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Oral microbiome and pancreatic cancer

BACKGROUND: Microbiota profiles differ between patients with pancreatic cancer and healthy people, and understanding these differences may help in early detection of pancreatic cancer. Saliva sampling is an easy and cost-effective way to determine microbiota profiles compared to fecal and tissue sam...

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Autores principales: Wei, Ai-Lin, Li, Mao, Li, Guo-Qing, Wang, Xuan, Hu, Wei-Ming, Li, Zhen-Lu, Yuan, Jue, Liu, Hong-Ying, Zhou, Li-Li, Li, Ka, Li, Ang, Fu, Mei Rosemary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789059/
https://www.ncbi.nlm.nih.gov/pubmed/33505144
http://dx.doi.org/10.3748/wjg.v26.i48.7679
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author Wei, Ai-Lin
Li, Mao
Li, Guo-Qing
Wang, Xuan
Hu, Wei-Ming
Li, Zhen-Lu
Yuan, Jue
Liu, Hong-Ying
Zhou, Li-Li
Li, Ka
Li, Ang
Fu, Mei Rosemary
author_facet Wei, Ai-Lin
Li, Mao
Li, Guo-Qing
Wang, Xuan
Hu, Wei-Ming
Li, Zhen-Lu
Yuan, Jue
Liu, Hong-Ying
Zhou, Li-Li
Li, Ka
Li, Ang
Fu, Mei Rosemary
author_sort Wei, Ai-Lin
collection PubMed
description BACKGROUND: Microbiota profiles differ between patients with pancreatic cancer and healthy people, and understanding these differences may help in early detection of pancreatic cancer. Saliva sampling is an easy and cost-effective way to determine microbiota profiles compared to fecal and tissue sample collection. AIM: To investigate the saliva microbiome distribution in patients with pancreatic adenocarcinoma (PDAC) and the role of oral microbiota profiles in detection and risk prediction of pancreatic cancer. METHODS: We conducted a prospective study of patients with pancreatic cancer (n = 41) and healthy individuals (n = 69). Bacterial taxa were identified by 16S ribosomal ribonucleic acid gene sequencing, and a linear discriminant analysis effect size algorithm was used to identify differences in taxa. Operational taxonomic unit values of all selected taxa were converted into a normalized Z-score, and logistic regressions were used to calculate risk prediction of pancreatic cancer. RESULTS: Compared with the healthy control group, carriage of Streptococcus and Leptotrichina (z-score) was associated with a higher risk of PDAC [odds ratio (OR) = 5.344, 95% confidence interval (CI): 1.282-22.282, P = 0.021 and OR = 6.886, 95%CI: 1.423-33.337, P = 0.016, respectively]. Veillonella and Neisseria (z-score) were considered a protective microbe that decreased the risk of PDAC (OR = 0.187, 95%CI: 0.055-0.631, P = 0.007 and OR = 0.309, 95%CI: 0.100-0.952, P = 0.041, respectively). Among the patients with PDAC, patients reporting bloating have a higher abundance of Porphyromonas (P = 0.039), Fusobacterium (P = 0.024), and Alloprevotella (P = 0.041); while patients reporting jaundice had a higher amount of Prevotella (P = 0.008); patients reporting dark brown urine had a higher amount of Veillonella (P = 0.035). Patients reporting diarrhea had a lower amount of Neisseria and Campylobacter (P = 0.024 and P = 0.034), and patients reporting vomiting had decreased Alloprevotella (P = 0.036). CONCLUSION: Saliva microbiome was able to distinguish patients with pancreatic cancer and healthy individuals. Leptotrichia may be specific for patients living in Sichuan Province, southwest China. Symptomatic patients had different bacteria profiles than asymptomatic patients. Combined symptom and microbiome evaluation may help in the early detection of pancreatic cancer.
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spelling pubmed-77890592021-01-26 Oral microbiome and pancreatic cancer Wei, Ai-Lin Li, Mao Li, Guo-Qing Wang, Xuan Hu, Wei-Ming Li, Zhen-Lu Yuan, Jue Liu, Hong-Ying Zhou, Li-Li Li, Ka Li, Ang Fu, Mei Rosemary World J Gastroenterol Observational Study BACKGROUND: Microbiota profiles differ between patients with pancreatic cancer and healthy people, and understanding these differences may help in early detection of pancreatic cancer. Saliva sampling is an easy and cost-effective way to determine microbiota profiles compared to fecal and tissue sample collection. AIM: To investigate the saliva microbiome distribution in patients with pancreatic adenocarcinoma (PDAC) and the role of oral microbiota profiles in detection and risk prediction of pancreatic cancer. METHODS: We conducted a prospective study of patients with pancreatic cancer (n = 41) and healthy individuals (n = 69). Bacterial taxa were identified by 16S ribosomal ribonucleic acid gene sequencing, and a linear discriminant analysis effect size algorithm was used to identify differences in taxa. Operational taxonomic unit values of all selected taxa were converted into a normalized Z-score, and logistic regressions were used to calculate risk prediction of pancreatic cancer. RESULTS: Compared with the healthy control group, carriage of Streptococcus and Leptotrichina (z-score) was associated with a higher risk of PDAC [odds ratio (OR) = 5.344, 95% confidence interval (CI): 1.282-22.282, P = 0.021 and OR = 6.886, 95%CI: 1.423-33.337, P = 0.016, respectively]. Veillonella and Neisseria (z-score) were considered a protective microbe that decreased the risk of PDAC (OR = 0.187, 95%CI: 0.055-0.631, P = 0.007 and OR = 0.309, 95%CI: 0.100-0.952, P = 0.041, respectively). Among the patients with PDAC, patients reporting bloating have a higher abundance of Porphyromonas (P = 0.039), Fusobacterium (P = 0.024), and Alloprevotella (P = 0.041); while patients reporting jaundice had a higher amount of Prevotella (P = 0.008); patients reporting dark brown urine had a higher amount of Veillonella (P = 0.035). Patients reporting diarrhea had a lower amount of Neisseria and Campylobacter (P = 0.024 and P = 0.034), and patients reporting vomiting had decreased Alloprevotella (P = 0.036). CONCLUSION: Saliva microbiome was able to distinguish patients with pancreatic cancer and healthy individuals. Leptotrichia may be specific for patients living in Sichuan Province, southwest China. Symptomatic patients had different bacteria profiles than asymptomatic patients. Combined symptom and microbiome evaluation may help in the early detection of pancreatic cancer. Baishideng Publishing Group Inc 2020-12-28 2020-12-28 /pmc/articles/PMC7789059/ /pubmed/33505144 http://dx.doi.org/10.3748/wjg.v26.i48.7679 Text en ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Observational Study
Wei, Ai-Lin
Li, Mao
Li, Guo-Qing
Wang, Xuan
Hu, Wei-Ming
Li, Zhen-Lu
Yuan, Jue
Liu, Hong-Ying
Zhou, Li-Li
Li, Ka
Li, Ang
Fu, Mei Rosemary
Oral microbiome and pancreatic cancer
title Oral microbiome and pancreatic cancer
title_full Oral microbiome and pancreatic cancer
title_fullStr Oral microbiome and pancreatic cancer
title_full_unstemmed Oral microbiome and pancreatic cancer
title_short Oral microbiome and pancreatic cancer
title_sort oral microbiome and pancreatic cancer
topic Observational Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789059/
https://www.ncbi.nlm.nih.gov/pubmed/33505144
http://dx.doi.org/10.3748/wjg.v26.i48.7679
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