TY - JOUR
T1 - Oral microbiome and pancreatic cancer
AU - Wei, Ai Lin
AU - Li, Mao
AU - Li, Guo Qing
AU - Wang, Xuan
AU - Hu, Wei Ming
AU - Li, Zhen Lu
AU - Yuan, Jue
AU - Liu, Hong Ying
AU - Zhou, Li Li
AU - Li, Ka
AU - Li, Ang
AU - Fu, Mei Rosemary
N1 - Funding Information:
Supported by Expert Funding of
Funding Information:
Expert Funding of National Natural Science Foundation of China, No. 81773174; 1?3?5 project for disciplines of excellence- Clinical Research Incubation and Innovation Project, West China Hospital, Sichuan University, No. ZYJC18044; Clinical Research Incubation and Innovation Project of West China Hospital, No. 2019HXFH009; Science and technology project of Sichuan Province, No. 2020YFS0264.
Publisher Copyright:
© The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
PY - 2020/12/28
Y1 - 2020/12/28
N2 - 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.
AB - 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.
KW - 16s rRNA
KW - Cancer detection
KW - Dysbiosis
KW - High-throughput sequencing
KW - Oral microbiota
KW - Pancreatic cancer
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U2 - 10.3748/WJG.V26.I48.7679
DO - 10.3748/WJG.V26.I48.7679
M3 - Article
C2 - 33505144
AN - SCOPUS:85099152221
SN - 1007-9327
VL - 26
SP - 7679
EP - 7692
JO - World Journal of Gastroenterology
JF - World Journal of Gastroenterology
IS - 48
ER -