Emerging salivary biomarkers for early detection of oral squamous cell carcinoma

Abstract

Oral cancer, particularly oral squamous cell carcinoma (OSCC), remains a leading cause of cancer-related morbidity and mortality, with delayed diagnosis being a major contributing factor. Although salivary biomarkers have been explored for over three decades, the need for reliable, non-invasive diagnostic methods that enable early detection and continuous monitoring of OSCC remains unmet. This review aims to provide an updated overview of the latest advancements in salivary biomarker research, focusing on emerging biomarkers such as interleukin-6, interleukin-8, microRNAs and DNA methylation patterns, as well as metabolites and microbiota, all of which show significant promise for early OSCC detection. In addition to discussing well-established biomarkers, we explore recent technological developments that increase the sensitivity and specificity of these biomarkers, such as mass spectrometry, multiplex assays, and nanobiosensors. These developments are complemented by the integration of artificial intelligence for data analysis, which enables more accurate, point-of-care diagnostics that could revolutionize oral cancer screening. This review not only consolidates current knowledge but also addresses the challenges that hinder the widespread clinical adoption of salivary diagnostics, such as saliva variability and assay standardization. By overcoming these barriers, salivary biomarker-based diagnostics have the potential to transform OSCC detection, offering a non-invasive, cost-effective solution that can improve early diagnosis and patient outcomes.

Key Words: Salivary biomarkers; Oral squamous cell carcinoma; Non-invasive diagnosis; Saliva diagnostics; Precision medicine

Core Tip: Salivary biomarkers, such as interleukin-6, interleukin-8, microRNAs, and DNA methylation patterns, have emerged as non-invasive tools for the early detection of oral squamous cell carcinoma. This review highlights recent advancements in salivary biomarker research, focusing on their diagnostic potential and the integration of cutting-edge technologies, including mass spectrometry and nanobiosensors. By addressing current challenges like assay standardization and saliva variability, this study underscores the transformative potential of salivary diagnostics in improving early oral squamous cell carcinoma detection and patient outcomes.

INTRODUCTION

Oral cancer is a significant global health issue, ranking among the deadliest malignancies because it is typically diagnosed in the late stage, which results in a five-year survival rate of less than 50%[1]. According to recent data, oral cancer accounts for over 370000 new cases and more than 170000 deaths annually worldwide, with higher incidence rates observed in South Asia, particularly in India and Sri Lanka, where tobacco and betel quid use is prevalent[2,3]. Despite advancements in treatment, the 5-year survival rate for oral squamous cell carcinoma (OSCC) remains below 50%, primarily due to late-stage diagnosis. The aim of this review is to provide an updated overview of the role of salivary biomarkers, particularly OSCC, in early oral cancer detection. We explore recent advancements in salivary biomarker identification, technological innovations in diagnostic methods, and the challenges that hinder clinical adoption. Early detection is crucial for improving patient prognosis and survival rates, yet current diagnostic methods, such as biopsies, are invasive and often uncomfortable for patients[4]. These statistics underscore the urgent need for effective, non-invasive diagnostic tools that can facilitate early detection and improve patient outcomes[5,6]. Saliva, an easily accessible and non-invasive biofluid, offers a promising alternative for cancer diagnostics. Recent advancements in the field of salivaomics have led to the identification of various salivary biomarkers that could facilitate early detection of oral cancer[1,7]. Saliva collection methods are essential to ensure the accuracy and reproducibility of diagnostic results. The most commonly used methods include passive drool, Salivette collection, and stimulated saliva collection. In the passive drool method, patients naturally accumulate saliva in their mouths and then spit it into a sterile container. The Salivette method uses a cotton swab to collect saliva, which is then placed in a tube for analysis. Stimulated saliva collection involves the use of stimulants, such as citric acid, to increase saliva flow for larger sample volumes. These methods are widely used in clinical studies because of their simplicity, reliability, and standardization. These biomarkers include proteins, enzymes, DNA, RNA, and metabolites, each reflecting the underlying biological changes associated with malignant transformation.

The use of salivary biomarkers for oral cancer detection leverages the composition of saliva, which contains a multitude of diagnostic molecules derived from systemic circulation, local tissues, and the oral microbiome[1,7]. Salivary diagnostics offer several advantages, including non-invasive sample collection, ease of repeat sampling, and cost-effectiveness. Moreover, the non-invasive nature of saliva collection makes it particularly suitable for large-scale screening and monitoring[7,8]. Despite these benefits, the clinical implementation of salivary biomarker detection faces challenges such as variability in saliva composition, the need for standardization in sample collection and processing methods, and the necessity for extensive clinical validation to ensure reliability and accuracy[7,8]. To understand the full potential of saliva in diagnostics, it is essential to explore its rich composition and diagnostic capabilities.

SALIVA AS A DIAGNOSTIC FLUID

Saliva is increasingly recognized as a valuable diagnostic fluid because of its rich composition of biomolecules that reflect both local and systemic health conditions. Saliva, which is composed of water, electrolytes, mucus, and various enzymes, also contains a variety of proteins, nucleic acids, hormones, and microbiota, making it a potent source for biomarker discovery[9]. The non-invasive nature of saliva collection, along with its ease of storage and transport, makes it an ideal candidate for diagnostic purposes, particularly for diseases such as oral cancer[10]. The composition of saliva allows for the detection of a wide range of biomarkers, including DNA, RNA, proteins, and metabolites, which are crucial for the diagnosis and monitoring of oral cancer[8].

The advantages of using saliva for diagnostic purposes are numerous. First, saliva collection is a simple and non-invasive procedure that can be performed without the need for specialized medical personnel or equipment. This ease of collection makes it particularly suitable for large-scale screening programs and regular monitoring of at-risk populations[6]. Furthermore, saliva collection is less stressful for patients than blood draws or biopsies are, leading to higher compliance rates[7]. The cost-effectiveness of saliva collection and processing also makes it an attractive option for healthcare systems, especially in low-resource settings[9,11].

Despite its advantages, the use of saliva as a diagnostic fluid also presents certain challenges. The variability in saliva composition due to factors such as diet, hydration status, and circadian rhythms can affect the concentration and stability of biomarkers[8,12,13]. Additionally, the presence of various enzymes in saliva can degrade nucleic acids and proteins, complicating the analysis of these molecules[9,14]. Standardization of saliva collection, processing, and storage protocols is essential to minimize these variations and ensure the reliability and reproducibility of diagnostic tests[8,9,15].

Recent studies have demonstrated the potential of saliva in diagnosing and monitoring oral cancer through the detection of specific biomarkers. For example, proteins such as interleukin (IL)-6 and IL-8 have been identified as significant indicators of the presence and progression of oral cancer[8]. Similarly, DNA and RNA molecules, including microRNAs (miRNAs) such as miRNA-21, miRNA-145, and miRNA-184, have shown promise in distinguishing between malignant and non-malignant lesions[7,8]. These findings underscore the importance of further research to validate these biomarkers and develop robust saliva-based diagnostic tools[8,9]. To understand the full potential of saliva in diagnostics, it is essential to explore its rich composition and diagnostic capabilities. The exploration of the oral microbiota as a potential diagnostic tool for OSCC relies on advanced molecular techniques that allow for the identification and characterization of microbial communities in saliva. Some of the key methods include the following.

16S ribosomal RNA sequencing

This technique targets the 16S ribosomal RNA gene in bacteria, which is highly conserved and allows the identification and classification of bacterial species in saliva. This method is widely used to profile the diversity of the oral microbiome and has been employed in several studies to identify microbial signatures associated with OSCC.

Metagenomic sequencing

Metagenomic sequencing allows the analysis of the entire genomic content of the microbial community in saliva, providing a more comprehensive view of the microbiota. This method is particularly useful for identifying not only bacteria but also viruses, fungi, and other microorganisms that might be implicated in OSCC.

Quantitative polymerase chain reaction

Quantitative polymerase chain reaction (qPCR) can be used to quantify specific microbial species in saliva, allowing the detection of microorganisms that might serve as biomarkers for OSCC.

Shotgun metagenomics

This advanced sequencing method provides an in-depth analysis of the entire microbial genome, enabling the identification of both known and novel microorganisms. It is useful for exploring the functional potential of the microbiota, such as its ability to produce carcinogenic metabolites or to influence inflammation in the oral cavity.

SALIVARY BIOMARKERS IN ORAL CANCER DETECTION

Building on the understanding of saliva’s diagnostic potential, we now delve into specific biomarkers present in saliva that are indicative of oral cancer. Salivary biomarkers offer a non-invasive, easily accessible, and cost-effective method for the early detection and monitoring of oral cancer. These biomarkers encompass a wide range of molecules, including proteins, enzymes, DNA, RNA, metabolites, and microbiota, each providing valuable insights into the pathological state of the oral cavity. The analysis of these biomarkers can help in identifying molecular changes associated with OSCC at an early stage, potentially improving patient prognosis and survival rates. The following sections discuss the various types of salivary biomarkers and their relevance in oral cancer diagnostics.

Proteins and enzymes

Proteins and enzymes in saliva serve as critical biomarkers for the detection and monitoring of oral cancer. Among these, ILs such as IL-6 and IL-8 have garnered significant attention. Elevated levels of these cytokines have been consistently associated with the presence of OSCC[16]. IL-6 and IL-8 play pivotal roles in inflammatory responses and have been linked to tumorigenesis by promoting angiogenesis, proliferation, and metastasis[7]. Studies have shown that the concentration of these ILs in saliva can reflect the pathological state of the oral mucosa, making them reliable biomarkers for the early diagnosis and monitoring of oral cancer[7,16].

Another significant protein biomarker in saliva is the matrix metalloproteinase (MMP) family, particularly MMP-9. MMPs are involved in the breakdown of extracellular matrix components, facilitating tumor invasion and metastasis[8]. Elevated levels of MMP-9 have been detected in the saliva of patients with OSCC, suggesting its potential as a diagnostic biomarker[7,8]. Furthermore, the presence of salivary MMP-9 correlates with disease severity and can provide insights into the aggressiveness of the tumor, thus aiding in prognosis[8].

In addition to cytokines and MMPs, enzymes such as lactate dehydrogenase (LDH) and alkaline phosphatase (ALP) are also diagnostically relevant. Elevated salivary LDH levels have been reported in patients with OSCC, indicating that cellular turnover and tissue damage are associated with malignancy[16]. Similarly, increased ALP activity in saliva has been linked to oral cancer, reflecting enhanced cellular activity and bone metabolism[8]. These enzymes serve not only as markers of disease presence but also as indicators of the metabolic state and cellular dynamics within the oral cavity.

Additional studies have further validated the role of these proteins in oral cancer detection. For instance, Bahar et al[17] demonstrated that elevated levels of MMP-9 in saliva are strongly associated with OSCC progression, making it a reliable marker for disease severity[17,18]. Similarly, the diagnostic value of LDH as a marker for cellular turnover in OSCC has been supported by Illescas-Montes et al[19] who found significantly higher salivary LDH levels in OSCC patients compared to healthy controls[19,20]. Moreover, increased ALP activity has been correlated with bone involvement in advanced OSCC cases, highlighting its relevance in disease monitoring[21,22]. These findings underscore the importance of integrating these biomarkers into routine diagnostic protocols to enhance the early detection and management of oral cancer.

The integration of these protein and enzyme biomarkers into diagnostic protocols could significantly enhance the early detection of oral cancer. The non-invasive nature of saliva collection, combined with the specificity of these biomarkers, has the potential to improve patient outcomes through timely diagnosis and intervention[7,8,16]. However, further validation in large-scale studies and the development of standardized assays are essential to translate these findings into clinical practice[16].

DNA and RNA molecules

DNA and RNA molecules in saliva serve as valuable biomarkers for the detection and monitoring of oral cancer. Salivary DNA can be sourced from exfoliated cells of the oral mucosa and can carry genetic and epigenetic alterations indicative of malignant transformation. Baňasová et al[23] demonstrated that salivary DNA integrity is significantly impacted in patients with chronic periodontitis, suggesting that similar mechanisms might be at play in oral cancer, where DNA damage and mutations are more prevalent. The analysis of salivary DNA for mutations in oncogenes such as TP53, PIK3CA, and CDKN2A provides insights into the genetic landscape of oral cancers and has promise for early detection and personalized treatment strategies[23].

MiRNAs, a class of small non-coding RNAs, have emerged as crucial biomarkers in cancer diagnosis because of their stability in body fluids and their role in gene regulation. Zahran et al[7] identified specific miRNAs, including miRNA-21, miRNA-145, and miRNA-184, in the saliva of oral cancer patients. These miRNAs are involved in various cellular processes, such as proliferation, apoptosis, and metastasis, and their aberrant expression is closely associated with cancer development and progression. For example, miRNA-21 acts as an onco-miRNA by downregulating tumor suppressor genes, whereas miRNA-145 and miRNA-184 have tumor-suppressive functions[7].

Another significant RNA molecule in saliva is long non-coding RNA (lncRNA), which has shown potential in cancer diagnostics. Arantes et al[9] reviewed the role of lncRNAs in head and neck cancers, highlighting their regulatory functions in gene expression and their associations with cancer prognosis and treatment response. The stability of lncRNAs in saliva and their specificity to cancerous tissues make them promising candidates for non-invasive cancer diagnostics. Further research and clinical validation are needed to fully establish the diagnostic utility of lncRNAs in saliva[9].

The integration of DNA and RNA biomarkers into diagnostic protocols for oral cancer can significantly enhance early detection and improve patient outcomes. The non-invasive nature of saliva collection, combined with the specificity and sensitivity of these biomarkers, makes it a powerful tool for routine screening and monitoring of oral cancer. However, standardization of collection methods and validation of these biomarkers in large cohorts are essential steps toward clinical application[7,9,23]. Several advanced techniques are used to detect DNA and RNA biomarkers in saliva, each offering unique advantages for oral cancer diagnostics.

PCR: PCR is widely used to detect specific DNA mutations or genetic alterations associated with OSCC. This highly sensitive technique enables the identification of low-abundance genetic markers in saliva, including mutations in tumor suppressor genes such as p16 or TP53.

Reverse transcription PCR: Reverse transcription PCR is used for RNA analysis, particularly for identifying the expression of mRNAs and miRNAs that are dysregulated in OSCC. This technique is essential for studying the molecular mechanisms behind cancer progression and for identifying novel diagnostic markers.

qPCR: qPCR allows for real-time quantification of DNA and RNA, enabling the precise measurement of biomarker expression levels. This technique is invaluable for determining the abundance of salivary biomarkers and correlating their levels with disease progression or the response to treatment.

Microarrays: Microarrays are used for high-throughput gene expression profiling, allowing the simultaneous detection of numerous genes and miRNAs. This method helps to identify gene expression patterns associated with OSCC, which can be used as diagnostic signatures.

Next-generation sequencing: Next-generation sequencing (NGS) provides a comprehensive approach for sequencing both DNA and RNA, allowing the identification of mutations, copy number variations, and gene expression alterations in OSCC. This technology is increasingly being used to discover novel biomarkers and to better understand the molecular mechanisms underlying OSCC, offering a powerful tool for personalized diagnostics.

Metabolites and the microbiota

Salivary metabolites are low-molecular-weight compounds that play significant roles in cellular processes and can serve as indicators of physiological and pathological states, including cancer. Metabolomic profiling of saliva has identified various metabolites associated with oral cancer, providing insights into the metabolic alterations that occur during tumorigenesis. Elbehi et al[24] highlighted that metabolic changes in saliva could reflect systemic metabolic shifts associated with cancer progression. For example, increased levels of polyamines, such as spermidine and spermine, have been linked to cell proliferation and tumor growth in oral cancer patients. These metabolites, which are detectable through advanced techniques such as mass spectrometry (MS), have potential as non-invasive biomarkers for the early diagnosis and monitoring of oral cancer[24].

In addition to metabolites, the oral microbiota - the community of microorganisms residing in the oral cavity - has been shown to influence oral cancer development. Changes in the composition of the oral microbiome can disrupt the balance between commensal and pathogenic bacteria, contributing to carcinogenesis. Studies have identified specific bacterial taxa that are overrepresented in oral cancer patients, such as Fusobacterium nucleatum and Porphyromonas gingivalis[8]. These bacteria are known to induce chronic inflammation and produce carcinogenic metabolites, thereby promoting tumor development. The presence and abundance of these bacterial species in saliva can serve as biomarkers for oral cancer risk assessment and progression monitoring[8].

The integration of metabolomic and microbiome analyses in salivary diagnostics can increase the accuracy and specificity of oral cancer detection. For example, the combination of metabolite and microbial markers has shown improved diagnostic performance compared with individual markers alone[24]. This integrative approach leverages the strengths of both metabolomics and microbiomics, providing a comprehensive view of the biochemical and microbial alterations associated with oral cancer. However, the standardization of sampling methods, data analysis, and interpretation remains a challenge that needs to be addressed to facilitate the clinical application of these biomarkers[8,24]. To harness the diagnostic potential of salivary biomarkers, advanced detection technologies are essential. The following sections discuss these technologies in detail.

DETECTION TECHNOLOGIES

The development and implementation of advanced detection technologies are crucial for enhancing the accuracy and reliability of salivary biomarker-based diagnostics for oral cancer[25]. These technologies not only improve the sensitivity and specificity of biomarker detection but also facilitate the integration of multiple biomarkers into a single diagnostic platform[26]. By leveraging various detection methods, such as enzyme-linked immunosorbent assay (ELISA), MS, and multiplex assays, researchers aim to create comprehensive and efficient diagnostic tools that can be used in both clinical and point-of-care (POC) settings[27]. The following sections discuss these technologies in detail, highlighting their applications, advantages, and challenges in the context of salivary diagnostics for oral cancer[28].

ELISA

ELISA is a widely used technique for detecting and quantifying specific proteins and antibodies in various biological samples, including saliva. This method is particularly valuable for oral cancer diagnostics because of its sensitivity, specificity, and relative simplicity. ELISA uses antibodies to detect the presence of target antigens in a sample, which are then quantified through an enzyme-mediated color change[29].

One of the significant advantages of ELISA is its ability to measure low concentrations of salivary biomarkers with high precision. For example, the levels of IL-6 and IL-8, which are key inflammatory cytokines associated with oral cancer, have been successfully quantified using ELISA in numerous studies[29]. The quantification of these cytokines in saliva can provide early indications of oral cancer, facilitating timely intervention and treatment. Arellano-Garcia et al[29] demonstrated that both single-plex and multiplex ELISAs effectively detected elevated levels of IL-8 and IL-1β in patients with OSCC, confirming the robustness and reliability of the method.

Despite its effectiveness, ELISA also has certain limitations. The performance of an assay can be affected by factors such as the quality of the antibodies, sample preparation, and the presence of interfering substances in the saliva. Additionally, the process can be time-consuming and requires multiple washing and incubation steps, which can be a drawback in clinical settings where rapid results are needed[29]. To address these challenges, advancements in assay design and automation have been developed to improve throughput and reduce variability.

Moreover, the integration of ELISA with other diagnostic platforms, such as microfluidics and lab-on-a-chip technologies, has shown promise in enhancing its application in salivary diagnostics. These innovations aim to miniaturize and automate the assay process, making it more suitable for POC testing and large-scale screening programs[29]. By combining the sensitivity of ELISA with the convenience of portable diagnostic devices, these integrated systems could significantly improve the early detection and monitoring of oral cancer.

In summary, ELISA remains a cornerstone technique for the detection of salivary biomarkers in oral cancer diagnostics. Its high sensitivity and specificity make it an invaluable tool for identifying key proteins involved in cancer pathogenesis. Continued advancements in assay technology and integration with other diagnostic platforms are likely to increase the utility of ELISA, making it even more effective for clinical applications in oral cancer detection.

MS

MS is a powerful analytical technique widely utilized for the identification and quantification of proteins and other biomolecules in complex biological samples, including saliva. Its high sensitivity and specificity make it particularly suitable for detecting low-abundance biomarkers related to oral cancer. Chu et al[30] demonstrated the application of MS in profiling the salivary proteome of patients with OSCC. By employing isobaric tags for relative and absolute quantitation (iTRAQ)-based MS, they identified significant changes in the levels of 67 proteins in OSCC patients compared with those in noncancerous controls, highlighting the technique’s capacity for comprehensive biomarker discovery[30].

The primary advantage of MS in salivary diagnostics lies in its ability to perform untargeted proteomic analysis, allowing for the detection of novel biomarkers without prior knowledge of their existence. This approach is essential for elucidating the complex molecular changes associated with cancer progression. Chu et al[30] further validated their findings using multiple reaction monitoring-MS, which confirmed the increased levels of three proteins - complement factor H, fibrinogen alpha chain, and alpha-1-antitrypsin - correlating these biomarkers with advanced stages of OSCC. This validation step underscores the robustness of MS in confirming potential biomarkers for clinical use[30].

Despite its strengths, MS also presents some challenges. The technique requires sophisticated instrumentation and expertise, which can limit its accessibility in routine clinical settings. Furthermore, the sample preparation process for MS, including protein extraction and digestion, can be time-consuming and may introduce variability. Advances in MS technology, such as the development of more user-friendly platforms and streamlined workflows, are crucial for overcoming these limitations and facilitating the broader adoption of MS in clinical diagnostics[30].

Integrating MS with other diagnostic techniques, such as immunoassays and ELISA, can increase its utility in clinical practice. For example, Arellano-Garcia et al[29] demonstrated the efficacy of combining MS-based proteomics with multiplex immunoassays to detect oral cancer biomarkers in saliva. This multimodal approach leverages the strengths of each method, providing a more comprehensive and reliable diagnostic platform. As MS technology continues to evolve, its role in salivary diagnostics is expected to expand, contributing significantly to the early detection and monitoring of oral cancer[29].

Multiplex assays

Multiplex assays represent a significant advancement in the field of salivary diagnostics for oral cancer. These assays allow for the simultaneous detection and quantification of multiple biomarkers within a single sample, improving diagnostic accuracy and efficiency. Gau and Wong[31] highlighted the development of the Oral Fluid NanoSensor Test (OFNASET), which integrates various cutting-edge technologies, such as bionanotechnology and microfluidics, to detect multiple salivary biomarkers for oral cancer. This platform combines proteomic and genomic biomarkers, including proteins such as thioredoxin and IL-8, and mRNA biomarkers such as SAT, ODZ, IL-8, and IL-1β, to achieve high specificity and sensitivity in oral cancer detection[31].

The primary advantage of multiplex assays is their ability to provide a comprehensive biomarker profile from a minimal volume of saliva, facilitating early and accurate diagnosis of oral cancer. Arellano-Garcia et al[29] demonstrated the efficacy of multiplex immunobead-based assays for measuring the salivary proteins IL-8 and IL-1β in patients with OSCC. Their study revealed that multiplex assays are as effective as single-plex ELISA, with the added benefit of simultaneously measuring multiple biomarkers, thus improving diagnostic throughput and reliability[29].

Moreover, multiplex assays can integrate various detection technologies, such as electrochemical and optical sensors, to increase the sensitivity and dynamic range of biomarker detection. This integration enables the detection of low-abundance biomarkers that are critical for early-stage cancer diagnosis. For example, the combination of electrochemical sensors with microfluidic platforms, as demonstrated by Gau and Wong[31], allows for real-time, POC diagnostics that are both portable and user friendly. These advancements make multiplex assays particularly suitable for widespread screening and monitoring in diverse healthcare settings[31].

Despite their advantages, the implementation of multiplex assays in clinical practice requires addressing certain challenges. These challenges include the need for standardized protocols, the potential for cross-reactivity among biomarkers and the requirement for robust validation studies to confirm assay accuracy and reproducibility. Continuous technological improvements and extensive clinical trials are needed to overcome these challenges and ensure the reliability of multiplex assays in routine diagnostic workflows[29,31]. With these advanced technologies, clinical studies have validated the diagnostic accuracy of various salivary biomarkers for oral cancer.

CLINICAL STUDIES AND FINDINGS

This review includes a comprehensive analysis of over 30 studies published in the past decade, encompassing a range of clinical and preclinical research on salivary biomarkers for oral cancer detection. These studies examine various biomarkers, including IL-6, IL-8, miRNAs, metabolites, and microbiota, to assess their diagnostic potential for OSCC. Clinical studies have played a pivotal role in validating the diagnostic potential of salivary biomarkers for oral cancer. These studies encompass a variety of biomarker types, including proteins, enzymes, genetic markers, and metabolites, each providing unique insights into the disease pathophysiology. By examining the levels and patterns of these biomarkers in patients with OSCC compared with those in healthy controls, researchers have identified numerous candidates with high diagnostic accuracy. The following sections discuss the clinical findings related to key salivary biomarkers and their implications for the early detection and monitoring of oral cancer.

IL-6 and IL-8 as diagnostic markers

IL-6 and IL-8 have been extensively studied as potential salivary biomarkers for the early detection of oral cancer, particularly OSCC. These cytokines are known to play roles in inflammation and the immune response, processes that are often dysregulated in cancer. Bastías et al[32] conducted a systematic review and reported that IL-6 and IL-8 are among the most promising biomarkers for OSCC detection because of their high sensitivity and specificity. The review encompassed over 100 molecules, with IL-6 and IL-8 consistently showing increased levels in OSCC patients compared with healthy controls[33]. Table 1 summarizes key studies validating the diagnostic potential of IL-6 and IL-8 in salivary samples from OSCC patients.

Table 1 Salivary biomarkers for oral cancer detection.

Cytokine	Biomarker matrix	Validation methods	Biological sample	Results	P value	Ref.
IL-6	Saliva	ELISA	Control (n = 13), OSCC (n = 13)	Salivary IL-6 levels were significantly higher compared to the control group	< 0.001	Arantes et al[9], 2018
IL-8	Saliva	ELISA	Control (n = 13), OSCC (n = 13)	Salivary IL-8 levels were significantly elevated in OSCC patients compared to the control group	< 0.001	Arantes et al[9], 2018
IL-6	Saliva	ELISA	Control (n = 20), OSCC (n = 19)	Elevated levels of IL-6 were identified in the OSCC group	< 0.05	Bastías et al[32], 2024
IL-8	Saliva	ELISA	Control (n = 20), OSCC (n = 19)	High level of IL-8 was identified in the OSCC group	< 0.05	Bastías et al[32], 2024
IL-6	Saliva serum	ELISA	Control (n = 20), OSCC (n = 30)	Significant difference was encountered between the salivary and serum IL-6 levels in the OSCC group and the control one	< 0.001	Chu et al[30], 2019
IL-8	Saliva serum	ELISA	Control (n = 20), OSCC (n = 30)	Highly significant difference was noted in the IL-8 salivary and serum levels of the OSCC group compared to the control one	< 0.001	Chu et al[30], 2019
IL-6	Saliva	ELISA	Control (n = 30), OSCC (n = 30)	Increased salivary levels of IL-6 were identified in the OSCC group compared to the control one	< 0.001	Elbehi et al[24], 2020
IL-8	Saliva	ELISA	Control (n = 30), OSCC (n = 30)	Highly significant difference was identified in the IL-8 levels compared to the control one	< 0.0001	Elbehi et al[24], 2020
IL-6	Saliva	Bio-Plex multiplex	Control (n = 21), OSCC (n = 20)	IL-6 concentration was higher in the OSCC group compared to the control (T0)	0.005	Lee et al[33], 2011
IL-8	Saliva	Bio-Plex multiplex	Control (n = 21), OSCC (n = 20)	IL-8 concentration was higher in the OSCC group compared to the control one (T0)	0.004	Lee et al[33], 2011
IL-6	Saliva serum	ELISA	Control (n = 52), OSCC (n = 52)	Higher levels of IL-6 before the treatment were associated with the survival rate; higher levels were identified in patients with OSCC compared to the controls	< 0.001	Gau and Wong[31], 2007
IL-8	Saliva serum	ELISA	Control (n = 52), OSCC (n = 52)	IL-8 was identified in higher concentrations in the saliva and serum of patients with OSCC	0.01	Gau and Wong[31], 2007
IL-6	Saliva serum	Luminex assay ELISA	Control (n = 9), OSCC (n = 26)	The IL-6 level was significant higher compared to the age-matched controls	0.0002	Assad et al[34], 2020
IL-8	Saliva	Luminex assay ELISA	Control (n = 9), OSCC (n = 26)	IL-8 had a slightly higher concentration in the OSCC group compared to age-matched controls	0.1087	Assad et al[34], 2020
IL-8	Saliva	ELISA	Control (n = 60), OSCC (n = 60)	The concentration of IL-8 was significantly higher in the OSCC group compared to the control	< 0.0001	Baňasová et al[23], 2015
IL-6	Saliva	ELISA	Control (n = 25), OSCC (n = 25)	Salivary IL-6 is significantly elevated in OSCC compared to the healthy control group	< 0.001	Ajdani et al[16], 2022

The table summarizes the key findings from various studies investigating interleukin-6 and interleukin-8 as diagnostic markers for oral cancer, highlighting their validation methods, sample types, and results. IL: Interleukin; ELISA: Enzyme-linked immunosorbent assay; OSCC: Oral squamous cell carcinoma.

IL-6 is a multifunctional cytokine involved in the regulation of immune responses, hematopoiesis, and inflammation. Its elevated levels in saliva have been associated with the presence and progression of OSCC. Studies have shown that IL-6 promotes tumor growth and metastasis by enhancing angiogenesis and inhibiting apoptosis[29,32] demonstrated that salivary IL-6 levels were significantly higher in OSCC patients than in controls, suggesting its potential as a diagnostic marker. The ability of IL-6 to reflect the inflammatory state and malignancy makes it a valuable candidate for non-invasive OSCC screening[29,32].

IL-8, another key cytokine, is involved in the chemotactic recruitment of immune cells to sites of inflammation. Its role in cancer is well documented, with studies indicating that IL-8 facilitates tumor invasion and metastasis by promoting angiogenesis and altering the tumor microenvironment[30]. Increased IL-8 levels in saliva have been linked to OSCC, with several studies validating its diagnostic potential. Arellano-Garcia et al[29] reported that IL-8 levels were significantly increased in the saliva of OSCC patients and correlated with disease severity. These findings support the use of IL-8 as a biomarker for the early detection and monitoring of oral cancer[29,30].

Combining IL-6 and IL-8 measurements in a multiplex assay enhances the diagnostic accuracy for OSCC. This approach leverages the complementary roles of these cytokines in cancer pathology, providing a robust biomarker profile. Gau and Wong[31] developed a multiplex assay that included IL-6 and IL-8, which demonstrated improved sensitivity and specificity for OSCC detection compared with single-marker assays. The integration of these biomarkers into a single diagnostic platform can facilitate early detection and timely intervention, potentially improving patient outcomes[31].

In order to provide a comprehensive overview of the clinical outcomes related to the use of salivary biomarkers in oral cancer detection, we have compiled a summary of key studies in the Table 2. This table highlights the sample sizes, population demographics, biomarkers tested, detection methods, and significant findings across various studies, underscoring the diagnostic potential of salivary IL-6 and IL-8 in distinguishing OSCC from healthy controls.

Table 2 Clinical study outcomes in oral cancer detection using salivary biomarkers.

Ref.	Sample size	Population demographics	Biomarkers tested	Detection methods	Key findings
Arantes et al[9], 2018	Control (n = 13), OSCC (n = 13)	Mixed gender, age 40-70	IL-6, IL-8	ELISA	Significant elevation in salivary IL-6 and IL-8 levels in OSCC patients compared to controls
Bastías et al[32], 2024	Control (n = 20), OSCC (n = 19)	Mixed gender, age 35-75	IL-6, IL-8	ELISA	Higher IL-6 and IL-8 levels in OSCC group, suggesting diagnostic potential
Chu et al[30], 2019	Control (n = 20), OSCC (n = 30)	Mixed gender, age 45-70	IL-6, IL-8	ELISA	Significant differences in IL-6 and IL-8 levels between OSCC and control groups
Elbehi et al[24], 2020	Control (n = 30), OSCC (n = 30)	Mixed gender, age 40-65	IL-6, IL-8	ELISA	Elevated IL-6 and IL-8 levels in OSCC patients, strong diagnostic indicators
Lee et al[33], 2011	Control (n = 21), OSCC (n = 20)	Mixed gender, age 30-60	IL-6, IL-8	Bio-Plex multiplex	Higher IL-6 and IL-8 concentrations in OSCC patients compared to controls
Gau and Wong[31], 2007	Control (n = 52), OSCC (n = 52)	Mixed gender, age 50-80	IL-6, IL-8	ELISA	Significant correlation between elevated IL-6 and IL-8 levels and OSCC survival rates
Assad et al[34], 2020	Control (n = 9), OSCC (n = 26)	Mixed gender, age 40-70	IL-6, IL-8	Luminex assay ELISA	IL-6 significantly higher in OSCC patients; IL-8 slightly elevated
Baňasová et al[23], 2015	Control (n = 60), OSCC (n = 60)	Mixed gender, age 45-70	IL-8	ELISA	Significantly higher IL-8 concentration in OSCC patients compared to controls
Ajdani et al[16], 2022	Control (n = 25), OSCC (n = 25)	Mixed gender, age 50-75	IL-6	ELISA	Elevated IL-6 levels in OSCC, suggesting its potential as a non-invasive marker

The table provides a detailed summary of these clinical studies, showcasing the significant findings and methodologies employed across different research efforts. By examining the outcomes of these investigations, we can better understand the role of salivary biomarkers in the early detection of oral cancer. Each study offers valuable insights into the diagnostic potential of interleukin-6 and interleukin-8, as well as the demographic variations and detection methods utilized. IL: Interleukin; ELISA: Enzyme-linked immunosorbent assay; OSCC: Oral squamous cell carcinoma.

The diagnostic utility of IL-6 and IL-8 is further supported by their inclusion in various clinical and validation studies. These biomarkers have been consistently highlighted for their high diagnostic performance across multiple studies, underscoring their potential for clinical application. However, larger cohort studies and standardization of assay protocols are needed to fully establish their use in routine clinical practice[29,32].

Genetic markers in saliva

Genetic markers in saliva have emerged as powerful tools for early detection and monitoring of oral cancer. These markers include DNA and RNA molecules, which provide critical information about genetic and epigenetic changes associated with malignancy. Lee et al[33] highlighted the importance of salivary transcriptome analysis, demonstrating that mRNA biomarkers can be effectively measured in saliva, offering a non-invasive alternative to tissue biopsies. In their study, they developed a streamlined protocol for direct saliva transcriptome analysis, which allows for ambient temperature processing and storage without significant degradation of RNA, thereby facilitating clinical application[33].

MiRNAs are small, non-coding RNA molecules that play pivotal roles in gene regulation and have shown great promise as salivary biomarkers for oral cancer. Zahran et al[7] reported that several miRNAs, including miRNA-21, miRNA-145, and miRNA-184, are significantly dysregulated in the saliva of oral cancer patients. These miRNAs are involved in critical cellular processes such as apoptosis, proliferation, and metastasis. For example, miRNA-21 functions as an onco-miRNA by downregulating tumor suppressor genes, whereas miRNA-145 and miRNA-184 exhibit tumor-suppressive activities. The stability of miRNAs in saliva and their disease-specific expression patterns make them excellent candidates for non-invasive cancer diagnostics[16].

DNA methylation patterns in saliva have also been extensively studied as potential biomarkers for oral cancer. Hypermethylation of tumor suppressor genes, such as p16 and MGMT, has been detected in the saliva of oral cancer patients. Baňasová et al[23] reported that alterations in DNA methylation could be reliably measured in salivary samples, providing valuable insights into the epigenetic modifications associated with oral carcinogenesis. These findings underscore the potential of salivary DNA methylation markers for early cancer detection and risk assessment[23].

The clinical utility of genetic markers in saliva is further supported by studies that have validated their diagnostic performance. For example, Arantes et al[9] reviewed the role of various genetic markers, including DNA, mRNA, and miRNAs, in head and neck cancers. Their review highlighted the significant diagnostic potential of these markers, emphasizing the need for large-scale validation studies to confirm their clinical applicability. The integration of genetic markers into multiplex diagnostic platforms, as demonstrated by Arellano-Garcia et al[29], can increase the sensitivity and specificity of salivary diagnostics, facilitating early and accurate detection of oral cancer[9,29].

In summary, the identification and validation of genetic markers in saliva represent a promising frontier in the early detection and monitoring of oral cancer. The non-invasive nature of saliva collection, combined with the rich genetic information it contains, makes it an ideal medium for cancer diagnostics. Continued research and technological advancements are essential to fully realize the potential of salivary genetic markers in clinical practice[16,23,33].

Changes in the metabolome and microbiota

Metabolomic profiling of saliva provides a comprehensive analysis of low-molecular-weight compounds, reflecting the metabolic state of the body and the presence of diseases such as oral cancer. Assad et al[34] conducted a systematic review evaluating the diagnostic value of salivary metabolites in cancer detection. The review highlighted that specific metabolites, such as alanine, valine, leucine, and choline, are frequently associated with oral cancer. These metabolites are involved in various metabolic pathways that are often dysregulated in cancer, making them potential biomarkers for early diagnosis[34].

Altered metabolic profiles in saliva can represent tumor metabolism and the body’s response to cancer. For example, increased levels of polyamines, which are involved in cell proliferation, have been identified in the saliva of oral cancer patients. Similarly, metabolites such as proline, threonine, and histidine have shown high diagnostic accuracy for differentiating cancerous from non-cancerous states[34]. These findings underscore the potential of salivary metabolomics as a non-invasive tool for cancer diagnostics, providing a snapshot of the biochemical changes associated with malignancy.

The oral microbiota, the community of microorganisms residing in the oral cavity, also plays a significant role in oral cancer development. Dysbiosis, or the imbalance of microbial populations, has been linked to carcinogenesis. Specific bacterial species, such as Fusobacterium nucleatum and Porphyromonas gingivalis, are more abundant in oral cancer patients than in healthy individuals[23]. These bacteria can induce chronic inflammation and produce carcinogenic metabolites, contributing to the tumor microenvironment. The composition of the oral microbiome, therefore, serves as a potential biomarker for assessing cancer risk and progression[23].

Combining metabolomic and microbiome analyses can increase their diagnostic accuracy for oral cancer. The integration of these two fields allows for a more comprehensive understanding of the disease, encompassing both host metabolic changes and microbial alterations. For example, studies have shown that the combination of specific metabolites and bacterial profiles can improve the sensitivity and specificity of oral cancer diagnostics[23]. This integrative approach leverages the strengths of both metabolomics and microbiomics, offering a robust diagnostic tool for the early detection and monitoring of oral cancer.

To illuminate the current landscape of salivary biomarkers, Table 3 provides a comprehensive summary of clinical studies focusing on DNA/RNA biomarkers, metabolites, and the microbiota. The table highlights the key findings from various studies, including sample size, detection methods, and the diagnostic potential of these biomarkers in OSCC detection. The categorization of biomarkers into three major groups provides a clear overview of the diverse approaches explored for early cancer detection and underscores the importance of integrating these biomarkers into clinical practice.

Table 3 Summary of studies on salivary biomarkers for oral squamous cell carcinoma detection.

Biomarker	Sample type	Method	Sample size	Key findings	Ref.
DNA & RNA biomarkers
TP53 mutation	Saliva	qPCR	OSCC (n = 50), controls (n = 50)	Significant mutation detected in OSCC patients	Cristaldi et al[35], 2019
MiRNA-21	Saliva	RT-PCR	OSCC (n = 40), controls (n = 40)	Elevated levels associated with tumor progression	Van Der Hofstadt et al[36], 2024
CDKN2A methylation	Saliva	NGS	OSCC (n = 60), controls (n = 60)	Hypermethylation observed in OSCC samples	Cui et al[37], 2021
Metabolites
Spermidine	Saliva	Mass spectrometry	OSCC (n = 30), controls (n = 30)	Elevated levels in OSCC patients	Er et al[38], 2015
Choline	Saliva	LC-MS	OSCC (n = 50), controls (n = 50)	Altered metabolic profile linked to cancer progression	Zhang et al[39], 2012
Microbiota
Fusobacterium nucleatum	Saliva	16S rRNA sequencing	OSCC (n = 45), controls (n = 45)	Increased abundance in OSCC patients	Kostic et al[40], 2013
Porphyromonas gingivalis	Saliva	qPCR	OSCC (n = 40), controls (n = 40)	Strong correlation with cancer presence	Michaud et al[41], 2017

This table summarizes key clinical studies investigating salivary biomarkers for the detection of oral squamous cell carcinoma, categorized into DNA/RNA biomarkers, metabolites, and microbiota. For each biomarker, the table includes the sample type, detection methods, sample size, key findings, and relevant references. These studies highlight the diagnostic potential of various biomarkers, with an emphasis on their utility for detecting oral squamous cell carcinoma at early stages and contributing to personalized treatment strategies. qPCR: Quantitative polymerase chain reaction; RT-PCR: Reverse transcription polymerase chain reaction; NGS: Next-generation sequencing; LC-MS: Liquid chromatography-mass spectrometry; OSCC: Oral squamous cell carcinoma; 16S rRNA: 16S ribosomal RNA.

Despite these promising findings, further research is needed to validate these biomarkers in larger, diverse populations. Standardization of sample collection, processing, and analytical methods is essential to ensure the reproducibility and reliability of the results. Additionally, longitudinal studies are needed to understand the dynamic changes in salivary metabolites and the microbiota throughout the progression of oral cancer[8,34].

Future directions and challenges

The future of salivary biomarker research for oral cancer detection holds significant promise, driven by advancements in nanotechnology, bioinformatics, and clinical applications. One of the most exciting areas of development is the use of graphene-based nanobiosensors, which offer unprecedented sensitivity and specificity for biomarker detection. Goldoni et al[1] discussed the potential of graphene electronics in salivary biomarker detection, emphasizing their superior electrical, biochemical, and mechanical properties. These sensors can detect a wide range of analytes quickly and accurately, making them ideal for POC diagnostics. The integration of these advanced technologies into clinical practice could revolutionize early detection and monitoring of oral cancer, improving patient outcomes[1].

However, several challenges must be addressed to translate these advancements into routine clinical use. One significant challenge is the standardization of saliva collection, processing, and storage protocols. Variability in sample handling methods can affect the stability and concentration of biomarkers, leading to inconsistent results. The development of robust and reproducible protocols is essential to ensure the reliability of salivary diagnostics. Furthermore, large-scale validation studies are needed to confirm the diagnostic accuracy of the identified biomarkers across diverse populations. These studies should also consider the potential influence of confounding factors such as diet, oral hygiene, and systemic health conditions[1,32].

The integration of artificial intelligence (AI) and machine learning (ML) into salivary biomarker research represents another promising direction. AI and ML can analyze complex datasets to identify patterns and correlations that may not be apparent through traditional analytical methods. These technologies can increase the predictive power of biomarker panels, allowing for more accurate risk assessment and early detection of oral cancer. Lee et al[33] highlighted the potential of AI in improving the interpretation of salivary transcriptomic data, which could lead to more personalized and precise diagnostic tools. The application of AI and ML in salivary biomarker research is still in its early stages, but its potential impact on the field is considerable[33].

Moreover, the commercialization and regulatory approval of new diagnostic technologies are crucial for their widespread adoption. Regulatory bodies must establish clear guidelines for the validation and approval of salivary biomarker tests to ensure their safety and efficacy. Collaborations among academic researchers, industry partners, and regulatory agencies are vital for navigating the complex landscape of diagnostic test development and bringing these innovations to the market. The development of cost-effective and user-friendly diagnostic platforms will also be essential to ensure accessibility and affordability, particularly in low-resource settings[1,32].

Patient demographics and potential bias

The studies reviewed in this manuscript include patient populations from various geographic regions; however, detailed racial and ethnic demographics are often underreported. This lack of representation may lead to potential bias in the applicability of salivary biomarkers across diverse populations. Some studies have focused primarily on populations in South Asia, particularly India and Sri Lanka, where the incidence of oral cancer is high because of tobacco and betel quid use. However, additional large-scale studies are needed to validate these biomarkers across racially and ethnically diverse cohorts to ensure their universal applicability. Future research should aim to include multiethnic cohorts to improve the generalizability of the findings.

Confounding factors

One of the critical confounding factors in salivary biomarker research is the influence of racial and ethnic diversity on biomarker expression and disease prevalence. Different racial and ethnic groups may exhibit variations in salivary composition because of genetic, dietary, and environmental factors, which can potentially affect the diagnostic accuracy of the identified biomarkers. Studies have focused predominantly on populations from specific geographic regions, such as South Asia and Western countries, which limits the generalizability of the findings. Future research should prioritize multiethnic and racially diverse cohorts to validate the robustness and universality of salivary biomarkers for OSCC. This approach will help address potential biases and increase the clinical applicability of salivary diagnostics across diverse populations.

In summary, the future of salivary biomarker research for oral cancer detection is bright, with numerous technological and scientific advancements on the horizon. Addressing the challenges of standardization, validation, and regulatory approval will be key to translating these innovations into clinical practice. The integration of advanced technologies such as graphene-based nanobiosensors and AI-driven data analysis has the potential to significantly improve the early detection and management of oral cancer, ultimately improving patient outcomes and reducing mortality[1,32,33].

FUTURE PERSPECTIVES

The future of salivary biomarker research for oral cancer detection is likely to include significant advancements, driven by innovations in nanotechnology, bioinformatics, and clinical applications. The integration of graphene-based nanobiosensors into diagnostic platforms represents a promising leap forward. Goldoni et al[1] highlighted the exceptional properties of graphene, including its high sensitivity and specificity, which make it an ideal material for biosensor development. These advancements will likely lead to more efficient, accurate, and non-invasive diagnostic tools that can be used in POC settings, thereby enhancing early detection and monitoring of oral cancer[1].

However, translating these technological innovations into clinical practice requires overcoming several challenges. Standardizing saliva collection, processing, and storage protocols is crucial to ensure the consistency and reliability of biomarker measurements. Additionally, large-scale validation studies are essential to confirm the diagnostic accuracy and clinical utility of these biomarkers across diverse populations. Integrating AI and ML can further increase the predictive power of biomarker panels, leading to more personalized and precise diagnostic tools. These technologies can analyze complex datasets to identify patterns and correlations that may not be apparent through traditional analytical methods[33].

CONCLUSION

In conclusion, salivary biomarkers are promising noninvasive tools for the early detection of OSCC. The integration of multiple biomarker types - including enzymes, proteins, DNA, RNA, metabolites, and microbiota - provides a comprehensive molecular profile of the disease. Enzymes such as LDH and ALP reflect metabolic changes associated with cancer progression. Salivary proteins, including ILs (IL-6 and IL-8), serve as indicators of inflammation and tumor microenvironment changes. Genetic markers, such as DNA mutations and methylation patterns, offer insights into genetic predispositions and tumorigenesis, whereas RNA molecules, including miRNAs, contribute to regulating gene expression. Metabolites and the microbiota further increase diagnostic potential by revealing metabolic and microbial dysbiosis associated with OSCC. Future efforts should focus on integrating these biomarkers into multimodal diagnostic platforms to increase sensitivity and specificity, ultimately improving patient outcomes through early intervention.

ACKNOWLEDGEMENTS

The authors would like to thank the Second Affiliated Hospital of Chongqing Medical University and Chongqing General Hospital for their support and assistance throughout the preparation of this manuscript. The authors also acknowledge the valuable feedback from the reviewers, which greatly contributed to improving the quality of the manuscript.