Diagnostic oral microbiota signatures for gastric cancer and associations with carcinogenic signaling pathways.
1/5 보강
[BACKGROUND/OBJECTIVE] Gastric cancer (GC) is a major cause of cancer mortality worldwide.
APA
Kim YH, Choi IJ, et al. (2026). Diagnostic oral microbiota signatures for gastric cancer and associations with carcinogenic signaling pathways.. Journal of oral microbiology, 18(1), 2613531. https://doi.org/10.1080/20002297.2026.2613531
MLA
Kim YH, et al.. "Diagnostic oral microbiota signatures for gastric cancer and associations with carcinogenic signaling pathways.." Journal of oral microbiology, vol. 18, no. 1, 2026, pp. 2613531.
PMID
41531453 ↗
Abstract 한글 요약
[BACKGROUND/OBJECTIVE] Gastric cancer (GC) is a major cause of cancer mortality worldwide. We evaluated whether oral microbiota could be sensitive, specific, and non-invasive markers for early GC detection.
[MATERIALS AND METHODS] Saliva samples were analyzed using rRNA sequencing, and oral microbial markers were validated using an internal validation dataset. Machine learning was used to identify key genera, and functional associations were inferred using Kyoto Encyclopedia of Genes and Genomes pathway and ortholog analyses. Blood samples were also collected, and plasma cytokines were quantified by enzyme-linked immunosorbent assay (ELISA) for pathway-level interpretations.
[RESULTS] Eight genera-, , , , , , , and -were validated as diagnostic microbial markers (area under the receiver operating characteristic curve [AUC] = 0.91). and were enriched in GC, whereas was depleted and associated with reduced risk. These genera may be functionally linked to pathways involved in GC progression, including NF-κB, IL-6, STAT3, TGF-β1, and Smad2/3. The proposed classification method effectively identified early-stage and tumor-marker-negative GCs, underscoring its clinical translation potential.
[CONCLUSIONS] Oral microbial markers, including , , and , may serve as non-invasive diagnostic markers for GC and may be related to carcinogenic signaling activity.
[MATERIALS AND METHODS] Saliva samples were analyzed using rRNA sequencing, and oral microbial markers were validated using an internal validation dataset. Machine learning was used to identify key genera, and functional associations were inferred using Kyoto Encyclopedia of Genes and Genomes pathway and ortholog analyses. Blood samples were also collected, and plasma cytokines were quantified by enzyme-linked immunosorbent assay (ELISA) for pathway-level interpretations.
[RESULTS] Eight genera-, , , , , , , and -were validated as diagnostic microbial markers (area under the receiver operating characteristic curve [AUC] = 0.91). and were enriched in GC, whereas was depleted and associated with reduced risk. These genera may be functionally linked to pathways involved in GC progression, including NF-κB, IL-6, STAT3, TGF-β1, and Smad2/3. The proposed classification method effectively identified early-stage and tumor-marker-negative GCs, underscoring its clinical translation potential.
[CONCLUSIONS] Oral microbial markers, including , , and , may serve as non-invasive diagnostic markers for GC and may be related to carcinogenic signaling activity.
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