any debris. The clarified saliva was then stored at \u0026minus;\u0026thinsp;80\u0026deg;C until exosome isolation. All samples were processed within 3 hours of collection to preserve their integrity. Notably, blood and saliva were collected from the same individual on the same day to ensure sample comparability. Informed consent was obtained from all participants prior to sample collection, and individuals who were unwilling to provide consent were excluded from the study without prejudice.\u003c/p\u003e \u003cp\u003eIsolation of Exosomes from Serum and Saliva:\u003c/p\u003e \u003cp\u003eExosomes were isolated from both serum and saliva samples using commercial Total Exosome Isolation Kits (Thermo Fisher Scientific, USA), following the manufacturer\u0026rsquo;s protocols. Frozen serum and saliva samples were thawed on ice and centrifuged at 2000 \u0026times; g for 30 minutes at 25\u0026deg;C to remove any residual cellular debris. The clarified supernatants were then transferred to fresh 1.5 mL microcentrifuge tubes for exosome isolation. For serum exosome isolation, 500 \u0026micro;L of the sample was mixed with 100 \u0026micro;L of the Total Exosome Isolation Reagent for serum (0.2 volume ratio). The mixture was gently vortexed and incubated at 4\u0026deg;C for 30 minutes. For saliva, 250 \u0026micro;L of the sample was first diluted with 250 \u0026micro;L of phosphate-buffered saline (PBS), followed by the addition of 250 \u0026micro;L of the Total Exosome Isolation Reagent for other body fluids (0.5 volume ratio). The mixture was incubated at 4\u0026deg;C for 60 minutes. Following incubation, both serum and saliva mixtures were centrifuged at 10,000 \u0026times; g for 10 minutes at room temperature to pellet the exosomes. The resulting exosome pellets were resuspended in 1X PBS and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further analysis.\u003c/p\u003e \u003cp\u003eIdentification of Exosomes:\u003c/p\u003e \u003cp\u003eExosomes isolated from serum and saliva were comprehensively characterized using biochemical, biophysical, and molecular methods to evaluate their biochemical composition, size, surface charge, morphology,, and specific protein markers, in accordance with the MISEV2024 guidelines, ensuring their structural integrity and quality \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBiochemical Characterization:\u003c/p\u003e \u003cp\u003eBiochemical characterization included quantification of total protein and lipid content. The protein concentration of the isolated particles was measured using the Bicinchoninic Acid (BCA) assay, while the sulfo-phospho-vanillin (SPV) assay was employed to estimate the lipid content, following established protocols. From these measurements, the protein-to-lipid ratio was calculated, providing insight into the purity of isolated vesicles \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBiophysical Characterization:\u003c/p\u003e \u003cp\u003eNanoparticle Tracking Analysis (NTA) was performed using the ZetaView\u0026reg; x30 system (Particle Metrix, Germany) to determine the size distribution and zeta potential of the particles. This helped confirm that the isolated vesicles were within the expected exosomal size range and exhibited surface charges consistent with stable colloidal particles. Transmission Electron Microscopy (TEM) was used to examine the morphology of the particles. For this, 50 \u0026micro;L of the exosome suspension was loaded onto carbon-coated copper grids and air-dried. The grids were then visualized under the TEM, where the vesicles appeared as round shaped structures, confirming successful exosome isolation \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMolecular characterization:\u003c/p\u003e \u003cp\u003eWestern blotting analysis was performed to analyse the protein expression of exosome specific markers in the isolated particles. In brief, equal amounts of total protein (20 \u0026micro;g) from serum- and saliva-derived exosomes from both OSCC patients and HC were used. The samples were lysed using RIPA buffer, denatured by adding Laemmli buffer, and incubated at 95\u0026deg;C for 10 minutes. Proteins were resolved on a 10% SDS-PAGE gel and transferred onto nitrocellulose membranes. After blocking the membranes with 5% BSA to prevent nonspecific binding, they were incubated overnight at 4\u0026deg;C with primary antibodies against human CD81, TSG101, and HSP70 (Abcam, UK). Following TBST washes, membranes were incubated with HRP-conjugated secondary antibodies for 1 hour at room temperature. Signal detection was performed using a Bio-Rad ECL kit, and the bands were visualized using the ChemiDoc Imaging System \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExosome mRNA Extraction and expression profiling:\u003c/p\u003e \u003cp\u003eTotal RNA was extracted from isolated exosomes using TRIzol\u0026trade; Reagent (Invitrogen, USA) in accordance with the manufacturer's protocol. The concentration and purity of the extracted RNA were assessed using a biospectrophotometer, with 1 \u0026micro;L of each sample measured. Subsequently, 500 ng of total RNA was reverse-transcribed into complementary DNA (cDNA) utilizing the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, USA), following the supplier's instructions. For gene expression analysis, nine target genes including IL1, IL6, IL8, TNFα, OAZ1, SAT, S100P, MMP9, and Chemerin, were selected. Specific primers for these genes were procured from Bioserve Biotechnologies (India) PVT. Ltd and their sequences detailed in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eTo enhance detection sensitivity, 100 ng of cDNA from each sample underwent pre-amplification through 15 PCR cycles using High-Fidelity PCR Master Mix (DXBIDT Laboratories, India) in a thermal cycler (Bio-Rad T100 thermal cycler). The cycling conditions as follows: initial denaturation at 98\u0026deg;C for 30 seconds, denaturation at 98\u0026deg;C for 10 seconds, annealing at 58\u0026ndash;62\u0026deg;C (gene-specific) for 30 seconds (Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), extension at 72\u0026deg;C for 60 seconds, and final extension at 72\u0026deg;C for 10 minutes. The resulting pre-amplified products were diluted into 1:4 ratio with nuclease-free water. Subsequently, 1 \u0026micro;L of the diluted product was subjected to two-step quantitative real-time PCR (qRT-PCR) over 30 cycles using gene-specific primers and High-Throughput qPCR Master Mix (DXBIDT Laboratories, India) on a Bio-Rad Opus 96 Real-Time PCR System. Detailed PCR conditions are provided in Supplementary Table\u0026nbsp;1. Gene expression levels were quantified using the comparative Ct (ΔΔCt) method, with B2M serving as the internal control gene \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStatistical Analyses:\u003c/p\u003e \u003cp\u003eStatistical analyses were conducted using IBM SPSS Statistics (Version 24, Chicago, USA) and GraphPad Prism (Version 8, Boston, USA). Descriptive statistics, including mean, meadian, and standard deviation (SD), were calculated for continuous variables to summarize the data. Chi squire test was used to study the association between gender and groups. To assess differences between HC and OSCC groups in saliva and serum samples, the non-parametric Mann\u0026ndash;Whitney U test was employed, given its suitability for comparing two independent groups without assuming normal distribution, as the data homogeneity has significant deviation. Accordingly, the fold change was represented as the Median with interquartile range (IQR). For evaluating gene expression differences across multiple groups, one-way analysis of variance (ANOVA) was utilized, followed by the Least Significant Difference (LSD) post hoc test to identify specific group differences. In instances where assumptions of normality and homogeneity of variances were not met, the Kruskal\u0026ndash;Walli\u0026rsquo;s test, a non-parametric alternative to ANOVA, was applied. To determine the diagnostic performance of identified gene markers for OSCC, receiver operating characteristic (ROC) curve analyses were performed, calculating the area under the curve (AUC) along with 95% confidence intervals to assess sensitivity and specificity. The diagnostic effectiveness was assessed by Youden index. Furthermore, a combined panel of top-performing individual genes from each category was proposed by computing the cumulative AUC, aiming to enhance diagnostic accuracy using stepwise discriminant function analysis. Throughout the study, a p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDemographic and Clinical Profiling of the selected cohort:\u003c/p\u003e \u003cp\u003eThis study included 80 individuals, comprising 40 patients diagnosed with OSCC and 40 HC. The mean age of OSCC patients was 47.60\u0026thinsp;\u0026plusmn;\u0026thinsp;11.02 years, while the age-matched control group had a mean age of 42.88\u0026thinsp;\u0026plusmn;\u0026thinsp;8.33 years. In terms of gender distribution, the OSCC group predominantly consisted of males (92.5%, n\u0026thinsp;=\u0026thinsp;37), with only 7.5% females (n\u0026thinsp;=\u0026thinsp;3), reflecting the known higher incidence of OSCC among males. The healthy control group also had a male predominance (72.5%, n\u0026thinsp;=\u0026thinsp;29), though with a slightly higher proportion of females (27.5%, n\u0026thinsp;=\u0026thinsp;11) compared to the OSCC group. Tumor localization in the OSCC cohort revealed that the most common sites were the left side of the tongue, right buccal mucosa, and left border of the tongue (n\u0026thinsp;=\u0026thinsp;3 each). These were followed by the left buccal mucosa, right border of the tongue, left lower alveolus, and middle third mandible (n\u0026thinsp;=\u0026thinsp;2 each), while the remaining 23 patients presented with lesions at various other intraoral sites, reflecting the heterogeneity of tumor localization in OSCC. Histopathological grading showed that 40% of tumors were classified as grade I (n\u0026thinsp;=\u0026thinsp;16), another 40% as grade II (n\u0026thinsp;=\u0026thinsp;16), and 20% as grade III (n\u0026thinsp;=\u0026thinsp;8), indicating that the majority of patients had moderately to well-differentiated tumors. TNM staging further revealed that 21 patients (52.5%) had evidence of nodal involvement or metastasis, while 19 patients (47.5%) showed no lymph node involvement (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These demographic and clinical characteristics of the selected cohort highlight the diversity in tumor location, histological grade, and metastatic status in OSCC, providing a foundation for the diagnostic investigations.\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\u003eDemographic and clinical characteristics of oral cancer patients and HC included in the study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOSCC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal Number\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (Mean\u0026thinsp;+\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.6\u0026thinsp;+\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.8\u0026thinsp;+\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (92.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (27.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumour Site\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eleft side of tongue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight buccal mucosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft border tongue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft buccal mucosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight border of tongue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft lower alveolus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle third mandible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTNM (Tumour node metastasis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExosome Characterization Revealed Successful Isolation and Integrity of Serum and Saliva-Derived Exosomes:\u003c/p\u003e \u003cp\u003eExosomes isolated from serum and saliva of OSCC patients and HC were comprehensively characterized using biochemical, biophysical, and molecular approaches to confirm their integrity and purity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Initial biochemical assessment of the isolated particles from both serum and saliva serum showed the higher levels of total protein in OSCC patients, when compared to HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B). However, lipid concentration of the serum derived particles was not shown significance between HC and OSCC, while saliva derived particles had a comparable difference with heightened levels in OSCC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Additionally, the protein-to-lipid ratio of the vesicles was estimated to be 1\u0026ndash;2, supporting the bilayered membrane structure characteristic of exosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). NTA analysis demonstrated that the isolated particles are in the average size of 150 to 200 in diameter with a negative zeta potential, consistent with the size and surface charge typically associated with exosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD and E). TEM analysis further determined their spherical morphology and most vesicles measured below 100 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), indicating the confirmation of exosomes. Further, western blot analysis of exosomal lysates revealed the presence of classical exosome-specific protein markers CD81, HSP70, and TSG101 in both serum- and saliva-derived samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG), validating the exosomal origin of the isolated particles. These findings confirm the successful isolation and structural integrity of exosomes from both biofluids, supporting their utility for subsequent molecular and diagnostic applications.\u003c/p\u003e \u003cp\u003eSalivary Exosomes Exhibit Elevated mRNA Expression in OSCC Patients:\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, all the evaluated genes including, inflammatory cytokines (IL1, IL6, IL8, TNF-α), proliferation/invasion markers (S100P, SAT OAZ1), metastasis related molecules (MMP9, Chemerin) were significantly upregulated in saliva exosoms from OSCC patients compared to HC. Among these, TNF-α demonstrated the highest upregulation of inflammatory cytokines with a 6.0-fold increase (p\u0026thinsp;=\u0026thinsp;0.0001), while the proliferation genes OAZ1 and S100P showed marked upregulation of 9.7-fold and 6.9-fold, respectively (p\u0026thinsp;=\u0026thinsp;0.0001). Notably, in the metastatic panel MMP9 showed a heightened expression with 4.5-folds difference (p\u0026thinsp;=\u0026thinsp;0.0001). The moderate yet statistically significant increases were also observed for Chemerin (2.4-fold; p\u0026thinsp;=\u0026thinsp;0.0001), IL1 (2.7-fold; p\u0026thinsp;=\u0026thinsp;0.001), IL6 (2.9-fold), IL8 (3.85-fold; p\u0026thinsp;=\u0026thinsp;0.002), and SAT (5.79-fold; p\u0026thinsp;=\u0026thinsp;0.0001). These findings indicate a strong inflammatory response, enhanced cellular proliferation, and invasion potential in OSCC, reflecting the underlying tumor biology and suggesting their relevance as diagnostic indicators. Furthermore, ROC curve analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed that TNF-α, MMP9, and OAZ1 individually possess good predictive power for OSCC diagnosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). TNF-α showed 90% sensitivity and 80% specificity (AUC: 0.88), while cell proliferation gene OAZ1 demonstrated a sensitivity of 77.5% and specificity of 87.5% (AUC: 0.87). The invasion/metastasis gene MMP9 achieved a sensitivity of 72% and specificity of 85% (AUC: 0.84). The OSCC-specific gene OAZ1 demonstrated a sensitivity of 77.5% and specificity of 87.5% (AUC: 0.87). Interestingly, combining these markers further improved diagnostic accuracy. The panel TNF-α\u0026thinsp;+\u0026thinsp;OAZ1\u0026thinsp;+\u0026thinsp;MMP9 yielded a sensitivity of 85% and specificity of 80% (AUC: 0.89), while the combination TNF-α with OAZ1 achieved high discriminate power with 80% sensitivity and 90% specificity (AUC: 0.89) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These findings underscore the potential of using single or combined salivary biomarkers for the effective diagnosis of OSCC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC curve characteristics for the significantly upregulated mRNA markers in saliva and serum exosomes and their combined diagnostic potential.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYouden index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSaliva\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.88\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS100P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e77.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e87.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.87\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemerin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP9\u0026thinsp;+\u0026thinsp;TNF-α\u0026thinsp;+\u0026thinsp;OAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u0026thinsp;+\u0026thinsp;OAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOAZ1\u0026thinsp;+\u0026thinsp;SAT\u0026thinsp;+\u0026thinsp;S100P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e87.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.86\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS100P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e85.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e82.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.52\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemerin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP9\u0026thinsp;+\u0026thinsp;IL1\u0026thinsp;+\u0026thinsp;OAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL1\u0026thinsp;+\u0026thinsp;OAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOAZ1\u0026thinsp;+\u0026thinsp;SAT\u0026thinsp;+\u0026thinsp;S100P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIncreased expression of mRNA biomarkers detected in serum exosomes from OSCC patients:\u003c/p\u003e \u003cp\u003eThe median gene expression profiles in serum-derived exosomes demonstrated a pattern consistent with that observed in saliva, with eight out of nine genes significantly upregulated in OSCC when compared to HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). When stratified based on expression magnitude, IL1, TNF-α and OAZ1 exhibited the highest fold changes (9.4, 5.8 and 5.0 respectively; p\u0026thinsp;=\u0026thinsp;0.0001), while S100P, MMP9, SAT and Chemerin showed moderate elevations with median fold changes of 3.1, 2.9, 2.4 and 2.4 (p\u0026thinsp;=\u0026thinsp;0.0001). Lower, yet statistically significant fold increases were observed for chemerin (2.3; p\u0026thinsp;=\u0026thinsp;0.0001) and IL8 (1.5; p\u0026thinsp;=\u0026thinsp;0.032). However, IL6 showed a median fold change of 1.4, but lacked statistical significance (p\u0026thinsp;=\u0026thinsp;0.240), whereas it was significantly upregulated in saliva (2.92-fold; p\u0026thinsp;=\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although gene expression was elevated in both biofluids, overall mRNA levels were shown higher trend in saliva-derived exosomes, suggesting saliva as a more responsive matrix for capturing tumor-associated molecular changes.\u003c/p\u003e \u003cp\u003eFurther, ROC curve analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed the diagnostic potential of serum exosomal markers. IL1 (Sensitivity: 87.5%, Specificity:70%, AUC: 0.86), OAZ1 (75%, 85.5%, 0.80), and MMP9 (82.5%, 70%, 0.83), and emerged as top-performing individual markers (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Importantly, combining these genes enhanced diagnostic power, with the MMP9, IL1, OAZ1 panel achieving 80% sensitivity, 85% specificity, and a higher AUC and Youden index of 0.89 and 0.65 respectively. Similarly, the IL-1 and OAZ1 combination yielded a sensitivity of 75%, specificity of 90%, and an identical AUC of 0.89 with a Youden index of 0.65. These findings further align with results from saliva, where the TNF-α and OAZ1 panel displayed a higher sensitivity (80%) and Youden index (0.70) with comparable specificity and AUC values (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Overall, this consistent and parallel upregulation of selected genes in both saliva and serum exosomes underscores their translational value. Notably, the saliva-based panel offers slightly superior discriminatory performance, reinforcing its promise as a robust, non-invasive genomic biomarker set for OSCC diagnosis.\u003c/p\u003e \u003cp\u003eSaliva exosomal mRNAs Correlated with OSCC Tumor grade and lymph node metastasis:\u003c/p\u003e \u003cp\u003eBeyond their ability to differentiate OSCC patients from HC, saliva-derived exosomal gene markers also demonstrated a significant correlation with tumor progression. A clear trend of increasing gene expression was observed from garde I to grade III in saliva samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), whereas serum-derived exosomal markers did not show any statistically significant association with tumor grades (Supplementary table 2), highlighting the superior discriminatory potential of saliva. Among the identified markers, MMP9 exhibited a marked upregulation, with significantly higher expression from grade II to III (p\u0026thinsp;=\u0026thinsp;0.001) and between grade I and III (p\u0026thinsp;=\u0026thinsp;0.001), indicating its strong association with advanced disease. In the cytokine category, IL8 showed a progressive increase with significant differences between grade II and III (p\u0026thinsp;=\u0026thinsp;0.027) and grade I and III (p\u0026thinsp;=\u0026thinsp;0.011). Although IL6 demonstrated an increasing trend across grades, the difference between grade I and III did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.066), suggesting a weaker grade-association. Notably, within the proliferation/invasion markers, three out of four S100P, SAT, and OAZ1 displayed significant stage-related elevation. Among them, OAZ1 emerged as the most prominent marker, with substantial upregulation in grade III compared to both grade I and II (p\u0026thinsp;=\u0026thinsp;0.006). S100P and SAT also followed a similar trend, with expression levels significantly elevated in grade III (p\u0026thinsp;=\u0026thinsp;0.017, 0.022), supporting their role in tumor progression. However, we did not observe any significant trend changes in the median expression levels of other markers including IL1 (p\u0026thinsp;=\u0026thinsp;0.72), TNF-α (p\u0026thinsp;=\u0026thinsp;0.366) Chemerin (p\u0026thinsp;=\u0026thinsp;0.390) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Collectively, these findings emphasize that saliva-derived exosomal gene signatures, particularly MMP9 not only differentiate OSCC patients from HC but also reflect tumor progression. On other hand, salivary exosomal IL6 levels were significantly higher in lymph node-positive OSCC patients (median\u0026thinsp;=\u0026thinsp;4.08) compared to lymph node-negative patients (median\u0026thinsp;=\u0026thinsp;1.83; p\u0026thinsp;=\u0026thinsp;0.013) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), whereas none of the serum-derived exosome markers correlated with lymph node status (Supplementary Table\u0026nbsp;3). Overall, this data highlights the role of these markers in the OSCC progression and underscores the clinical potential of saliva exosomes as a non-invasive, grade and lymph node\u0026ndash;sensitive biomarker platform for oral cancer diagnostics.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of saliva exosome derived transcripts with lymph node metastasis in OSCC\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eBiomarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLN\u0026minus; (Median)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIQR (25%, 75%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLN+ (Median)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIQR (25%, 75%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70, 8.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.34, 8.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.24, 3.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.11, 9.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.013*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84, 18.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.37, 15.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTNF-α\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.54, 57.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.65, 50.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eS100P\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.39, 21.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.19, 21.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.675\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.40, 60.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.18, 13.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOAZ1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.09, 25.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.73, 17.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMMP9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.70, 6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.51\u0026ndash;10.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChimerin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.47, 5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.41, 4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOSCC constitutes the majority of oral cancer cases, with a particularly high prevalence in South Asia, notably in India \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Although histopathological evaluation remains the gold standard for OSCC diagnosis, its invasive nature, high cost, and unsuitability for frequent monitoring limits its broad clinical application. This underscores the vital need for non-invasive, cost-effective diagnostic alternatives. Consequently, serum and salivary biomarkers have emerged as potential candidates for early detection and risk stratification of OSCC \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Previous studies from the Serbian \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, Sri Lankan \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and Indian \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e cohorts have explored salivary mRNAs and proteins, demonstrating promising diagnostic potential. However, these investigations are largely limited by small sample sizes and lack of validation in large, diverse populations. Given the heterogeneity of OSCC and its multifactorial progression, analyzing multiple biomolecules involved in key oncogenic processes such as inflammation, proliferation, invasion, and metastasis could enhance the diagnostic accuracy, especially when combined into molecular panels \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Despite this, the comprehensive evaluation of such multi-marker panels, particularly within exosomes derived from saliva and serum, remains unexplored. To address these gaps, our study aimed to validate the discriminatory potential of nine mRNA transcripts in serum and salivary exosomes for OSCC detection in the Indian population.\u003c/p\u003e \u003cp\u003eExosomes isolated from saliva and serum are generally less complex, more stable and sensitive for disease detection \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, their comprehensive characterization is crucial prior to biomarker analysis. In line with previous OSCC studies, our data revealed elevated total protein and lipid levels in both saliva and serum-derived particles, with notably higher levels observed in saliva \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. However, serum exosomes exhibited a higher protein concentration relative to lipids, while the protein-to-lipid ratio was approximately 1 in saliva and around 2 in serum, supporting the lipid bilayer structure of the vesicles \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Biophysical analysis confirmed the presence of vesicles with sizes below 200 nm, round shaped morphology, and negative zeta potential, which are hallmarks of exosomes \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Further, the presence of membrane protein CD81 supported lipid bilayer integrity, while cytosolic markers HSP70 and TSG101 confirmed vesicle integrity and quality \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Overall, these evaluations aligned with the MISEV guidelines and confirming the suitability of these exosomes for downstream diagnostic applications.\u003c/p\u003e \u003cp\u003eNotably, our gene expression data revealed that salivary exosomal mRNA panels outperform the serum-derived exosomes, with TNF-α combined with OAZ1 demonstrating the highest diagnostic accuracy. Pro-inflammatory cytokines such as IL1, IL6, IL8, and TNF-α were found to be significantly elevated in salivary exosomes of patients with OSCC. These cytokines, primarily secreted by immune and stromal cells within the tumor microenvironment, are known to promote tumor progression by facilitating cancer cell proliferation, survival, migration, invasion, and immune evasion \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Previous studies have similarly reported elevated levels of these cytokines in both serum and saliva \u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e; however, the choice of biofluid remains debatable. Our comparative analysis indicated higher median expression levels of IL6, IL8, and TNF-α in salivary exosomes, with IL1 as an exception. This finding aligns with the report by Thayalan et al. (2016), who demonstrated 2-3-fold higher IL6 levels in saliva compared to serum \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, suggesting that saliva is a more optimal diagnostic biofluid.\u003c/p\u003e \u003cp\u003eAlthough cytokines are well-established biomarkers of OSCC and other cancer types, it is important to acknowledge their limited specificity, as their expression can be influenced by other inflammatory conditions. For instance, Yi-Shing et al. (2013) reported elevated IL6 and IL8 levels in chronic periodontitis patients \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Therefore, our study extended the analysis to additional molecules directly implicated in tumor cell proliferation, including S100P, SAT, and OAZ1. S100P, a calcium-binding protein, activates key signaling pathways such as NF-κB and MAPKs, thereby promoting cancer cell survival and proliferation \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. SAT, an enzyme involved in polyamine catabolism, supports uncontrolled tumor growth \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, whereas OAZ1, a regulator of polyamine synthesis, has been associated with enhanced metastatic potential in OSCC \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Despite their biological relevance, these molecules remain underexplored as exosomal biomarkers. Our investigation provided compelling evidence of elevated SAT, S100P, and OAZ1 expression in both salivary and serum exosomes of OSCC patients, with a higher trend observed in saliva. These findings are in agreement with recent observations by Kalpani et al. (2024), who reported the upregulation of these genes in salivary samples from OSCC, OSF, and OLP patients in a Sri Lankan cohort \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, suggesting their broader applicability across Asian populations.\u003c/p\u003e \u003cp\u003eIn addition to proliferation-related markers, our study examined invasion markers particularly MMP9, and Chemerin, both of which are critical regulators of tumor metastasis \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. MMP9 has been extensively correlated with poor prognosis and increased metastatic potential in OSCC \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, while Chemerin modulates immune responses and extracellular matrix remodeling to facilitate tumor progression \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Our data demonstrated elevated MMP9 expression in both salivary and serum exosomal transcripts from OSCC patients, with higher levels detected in serum, rather than saliva. These observations are consistent with findings from Georgia (2023) and Xiaoyuan et al. (2024), who highlighted the diagnostic relevance of MMP9 and Chemerin in OSCC \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Importantly, our study analysed exosomes derived from paired saliva and serum samples, providing a more comprehensive validation of these biomarkers.\u003c/p\u003e \u003cp\u003eAssessing the diagnostic performance of biomarkers requires evaluation of their sensitivity and specificity. To this end, ROC curve analysis identified salivary exosomal TNF-α, OAZ1 and MMP9 as top-performing markers, with AUC values of 0.88, 0.87, and 0.84, respectively, when selecting the most highly expressed molecule from each category (cytokines, proliferation, and invasion). On other hand, serum exosome biomarkers including IL1, OAZ1, and MMP9 were also showed notable performance, with AUC values of 0.86, 0.80, and 0.83, respectively. Consistent with previous studies suggesting that multi-marker panels enhance diagnostic efficiency \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, combining TNF-α, OAZ1 and MMP9 improved the AUC to 0.89, with a sensitivity and specificity of 85% and 80%, respectively. However, when excluded MMP9, a two-marker panel of TNF-α and OAZ1 achieved superior specificity of 90% with comparable sensitivity of 80%, an AUC of 0.89, and a Youden index of 0.70. This could be attributed from grade-specific expression of MMP9 \u003csup\u003e52\u003c/sup\u003e, which our data showed to be more prominent in advanced OSCC grades (II and III), thus slightly lowering the overall AUC. To this end, Yudan et al 2022 review provide evidence of MMP9 positive correlation with clinical stages of various human cancers \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, serum exosome panels, particularly IL1 and OAZ1, also demonstrated good diagnostic potential, with a sensitivity and specificity of 75% and 90%, respectively (AUC: 0.89, Youden index: 0.65). However, their overall sensitivity was lower than that of salivary exosome panels. Notably, unlike saliva, serum-derived exosomal MMP9 levels did not show significant variation across OSCC grades (II, II, III), limiting its prognostic applicability. Furthermore, other salivary exosomal markers such as IL8, S100P, SAT, and OAZ1 were also exhibited significant expression differences between early and advanced OSCC grades, providing the first evidence of their potential role in disease staging. Additionally, salivary exosomal IL6 expression showed a positive correlation with lymph node metastasis, a finding that was not observed with serum biomarkers. Although direct evidence linking IL6 to lymph node metastasis in OSCC is limited, similar associations have been reported in bladder cancer and other malignancies. For instance, Jun et al. (2017) reported higher IL-6 immunopositivity in deeply invasive cancer cells \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, supporting the relevance of our observations.\u003c/p\u003e \u003cp\u003eTaken together, these findings underscore the diagnostic and prognostic value of salivary exosomal mRNAs in OSCC. Although several serum-derived exosomal biomarkers were elevated in patients with OSCC, their overall sensitivity and grade-specific discriminatory power were comparatively lower. Therefore, our study highlights salivary exosomal TNF-α, OAZ1, and MMP9 as promising biomarkers for OSCC detection.\u003c/p\u003e \u003cp\u003eDespite these promising findings, this study had several limitations. First, the absence of data from benign tumor cases limits the assessment of marker specificity. Second, while the model effectively distinguished OSCC from healthy controls, evaluating the expression of these markers in other cancer types could offer broader insights into their diagnostic utility. Third, increasing the sample size and validating the proposed mRNA panel across diverse cohorts, along with a longitudinal analysis, would help improve the robustness of the model. Lastly, incorporating additional exosomal biomolecules, such as miRNAs, may further strengthen the diagnostic potential and enhance our understanding of OSCC pathophysiology. Future studies are warranted to explore these aspects and advance the development of a more comprehensive and clinically robust diagnostic model.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study highlights that elevated levels of exosomal mRNAs including IL1, IL6, IL8, TNF-α, OAZ1, SAT, S100P, MMP9, and Chemerin in serum and saliva exosomes may serve as biomarkers for OSCC screening. Among these, a salivary exosomal panel comprising TNF-α and OAZ1 has demonstrated strong diagnostic potential with high sensitivity and specificity. Furthermore, salivary markers such as MMP9 and IL6 are relevant for tumor grading and metastasis, suggesting their prognostic value. Therefore, salivary exosomal mRNA profiling could be a valuable, non-invasive, and cost-effective approach for OSCC detection and clinical stratification. Future studies involving large, multicentric cohorts are warranted to validate these findings and enable the development of rapid, clinically applicable diagnostic kits for OSCC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest:\u003c/h2\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by Apollo Hospitals Educational and Research Foundation (AHERF), Hyderabad, India.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSarwareddy Kartik Kumar contributed to conceptualization, methodology, sample collection, molecular profiling, data analysis, interpretation, visualization, and manuscript preparation. Neeharika Kanaparthi supported methodology development, data generation, and curation. Babiola Annes Sesuraj, Rajesh V. Bendre, and Nagalla Balakrishna contributed to data analysis and visualization. Saroj Kumar assisted with data visualization. Arsheed Hussain Hakeem provided clinical supervision, coordinated sample collection, supported data interpretation, and reviewed the manuscript. Manda Venkata Sasidhar supervised the project, contributed to strategic planning, funding acquisition, data interpretation, and final manuscript review and editing. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank our AHERF President, Dr.N.K.Ganguly, Vice president; Ishita Shively, Clinical Director; Dr. Jayanthi Swaminathan for active organizational support\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSilva, L. C. et al. The importance of early treatment of oral squamous cell carcinoma: Case report. \u003cem\u003eOral Oncol.\u003c/em\u003e \u003cb\u003e144\u003c/b\u003e, 106442 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang, J. et al. Survival analysis of age-related oral squamous cell carcinoma: A population study based on SEER. \u003cb\u003e28\u003c/b\u003e, 413 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAli, K. J. E. B. D. Oral cancer-the fight must go on against all odds. \u003cb\u003e23\u003c/b\u003e, 1038 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkashanand et al. Burden of oral cancer and associated risk factors at national and state levels: A systematic analysis from the global burden of disease in India, 1990\u0026ndash;2021. \u003cem\u003eOral Oncol.\u003c/em\u003e \u003cb\u003e159\u003c/b\u003e, 107063 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePekarek, L. et al. Emerging histological and serological biomarkers in oral squamous cell carcinoma: Applications in diagnosis, prognosis evaluation and personalized therapeutics (Review). \u003cem\u003eOncology reports\u003c/em\u003e 50, (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3892/or.2023.8650\u003c/span\u003e\u003cspan address=\"10.3892/or.2023.8650\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhallab, N. A. \u0026amp; Shaker, O. G. Serum and salivary levels of chemerin and MMP-9 in oral squamous cell carcinoma and oral premalignant lesions. \u003cem\u003eClin. Oral Invest.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e, 937\u0026ndash;947. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00784-016-1846-8\u003c/span\u003e\u003cspan address=\"10.1007/s00784-016-1846-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBast\u0026iacute;as, D., Maturana, A., Mar\u0026iacute;n, C., Mart\u0026iacute;nez, R. \u0026amp; Niklander, S. E. J. I. J. o. M. S. Salivary biomarkers for oral cancer detection: an exploratory systematic review. 25, 2634 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManda, S. \u0026amp; Sarvareddy, K. in \u003cem\u003eBeyond the Blueprint - Decoding the Elegance of Gene Expression\u003c/em\u003e (ed Morteza Seifi)IntechOpen, (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, S., Yang, M., Li, R. \u0026amp; Bai, J. J. E. j. o. m. r. Current advances in noninvasive methods for the diagnosis of oral squamous cell carcinoma: a review. \u003cb\u003e28\u003c/b\u003e, 53 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuri, S. et al. Recent advances in minimally invasive biomarkers of OSCC: from generalized to personalized approach. \u003cem\u003eFront. oral health\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e, 1426507. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/froh.2024.1426507\u003c/span\u003e\u003cspan address=\"10.3389/froh.2024.1426507\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBozyk, N. et al. Salivary exosomes as biomarkers for early diagnosis of oral squamous cell carcinoma. \u003cem\u003eOral Oncol. Rep.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 100017 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, X. et al. Prognostic significance of serum Chemerin and neutrophils levels in patients with oral squamous cell carcinoma. \u003cem\u003eHeliyon\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, e32393 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohtasham, N. et al. Serum mir-31-5p is a reliable biomarker in patients with oral squamous cell carcinoma and oral lichen planus. \u003cb\u003e25\u003c/b\u003e, 77 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBao, Z. \u0026amp; Yi, B. J. S. R. Analysis of preoperative serum cytokine levels in patients with oral squamous cell carcinoma. \u003cb\u003e15\u003c/b\u003e, 13537 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu, J. Y. et al. Potential biomarkers in saliva for oral squamous cell carcinoma. \u003cem\u003eOral Oncol.\u003c/em\u003e \u003cb\u003e46\u003c/b\u003e, 226\u0026ndash;231 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSenevirathna, K. et al. Diagnostic potential of salivary IL-1β, IL-8, SAT, S100P, and OAZ1 in oral squamous cell carcinoma, oral submucous fibrosis, and oral lichen planus based on findings from a Sri Lankan cohort. 14, 27226 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJain, A. et al. Identification of potential salivary biomarker panels for oral squamous cell carcinoma. \u003cb\u003e11\u003c/b\u003e, 3365 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDai, J. et al. Exosomes: key players in cancer and potential therapeutic strategy. 5, 145 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaqsood, Q., Sumrin, A., Saleem, Y., Wajid, A. \u0026amp; Mahnoor, M. Exosomes in Cancer: Diagnostic and Therapeutic Applications. \u003cem\u003eClin. Med. Insights Oncol.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 11795549231215966. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/11795549231215966\u003c/span\u003e\u003cspan address=\"10.1177/11795549231215966\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, F. et al. Identification of blood-derived exosomal tumor RNA signatures as noninvasive diagnostic biomarkers for multi-cancer: a multi-phase, multi-center study. \u003cb\u003e24\u003c/b\u003e, 60 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar, S. K. \u0026amp; Sasidhar, M. V. J. M. P. Recent trends in the use of small extracellular vesicles as optimal drug delivery vehicles in oncology. \u003cb\u003e20\u003c/b\u003e, 3829\u0026ndash;3842 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarwareddy, K. K. et al. Harnessing tomato-derived small extracellular vesicles as drug delivery system for cancer therapy. \u003cb\u003e11\u003c/b\u003e, 2461956 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, C. M. et al. Exosome-derived microRNAs in oral squamous cell carcinomas impact disease prognosis. \u003cem\u003eOral Oncol.\u003c/em\u003e \u003cb\u003e120\u003c/b\u003e, 105402 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWelsh, J. A. et al. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches. \u003cem\u003eJ. Extracell. vesicles\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e, e12404. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jev2.12404\u003c/span\u003e\u003cspan address=\"10.1002/jev2.12404\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Nunzio, V. et al. Plasma-Derived Exosomes from NAFLD Patients Modulate the Cannabinoid Receptors\u0026rsquo; Expression in Cultured HepaRG Cells. \u003cb\u003e24\u003c/b\u003e, 1739 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar, S. K. \u0026amp; Mani, K. P. J. C. Proinflammatory signaling mechanism of endocan in macrophages: Involvement of TLR2 mediated MAPK-NFkB pathways. \u003cb\u003e175\u003c/b\u003e, 156482 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBracht, J. W. et al. Analysis of extracellular vesicle mRNA derived from plasma using the nCounter platform. \u003cb\u003e11\u003c/b\u003e, 3712 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar, S. K. \u0026amp; Mani, K. P. Endocan alters nitric oxide production in endothelial cells by targeting AKT/eNOS and NFkB/iNOS signaling. \u003cem\u003eNitric Oxide\u003c/em\u003e. \u003cb\u003e117\u003c/b\u003e, 26\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.niox.2021.09.006\u003c/span\u003e\u003cspan address=\"10.1016/j.niox.2021.09.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuri, S. et al. Recent advances in minimally invasive biomarkers of OSCC: from generalized to personalized approach. \u003cb\u003e5\u003c/b\u003e, 1426507 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh, P., Verma, J. K. \u0026amp; Singh, J. K. J. S. r. Validation of salivary markers, IL-1β, IL-8 and Lgals3bp for detection of oral squamous cell carcinoma in an Indian population. \u003cb\u003e10\u003c/b\u003e, 7365 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan, Y. et al. Oral squamous cell carcinomas: state of the field and emerging directions. \u003cem\u003eInt. J. Oral Sci.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41368-023-00249-w\u003c/span\u003e\u003cspan address=\"10.1038/s41368-023-00249-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhosh, S. et al. Harnessing exosomes as cancer biomarkers in clinical oncology. \u003cb\u003e24\u003c/b\u003e, 278 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamichi, E. et al. Detection of serum/salivary exosomal Alix in patients with oral squamous cell carcinoma. \u003cb\u003e27\u003c/b\u003e, 439\u0026ndash;447 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZlotogorski-Hurvitz, A. et al. FTIR-based spectrum of salivary exosomes coupled with computational-aided discriminating analysis in the diagnosis of oral cancer. \u003cb\u003e145\u003c/b\u003e, 685\u0026ndash;694 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOsteikoetxea, X. et al. Improved characterization of EV preparations based on protein to lipid ratio and lipid properties. \u003cem\u003ePloS one\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e, e0121184. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0121184\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0121184\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabiuch, K. et al. Evaluation of Proinflammatory, NF-kappaB Dependent Cytokines: IL-1α, IL-6, IL-8, and TNF-α in Tissue Specimens and Saliva of Patients with Oral Squamous Cell Carcinoma and Oral Potentially Malignant Disorders. \u003cem\u003eJ. Clin. Med.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm9030867\u003c/span\u003e\u003cspan address=\"10.3390/jcm9030867\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSahibzada, H. A. et al. Salivary IL-8, IL-6 and TNF-α as Potential Diagnostic Biomarkers for Oral Cancer. \u003cem\u003eDiagnostics (Basel Switzerland)\u003c/em\u003e. \u003cb\u003e7\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/diagnostics7020021\u003c/span\u003e\u003cspan address=\"10.3390/diagnostics7020021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSt John, M. A. et al. Interleukin 6 and interleukin 8 as potential biomarkers for oral cavity and oropharyngeal squamous cell carcinoma. \u003cem\u003eArchives otolaryngology\u0026ndash;head neck Surg.\u003c/em\u003e \u003cb\u003e130\u003c/b\u003e, 929\u0026ndash;935. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archotol.130.8.929\u003c/span\u003e\u003cspan address=\"10.1001/archotol.130.8.929\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrishnan, R. et al. Association of serum and salivary tumor necrosis factor-α with histological grading in oral cancer and its role in differentiating premalignant and malignant oral disease. \u003cem\u003eAsian Pac. J. cancer prevention: APJCP\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e, 7141\u0026ndash;7148. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7314/apjcp.2014.15.17.7141\u003c/span\u003e\u003cspan address=\"10.7314/apjcp.2014.15.17.7141\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDineshkumar, T. et al. Salivary and Serum Interleukin-6 Levels in Oral Premalignant Disorders and Squamous Cell Carcinoma: Diagnostic Value and Clinicopathologic Correlations. \u003cem\u003eAsian Pac. J. cancer prevention: APJCP\u003c/em\u003e. \u003cb\u003e17\u003c/b\u003e, 4899\u0026ndash;4906. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.22034/apjcp.2016.17.11.4899\u003c/span\u003e\u003cspan address=\"10.22034/apjcp.2016.17.11.4899\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLisa Cheng, Y. S. et al. Salivary interleukin-6 and‐8 in patients with oral cancer and patients with chronic oral inflammatory diseases. \u003cb\u003e85\u003c/b\u003e, 956\u0026ndash;965 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, Y., Han, Y., He, M., Zhang, Y. \u0026amp; Zou, X. J. O. L. S100 proteins in head and neck squamous cell carcinoma. \u003cb\u003e26\u003c/b\u003e, 362 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGibadulinova, A., Tothova, V., Pastorek, J. \u0026amp; Pastorekova, S. J. A. a. Transcriptional regulation and functional implication of S100P in cancer. \u003cb\u003e41\u003c/b\u003e, 885\u0026ndash;892 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsuji, T. et al. Ornithine decarboxylase antizyme upregulates DNA-dependent protein kinase and enhances the nonhomologous end-joining repair of DNA double-strand breaks in human oral cancer cells. \u003cb\u003e46\u003c/b\u003e, 8920\u0026ndash;8932 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarillari, G. The Impact of Matrix Metalloproteinase-9 on the Sequential Steps of the Metastatic Process. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms21124526\u003c/span\u003e\u003cspan address=\"10.3390/ijms21124526\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun, X., Guo, Y. \u0026amp; J. I. J. o. E. Chemerin Enhances Migration and Invasion of OC Cells via CMKLR1/RhoA/ROCK-Mediated EMT. 7957018 (2024). (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJose, D. \u0026amp; Mane, D. R. Correlation of matrix metalloproteinase-9 expression with morphometric analysis of mucosal vasculature in oral squamous cell carcinoma, oral epithelial dysplasia, and normal oral mucosa. \u003cem\u003eInt. J. health Sci.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 36\u0026ndash;43 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, X. et al. Neutrophils Promote Tumor Progression in Oral Squamous Cell Carcinoma by Regulating EMT and JAK2/STAT3 Signaling Through Chemerin. \u003cem\u003eFront. Oncol.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 812044. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fonc.2022.812044\u003c/span\u003e\u003cspan address=\"10.3389/fonc.2022.812044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenitha, G. et al. Evaluation of Serum Levels of Matrix MetalloProteinase-9 (MMP-9) in Oral Squamous Cell Carcinoma and Its Clinicopathological Correlation. \u003cem\u003eCureus\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, e34954. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7759/cureus.34954\u003c/span\u003e\u003cspan address=\"10.7759/cureus.34954\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLima, A. R. et al. Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine. \u003cem\u003eBr. J. Cancer\u003c/em\u003e. \u003cb\u003e121\u003c/b\u003e, 857\u0026ndash;868. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41416-019-0585-4\u003c/span\u003e\u003cspan address=\"10.1038/s41416-019-0585-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang, S. et al. Combination of four serum exosomal MiRNAs as novel diagnostic biomarkers for early-stage gastric cancer. \u003cb\u003e11\u003c/b\u003e, 237 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatil, R. et al. Expression of matrix metalloproteinase-9 in histological grades of oral squamous cell carcinoma: An immunohistochemical study. \u003cem\u003eJ. oral maxillofacial pathology: JOMFP\u003c/em\u003e. \u003cb\u003e25\u003c/b\u003e, 239\u0026ndash;246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/0973-029x.325121\u003c/span\u003e\u003cspan address=\"10.4103/0973-029x.325121\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng, Y., Gao, M., Lin, D., Du, G. \u0026amp; Cai, Y. Prognostic and Immunological Roles of MMP-9 in Pan-Cancer. \u003cem\u003eBioMed research international\u003c/em\u003e 2592962, (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2022/2592962\u003c/span\u003e\u003cspan address=\"10.1155/2022/2592962\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng, J., Tang, Z. H., Liu, S. \u0026amp; Guo, S. S. Clinicopathological significance of overexpression of interleukin-6 in colorectal cancer. \u003cem\u003eWorld J. Gastroenterol.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e, 1780\u0026ndash;1786. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3748/wjg.v23.i10.1780\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v23.i10.1780\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Exosomes, Saliva, Serum, Oral cancer, Biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-6905382/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6905382/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMinimally-invasive or non-invasive biomarkers from serum and saliva hold significant promise for real-time monitoring of oral squamous cell carcinoma (OSCC). However, the diagnostic potential of exosomes, which carry heterogeneous tumor-derived functional cargo remains largely underexplored. This study aimed to evaluate the diagnostic and prognostic utility of exosomal mRNAs derived from saliva and serum samples of OSCC patients. \u0026nbsp;Exosomes were isolated from paired serum and saliva samples of 40 OSCC patients and 40 healthy controls using commercial kits. Characterization was performed using NTA, TEM, zeta potential, protein/lipid quantification, and western blotting. Expression of nine mRNA markers including cytokines (IL1, IL6, IL8, TNF-α), proliferation markers (OAZ1, SAT, S100P), and metastasis-related molecules (MMP9, Chemerin) was analyzed by qRT-PCR. Diagnostic accuracy was evaluated using ROC curve analysis, and correlations with tumor grade and lymph node metastasis were systematically investigated. Results demonstrated that salivary exosomal MMP9, TNF-α, and OAZ1 exhibited markedly higher diagnostic sensitivity and specificity compared to the top-performing serum exosomal derived markers (MMP9, IL1, and OAZ1). Notably, a two-gene salivary mRNA panel combining TNF-α and OAZ1 demonstrated strong discriminatory power (AUC: 0.89, sensitivity: 80%, specificity: 90%; Youden Index: 0.70). Additionally, salivary exosomal MMP9, IL8, S100P, SAT, and OAZ1 significantly differentiated between grade I and grade III OSCC. Moreover, IL6 expression positively correlated with lymph node metastasis. In contrast, serum exosomal markers lacked clear discriminatory potential. Therefore, salivary exosomal panel of TNF-α and OAZ1 represent promising non-invasive biomarkers for OSCC diagnosis, while MMP9 and IL6 is informative for tumor grading.\u003c/p\u003e","manuscriptTitle":"Evaluation of salivary and serum exosomal mRNAs as biomarkers for the diagnosis and prognosis of oral squamous cell carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-29 14:34:36","doi":"10.21203/rs.3.rs-6905382/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-22T14:42:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-17T12:48:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-15T11:46:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7276365890195741111789904980152091703","date":"2025-07-09T13:55:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77416185008613717575010742453818858990","date":"2025-07-08T15:03:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315110633915066723529531052041911264010","date":"2025-06-25T09:35:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-23T13:08:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T12:36:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-19T05:55:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-06-19T05:51:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cb517eeb-a45a-4d5e-bc26-0022facc92ef","owner":[],"postedDate":"June 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":50497537,"name":"Biological sciences/Biochemistry"},{"id":50497538,"name":"Biological sciences/Cancer"},{"id":50497539,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-11-10T16:02:08+00:00","versionOfRecord":{"articleIdentity":"rs-6905382","link":"https://doi.org/10.1038/s41598-025-22246-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-03 15:57:43","publishedOnDateReadable":"November 3rd, 2025"},"versionCreatedAt":"2025-06-29 14:34:36","video":"","vorDoi":"10.1038/s41598-025-22246-1","vorDoiUrl":"https://doi.org/10.1038/s41598-025-22246-1","workflowStages":[]},"version":"v1","identity":"rs-6905382","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6905382","identity":"rs-6905382","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}