Betel nut chewing is a major etiological factor for oral squamous cell carcinoma (OSCC), yet its mechanistic underpinnings remain poorly defined. Here, we performed single-cell RNA sequencing and spatial transcriptomics from six OSCC patients to comprehensively dissect the tumor microenvironment (TME) dynamics and cellular heterogeneity associated with betel nut-induced oral mucosal carcinogenesis. We identify a fibrotic, immunosuppressive TME characterized by expanded cancer-associated fibroblasts (CAFs) and B/plasma cells, alongside depletion of cytotoxic T/NK cells and macrophages. CAFs, particularly antigen-presenting CAFs, are spatially enriched at the invasive front and drive epithelial plasticity and malignant transformation. Notably, we uncover a malignant epithelial subpopulation, LAMC2+ EpiC6, enriched for epithelial–mesenchymal transition (EMT) programs, angiogenesis, and metastasis-associated pathways, which engaged in extensive crosstalk with CAFs and other nonmalignant components. Clinically, LAMC2 expression was significantly elevated in OSCC tissues from betel nut chewers, and arecoline treatment of OSCC cell lines induced LAMC2 upregulation, EMT, and enhanced migratory and invasive capacities in vitro. Collectively, our study delineates a malignant trajectory of epithelial cell progression, highlighting LAMC2+ EpiC6 as a key aggressive subpopulation orchestrated by EMT-related transcriptional regulators and extracellular matrix remodeling. These findings offer mechanistic insights and identify potential therapeutic targets to disrupt tumor–stroma interplay and mitigate disease progression.
| [1] |
H. Rumgay, S. T. Nethan, R. Shah, et al., “Global Burden of Oral Cancer in 2022 Attributable to Smokeless Tobacco and Areca Nut Consumption: A Population Attributable Fraction Analysis,” The Lancet Oncology 25, no. 11 (2024): 1413–1423.
|
| [2] |
S. Warnakulasuriya and T. H. H. Chen, “Areca Nut and Oral Cancer: Evidence From Studies Conducted in Humans,” Journal of Dental Research 101, no. 10 (2022): 1139–1146.
|
| [3] |
K. Krishnakumar, R. Ramadoss, R. Krishnan, and H. Sukhija, “In Vitro Quantification of Collagen and Snail1 Gene Expression in Experimentally Induced Fibrosis by Arecoline and Commercial Smokeless Tobacco Products,” Asian Pacific Journal of Cancer Prevention 21, no. 4 (2020): 1143–1148.
|
| [4] |
Y. W. Shen, Y. H. Shih, L. J. Fuh, and T. M. Shieh, “Oral Submucous Fibrosis: A Review on Biomarkers, Pathogenic Mechanisms, and Treatments,” International Journal of Molecular Sciences 21, no. 19 (2020): 7231.
|
| [5] |
Y. W. Liao, C. C. Yu, C. W. Hsieh, S. C. Chao, and P. L. Hsieh, “Aberrantly Downregulated FENDRR by Arecoline Elevates ROS and Myofibroblast Activation via Mitigating the miR-214/MFN2 Axis,” International Journal of Biological Macromolecules 264, no. Pt 1 (2024): 130504.
|
| [6] |
X. Hu, W. Wang, Y. Hu, et al., “Overexpression of DEC1 in the Epithelium of OSF Promotes Mesenchymal Transition via Activating FAK/Akt Signal Axis,” Journal of Oral Pathology & Medicine 51, no. 9 (2022): 780–790.
|
| [7] |
A. M. Ko, H. P. Tu, and Y. C. Ko, “Systematic Review of Roles of Arecoline and Arecoline N-Oxide in Oral Cancer and Strategies to Block Carcinogenesis,” Cells 12, no. 8 (2023): 1208.
|
| [8] |
M. C. Chang, Y. J. Chen, H. H. Chang, et al., “Areca Nut Components Affect COX-2, Cyclin B1/cdc25C and Keratin Expression, PGE2 Production in Keratinocyte Is Related to Reactive Oxygen Species, CYP1A1, Src, EGFR and Ras Signaling,” PLoS ONE 9, no. 7 (2014): e101959.
|
| [9] |
T. M. Kuo, S. Y. Luo, S. L. Chiang, et al., “Fibrotic Effects of Arecoline N-Oxide in Oral Potentially Malignant Disorders,” Journal of Agricultural and Food Chemistry 63, no. 24 (2015): 5787–5794.
|
| [10] |
W. Yang, S. Zhang, T. Li, Z. Zhou, and J. Pan, “Single-cell Analysis Reveals That Cancer-associated Fibroblasts Stimulate Oral Squamous Cell Carcinoma Invasion via the TGF-beta/Smad Pathway,” Acta Biochimica et Biophysica Sinica (Shanghai) 55, no. 2 (2022): 262–273.
|
| [11] |
C. Ma, C. Yang, A. Peng, et al., “Pan-cancer Spatially Resolved Single-cell Analysis Reveals the Crosstalk Between Cancer-associated Fibroblasts and Tumor Microenvironment,” Molecular Cancer 22, no. 1 (2023): 170.
|
| [12] |
Y. Zhang, J. Zhang, S. Zhao, et al., “Single-cell RNA Sequencing Highlights the Immunosuppression of IDO1(+) Macrophages in the Malignant Transformation of Oral Leukoplakia,” Theranostics 14, no. 12 (2024): 4787–4805.
|
| [13] |
S. Hu, H. Lu, W. Xie, et al., “TDO2+ myofibroblasts Mediate Immune Suppression in Malignant Transformation of Squamous Cell Carcinoma,” Journal of Clinical Investigation 132, no. 19 (2022): e157649.
|
| [14] |
L. Y. Huang, Y. P. Hsieh, Y. Y. Wang, et al., “Single-Cell Analysis of Different Stages of Oral Cancer Carcinogenesis in a Mouse Model,” International Journal of Molecular Sciences 21, no. 21 (2020): 8171.
|
| [15] |
S. Kurkalang, S. Roy, A. Acharya, et al., “Single-cell Transcriptomic Analysis of Gingivo-buccal Oral Cancer Reveals Two Dominant Cellular Programs,” Cancer Science 114, no. 12 (2023): 4732–4746.
|
| [16] |
C. Trapnell, D. Cacchiarelli, J. Grimsby, et al., “The Dynamics and Regulators of Cell Fate Decisions Are Revealed by Pseudotemporal Ordering of Single Cells,” Nature Biotechnology 32, no. 4 (2014): 381–386.
|
| [17] |
X. Qiu, Q. Mao, Y. Tang, et al., “Reversed Graph Embedding Resolves Complex Single-cell Trajectories,” Nature Methods 14, no. 10 (2017): 979–982.
|
| [18] |
Z. Tang, B. Kang, C. Li, T. Chen, and Z. Zhang, “GEPIA2: An Enhanced Web Server for Large-scale Expression Profiling and Interactive Analysis,” Nucleic Acids Research 47, no. W1 (2019): W556–W560.
|
| [19] |
S. Jin, M. V. Plikus, and Q. Nie, “CellChat for Systematic Analysis of Cell-cell Communication From Single-cell Transcriptomics,” Nature Protocols 20, no. 1 (2025): 180–219.
|
| [20] |
B. J. Boucher and N. Mannan, “Metabolic Effects of the Consumption of Areca Catechu,” Addiction Biology 7, no. 1 (2002): 103–110.
|
| [21] |
P. C. Gupta and S. Warnakulasuriya, “Global Epidemiology of Areca Nut Usage,” Addiction Biology 7, no. 1 (2002): 77–83.
|
| [22] |
N. C. Huynh, T. T. Huang, C. T. Nguyen, and F. K. Lin, “Comprehensive Integrated Single-Cell Whole Transcriptome Analysis Revealed the p-EMT Tumor Cells-CAFs Communication in Oral Squamous Cell Carcinoma,” International Journal of Molecular Sciences 23, no. 12 (2022): 6470.
|
| [23] |
S. Affo, A. Nair, F. Brundu, et al., “Promotion of Cholangiocarcinoma Growth by Diverse Cancer-associated Fibroblast Subpopulations,” Cancer Cell 39, no. 6 (2021): 883.
|
| [24] |
G. Biffi, T. E. Oni, B. Spielman, et al., “IL1-Induced JAK/STAT Signaling Is Antagonized by TGFbeta to Shape CAF Heterogeneity in Pancreatic Ductal Adenocarcinoma,” Cancer Discovery 9, no. 2 (2019): 282–301.
|
| [25] |
G. Biffi and D. A. Tuveson, “Diversity and Biology of Cancer-Associated Fibroblasts,” Physiological Reviews 101, no. 1 (2021): 147–176.
|
| [26] |
W. H. Fridman, M. Meylan, F. Petitprez, C. M. Sun, and A. Italiano, “Sautes-Fridman C. B Cells and Tertiary Lymphoid Structures as Determinants of Tumour Immune Contexture and Clinical Outcome,” Nature Reviews Clinical Oncology 19, no. 7 (2022): 441–457.
|
| [27] |
M. Meylan, F. Petitprez, E. Becht, et al., “Tertiary Lymphoid Structures Generate and Propagate Anti-tumor Antibody-producing Plasma Cells in Renal Cell Cancer,” Immunity 55, no. 3 (2022): 527–541.e525.
|
| [28] |
A. E. Overacre-Delgoffe, H. J. Bumgarner, A. R. Cillo, et al., “Microbiota-specific T Follicular Helper Cells Drive Tertiary Lymphoid Structures and Anti-tumor Immunity Against Colorectal Cancer,” Immunity 54, no. 12 (2021): 2812–2824.e2814.
|
| [29] |
C. Li, H. Guo, P. Zhai, et al., “Spatial and Single-Cell Transcriptomics Reveal a Cancer-Associated Fibroblast Subset in HNSCC That Restricts Infiltration and Antitumor Activity of CD8+ T Cells,” Cancer Research 84, no. 2 (2024): 258–275.
|
| [30] |
J. Liu, Z. Sun, S. Cao, et al., “Desmoglein-2 Was a Novel Cancer-associated Fibroblasts-related Biomarker for Oral Squamous Cell Carcinoma,” BMC Oral Health 25, no. 1 (2025): 102.
|
| [31] |
D. Hanahan, “Hallmarks of Cancer: New Dimensions,” Cancer Discovery 12, no. 1 (2022): 31–46.
|
| [32] |
Y. Zhi, Q. Wang, M. Zi, et al., “Spatial Transcriptomic and Metabolomic Landscapes of Oral Submucous Fibrosis-Derived Oral Squamous Cell Carcinoma and Its Tumor Microenvironment,” Advanced Sci ence(Weinh) 11, no. 12 (2024): e2306515.
|
| [33] |
J. Li, S. Chen, Y. Liao, H. Wang, D. Zhou, and B. Zhang, “Arecoline Is Associated with Inhibition of Cuproptosis and Proliferation of Cancer-Associated Fibroblasts in Oral Squamous Cell Carcinoma: A Potential Mechanism for Tumor Metastasis,” Frontiers in Oncology 12 (2022): 925743.
|
| [34] |
A. Dobin, C. A. Davis, F. Schlesinger, et al., “STAR: Ultrafast Universal RNA-seq Aligner,” Bioinformatics 29, no. 1 (2013): 15–21.
|
| [35] |
Y. Hao, S. Hao, E. Andersen-Nissen, et al., “Integrated Analysis of Multimodal Single-cell Data,” Cell 184, no. 13 (2021): 3573–3587.e3529.
|
| [36] |
T. Wu, E. Hu, S. Xu, et al., “clusterProfiler 4.0: A Universal Enrichment Tool for Interpreting Omics Data,” Innovation (Camb) 2, no. 3 (2021): 100141.
|
| [37] |
M. Andreatta and S. J. Carmona, “UCell: Robust and Scalable Single-cell Gene Signature Scoring,” Computational and Structural Biotechnology Journal 19 (2021): 3796–3798.
|
| [38] |
E. Azizi, A. J. Carr, G. Plitas, et al., “Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment,” Cell 174, no. 5 (2018): 1293–1308.e1236.
|
| [39] |
I. M. P. Badia, J. Velez Santiago, J. Braunger, et al., “decoupleR: Ensemble of Computational Methods to Infer Biological Activities From Omics Data,” Bioinformatics Advances 2, no. 1 (2022): vbac016.
|
| [40] |
V. A. Huynh-Thu, A. Irrthum, L. Wehenkel, and P. Geurts, “Inferring Regulatory Networks From Expression Data Using Tree-based Methods,” PLoS ONE 5, no. 9 (2010): e12776.
|
| [41] |
P. Shannon, A. Markiel, O. Ozier, et al., “Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks,” Genome Research 13, no. 11 (2003): 2498–2504.
|
| [42] |
I. Korsunsky, N. Millard, J. Fan, et al., “Fast, Sensitive and Accurate Integration of Single-cell Data With Harmony,” Nature Methods 16, no. 12 (2019): 1289–1296.
|
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