Oral Microbiome Signatures as Potential Biomarkers for Gastric Cancer Risk Assessment.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
98 participants included 30 (30.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSIONS] Oral rinses of GC and Pre-GC participants exhibited distinct but similar microbiome profiles, distinguishing them from controls. This compositional difference raises the possibility of utilizing these microbial signatures to predict GC risk.
[BACKGROUND] Gastric cancer (GC) is the fifth leading cause of cancer-related death worldwide.
- p-value p<0.02
APA
In H, Perati SR, et al. (2024). Oral Microbiome Signatures as Potential Biomarkers for Gastric Cancer Risk Assessment.. Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 101933. https://doi.org/10.1016/j.gassur.2024.101933
MLA
In H, et al.. "Oral Microbiome Signatures as Potential Biomarkers for Gastric Cancer Risk Assessment.." Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 2024, pp. 101933.
PMID
39706288 ↗
Abstract 한글 요약
[BACKGROUND] Gastric cancer (GC) is the fifth leading cause of cancer-related death worldwide. The oral microbiota was investigated for distinguishable characteristics between GC, premalignant gastric conditions (Pre-GC), and control participants.
[METHODS] Mouthwash samples from GC, Pre-GC, and control participants at a tertiary care center were prospectively collected. Following DNA extraction and sequencing, analyses of oral microbiome biodiversity and composition were performed, and receiver operating characteristic curves were created to evaluate the discriminative power of oral microbiome signatures.
[RESULTS] Oral samples from 98 participants included 30 (30.6%) GC, 30 (30.6%) Pre-GC and 38 (38.8%) controls. Of these, 61 (62.2%) were female, 31 (31.6%) were Hispanic, and 18 (18.3%) were smokers. GC compared to controls demonstrated notable differences in beta diversity (Jensen-Shannon Divergence and Bray-Curtis Dissimilarity, p<0.02). 32 bacterial genera were found to be differentially abundant when comparing GC and controls, and 23 bacterial genera demonstrated differential abundance when comparing Pre-GC and controls (W-statistic >2). Minimal compositional differences between GC and Pre-GC were found, with only three differentially abundant bacterial genera (W-statistic >2). Models were constructed from the most significant bacterial signatures (W-statistic >5). These models discriminated between GC and control oral samples with an AUC of 0.880 (95% CI 0.808, 0.952) and between Pre-GC and control oral samples with an AUC of 0.943 (95% CI 0.887, 0.999).
[CONCLUSIONS] Oral rinses of GC and Pre-GC participants exhibited distinct but similar microbiome profiles, distinguishing them from controls. This compositional difference raises the possibility of utilizing these microbial signatures to predict GC risk.
[METHODS] Mouthwash samples from GC, Pre-GC, and control participants at a tertiary care center were prospectively collected. Following DNA extraction and sequencing, analyses of oral microbiome biodiversity and composition were performed, and receiver operating characteristic curves were created to evaluate the discriminative power of oral microbiome signatures.
[RESULTS] Oral samples from 98 participants included 30 (30.6%) GC, 30 (30.6%) Pre-GC and 38 (38.8%) controls. Of these, 61 (62.2%) were female, 31 (31.6%) were Hispanic, and 18 (18.3%) were smokers. GC compared to controls demonstrated notable differences in beta diversity (Jensen-Shannon Divergence and Bray-Curtis Dissimilarity, p<0.02). 32 bacterial genera were found to be differentially abundant when comparing GC and controls, and 23 bacterial genera demonstrated differential abundance when comparing Pre-GC and controls (W-statistic >2). Minimal compositional differences between GC and Pre-GC were found, with only three differentially abundant bacterial genera (W-statistic >2). Models were constructed from the most significant bacterial signatures (W-statistic >5). These models discriminated between GC and control oral samples with an AUC of 0.880 (95% CI 0.808, 0.952) and between Pre-GC and control oral samples with an AUC of 0.943 (95% CI 0.887, 0.999).
[CONCLUSIONS] Oral rinses of GC and Pre-GC participants exhibited distinct but similar microbiome profiles, distinguishing them from controls. This compositional difference raises the possibility of utilizing these microbial signatures to predict GC risk.
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🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반
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