Abstract
BACKGROUND: Oral mucositis is a painful complication commonly observed in head and neck cancer patients receiving cancer treatment. Emerging evidence suggests that changes in the oral microbiome can contribute to oral mucositis development, making microbial signatures potential targets for therapeutic interventions. This study aimed to: (1) characterize longitudinal microbial patterns of oral mucositis severity among head and neck cancer patients; (2) determine clinically relevant patient clusters based on oral mucositis severity trajectories; and (3) identify microbial signatures specific to these clusters. RESULTS: We derived a calibrated oral mucositis score by applying non-negative sparse principal component analysis to seven oral mucositis related symptom ratings, using longitudinal microbiome data from 140 head and neck cancer patients. Functional data analysis and hierarchical clustering identified three distinct patient clusters with differing microbial trajectories of oral mucositis progression. One cluster exhibited patients with a rapid increase in oral mucositis severity following treatment initiation, while the other clusters displayed more gradual increase. Demographic comparisons revealed significant differences in age and weight distributions between clusters, with older, lighter patients more common in clusters experiencing more gradual oral mucositis progression. Partial least squares knockoff analysis identified cluster-specific microbial signatures: notably, Prevotella spp. positively associated with calibrated oral mucositis score across all clusters, while Alloprevotella (Alloprevotella0302) was significantly enriched only in patients experiencing rapid oral mucositis progression. Conversely, genera associated with oral health, including Haemophilus, Rothia, and Actinomyces, were negatively correlated with calibrated oral mucositis score. CONCLUSIONS: Distinct trajectories of oral mucositis scores in head and neck cancer patients are linked to specific oral microbial profiles and demographic factors. The identification of cluster-specific microbial profiles highlights the potential for microbiome-targeted interventions to manage oral mucositis severity. While most taxa were cluster-specific, Prevotella consistently ranked among the top taxa positively associated with the calibirated oral mucositis score across clusters, suggesting it may not differentiate between patient groups but rather reflects overall disease severity.