Introduction
Approximately 38 trillion microorganisms, including bacteria, fungi, viruses, and protozoa, coexist in humans, and their numbers roughly equal those of human cells [
1]. These microorganisms play crucial roles in various physiological and pathological processes, including cancer [
2]. The concept of intratumoral microbes has emerged to describe microorganisms residing within the tumor microenvironment [
3]. These microbes are located within or adjacent to tumor tissues and have been shown to influence various aspects of tumor biology. Their presence can affect tumor development, progression, and therapeutic responses. The roles of these intratumoral microbes in cancer are gaining recognition as they can modulate the tumor’s biological behavior and interact with the host’s immune system [
4]. Understanding these interactions is critical for advancing cancer research and for developing novel therapeutics.
Oral squamous cell carcinoma (OSCC) affects the oral cavity and oropharynx and is the most common form of head and neck cancer. OSCC accounts for more than 90% of cancer cases in this region [
5]. It can occur anywhere in the mouth, including the tongue, upper and lower gums, floor of the mouth, palate, and buccal mucosa [
6]. Globally, OSCC is one of the most prevalent human malignant tumors, responsible for 1–4% of all cancers and contributing to 2.4% of all cancer-related deaths, reflecting its high mortality rate [
7]. Nonetheless, survival rates for oral cancer have significantly improved, increasing by approximately 27% from the mid-1970s to 2018, according to data from the National Institutes of Health [
8]. Currently, the overall 5-year survival rate for individuals with oral cancer is 68%, although this rate varies depending on factors such as sex, race, and cancer stage [
9]. While smoking and alcohol consumption are the most common risk factors, other etiological factors, such as genetic predisposition and interactions between the host and microorganisms, remain incompletely understood. Mounting evidence suggests that oral microbes play crucial roles in the initiation and progression of oral cancer [
10,
11,
12]. Improvements in mortality and treatment outcomes have been supported by advancements in diagnostic tools that allow earlier detection and prevention of disease progression.
Numerous oral microbes have been implicated in OSCC pathogenesis. The oral cavity harbors a highly diverse and complex microbiome, second only to the gut in terms of microbial richness, comprising over 700 bacterial species alongside fungi, viruses, and protozoa [
13]. Although the presence of bacteria in human tumors was first documented over a century ago, characterization of the tumor-associated microbiome has proven challenging owing to its low biomass. In 2020, Nejman et al. conducted a comprehensive and rigorous analysis of bacterial communities across various human tumors, including those of the breast, lung, ovary, pancreas, melanoma, bone, and brain, demonstrating that distinct bacterial profiles are associated with specific cancer types [
14]. Additionally, the detection of fungi within multiple tumor types highlights the need to further investigate the role of intratumoral fungi in cancer diagnosis and prognosis [
15]. However, research has not focused on identifying OSCC-specific oral microbial profiles or elucidating the microbial shifts that occur as a healthy oral cavity progresses to a premalignant state or early-stage OSCC. Such investigations are pivotal for advancing our understanding of OSCC, particularly in the areas of early detection and prevention of disease and development of targeted therapeutic strategies.
Several key factors influence the development and progression of OSCC, including oral and systemic health status, immune responses, and microbial dysbiosis of the oral cavity. This study specifically focused on oral microbes. The primary objective of this study was to present the microbial profiles of patients with OSCC by investigating 15 oral microbes, including 14 predominantly detected oral bacteria and 1 fungus, and to elucidate the correlations among these microbes. The hypothesis of this study was that, instead of a single species being OSCC-specific, certain species may serve as keystone members in forming a pathological microbial network. In addition, we reviewed the significance of OSCC-specific intratumoral microbes.
Materials and methods
Study population
Twelve participants (8 females and 4 males; mean age, 54.33 ± 20.65 years) voluntarily participated in this study at the Kyung Hee University Dental Hospital, recruited through advertising between October 1, 2023, and June 30, 2024. The research protocol for this study was reviewed for compliance with the Declaration of Helsinki and approved by the Institutional Review Board of Kyung Hee University Dental Hospital in Seoul, South Korea (KHD IRB, IRB No-KH-DT20030). Informed consent was obtained from all participants. The participants were divided into three groups: Group 1—healthy controls (3 females and 1 male, 28.25 ± 3.86 years), Group 2—patients with stomatitis (2 females and 2 males, 59.75 ± 5.74 years), and Group 3—patients with OSCC (3 females and 1 male, 75.00 ± 1.82 years). The health status of all participants was assessed by examining oral tissues, including the periodontal tissues and buccal mucosa, as well as general conditions such as oral hygiene and dental calculus deposition.
1) Inclusion criteria: Participants were required to voluntarily read, understand, and sign the consent form and be capable of participating in the study. Group 1 consisted of medically healthy adults with healthy periodontal and oral mucosal conditions, fewer than two missing teeth in the permanent dentition, and intact oral mucosal integrity. Group 2 comprised patients with stomatitis, characterized by inflammation of the oral mucosa affecting the mouth and lips, with or without oral ulceration. Group 3 comprised patients with OSCC, with inclusion limited to those whose OSCC was confirmed by pathological examination following an incisional biopsy.
2) Exclusion criteria: Individuals with severe xerostomia who were unable to produce 2 mL of saliva, pregnant or lactating women, adults who did not comply with clinical examination or sample collection protocols, and those with insufficient data or who withdrew from the study for any reason were excluded.
Collection of unstimulated whole saliva
For microbial analysis, 2 mL of unstimulated whole saliva was collected from all participants using the spitting method. For patients with stomatitis and OSCC, saliva samples were collected before any treatment. Before the saliva sampling session, the participants were instructed to refrain from consuming caffeine and/or nicotine for at least 4 h and alcohol for at least 24 h. All participants were instructed to abstain from eating, drinking, or brushing their teeth before saliva collection. Unstimulated whole saliva samples were collected between 9:30 and 11:30 a.m. to minimize diurnal variability, with an average time of 3 h between waking up and collection.
Contamination prevention
To minimize contamination, stringent protocols were followed throughout the saliva sample collection and microbial identification processes. The researchers wore masks, sanitized their hands, and used disinfected dental gloves, which were replaced between participants. The experimental table was cleaned with alcohol before each experiment. All equipment and reagents that came into direct contact with the samples, such as pipette tips and tubes, were sterilized before use and discarded after a single use. To avoid aerosol contamination, a centrifuge with a closed lid was used, and the reagent and reaction preparations for PCR were conducted on a clean bench.
Identification and quantification of oral bacterial and fungal species
The bacterial DNA quantity, community composition, and individual abundance of oral bacterial species were determined. In saliva samples, the absolute amount and abundance of 14 bacteria were assessed, namely, Aggregatibacter actinomycetemcomitans, Prevotella intermedia, Prevotella nigrescens, Eikenella corrodens, Campylobacter rectus, Fusobacterium nucleatum, Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, Lactobacillus casei, Streptococcus mutans, Streptococcus sobrinus, Parvimonas micra, and Eubacterium nodatum. Additionally, Candida albicans was identified as a representative fungal species. The detailed methods for the identification and quantification of oral bacterial and fungal species are as follows.
1) Oral microbe DNA isolation
The saliva samples were first subjected to vigorous vortexing to ensure thorough mixing. Subsequently, 500 μL from each sample was then combined with 500 μL of lysis buffer (5 mM EDTA, 5 M guanidine hydrochloride, and 0.3 M sodium acetate) in a tube. The mixture was vortexed and incubated at 65°C for 10 min. Thereafter, 20 μL of S2 buffer (0.25 g/mL silicon dioxide; Merck KGaA, Darmstadt, Germany) was added to the sample-lysis buffer mixture, which was then vortexed and incubated at room temperature for 5 min, with periodic inversion using an automatic system. The mixture was centrifuged at 5,000 rpm for 30 s, and the supernatant was carefully removed. Subsequently, 1 mL of PureLink (Invitrogen Corporation, Carlsbad, CA, USA) and PCR purification washing buffer 1 (50 mM 3-(N-morpholino) propanesulfonic acid buffer, pH 7.0, with 1 M sodium chloride) activated with 160 mL of 100% ethanol were added to the tube. The contents were vortexed until the beads were completely resuspended. After another 30 s centrifugation at 5,000 rpm, the supernatant was carefully removed. Next, 1,000 μL of ethanol wash buffer 2 was added, and the beads were resuspended by vortexing. The tube was then centrifuged at 5,000 rpm for 30 s, and the supernatant was removed. To elute the DNA, 100 μL of elution buffer (100 mM Tris-HCl, pH 7.5, and 1 M EDTA) was added to the tube, vortexed, and incubated at 65°C for 10 min. DNA was then isolated. For PCR analysis, the samples were centrifuged at 13,000 rpm for 5 min, and the supernatant was transferred to a sterile microcentrifuge tube.
2) Real-time PCR (qPCR) amplification
qPCR amplification was performed to detect 14 salivary bacterial species using species-specific primers. Total bacterial quantities were assessed using 16S ribosomal RNA (rRNA) primers designed to target each bacterium. The primers used were consistent with those used in our previous study [
16]. To quantify the total bacterial DNA, a conserved 16S rRNA primer probe was used. To amplify
C. albicans, primers were selected based on previous studies [
17] and verified through in silico analyses. A reaction mixture was prepared by combining 5 μL of DNA template, 2.5 μM of each forward and reverse primer, and 10 μL of 2X master mix (GeNet Bio, Daejeon, Korea). Subsequently, 20 μL of this mixture was used for qPCR. The qPCR thermal cycling protocol included an initial denaturation step at 95°C for 10 min, followed by 45 cycles of denaturation at 95°C for 15 s and annealing/extension at 60°C for 1 min. The positive controls comprised plasmid DNA from each target bacterium and
C. albicans, whereas DNase/RNase-free water was used as a negative control.
3) Calculation of DNA copy numbers for oral bacteria and C. albicans
Samples were prepared by mixing 2 mL of saliva with 2 mL of the sample stock solution. For DNA extraction, 500 μL of this preservation solution was used, and 100 μL of the extract was finally eluted. qPCR was conducted using 5 μL of the total 100 μL solution. DNA quantification was performed using the standard curve method, with the analysis based on a 5-μL aliquot. The DNA copy number was calculated for 1 mL of saliva and 20 mL of the preservation solution. The preservation solution consisted of Tris-HCl, urea, sodium acetate, sodium dodecyl sulfate, ethylenediaminetetraacetic acid, sodium ascorbate, and ethanol.
4) α-Diversity based on Shannon’s diversity index
The α-diversity of microbial communities was evaluated using Shannon’s diversity index, with bacterial richness determined by the total number of bacterial DNA copies. Shannon’s diversity index was calculated using the following formula:
where
pi represents the relative abundance of the
ith species, calculated as
n/N, where
n is the number of individuals of the
ith species and N is the total number of individuals across all species in the community. Shannon’s diversity index
H measures diversity, where a value of zero indicates no diversity, and higher values signify greater diversity [
18,
19].
Statistical analyses
Descriptive statistics are reported as means ± standard deviations or numbers with percentages, as appropriate. To analyze the distribution of discontinuous data, we used χ2 tests for equality of proportions, Fisher’s exact tests, and Bonferroni tests. Analysis of variance (ANOVA) was used to investigate differences in the mean values related to the oral microbiome among the three groups. Spearman’s correlation analysis was used to determine the correlations between the variables, and the correlation coefficient (r) was closer to the absolute value of 1, indicating a stronger correlation. All statistical analyses were performed using IBM SPSS Statistics for Windows (version 26.0; IBM Corp., Armonk, NY, USA) and R Version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was set at a two-tailed p-value < 0.05.
Results
Demographics and oral examination
Among the three groups in this study, the ages of patients with stomatitis (59.75 ± 5.74 years) and OSCC (75.00 ± 1.82 years) were significantly higher than those of the healthy control group (28.25 ± 3.86 years). Furthermore, the age of the patients with OSCC was significantly higher than that of the patients with stomatitis (p < 0.001). There was no statistically significant difference in the female-to-male ratio among the groups, which was 1:1 in the stomatitis group and 3:1 in the OSCC group. Considering the lesion site, visual inspection, X-ray, and CT scans revealed that 100% of the lesions in the stomatitis group were located in the buccal mucosa, while 100% of the lesions in the OSCC group were found in the mandible. During oral examinations, the incidence of periodontitis was significantly higher in the OSCC group than in the healthy control group (0.0% vs. 70%, p = 0.018). However, there were no differences between the groups regarding the presence of calculus deposition or poor oral hygiene. In the OSCC group, calculus deposition was observed in 25% of the patients, and poor oral hygiene was noted in 50% of the patients (
Table 1).
DNA copy numbers of bacterial and fungal species
The DNA copy numbers of 14 bacteria and 1 fungus were compared across the healthy control, stomatitis, and OSCC groups (
Table 2). Among these,
T. denticola, L. casei, and
C. albicans exhibited statistically significant differences between groups (all p < 0.05). Specifically,
T. denticola was found in the highest quantity in the OSCC group (5,358,692.95 ± 3,540,767.33) compared to that in the stomatitis (123,355.54 ± 197,490.86) and healthy control (9,999.21 ± 11,998.40) groups, with a significant increase in DNA copy numbers in the stomatitis group relative to the healthy control group (p = 0.007).
L. casei was not detected in the healthy control group, but it was significantly more abundant in the stomatitis group (1,653.94 ± 2,981.98) and even higher in the OSCC group (21,336.95 ± 9,258.79) (p = 0.001). A similar pattern was observed for
C. albicans, with DNA copy numbers increasing from the healthy control (464.29 ± 716.76) to the stomatitis (1,861.30 ± 1,206.15) to the OSCC group (9,347.98 ± 5,128.54) (p = 0.006).
A. actinomycetemcomitans was not detected in any group. Aside from
T. denticola, L. casei, and
C. albicans, no significant quantitative differences were observed among the other 12 microbial species across the groups (
Figure 1).
Total bacterial amount and Shannon’s diversity index
The total bacterial DNA copies, measured using a universal probe for oral bacteria, followed the pattern of healthy control (246,015,329.80 ± 250,216,570.66) < stomatitis (671,981,670.25 ± 645,482,366.81) < OSCC (40,082,611.47 ± 37,609,107.97), with no statistically significant differences (p = 0.406). The mean total DNA copies of gram-negative microorganisms followed the trend of healthy control (1,959,265.36 ± 1,372,737.86) < stomatitis (16,984,317.46 ± 14,157,382.83) < OSCC (26,708,490.05 ± 22,693,303.84), although no statistically significant differences were observed between the groups (p = 0.128). Similarly, the total DNA copy numbers of gram-positive microorganisms increased from the healthy control (92,020.78 ± 82,510.78) to the stomatitis (1,861.30 ± 1,206.15) to the OSCC group (9,347.98 ± 5,128.54), yet these differences were not statistically significant (p = 0.119). Shannon’s diversity index also increased from the healthy control (1.17 ± 0.35) to the stomatitis (1.42 ± 0.42) to the OSCC group (1.85 ± 1.26), but the difference was not statistically significant (p = 0.502) (
Table 2 and
Figure 1). In general, Shannon’s diversity index falls between 1.5 and 3.5, with values above 4.5 being rare [
18].
Prevalence of bacterial and fungal species
The comparison of the prevalence of 15 oral microbes, including 14 oral bacteria and 1 fungus, across the three study groups revealed several significant differences. First, the proportion of
F. nucleatum relative to the total DNA copies of the 15 oral microorganisms analyzed was significantly higher in the healthy control group (60.47 ± 21.04%) than in the stomatitis (30.82 ± 23.06%) and OSCC groups (7.75 ± 3.62%) (p = 0.008). Second,
P. gingivalis exhibited a significantly different distribution among the groups, with the highest prevalence in the stomatitis group (43.45 ± 24.93%), followed by the OSCC group (16.39 ± 23.18%) and the healthy control group (0.17 ± 0.17%) (p = 0.035) (
Table 3).
When ranking the mean prevalence of the analyzed microorganisms within each group from highest to lowest, the following patterns were observed:
(1) Healthy control group: F. nucleatum > P. nigrescens > E. corrodens > P. micra > T. forsythia > C. rectus > T. denticola > P. intermedia > S. mutans > P. gingivalis > C. albicans > E. nodatum > S. sanguinis ≈ L. casei > A. actinomycetemcomitans.
(2) Stomatitis groups were as follows: P. gingivalis, F. nucleatum, P. nigrescens, T. forsythia > E. corrodens, C. rectus, T. denticola, P. micra, P. intermedia, E. nodatum, S. mutans, L. casei, S. sanguinis, A. actinomycetemcomitans.
(3) OSCC group: P. micra > P. nigrescens > E. corrodens > T. denticola > F. nucleatum > P. gingivalis > T. forsythia > C. rectus > S. mutans > E. nodatum > L. casei > C. albicans > S. sanguinis ≈ P. intermedia > A. actinomycetemcomitans.
Notably, the most prevalent oral bacterial species varied among the groups.
F. nucleatum was the most prevalent in the healthy control group (60.47%),
P. gingivalis in the stomatitis group (43.45%), and
P. micra in the OSCC group (18.85%) (
Figure 2A). When the presence of each microbe was analyzed,
T. denticola,
P. micra,
L. casei,
S. mutans, and
C. albicans were found to be more prevalent in the OSCC group than in the other groups (
Figure 2B).
Correlations among oral microbes
Spearman’s correlation analysis was conducted to examine the relationship between the DNA copies of oral microbes. Importantly, several significant positive correlations were observed between gram-negative and gram-positive bacteria and fungi (
Table 4).
Based on DNA copy numbers, T. denticola, L. casei, and C. albicans were the oral microbes that exhibited significantly higher levels in the OSCC group; therefore, we focused on the relationships between these species. First, T. denticola, L. casei, and C. albicans showed strong positive correlations. Considering the strength of the correlations with T. denticola, T. denticola was positively correlated with L. casei (r = 0.890, p < 0.001), E. corrodens (r = 0.752, p = 0.005), P. micra (r = 0.742, p = 0.006), C. albicans (r = 0.724, p = 0.008), P. nigrescens (r = 0.708, p = 0.010), and T. forsythia (r = 0.634, p = 0.027). Species that were positively correlated with L. casei DNA copy numbers presented with the following correlation strengths: C. albicans (r = 0.931, p < 0.001) > T. denticola (r = 0.890, p < 0.001) > P. nigrescens (r = 0.849, p < 0.001) > P. micra (r = 0.889, p < 0.001) > E. corrodens (r = 0.849, p < 0.001), E. nodatum (r = 0.751, p = 0.005) > C. rectus (r = 0.653, p = 0.021). The oral microbes that were positively correlated with C. albicans DNA copy numbers were L. casei (r = 0.931, p < 0.001), P. micra (r = 0.913, p < 0.001), E. corrodens (r = 0.909, p < 0.001), P. nigrescens (r = 0.878, p < 0.001), C. rectus (r = 0.790, p = 0.002), T. denticola (r = 0.724, p = 0.008), and E. nodatum (r = 0.674, p = 0.016). Additionally, P. micra, which was the most abundant in the OSCC group compared to that in the healthy control and stomatitis groups, was positively correlated with E. corrodens (r = 0.998, p < 0.001), P. nigrescens (r = 0.974, p < 0.001), C. albicans (r = 0.931, p < 0.001), L. casei (r = 0.889, p < 0.001), C. rectus (r = 0.761, p = 0.004), and T. denticola (r = 0.742, p = 0.006). Notably, no significant negative correlations were observed among the microbes, suggesting an inhibition or reduction in the presence of certain species.
In-depth analysis of T. denticola, C. albicans, and L. casei
An in-depth analysis based on the schematic diagram illustrating the direct and indirect relationships between the three prominent microbes in the OSCC group—
T. denticola, C. albicans, and
L. casei—revealed the following findings:
T. denticola was directly correlated with gram-negative species such as
P. nigrescens,
E. corrodens, and
P. gingivalis.
F. nucleatum exhibited an indirect positive correlation with
T. denticola via
P. nigrescens. Although
C. rectus was not directly correlated with
T. denticola, it was indirectly correlated with
P. nigrescens,
E. corrodens,
T. forsythia, and
P. gingivalis. Among the gram-positive species,
T. denticola showed a direct positive correlation with
L. casei and
P. micra. A strong, direct positive correlation was observed between
T. denticola and
C. albicans (
Figure 3A).
C. albicans was positively correlated with several gram-negative species, including
T. denticola, E. corrodens, P. nigrescens, and
C. rectus. Among the gram-positive species,
C. albicans was significantly and positively correlated with
P. micra,
E. nodatum, and
L. casei (
Figure 3B).
L. casei was positively correlated with several gram-positive species, including
P. nigrescens,
E. corrodens,
P. micra, and
E. nodatum. Among the gram-negative species,
L. casei had significant positive correlations with
T. denticola and
C. rectus and also showed a strong positive correlation with
C. albicans (
Figure 3C).
Discussion
In this study, we investigated the distribution of 14 major oral bacteria and C. albicans across three groups: healthy controls, patients with stomatitis, and patients with OSCC. Our findings revealed that T. denticola, L. casei, and C. albicans were significantly more abundant in the OSCC group than in the other groups. Specifically, T. denticola was present in the highest quantity in the OSCC group, followed by the stomatitis and healthy control groups. L. casei was undetectable in healthy controls, but showed a marked increase in both the stomatitis and OSCC groups. Similarly, C. albicans exhibited a progressive increase in DNA copy numbers from healthy controls to patients with stomatitis and those with OSCC. Considering the correlations among oral microbes, a wide range of positive associations were observed between gram-negative and gram-negative bacteria, gram-positive and gram-positive bacteria, gram-negative and gram-positive bacteria, C. albicans and gram-negative bacteria, and C. albicans and gram-positive bacteria. Despite these trends, overall microbial diversity, as measured by the Shannon’s diversity index, did not differ significantly between the groups. These results suggest a potential association between these specific microbes and OSCC, warranting further investigation into their roles as OSCC-specific markers.
Among the gram-negative species,
T. denticola was notably more abundant in the OSCC group than in the healthy control and stomatitis groups.
T. denticola is a motile, obligate anaerobic bacterium and highly proteolytic spirochete that lives in the oral cavity of humans and is predominantly found in periodontal lesions associated with adult periodontitis [
20].
T. denticola, along with
P. gingivalis and
F. nucleatum, forms a red complex that plays a crucial role in periodontal disease. Numerous studies have demonstrated an association between periodontitis and OSCC, and periodontal pathogens, such as
T. denticola, are implicated in the pathogenesis of OSCC [
11,
21]. In addition,
T. denticola directly promotes OSCC cell proliferation, and the mechanism has been associated with intracellular TGF-β pathway activation [
11]. In the present study,
T. denticola was directly correlated with gram-negative species, such as
P. gingivalis,
P. nigrescens, and
E. corrodens.
P. nigrescens plays a bridging role between
T. denticola and
F. nucleatum. In a recent study, more abundant
Fusobacteria (at the phylum level),
Fusobacterium (at the genus level), and
F. nucleatum (at the species level) were identified in OSCC patients [
22].
F. nucleatum is a major pro-tumorigenic bacterium that accumulates at the invasive margins of OSCC tissues and drives tumor-associated macrophage formation [
23]. However, it is important to note that the association of these bacteria with OSCC has not been fully established. Further research is required to explore their potential roles in the prognosis and pathogenesis of OSCC.
T. denticola exhibited a direct positive correlation with
L. casei and
P. micra and a strong direct positive correlation with
C. albicans. Additionally, several direct and indirect complex interactions among the oral microbes were observed. Avril et al. proposed a "bacterial driver–passenger" model in colorectal cancer, wherein initial "driver" bacteria induce alterations in the microenvironment, thereby facilitating tumor formation [
24]. In the early stages of oral cancer, key pathogens increase, followed by subsequent changes in the associated microbial communities [
25]. As the tumor progresses, these driver bacteria are gradually supplanted by "passenger" bacteria, including opportunistic pathogens and commensal or probiotic species. These passenger bacteria may further influence tumor progression through interactions with both the host and existing tumor microenvironment [
26]. In patients with OSCC, additional research is required to elucidate driver–passenger microbe relationships and delineate the sequential dynamics of microbial populations within the tumor context.
Among the gram-positive bacteria,
L. casei has emerged as the most prominent species associated with OSCC.
Lactobacilli are gram-positive, anaerobic, rod-shaped commensal bacteria typically found in the oral, genitourinary, and gastrointestinal tracts of humans [
27].
Lactobacillus is one of the most common bacterial genera found in the saliva of individuals with OSCC [
28,
29].
L. casei was positively correlated with several gram-positive species, including
P. nigrescens,
E. corrodens,
P. micra, and
E. nodatum. Among the gram-negative species,
L. casei had a significantly strong positive correlation with
T. denticola and
C. rectus. Notably, members of the
Lactobacillus genus exhibit both carcinogenic and anticarcinogenic properties. The production of lactic acid and other organic acids by these bacteria can acidify the tumor microenvironment, potentially promoting OSCC growth [
30]. Additionally, variations in the activities of nicotinamide adenine dinucleotide phosphate oxidase and nitric oxide synthase may lead to the accumulation of reactive oxygen and nitrogen species, thereby contributing to chronic inflammation [
31]. Some
Lactobacillus species may exacerbate this process by generating hydrogen peroxide [
32]. However, it is crucial to recognize that, while
Lactobacillus species are prevalent in individuals with OSCC, their presence does not necessarily imply a causative role in the disease [
33]. Further research is required to fully elucidate the roles of
Lactobacillus and other microbes in OSCC development.
C. albicans positively correlated with several gram-negative species, including
T. denticola,
E. corrodens,
P. nigrescens, and
C. rectus. This study focused on
C. albicans, which is the fungus most commonly associated with oral diseases.
C. albicans can cause oral candidiasis, commonly known as thrush [
34]. Although extensive research has been conducted on the bacterial components of the OSCC microbiome, fungal components remain relatively underexplored and poorly defined [
35]. Nonetheless,
Candida, a genus of yeast-like fungi, continues to be a prominent subject of study in OSCC. Although
C. albicans is the most prevalent species, other
Candida species have also been identified in patients with OSCC [
28,
36]. Studies have found that 72.2% of these patients have
Candida species in their saliva [
28]. The potential carcinogenic mechanisms of
C. albicans infection are complex. The initial step in its colonization and invasion involves adhesion to mucosal epithelial cells, which are the first line of defense against pathogens [
37]. This adhesion can compromise the host’s immune defenses, facilitating further infection. Additionally,
C. albicans produces carcinogens, such as nitrosamines, which can activate proto-oncogenes and induce carcinomatous changes [
38]. Chronic inflammation associated with
C. albicans infection may also contribute to cancer development [
39]. Furthermore,
C. albicans may promote carcinogenesis by stimulating the T helper 17 (Th17) response. Th17 cells play a crucial role in maintaining mucosal barriers and eliminating pathogens from mucosal surfaces [
40].
C. albicans exhibited significant positive correlations with
L. casei,
P. micra, and
E. nodatum among gram-positive species. However, these complex interactions remain underexplored, and further research employing advanced statistical and analytical methods is required to fully elucidate these relationships.
In this study, although the mean Shannon’s index, which is an index of α-diversity, increased from healthy controls to stomatitis patients and then to OSCC patients, the differences were not statistically significant. Consistent with the results of Zhao et al. [
41], oral cancer samples exhibited a greater variety of bacterial species than did healthy control samples. This finding is supported by recent reviews that have reported higher α-diversity in OSCC patient samples than in healthy controls [
22]. Additionally, patients with OSCC and a history of tobacco use showed an increase in α-diversity [
42]. Studies have similarly indicated that cancers at various sites often present with elevated α-diversity in the microbiome compared with that in healthy controls [
43]. This increase in microbial diversity may be attributed to several factors, including a chronic inflammatory environment, alterations in local pH and nutrient availability, changes in tumor-associated inflammatory responses, and environmental conditions. In the current study, no specific microbial species were found to be directly correlated with the increase in Shannon’s diversity index observed in OSCC. Future research with a larger cohort of OSCC samples is needed to identify the microbes associated with microbial diversity and to further investigate changes in microbial profiles relative to healthy controls.
A limitation of this preliminary study is its small sample size of only 12 participants, including only 4 patients with OSCC. Additionally, we did not utilize advanced analytical techniques such as next-generation sequencing or state-of-the-art AI-driven analyses. Despite these limitations, this study has several strengths. We concurrently assessed both the major bacterial species and fungi using qPCR, which allowed for a comprehensive analysis of the oral microbial profile and the interrelationships within the same saliva samples. This methodology enabled us to investigate the roles of specific microbes and their complex interactions in the pathological mechanisms of OSCC. Previous studies targeting OSCC-specific pathogens have often concentrated on individual microbes, such as
P. gingivalis or
T. denticola [
10,
11,
44,
45]. Although our preliminary results are encouraging, further studies with larger sample sizes and multicenter designs are essential to validate these findings. Follow-up studies are being planned to address these issues.
Figure 4.
Oral microbes associated with oral squamous cell carcinoma. T. denticola: Treponema denticola, L. casei: Lactobacillus casei, C. albicans: Candida albicans, OSCC: oral squamous cell carcinoma.
Figure 4.
Oral microbes associated with oral squamous cell carcinoma. T. denticola: Treponema denticola, L. casei: Lactobacillus casei, C. albicans: Candida albicans, OSCC: oral squamous cell carcinoma.
Author Contributions
Writing and original draft preparation: Y-HL; conceptualization: Y-HL and JJ; methodology: Y-HL, J-YH, and JJ; software: Y-HL; validation and formal analysis: Y-HL; investigation: Y-HL and JJ; resources: Y-HL, J-YH, and JJ; data curation: Y-HL; writing, review, and editing: Y-HL; supervision: Y-HL, J-YH, and JJ; project administration: Y-HL; funding acquisition: Y-HL. All the authors contributed to and approved the submission of the manuscript.
Funding
This work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health & Welfare, Republic of Korea, Ministry of Food and Drug Safety) (Project Number: KMDF_PR_20200901_0023, 9991006696).
Informed consent
Informed consent was obtained from all patients involved in the study.
Data availability statement
The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors extend their gratitude to Sung-Woo Lee and Hee-Kyung Park, Department of Oral Medicine and Oral Diagnosis, Seoul National University.
Conflict of interest
The authors declare that this study was conducted in the absence of any commercial or financial relationships that could be construed as a conflict of interest.
Ethics statement
The research protocol complied with the Declaration of Helsinki and was approved by the Institutional Review Board of Kyung Hee University Dental Hospital, Seoul, South Korea (IRB No-KH-DT20030).
Declaration of generative AI in scientific writing
Not applicable.
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Figure 1.
Comparison of DNA copy numbers of oral bacteria and Candida albicans between groups.
Figure 1.
Comparison of DNA copy numbers of oral bacteria and Candida albicans between groups.
Figure 2.
Group-wise comparison of the prevalence of each oral microbe. Aa, Aggregatibacter actinomycetemcomitans; Pi, Prevotella intermedia; Pn, Prevotella nigrescens; Ec, Eikenella corrodens; Cr, Campylobacter rectus; Fn, Fusobacterium nucleatum; Pg, Porphyromonas gingivalis; Td, Treponema denticola; Tf, Tannerella forsythia; Lc, Lactobacillus casei; Sm, Streptococcus mutans; Ss, Streptococcus sobrinus; Pm, Parvimonas micra; En, Eubacterium nodatum; Ca, Candida albicans.
Figure 2.
Group-wise comparison of the prevalence of each oral microbe. Aa, Aggregatibacter actinomycetemcomitans; Pi, Prevotella intermedia; Pn, Prevotella nigrescens; Ec, Eikenella corrodens; Cr, Campylobacter rectus; Fn, Fusobacterium nucleatum; Pg, Porphyromonas gingivalis; Td, Treponema denticola; Tf, Tannerella forsythia; Lc, Lactobacillus casei; Sm, Streptococcus mutans; Ss, Streptococcus sobrinus; Pm, Parvimonas micra; En, Eubacterium nodatum; Ca, Candida albicans.
Figure 3.
Schematic presentation of the relationships between oral microbes. Based on the results of Spearman’s correlation analysis, the diagram illustrates the microbial relationships. The thickness of each bar reflects the strength of the correlation between two oral microbes. P. intermedia: Prevotella intermedia, P. nigrescens: Prevotella nigrescens, E. corrodens: Eikenella corrodens, C. rectus: Campylobacter rectus, F. nucleatum: Fusobacterium nucleatum, P. gingivalis: Porphyromonas gingivalis, T. denticola: Treponema denticola, T. forsythia: Tannerella forsythia, L. casei: Lactobacillus casei, S. mutans: Streptococcus mutans, S. sobrinus: Streptococcus sobrinus, P. micra: Parvimonas micra, E. nodatum: Eubacterium nodatum. C. albicans: Candida albicans.
Figure 3.
Schematic presentation of the relationships between oral microbes. Based on the results of Spearman’s correlation analysis, the diagram illustrates the microbial relationships. The thickness of each bar reflects the strength of the correlation between two oral microbes. P. intermedia: Prevotella intermedia, P. nigrescens: Prevotella nigrescens, E. corrodens: Eikenella corrodens, C. rectus: Campylobacter rectus, F. nucleatum: Fusobacterium nucleatum, P. gingivalis: Porphyromonas gingivalis, T. denticola: Treponema denticola, T. forsythia: Tannerella forsythia, L. casei: Lactobacillus casei, S. mutans: Streptococcus mutans, S. sobrinus: Streptococcus sobrinus, P. micra: Parvimonas micra, E. nodatum: Eubacterium nodatum. C. albicans: Candida albicans.
Table 1.
Demographics and oral examination.
Table 1.
Demographics and oral examination.
Parameters |
Healthy control mean ± SD or n (%) |
Stomatitis mean ± SD or n (%) |
OSCC mean ± SD or n (%) |
p-value |
post-hoc |
Age (years) a
|
28.25 ± 3.86 |
59.75 ± 5.74 |
75.00 ± 1.82 |
<0.001*** |
Healthy control < Stomatitis and OSCC, Stomatitis < OSCC |
Sexb
|
|
|
|
|
|
Female |
3 (75.0%) |
2 (50.0%) |
3 (75.0%) |
0.687 |
|
Male |
1 (25.0%) |
2 (50.0%) |
1 (25.0%) |
|
|
Lesion site |
|
|
|
|
|
Buccal mucosa b |
0 (0.0%) |
4 (100.0%) |
0 (0.0%) |
<0.001*** |
|
Mandible b |
0 (0.0%) |
0 (0.0%) |
4 (100.0%) |
<0.001*** |
|
Oral examination |
|
|
|
|
|
Periodontitis b |
0 (0.0%) |
2 (50.0%) |
3 (75.0%) |
0.018* |
|
Calculus deposition b
|
0 (0.0%) |
1 (25.0%) |
1 (25.0%) |
0.549 |
|
Poor oral hygiene b |
0 (0.0%) |
0 (0.0%) |
2 (50.0%) |
0.091 |
|
Table 2.
Comparison of DNA copies of bacterial and fungal species, and Shannon’s diversity index.
Table 2.
Comparison of DNA copies of bacterial and fungal species, and Shannon’s diversity index.
Microbial parameter |
Healthy control mean ± SD |
Stomatitis mean ± SD |
OSCC mean ± SD |
p-value |
post-hoc |
Gram (-) |
Aa |
0 ± 0 |
0 ± 0 |
0 ± 0 |
NA |
|
Pi |
4721.43 ± 9338.45 |
97123.55 ± 163965.30 |
0 ± 0 |
0.311 |
|
Pn |
313182.60 ± 162170.03 |
1783400.78 ± 1859234.18 |
7444085.88 ± 7776100.68 |
0.124 |
|
Ec |
161638.36 ± 73445.12 |
497355.67± 376410.96 |
5455613.30 ± 5929438.11 |
0.101 |
|
Cr |
17702.63 ± 19738.29 |
431907.02 ± 725172.58 |
869577.08 ± 745262.35 |
0.189 |
|
Fn |
1414677.53 ± 1248019.45 |
5425576.88 ± 6134874.96 |
3928871.25 ± 4209210.50 |
0.453 |
|
Pg |
2076.07 ± 1336.47 |
7803707.73 ± 10628172.40 |
2501079.28 ± 1786087.94 |
0.247 |
|
Td |
9999.21 ± 11998.40 |
123355.54 ± 197490.86 |
5358692.95 ± 3540767.33 |
0.007** |
Healthy control < Stomatitis and OSCC, Stomatitis< OSCC |
Tf |
35267.53 ± 25096.14 |
821889.97 ± 910730.89 |
1150570.3 ± 721737.42 |
0.106 |
|
Gram (+) |
Lc |
0 ± 0 |
1653.94 ± 2981.98 |
21336.95 ± 9258.79 |
0.001** |
Healthy control < Stomatitis and OSCC, Stomatitis< OSCC |
Sm |
3258.15 ± 3492.39 |
18238.71 ± 35986.69 |
100785.83 ± 181256.31 |
0.416 |
|
Ss |
0 ± 0 |
641.81 ± 1283.62 |
0 ± 0 |
0.405 |
|
Pm |
88593.26 ± 81242.44 |
112672.78 ± 85587.27 |
13204631.90 ± 15038585.05 |
0.098 |
|
En |
169.37 ± 226.55 |
22360.99 ± 32330.07 |
38018.78 ± 37252.07 |
0.223 |
|
Fugus |
Ca |
464.29 ± 716.76 |
1861.30 ± 1206.15 |
9347.98 ± 5128.54 |
0.006** |
Healthy control < Stomatitis and OSCC, Stomatitis< OSCC |
Gram (-) |
1959265.36 ± 1372737.86 |
16984317.46 ± 14157382.83 |
26708490.05 ± 22693303.84 |
0.128 |
|
Gram (+) |
92020.78 ± 82510.78 |
155568.13 ± 131036.11 |
13364773.45 ± 14988291.76 |
0.093 |
|
DNA copies of 15 microbes |
2051750.43 ± 1394889.68 |
17141746.89 ± 14070899.96 |
40082611.47 ± 37609107.97 |
0.119 |
|
Total bacteria |
246015329.80 ± 250216570.66 |
671981670.25 ± 645482366.81 |
827473263.93 ± 781237168.13 |
0.406 |
|
Shannon’s diversity index |
1.17 ± 0.35 |
1.42 ± 0.42 |
1.85 ± 1.26 |
0.502 |
|
Table 3.
Comparison of the prevalence of 14 oral bacterial and 1 fungal species.
Table 3.
Comparison of the prevalence of 14 oral bacterial and 1 fungal species.
Microbial parameters |
Healthy control mean ± SD |
Stomatitis mean ± SD |
OSCC mean ± SD |
p-value |
post-hoc |
Gram (−) |
Aa |
0 ± 0 |
0 ± 0 |
0 ± 0 |
NA |
|
Pi |
0.47 ± 0.93 |
1.37 ± 1.86 |
0 ± 0 |
0.311 |
|
Pn |
19.88 ± 16.99 |
11.09 ± 6.83 |
16.91 ± 7.35 |
0.561 |
|
Ec |
9.65 ± 6.59 |
2.78 ± 1.55 |
8.64 ± 7.23 |
0.239 |
|
Cr |
1.37 ± 2.07 |
1.53 ± 1.94 |
4.17 ± 5.11 |
0.451 |
|
Fn |
60.47 ± 21.04 |
30.82 ± 23.06 |
7.75 ± 3.62 |
0.008** |
Healthy control > Stomatitis > OSCC |
Pg |
0.17 ± 0.17 |
43.45 ± 24.93 |
16.39 ± 23.18 |
0.035* |
Healthy control < Stomatitis, OSCC < Stomatitis |
Td |
1.05 ± 1.28 |
1.32 ± 2.33 |
20.96 ± 27.89 |
0.192 |
|
Tf |
1.98 ± 1.72 |
4.74 ± 2.31 |
5.28 ± 5.15 |
0.379 |
|
Gram (+) |
Lc |
0 ± 0 |
0.05 ± 0.09 |
0.14 ± 0.15 |
0.195 |
|
Sm |
0.22 ± 0.27 |
0.58 ± 1.15 |
0.77± 1.52 |
0.783 |
|
Ss |
0 ± 0 |
0.02 ± 0.04 |
0 ± 0 |
0.405 |
|
Pm |
4.68 ± 4.26 |
1.67 ± 2.04 |
18.85 ± 20.05 |
0.148 |
|
En |
0.01 ± 0.01 |
0.57 ± 1.08 |
0.07 ± 0.05 |
0.415 |
|
Fungus |
Ca |
0.04 ± 0.07 |
0.02 ± 0.02 |
0.07 ± 0.10 |
0.658 |
|
Table 4.
Correlation between DNA copies of oral microbes.
Table 4.
Correlation between DNA copies of oral microbes.
Correlation coefficient |
Gram (−) |
Gram (+) |
Fungus |
Pn |
Ec |
Cr |
Fn |
Pg |
Td |
Tf |
Lc |
Sm |
Ss |
Pm |
En |
Ca |
Gram (−) |
Pi |
-0.193 |
-0.160 |
-0.215 |
-0.129 |
-0.006 |
-0.176 |
-0.075 |
-0.233 |
-0.115 |
0.045 |
-0.163 |
-0.151 |
-0.112 |
Pn |
|
0.980 |
0.780 |
0.612 |
0.097 |
0.708 |
0.498 |
0.849 |
-0.130 |
-0.165 |
0.974 |
0.761 |
0.878 |
Ec |
|
|
0.790 |
0.465 |
0.087 |
0.752 |
0.522 |
0.884 |
-0.091 |
-0.158 |
0.998 |
0.755 |
0.909 |
Cr |
|
|
|
0.410 |
0.657 |
0.515 |
0.788 |
0.653 |
-0.175 |
-0.208 |
0.761 |
0.497 |
0.790 |
Fn |
|
|
|
|
0.183 |
0.198 |
0.290 |
0.243 |
-0.264 |
-0.220 |
0.434 |
0.372 |
0.277 |
Pg |
|
|
|
|
|
-0.068 |
0.698 |
-0.058 |
-0.167 |
-0.086 |
0.036 |
-0.051 |
0.120 |
Td |
|
|
|
|
|
|
0.634 |
0.890 |
0.575 |
-0.180 |
0.742 |
0.572 |
0.724 |
Tf |
|
|
|
|
|
|
|
0.524 |
0.337 |
-0.220 |
0.472 |
0.296 |
0.522 |
Gram (+) |
Lc |
|
|
|
|
|
|
|
|
0.265 |
-0.043 |
0.889 |
0.751 |
0.931 |
Sm |
|
|
|
|
|
|
|
|
|
0.093 |
-0.104 |
0.049 |
-0.038 |
Ss |
|
|
|
|
|
|
|
|
|
|
-0.134 |
0.500 |
-0.138 |
Pm |
|
|
|
|
|
|
|
|
|
|
|
0.766 |
0.913 |
En |
|
|
|
|
|
|
|
|
|
|
|
|
0.674 |
|
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