Exploring oral microbiome in oral squamous cell carcinoma across environment-associated sample types

Area of Science:

• Microbiology
• Oncology
• Genomics

Background:

• The oral microbiome's role in oral squamous cell carcinoma (OSCC) is recognized, but systematic evaluations are lacking.
• Previous studies on the oral microbiome and OSCC were primarily single-center, limiting generalizability.
• Understanding microbiome alterations across OSCC phenotypes is crucial for cancer progression insights.

Purpose of the Study:

• To conduct a comprehensive meta-analysis of OSCC-related 16S rRNA gene data to characterize oral microbiome dynamics.
• To investigate differences in oral microbiome composition across various sample types and OSCC phenotypes.
• To develop and validate a diagnostic model for OSCC detection based on oral microbial signatures.

Main Methods:

• Performed a meta-analysis of 1,255 samples from diverse OSCC-related 16S rRNA gene datasets.
• Analyzed microbiome differences between sample types (Biopsy, Swab) and OSCC groups (Cancer, Normal Adjacent Tissue, Fibroepithelial Polyp).
• Developed a random forest diagnostic model using Swab samples and validated it on a separate sequencing platform.

Main Results:

• Distinct oral microbiome characteristics were observed between Biopsy and Swab samples across different phenotypes.
• Biopsy samples showed higher similarity between Cancer and Normal Adjacent Tissue (NAT) groups compared to Fibroepithelial Polyp (FEP) samples.
• The diagnostic model achieved an AUC of 0.918 on Swab samples and 0.849 on an independent dataset, demonstrating diagnostic potential.

Conclusions:

• The oral microbiome composition varies significantly by sample type and OSCC progression stage.
• Swab samples hold potential for developing reliable diagnostic tools for OSCC.
• This study provides a comprehensive overview of oral microbiome dynamics in OSCC, aiding early detection and treatment strategies.