Tongue-coating microbiome as a predictor of solid tumors: an updated scoping review of clinical studies

Abstract

This study explores the potential of tongue coating microbiota as a non-invasive biomarker for cancer and precancerous lesions by integrating insights from multi-omics technologies and Traditional Chinese Medicine (TCM) tongue diagnosis. By bridging modern molecular research with TCM diagnostic principles, this study systematically reviewed the relationship between tongue microbiota and oncological conditions, identifying 18 eligible studies through searches in PubMed, Embase, and Web of Science. The analysis reveals significant differences in microbial diversity, abundance, metabolic pathways, and functional characteristics, which enable the partial differentiation of cancer patients from healthy individuals. However, existing research remains constrained by limited sample sizes, inconsistent analytical approaches, and a lack of integrated multi-dimensional datasets. This review highlights the promising diagnostic potential of the tongue coating microbiota in cancer detection, while suggesting that future studies should focus on standardizing methodologies and employing integrated multi-omics approaches to elucidate underlying mechanisms and advance clinical applications.

1. INTRODUCTION

In Traditional Chinese Medicine (TCM), tongue diagnosis has a history spanning thousands of years and remains a cornerstone of clinical practice. TCM practitioners analyze the color, shape, moisture, and coating of the tongue to infer internal health conditions, particularly those related to the spleen, stomach, and other organ systems. In TCM, tongue coatings are diagnostically classified into distinct patterns including thin-white, thin-yellow, white-greasy, and yellow-greasy variants, each empirically correlated with specific clinical syndromes. Contemporary microbiological studies reveal that these visual patterns correspond to characteristic alterations in the tongue coating microbiota: The thin-yellow coating pattern, demonstrates significantly elevated abundances of Fusobacterium periodonticum and Neisseria mucosa coupled with peak α-diversity values, suggesting heightened microbial metabolic activity. Conversely, thin-white coatings display reduced α-diversity yet maintain intricate interspecies networks.¹ Notably, in primary liver cancer (PLC) patients, thick/greasy coatings exhibit marked enrichment of F. periodonticum and Actinomyces species, providing empirical evidence linking classical TCM diagnostic criteria with modern microbial ecology principles.² The tongue is a vital anatomical structure in the oral cavity due to its distinct position and function. The tongue coating is a visible layer attached to the lingual papillae, composed of desquamated epithelial cells, blood metabolites, bacteria, fungi, and saliva.³ Compared to other regions of the cavity, the tongue coating, owing to its distinctive surface structures, provides a favorable environment for microbial colonization and growth, with the highest microbial density found on the dorsal surface of the tongue.⁴ Studies have shown that the microbial density on the tongue dorsum significantly exceeds that of other oral regions, with approximately 100 bacteria adhering to each epithelial cell, forming an independent and stable microbial ecosystem.⁵ However, this stability is subject to dynamic changes influenced by factors such as age, medication, oral hygiene, and systemic diseases.

Alterations in the tongue coating microbiota are closely associated with the development of various diseases, including chronic insomnia,⁶ rheumatoid arthritis,⁷ and chronic hepatitis B.⁸ In recent years, preliminary studies have indicated significant changes in the diversity and abundance of tongue coating microbiota in cancers such as gastric cancer (GC),^9-13 PLC,² and colorectal cancer (CRC),^14-16 suggesting its potential as a biomarker for cancer diagnosis.¹⁷ Landmark studies have progressively demonstrated the diagnostic potential of tongue coating microbiota in oncology. The field achieved a significant breakthrough when Chen et al ⁹ conducted the first large-scale deep metaproteomic analysis of tongue coatings, identifying 50 microbial-derived protein biomarkers that collectively yielded an area under the curve of 0.91 for GC screening in their multicenter cohort. Parallel advances have been reported for PLC, with Zhang et al's 2022 study revealing that a 15-genus microbial signature in tongue coatings exhibited high diagnostic sensitivity.² Beyond traditional high-throughput sequencing technologies (e.g., 16S rRNA sequencing and metagenomic sequencing), integrative studies incorporating metabolomics, proteomics, and transcriptomics have offered multidimensional insights into the connection between tongue coating microbiota and cancer. For example, metabolomics has revealed changes in microbial metabolites and their possible effects on the tumor metabolic environment, proteomics has clarified the interactions between microbial and host proteins, and transcriptomics has examined the microbiota's functional potential at the gene expression leve.¹⁹

The tongue coating microbiota exhibits relative stability but can undergo dynamic changes under the influence of systemic or local diseases. In TCM, the tongue coating has long been regarded as a vital diagnostic indicator, reflecting the health status of internal organs and the balance of Yin-Yang and Qi-blood. Modern research corroborates these traditional observations, highlighting the tongue coating microbiota's potential as a non-invasive diagnostic tool. It has garnered increasing attention for its unique advantages in cancer diagnosis and its associations with other systemic diseases. However, the specific mechanisms underlying its role as a cancer biomarker remain unclear, and research methodologies have yet to be fully standardized. Furthermore, current studies integrating tongue coating microbiomics with metabolomics, proteomics, and transcriptomics are still in their infancy, lacking comprehensive and multi-dimensional analyses. The aim of this scoping review is to systematically identify and summarize observational studies that explore the potential of tongue coating microbiota as a biomarker for cancer and precancerous conditions, along with its potential for multi-omics applications.

2. METHODS

This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines¹⁹ and adopts the methodological framework proposed by Arksey and O'Malley.²⁰ The protocol of this scoping review has not been registered before the study.

2.1. Research question

This review aims to systematically summarize clinical studies exploring the relationship between tongue coating microbiota and precancerous or cancerous lesions, emphasizing its potential to differentiate such patients from healthy individuals based on bacterial diversity, abundance, and functional characteristics. The review adopts the PECOS framework, covering the following elements: Population (adult population), Exposure (patients diagnosed with precancerous or cancerous lesions), Comparison (healthy subjects), and Outcomes (diversity, bacterial abundance, metabolic pathways, and functional characteristics of the tongue coating microbiota). This review focuses on observational studies, such as cohort, case-control, and cross-sectional studies.

2.2. Study selection

Observational studies published in English were included if they utilized next-generation sequencing technologies (e.g., 16S rRNA, metagenomics, metatranscriptomics) or mass spectrometry techniques (e.g., metaproteomics, untargeted lipidomics) to compare the microbiota and functional characteristics of the dorsal tongue surface between patients with precancerous lesions or cancers and healthy controls (HCs), and reported outcomes such as microbiota diversity (primary outcome), bacterial abundance (secondary outcome), or metabolomic and functional characteristics( third outcome). Excluded studies were reviews, case reports, in vivo or in vitro studies, expert opinions, conference abstracts, studies without tongue-coating-specific microbiota analyses, those focusing on other oral sites (e.g., plaque, saliva) rather than the dorsal tongue, or studies primarily involving children or tongue-specific lesions unrelated to cancer or precancerous differentiation.

2.3. Data sources and search approach

As of November 2024, a search was performed in 3 databases: PubMed, Embase, and Web of Science (WoS). Additional studies were located through manual searches. The search combined keywords and index terms such as: (tongue microbiome, tongue biofilm, tongue dorsum, lingual surface, tongue-coating microbiome, tongue imaging, tongue features) AND (cancer, precancer, carcinoma, disease, disorder, lesion) AND (microbial diversity, bacterial community, bacterial composition, microbial detection, bacterial identification, metabolomics, proteomics, lipidomics, 16S rRNA, 18S rRNA, Next Generation Sequencing, NGS, metagenomic sequencing, metaproteomics, metatranscriptomics).

2.4. Study selection process

Retrieved articles were exported to EndNote X9 (Clarivate Analytics, Philadelphia, PA, USA), and duplicates were removed. The screening process allowed independent work by each author. In the first stage, titles and abstracts were assessed to identify potentially relevant studies, excluding those that did not meet the inclusion criteria. The second stage involved assessing the full-text articles for eligibility. Any disagreements regarding study selection were resolved through discussion, with reasons for exclusion documented.

2.5. Data charting

Two researchers collaboratively created and refined the data charting process. Data were independently extracted, including the following items: study ID (authors and publication year), study design, country, population details (sample size and gender distribution), cancer type, analytical methods, validation techniques, and key outcomes.

3. RESULTS

3.1. Study selection and features

A total of 928 studies were identified from the literature search (PubMed: 318, Embase: 39, WoS: 571). After removing duplicates (n = 282), 646 articles remained for further screening. After reviewing titles and abstracts, 608 articles were excluded. Full-text reviews were conducted for the remaining 38 studies, of which 18 studies met the inclusion criteria (Figure 1).

Figure 1. Flowchart of information progression in a scoping review.

3.2. Primary outcome: bacterial diversity and richness

The majority of studies emphasized differences in bacterial communities between precancerous or cancer cases and control groups. In 4 studies,^12,13,21,22 species richness was significantly lower in cases than in normal controls. Conversely, 7 studies ^{11,16,18,23-26} showed higher species richness in cases compared to healthy groups.

Alpha diversity indices such as Shannon, Simpson, inverse Simpson (invSimpson), observed OTUs (Obs), and Chao 1 were significantly higher in case groups than in controls in 7 studies.^10,18,22-26 In contrast, 5 studies,^{11,12,16,21,27} reported no statistical differences, while 2 studies^11,13 reported lower bacterial diversity indices in GC patients compared to healthy individuals.

3.3. Secondary outcome: bacterial abundance

3.3.1. Gastric cancer and precancerous lesions

An analysis of 18 studies indicated that 8 focused on precancerous or cancerous lesions of GC, while 6 studies highlighted notable distinctions in tongue-coating microbiota between GC patients and HCs. Specifically, the abundance of Proteobacteria was significantly lower in GC patients compared to HCs, with reduced levels of Fusobacterium, Neisseria, Haemophilus, and Porphyromonas genera also observed.¹³ Elevated levels of Streptococcus were associated with a higher risk of GC, whereas reduced levels of Neisseria, Prevotella, and Porphyromonas were linked to a lower risk of GC.¹² Additionally, GC patients exhibited a significantly higher Firmicutes/Bacteroidetes ratio than HCs. Alterations in fungal composition were also notable, with increased Basidiomycota and decreased Ascomycota abundances in GC patients.^10,13 The ZJC cohort study demonstrated that Solobacterium moorei was associated with a higher risk of GC, while Acetobacter and Capnocytophaga were linked to a reduced risk.⁹ Similarly, a multicenter cohort identified Neisseria brasiliensis as a risk factor for GC, whereas Jeotgalibaca porci was associated with a lower risk.⁹ Further validation through microbial 2b-RAD sequencing revealed that Bacteroidetes were significantly enriched in the saliva and tongue coatings of GC patients, while Actinobacteria were less abundant compared to controls.²³

In gastric inflammation with a precancerous cascade, no significant differences were observed in the phyla Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria between patients and HCs. However, the Fusobacteria phylum was significantly increased in patients. Further analysis revealed that 21 bacterial species exhibited significant abundance differences between the 2 groups. For instance, 11 species, including Veillonella parvula and Mitsuokella multacida, were significantly decreased in patients, whereas 10 species, such as Chlamydia trachomatis and Campylobacter rectus, were significantly increased.²² Additionally, a microbiological analysis demonstrated that the relative abundances of 5 genera, including Alloprevotella, Solobacterium, Rothia, Eikenella, and Aggregatibacter, were significantly elevated in the tongue coating of patients with a precancerous cascade, suggesting that microbial diversity may play a critical role in disease progression.¹⁸

3.3.2. Colorectal cancer

The tongue coating microbiota of CRC patients exhibits significant differences compared to that of HCs. In 16S rRNA gene sequencing studies, the abundance of Streptococcus was significantly higher in the CRC group, while Haemophilus was notably lower compared to the HCs. Additionally, in CRC patients with thick tongue coating, the abundance of Kingella and Shuttleworthia increased, whereas multiple taxa, including Acinetobacter, showed a significant decrease. In contrast, the thin tongue coating group demonstrated elevated levels of Enhydrobacter, Janthinobacterium, and Rahnella.¹⁶ Further findings based on metagenomic shotgun sequencing revealed significant alterations in microbial abundance across various taxonomic levels. Specifically, Veillonella atypica, Megasphaera micronuciformis, and Veillonella parvula were enriched in the CRC group, whereas Aspergillus and Rothia were more abundant in the HCs.¹⁵

3.3.3. Esophageal precancerous lesions and esophageal squamous cell carcinoma

Microbiome analysis in esophageal squamous cell carcinoma (ESCC) patients identified notable compositional differences at various taxonomic levels compared to the HCs. At the phylum level, ESCC patients showed a marked decrease in Proteobacteria abundance, while Fusobacteria was markedly increased. At the family level, Neisseriaceae and Pasteurellaceae exhibited significantly lower abundances in the ESCC group. Further genus-level analysis indicated that Neisseria and Aggregatibacter were significantly reduced in ESCC patients, whereas the abundance of Leptotrichia was notably elevated.²⁶

In addition, the study found that the development of esophageal precancerous lesions (EPL) significantly altered the composition of the tongue coating microbiota, leading to reduced symbiotic complexity, which may be closely related to cancer-associated oral intake habits. Bile acids were identified as key mediators of changes in the tongue coating microbiota. Although no significant differences were observed at the phylum level between cases and controls, genus-level analysis identified 9 significantly altered genera (P < 0.05). Compared to the control group, the relative abundances of Eubacterium yurii group, Capnocytophaga, Comamonas, Defluviitaleaceae UCG-011, Odoribacter, and Peptostreptococcus were significantly increased in the EPL group, while Atopobium, Hydrobacter, and Taonella were significantly decreased.²⁷

3.3.4. Primary liver cancer

In the microbiota of PLC patients, 13 significantly enriched families were identified, including Fusobacteriaceae, Filifactoraceae, Actinomycetaceae, and Lachnospiraceae. At the genus level, Haemophilus, Streptococcus, and Pseudomonas were highly enriched in the HCs, whereas Fusobacterium, Leptotrichia, Actinomyces, and Campylobacter were significantly enriched in the PLC group.²⁵ Further analysis classified the PLC group into a thick/greasy tongue coating group and a non-thick/non-greasy tongue coating group. At the phylum level, patients with thick or greasy tongue coatings exhibited slightly higher abundances of Bacteroidetes, Fusobacteria, and Actinobacteria, alongside reduced abundances of Firmicutes and Proteobacteria. Conversely, in patients with non-thick or non-greasy tongue coatings, Firmicutes and Actinobacteria were slightly more abundant, while Proteobacteria and Fusobacteria were lower. At the genus level, the PLC group showed slightly higher abundances of Prevotella_7, Streptococcus, Veillonella, and Actinomyces, while Neisseria and Fusobacterium were slightly reduced². This finding contrasts with previous studies that reported Fusobacterium as the predominant genus on the tongue coating of PLC patients, suggesting potential variations due to geographic, sample, or methodological differences.²⁵

3.3.5. Pancreatic head cancer

Among the 18 studies reviewed, 1 study specifically focused on the microbial changes in the tongue coating of pancreatic head cancer patients. At the phylum level, an increase in the relative abundance of Firmicutes, Fusobacteria, and Actinobacteria was observed in patients, while Bacteroidetes levels were reduced in comparison to HCs. At the family level, 14 bacterial families, including Lachnospiraceae, Fusobacteriaceae, and Actinomycetaceae, showed increased relative abundance in patients. At the genus level, Porphyromonas, Haemophilus, and Paraprevotella were more abundant in HCs, while Lachnospira, Fusobacterium, Actinomyces, and others were more prevalent in pancreatic head cancer patients.²⁴

3.3.6. Oral squamous cell carcinoma

An investigation utilizing laser microdissection combined with high-depth transcriptome sequencing comprehensively characterized the microbiome in oral squamous cell carcinoma (OSCC) tissues, revealing low-abundance but unique and transcriptionally active multi-kingdom microbial features. Compared to HCs, OSCC tissues were specifically enriched with Cutibacterium acnes and its associated enzyme HL, Malassezia restricta, human herpesvirus 6B, Nupapillomavirus, and bacteriophages. These microorganisms potentially interact with the host transcriptome through proliferation-related pathways.²⁸

3.3.7. Osteosarcoma

The tongue coating microbiota of osteosarcoma patients exhibited distinct compositional changes. At the phylum level, Actinobacteria and Proteobacteria showed notably reduced relative abundance compared to HCs, whereas Bacteroidetes and Campylobacterota were significantly increased. The relative abundance of Firmicutes showed no significant variation between the 2 groups. Within Bacteroidetes, Alloprevotella, Prevotella, and Campylobacter exhibited the highest relative abundance in osteosarcoma patients, with unclassified Crescentiibacteria following in relative abundance. Additionally, LDA analysis identified Prevotella, Alloprevotella, and Campylobacter as dominant genera in the tongue coating microbiota of osteosarcoma patients. Further investigation into the association between tongue coating microbiota and clinical indicators of osteosarcoma revealed a positive correlation between the abundance of Alloprevotella and alkaline phosphatase levels, suggesting that Alloprevotella may contribute to osteosarcoma progression through its potential role in bone metabolism.²¹

3.4. Third result: metabolic pathways and functional characteristics

Metabolomic analyses have highlighted significant metabolic abnormalities in gastrointestinal tumor patients. In patients with precancerous gastric lesions, metabolites such as sphingosine-1-phosphate, creatine, prostaglandin D2, leukotriene D4, and 5,6-dihydroxyindole were markedly upregulated.¹⁸ Additionally, 11 metabolites, mainly lysophospholipids, were found to be potential biomarkers for GC.¹⁰ Additionally, a pressure cycling technology-data independent acquisition mass spectrometry analysis of tongue coating samples from GC patients identified 1432 human proteins and 13 780 microbial proteins. The study showed a marked downregulation of keratin 2, keratin 9, and dermcidin, key keratins essential for tongue coating structural integrity. Their decreased expression indicates impaired mucosal defense functions.⁹ A non-targeted lipidomics study further revealed dysregulated lipid metabolism in tongue coating samples from CRC patients, characterized by a rise in long-chain unsaturated triacylglycerols and a reduction in monounsaturated fatty acid-phosphatidylethanolamine (Figure 2).¹⁴

Figure 2. Tongue coating microbiome and metabolic dysregulation in gastric and colorectal tumor progression.

DCD: dermcidin; KRT2: keratin 2; KRT9: keratin 9; IFN-γ: interferon-γ; IL-1α: interleukin-1α; IL-5: interleukin-5; IL-10: interleukin-10; IL-12: interleukin-12; IL-17α: interleukin-17α; IL-23P40: interleukin-23 subunit p40; TNF-β: tumor necrosis factor-β; VEGF: vascular endothelial growth factor. Red arrows denote disease progression, and black arrows indicate the release of cytokine or lipid release.

4. DISCUSSION

This review included 18 observational studies exploring the relationship between tongue coating microbiota and precancerous or cancerous conditions, highlighting its potential as a non-invasive biomarker. However, significant heterogeneity exists among the included studies, including variations in sample size, sample collection methods, detection techniques, and data interpretation. These methodological inconsistencies present major challenges, limiting the comparability and reproducibility of findings.

To advance this field, it is crucial to establish standardized protocols for tongue coating sample collection, sequencing methodologies, and data analysis. Additionally, leveraging advanced detection technologies and integrating multi-omics approaches will enhance the accuracy and depth of microbiota profiling. Further exploration of the intricate interactions between the tongue and gut microbiota may provide deeper mechanistic insights into cancer pathogenesis. Addressing these challenges will be key to translating tongue coating microbiota research into clinical applications as a reliable cancer biomarker.

4.1. Standardization of tongue coating collection

The standardization of tongue coating collection methods is crucial for research on tongue coating microbiota. Variations in sampling tools, preservation solutions, and handling methods can significantly affect the comparability of results. As early as 1966, Gordon and Gibbons analyzed the bacterial composition of the tongue surface and identified Streptococcus and Veillonella as the dominant genera.²⁹ Recent studies have further revealed the complexity of tongue coating microbiota. For instance, tongue coating microbiota may be linked to oral acetaldehyde production and exhibit significant differences across stimulated and unstimulated saliva, tongue surface, and mouth rinse samples.^30,31 Additionally, the microbiota of the tongue coating shows diurnal abundance fluctuations and correlations with gut microbiota, emphasizing the need for consistent sampling to ensure research accuracy.³² To enhance the standardization of tongue coating sampling, Zeng et al ³³ experimentally validated optimal sampling conditions. They found that a combination of sterile oral swab B, 30 scrapes, and commercial preservation solution could stabilize samples at room temperature for up to 7 d while maintaining DNA quality suitable for 16S rRNA gene sequencing analysis. This study provides practical guidelines for standardizing tongue coating sampling and lays a foundation for further research into the disease associations of tongue coating microbiota.

4.2. Advances in tongue coating microecology detection technologies

The study of the tongue coating microbiome has undergone significant progress, transitioning from traditional bacterial culturing and microscopy to modern molecular biology techniques. Although traditional methods, such as bacterial culturing and smear microscopy, are effective in certain specific cases, they have evident limitations when analyzing large-scale samples and revealing the diversity of microbial communities.^34,35 In recent years, non-cultivation-based techniques, such as 16S ribosomal RNA-denaturing gradient gel electrophoresis,³⁶ restriction fragment length polymorphism-polymerase chain reaction,³⁷ and random amplified polymorphic DNA-polymerase chain reaction,³⁸ have been increasingly applied to the composition analysis and microbial community structure studies of the tongue coating microbiota, providing a foundation for constructing microbial networks.³⁹

In microbial abundance assessment, cell count methods (e.g., direct counting and viable counting) and biomass measurement techniques (e.g., turbidity, wet weight, and dry weight) are effective in evaluating microbial activity and abundance.⁴⁰ However, these traditional techniques are limited by issues such as inconsistent sample collection and variations in researcher techniques, which can affect the reliability and comparability of results.⁴¹ With the rapid development of genomics and high-throughput sequencing technologies, research on the tongue coating microbiota has entered a new phase. 16S rRNA gene sequencing has become the gold standard for analyzing microbial community structure. Using platforms such as Illumina sequencing, researchers can conduct comprehensive classification and quantitative analysis of the microbial communities in tongue coating samples.⁴²

Although high-throughput sequencing technology has greatly expanded the breadth and depth of tongue coating microbiota research, it still has some limitations. First, data processing is complex, especially when microbial community diversity is high, requiring precise bioinformatics tools for data interpretation. Second, while 16S rRNA gene sequencing can capture the majority of microbial information, it may not cover certain microbial species, particularly uncultured microorganisms. Therefore, integrating metagenomics technology for a comprehensive analysis of the tongue coating microbiota is crucial.

4.3. The link between tongue coating microbiota and gut microbiota

The tongue coating microbiota and gut microbiota are closely connected in physiological function and metabolic mechanisms, yet they remain independent of each other.⁴³ Oral microorganisms may travel to the gut, possibly due to factors like gastrointestinal dysfunction, reduced gastric acid secretion, and decreased bile acid production.^44,45 This migration can influence the composition of gut microbiota and contribute to the development and progression of CRC.^46-48 Emerging evidence suggests oral-to-gut microbial migration, particularly of Fusobacterium nucleatum, occurs through 3 mechanisms: (a) epithelial barrier disruption via inflammatory cytokines, (b) Fap2-mediated hematogenous spread-where the bacterial lectin binds tumor-specific Gal-GalNAc glycans enabling bloodstream dissemination and tumor colonization, and (c) direct tissue invasion via proteolytic enzymes like Fusolisin. Crucially, Fap2-dependent colonization suppresses tumor-infiltrating T cells and promotes metastasis, explaining the poorer prognosis associated with oral Fusobacterium in colorectal/breast cancers. This mechanistic cascade highlights potential therapeutic targets at the oral-gut-tumor axis.^49,50 Furthermore, changes in the abundance of tongue coating microbiota are align with fluctuations in gut microbiota during disease states, with both exhibiting significant alterations. For instance, in patients with autoimmune liver disease, Veillonella spp. abundance is positively correlated between the oral cavity and gut.⁵¹

The tongue coating microbiota and gut microbiota jointly regulate various functions of the digestive system through reflex mechanisms and may influence energy metabolism via interactions with taste receptors. This mechanism is closely related to the "oral-gut axis" effect.⁵² However, there are differences in their metabolic functions.⁴³ Gut microbiota primarily regulates energy metabolism, bile acid metabolism, and the trimethylamine N-oxide pathway through the fermentation of short-chain fatty acids and branched-chain fatty acids,⁵³ while the tongue coating microbiota mainly relies on anaerobic respiration, with its metabolic functions yet to be fully elucidated.⁴³ Future research should explore the metabolic mechanisms of the tongue coating microbiota and its interactions with the gut microbiota.

In conclusion, the tongue coating microbiota has emerged as a promising predictive indicator for cancer and precancerous lesions. In TCM, tongue coating is regarded as a vital diagnostic marker, reflecting internal organ function and the balance of Yin-Yang and Qi-blood. This traditional perspective resonates with modern biomedical research, where advances in high-throughput sequencing technologies have enabled in-depth exploration of the microbial ecology of the tongue. However, to fully establish the clinical utility of tongue coating microbiota as reliable and non-invasive biomarkers for cancer diagnosis and monitoring, further comprehensive and mechanistic studies are essential.