ArticleNPJ biofilms and microbiomes2025
Oral microbiome-derived biomarkers for non-invasive diagnosis of head and neck squamous cell carcinoma.
Article in NPJ biofilms and microbiomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- OAPGC: a high-quality oral and airway prokaryotic genome catalog for enhanced ecological resolution and disease inference.NPJ biofilms and microbiomes · 2026Article
- A critical review on the roles of natural products in shaping oral microbiota and preventing chronic diseases.Natural products and bioprospecting · 2026Review
- The microbiome as a systems-level regulator of immune, metabolic, neural, and endocrine signaling in cancer.Frontiers in immunology · 2026Review
- Ipilimumab, -omics, and head and neck cancers-update in 2025.Frontiers in immunology · 2026Review
- Gut microbiome restructuring in laryngeal squamous cell carcinoma identifies stable microbial biomarkers with diagnostic potential.Frontiers in oncology · 2026Article
- Oral Microbiome in Oral Cancer Research from Sampling to Analysis: Strategies, Challenges, and Recommendations.Cancers · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Mounting evidence suggests that sustained microbial dysbiosis is associated with the development of multiple cancers, while the species-level bacterial taxa and metabolic dysfunction of oral microbiome in patients with head and neck squamous cell carcinoma (HNSCC) remains unclear. In this cross-sectional study, comprehensive metagenomic and 16S rRNA amplicon sequencing analyses of oral swab samples from 172 patients were performed. Unsupervised clustering algorithms of relative microbial abundance profiles revealed three distinctive microbiome clusters. Based on the metagenomic and 16S rRNA amplicon sequencing data, machine learning-based methods were used to construct the HNSCC diagnostic classifier, which exhibited high area under the curve values of 0.78-0.89. Our study provided the first exhaustive metagenomic and 16S rRNA amplicon sequencing analyses to date, revealing that microbial-metabolic dysbiosis is a potential risk factor for HNSCC progression and therefore providing a robust theoretical basis for potential diagnostic and therapeutic strategies for HNSCC patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.