Tongue Coating Bacteria as a Potential Stable Biomarker for Gastric Cancer Independent of Lifestyle.

Abstract

BACKGROUND:

Gastric cancer (GC) is one of the most common cancers, and the noninvasive diagnostic methods for monitoring GC are still lacking. Growing evidence shows that human microbiota has potential value for identifying digestive diseases.

AIMS:

The present study aimed to explore the association of the tongue coating microbiota with the serum metabolic features and inflammatory cytokines in GC patients and seek a potential, noninvasive biomarker for diagnosing GC.

METHODS:

The tongue coating microbiota was profiled by 16S rRNA and 18S rRNA genes sequencing technology in the original population with 181 GC patients and 112 healthy controls (HCs). Propensity score matching method was used to eliminate potential confounders including age, gender, and six lifestyle factors and a matching population with 66 GC patients and 66 HCs generated. Serum metabolomics profiling was performed by ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) in the matching population. Random forest model was constructed for the diagnosis of GC.

RESULTS:

Linear discriminant analysis effect size (LEfSe) revealed that the differential bacterial taxa between GC patients and HCs in the matching population were similar to that in the original population, while the differential fungal taxa between GC patients and HCs dramatically changed before and after PSM. By random forest analysis, the combination of six bacterial genera (Peptostreptococcus, Peptococcus, Porphyromonas, Megamonas, Rothia, and Fusobacterium) was the optimal predictive model to distinguish GC patients from HCs effectively, with an area under the curve (AUC) value of 0.85. The model was verified with a high predictive potential (AUC = 0.76 to 0.96). In the matching population, eighteen specific HCs-enriched bacterial genera (Porphyromonas, Parvimonas, etc.) had negative correlations with lysophospholipids metabolites, and three of them had also negative correlations with serum IL-17α.

CONCLUSIONS:

The alteration of tongue coating microbiota had a possible linkage with the inflammations and metabolome, and the tongue coating bacteria could be a potential noninvasive biomarker for diagnosing GC, which might be independent of lifestyle.

• Authors: Shuo Xu, Chunjie Xiang, Juan Wu, Yuhao Teng, Zhenfeng Wu, Ruiping Wang, Bin Lu, Zhen Zhan, Huangan Wu, Junfeng Zhang
• Journal: Digestive diseases and sciences (Dig Dis Sci) Vol. 66 Issue 9 Pg. 2964-2980 (09 2021) ISSN: 1573-2568 [Electronic] United States
• PMID: 33044677 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © 2020. Springer Science+Business Media, LLC, part of Springer Nature.

Chemical References

• IL17A protein, human
• Interleukin-17
• RNA, Ribosomal, 16S
• RNA, Ribosomal, 18S

Topics

• Area Under Curve
• Bacteria (classification, isolation & purification)
• China (epidemiology)
• Correlation of Data
• Female
• Humans
• Inflammation (immunology, microbiology)
• Interleukin-17 (blood)
• Life Style
• Male
• Mass Spectrometry (methods)
• Microbiota (genetics, immunology)
• Middle Aged
• Mycobiome (physiology)
• Predictive Value of Tests
• RNA, Ribosomal, 16S (analysis)
• RNA, Ribosomal, 18S (analysis)
• Sequence Analysis, RNA (methods)
• Stomach Neoplasms (blood, epidemiology, microbiology, pathology)
• Tongue (metabolism, microbiology)