Influence of oral microbiome on longitudinal patterns of oral mucositis severity in patients with squamous cell carcinoma of the head and neck

被引:7
作者
Zhang, Liangliang [1 ,2 ]
San Valentin, Erin Marie D. [3 ,4 ]
John, Teny M. [5 ]
Jenq, Robert R. [6 ]
Do, Kim-Anh [1 ]
Hanna, Ehab Y. [7 ]
Peterson, Christine B. [1 ,8 ]
Reyes-Gibby, Cielito C. [1 ,3 ,9 ]
机构
[1] Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX USA
[2] Case Western Reserve Univ, Sch Med, Dept Populat & Quantitat Hlth Sci, Cleveland, OH USA
[3] Univ Texas MD Anderson Canc Ctr, Dept Emergency Med, Houston, TX USA
[4] Univ Texas MD Anderson Canc Ctr, Dept Intervent Radiol, Houston, TX USA
[5] Univ Texas MD Anderson Canc Ctr, Dept Infect Dis, Houston, TX USA
[6] Univ Texas MD Anderson Canc Ctr, Dept Genom Med, Houston, TX USA
[7] Univ Texas MD Anderson Canc Ctr, Dept Head & Neck Surg, Houston, TX USA
[8] Univ Texas MD Anderson Canc Ctr, Dept Biostat, 1400 Pressler St, Houston, TX 77030 USA
[9] Univ Texas MD Anderson Canc Ctr, Dept Biostat & Emergency Med, Zayed Bldg Personalized Canc Res,6565 MD Anderson, Houston, TX 77030 USA
基金
美国国家卫生研究院;
关键词
latent class mixed model; locally estimated scatterplot smoothing; oral microbiome; oral mucositis; squamous cell carcinoma of the head and neck; PATIENTS RECEIVING RADIOTHERAPY; SYMPTOM INVENTORY-HEAD; DOUBLE-BLIND; PHASE-III; CANCER; TRIAL; ISEGANAN; THERAPY; MODULE;
D O I
10.1002/cncr.35001
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundThis 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.MethodsOM 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.ResultsFour 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.ConclusionsThese findings suggest the potential to personalize treatment for OM.Plain Language SummaryOral 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. Trends in the abundance of specific microbial features were observed to be associated with patterns of oral mucositis (OM) severity over time. These findings suggest the potential to personalize treatment plans for OM via tailored microbiome interventions.
引用
收藏
页码:150 / 161
页数:12
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