Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.
환자-대조
2/5 보강
OpenAlex 토픽 ·
Gut microbiota and health
Probiotics and Fermented Foods
Oral microbiology and periodontitis research
[PURPOSE] Lung cancer is the leading cause of cancer-related mortality worldwide, yet its underlying mechanisms remain unclear.
- 연구 설계 case-control
APA
Adrian Low, Yah Ru Juang, et al. (2026). Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.. Cellular oncology (Dordrecht, Netherlands), 49(2). https://doi.org/10.1007/s13402-026-01193-7
MLA
Adrian Low, et al.. "Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.." Cellular oncology (Dordrecht, Netherlands), vol. 49, no. 2, 2026.
PMID
41961381 ↗
Abstract 한글 요약
[PURPOSE] Lung cancer is the leading cause of cancer-related mortality worldwide, yet its underlying mechanisms remain unclear. Disruptions in the respiratory microbiome may promote inflammation and carcinogenesis. This study aimed to comprehensively compare genus-level sputum microbiota between lung cancer patients and healthy controls in a multiethnic Southeast Asian population.
[METHODS] Sputum samples were collected from lung cancer patients across three Singapore hospitals. Socio-demographic data were obtained via questionnaire. We analyzed 16S rRNA amplicon sequences from 70 lung cancer patients and 47 healthy controls from a separate local cohort, using identical sequencing protocols to minimize batch effects. Alpha- and beta-diversity metrics, random forest models, and ANCOM-BC2 were used to identify microbial features associated with lung cancer and host characteristics.
[RESULTS] Lung cancer cases showed significantly reduced genus richness compared to controls. Beta-diversity (Aitchison distance) differed by case-control status, sex, age, and smoking history. ANCOM-BC2 identified as differentially enriched in cases. However, this enrichment did not pass the pseudo-count test among never-smokers. Further sex-stratified analysis revealed that the enrichment was driven primarily by male cases. Conversely, group, , and emerged as robust inverse signatures for lung cancer, with their depletion consistently supported across stratified and unstratified differential abundance analyses, random forest modeling, and Wilcoxon rank-sum tests. However, these findings may still be subjected to residual confounding by exogenous factors, such as medication use, which could not be adequately adjusted for between case-control groups.
[CONCLUSION] This pilot case-control study, conducted in a multiethnic Southeast Asian population, identified distinct respiratory microbiota signatures associated with lung cancer using robust differential abundance and machine-learning methods, providing preliminary evidence for a potential role of the respiratory microbiome to lung carcinogenesis, warranting validation in larger, longitudinal studies.
[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s13402-026-01193-7.
[METHODS] Sputum samples were collected from lung cancer patients across three Singapore hospitals. Socio-demographic data were obtained via questionnaire. We analyzed 16S rRNA amplicon sequences from 70 lung cancer patients and 47 healthy controls from a separate local cohort, using identical sequencing protocols to minimize batch effects. Alpha- and beta-diversity metrics, random forest models, and ANCOM-BC2 were used to identify microbial features associated with lung cancer and host characteristics.
[RESULTS] Lung cancer cases showed significantly reduced genus richness compared to controls. Beta-diversity (Aitchison distance) differed by case-control status, sex, age, and smoking history. ANCOM-BC2 identified as differentially enriched in cases. However, this enrichment did not pass the pseudo-count test among never-smokers. Further sex-stratified analysis revealed that the enrichment was driven primarily by male cases. Conversely, group, , and emerged as robust inverse signatures for lung cancer, with their depletion consistently supported across stratified and unstratified differential abundance analyses, random forest modeling, and Wilcoxon rank-sum tests. However, these findings may still be subjected to residual confounding by exogenous factors, such as medication use, which could not be adequately adjusted for between case-control groups.
[CONCLUSION] This pilot case-control study, conducted in a multiethnic Southeast Asian population, identified distinct respiratory microbiota signatures associated with lung cancer using robust differential abundance and machine-learning methods, providing preliminary evidence for a potential role of the respiratory microbiome to lung carcinogenesis, warranting validation in larger, longitudinal studies.
[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s13402-026-01193-7.
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