Signatures of Mucosal Microbiome in Oral Squamous Cell Carcinoma Identified Using a Random Forest Model

Study information

Needs review

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

32753953

DOI Digital object identifier for electronic documents.

10.2147/CMAR.S251021

URI

Authors

Zhou J, Wang L, Yuan R, Yu X, Chen Z, Yang F, Sun G, Dong Q

Journal

Cancer management and research

Year

2020

Keywords:

microbiome, oral squamous cell carcinoma, predicted functions, random forest machine learning

Objective: The aim of this study was to explore the signatures of oral microbiome associated with OSCC using a random forest (RF) model. Patients and Methods: A total of 24 patients with OSCC were enrolled in the study. The oral microbiome was assessed in cancerous lesions and matched paracancerous tissues from each patient using 16S rRNA gene sequencing. Signatures of mucosal microbiome in OSCC were identified using a RF model. Results: Significant differences were found between OSCC lesions and matched paracancerous tissues with respect to the microbial profile and composition. Linear discriminant analysis effect size analyses (LEfSe) identified 15 bacteria genera associated with cancerous lesions. Fusobacterium, Treponema, Streptococcus, Peptostreptococcus, Carnobacterium, Tannerella, Parvimonas and Filifactor were enriched. A classifier based on RF model identified a microbial signature comprising 12 bacteria, which was capable of distinguishing cancerous lesions and paracancerous tissues (AUC = 0.82). The network of the oral microbiome in cancerous lesions appeared to be simplified and fragmented. Functional analyses of oral microbiome showed altered functions in amino acid metabolism and increased capacity of glucose utilization in OSCC. Conclusion: The identified microbial signatures may potentially be used as a biomarker for predicting OSCC or for clinical assessment of oral cancer risk.

Experiment 1

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Needs review

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks

Subjects

Location of subjects: China

Host species Species from which microbiome was sampled (if applicable): Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Mouth , Skin of cheek , Tongue , Gingiva , Oropharynx Adult mouth,Cavital oralis,Cavitas oris,Cavum oris,Mouth cavity,Oral region,Oral vestibule,Regio oralis,Rima oris,Stoma,Stomatodaeum,Trophic apparatus,Vestibule of mouth,Vestibulum oris,Mouth,Cheek skin,Skin of cheek,Glossus,Tongue,Gingival mucosa,Gum,Gum tissue,Gums,Gingiva,Mesopharynx,Oral part of pharynx,Pars oralis pharyngis,Oropharynx

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: oral squamous cell carcinoma mouth scc,mouth squamous cell carcinoma,OCSC,oral cavity scc,oral cavity squamous cell cancer,oral cavity squamous cell carcinoma,oral squamous cell carcinoma,scc of mouth,scc of oral cavity,scc of the mouth,scc of the oral cavity,squamous cell carcinoma of mouth,squamous cell carcinoma of oral cavity,squamous cell carcinoma of the mouth,squamous cell carcinoma of the oral cavity

Group 0 name Corresponds to the control (unexposed) group for case-control studies: paracancerous tissues
Group 1 name Corresponds to the case (exposed) group for case-control studies: cancerous lesions
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: patients at different stages of OSCC were enrolled in the study
Group 0 sample size Number of subjects in the control (unexposed) group: 24
Group 1 sample size Number of subjects in the case (exposed) group: 24
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 2 weeks

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V3-V4

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes
LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 3

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: unchanged
Chao1 Abundance-based estimator of species richness: unchanged