本研究调查了口腔微生物特征对头颈部鳞状细胞癌患者口腔黏膜炎（OM）进展的影响。通过对OM的严重程度评估和在基线、癌症治疗开始时、癌症治疗期间的每周、癌症治疗结束时以及癌症治疗终止后采集腮腺拭子，运用Illumina平台对口腔微生物组进行了16S rRNA V4区域的特征化。采用潜在类混合模型分析将具有相似OM严重程度轨迹的个体分组。采用局部估计散点平滑方法在每个组中拟合一个平均趋势，并评估纵向OM评分与纵向微生物丰度之间的关联。对于142名受试者，识别出了4个具有不同OM严重度模式的潜在组（LGs）。 LG1表现为早期高OM评分。LG2和LG3的OM评分在第8周和第11周之前相对较低。LG4的OM评分基本持平。这些LGs不因治疗或临床或人口统计学变量而异。相关分析显示，Bacteroidota、Proteobacteria、Bacteroidia、Gammaproteobacteria、Enterobacterales、Bacteroidales、Aerococcaceae、Prevotellaceae、Abiotrophia和Prevotella_7的丰度与四个LG中OM严重度呈正相关。对于几个微生物特征，OM严重度表现为负相关：对于LG2和LG3，Abiotrophia和Aerococcaceae；对于LG2、LG3和LG4，Gammaproteobacteria和Proteobacteria；对于LG2和LG4，Enterobacterales。这些发现表明个性化OM治疗的潜力。口腔黏膜炎（OM）是头颈部鳞状细胞癌患者治疗后常见且令人困扰的副作用。特定微生物特征丰度的变化趋势可能与OM严重度的模式随时间变化相关。我们的发现表明通过个体化的微生物组干预方法可能实现个性化OM治疗计划的潜力。© 2023美国癌症学会。

This study investigated the influence of oral microbial features on the trajectory of oral mucositis (OM) in patients with squamous cell carcinoma of the head and neck.OM severity was assessed and buccal swabs were collected at baseline, at the initiation of cancer treatment, weekly during cancer treatment, at the termination of cancer treatment, and after cancer treatment termination. The oral microbiome was characterized via the 16S ribosomal RNA V4 region with the Illumina platform. Latent class mixed-model analysis was used to group individuals with similar trajectories of OM severity. Locally estimated scatterplot smoothing was used to fit an average trend within each group and to assess the association between the longitudinal OM scores and longitudinal microbial abundances.Four latent groups (LGs) with differing patterns of OM severity were identified for 142 subjects. LG1 has an early onset of high OM scores. LGs 2 and 3 begin with relatively low OM scores until the eighth and 11th week, respectively. LG4 has generally flat OM scores. These LGs did not vary by treatment or clinical or demographic variables. Correlation analysis showed that the abundances of Bacteroidota, Proteobacteria, Bacteroidia, Gammaproteobacteria, Enterobacterales, Bacteroidales, Aerococcaceae, Prevotellaceae, Abiotrophia, and Prevotella_7 were positively correlated with OM severity across the four LGs. Negative correlation was observed with OM severity for a few microbial features: Abiotrophia and Aerococcaceae for LGs 2 and 3; Gammaproteobacteria and Proteobacteria for LGs 2, 3, and 4; and Enterobacterales for LGs 2 and 4.These findings suggest the potential to personalize treatment for OM.Oral mucositis (OM) is a common and debilitating after effect for patients treated for squamous cell carcinoma of the head and neck. Trends in the abundance of specific microbial features may be associated with patterns of OM severity over time. Our findings suggest the potential to personalize treatment plans for OM via tailored microbiome interventions.© 2023 American Cancer Society.