Table · dataset · 2026
Table 1_A spatial–microbial–metabolic–immune framework for high-risk oral potentially malignant disorders: an evidence-ranked review for malignant transformation risk stratification.docx
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<p>The oral mucosa is a microbe-exposed barrier ecosystem in which surface biofilms, epithelial differentiation programs, microbial products, metabolic stress, stromal remodeling, and immune surveillance are spatially organized.
Description
Although oral microbiome studies have associated dysbiosis with oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC), most evidence remains saliva-based, rinse-based, swab-based, tissue-homogenate-based, or taxon-centered.
These approaches can identify disease-associated microbial patterns but cannot determine whether microbial signals are locally aligned with epithelial, metabolic, stromal, and immune changes within the same mucosal microdomains. Here, we propose a spatial–microbial–metabolic–immune (SMMI) framework as an evidence-ranked and testable approach for studying malignant transformation risk in high-risk OPMDs. The acronym denotes four analytical dimensions—spatial organization, microbial signals, metabolic mediation, and immune remodeling—all interpreted within oral host tissue.
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The framework asks whether dysbiosis-associated microbial signals, epithelial barrier-response states, metabolic stress, stromal remodeling, macrophage-centered immunoregulation, altered epithelial immune visibility, and T-cell positioning become locally aligned within candidate mucosal microdomains. SMMI is a conceptual and validation framework rather than an established causal mechanism, fixed anatomical structure, or immediate therapeutic target.
This article is an evidence-ranked conceptual review rather than a systematic review. We distinguish direct human OPMD evidence from OSCC-derived inference, preclinical perturbation data, broader cancer biology, methods papers, and speculative but testable hypotheses. We outline a modular validation roadmap that proceeds from pathology-anchored sampling and contamination-aware microbial localization to hypothesis-selected spatial modules, targeted functional testing, and longitudinal clinical validation.
The near-term translational goal is improved risk stratification and risk-adapted surveillance, rather than ecological intervention. By reframing high-risk OPMDs as spatial oral microbe–host immune-metabolic ecosystems, the SMMI framework provides a cautious structure for hypothesis generation, spatial validation, and clinically relevant risk modeling.</p>
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Where it is published
- DOI doi.org/10.3389/fcimb.2026.1928595.s001 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Astronomy & Astrophysics · Chemistry · Clinical microbiology · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Cancer 75% · Longitudinal study 65% · Tabular 65%
Provenance · 1 source records, 20 field assertions
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|---|---|---|---|
| figshare | oai:figshare.com:article/33786838 | 9 d ago | JSON v1 |
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| concepts[field].anzsrc:field:320203 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Clinical Microbiology'] |
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