Taxonomic and Functional Differences in Cervical Microbiome Associated with Cervical Cancer Development
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Tango CN, Seo SS, Kwon M, Lee DO, Chang HK, Kim MK
Journal
Scientific reports
Year
2020
The cervical microbiome is associated with cervical cancer risk, but how microbial diversity and functional profiles change in cervical cancer remains unclear. Herein, we investigated microbial-compositional and functional differences between a control group and a high-grade cervical intraepithelial neoplasia and cervical cancer (CIN2/3-CC) group. After retrospective collection of 92 cervical swab samples, we carried out 16S rRNA amplicon sequencing on 50 and 42 samples from the control and CIN2/3-CC groups, respectively. The EzBioCloud pipeline was applied to identify the genomic features associated with the groups using 16S rRNA data. A linear discriminant analysis effect size (LEfSe) was performed to assess the enrichment in the assigned taxonomic and functional profiles. We found a lower richness in the control group relative to the CIN2/3-CC group; however, the β-diversity tended to be similar between the groups. The LEfSe analysis showed that a phylum Sacchaaribacteria_TM7, 11 genera, and 21 species were more abundant in the CIN2/3-CC group and that one uncharacterized Gardnerella species was more abundant only in the control group. Further characterization of the functional pathways using EzBioCloud showed that the 4 KEGG orthologs (Phosphotransferase system [PTS] sucrose-specific IIA, IIB, IIC components and PTS cellubiose-specific IIC component) were involved in the KEGG pathway of starch and sucrose metabolism. The two pathways of folate biosynthesis and oxidative phosphorylation were more abundant in the CIN2/3-CC group. Further confirmation of these results in larger samples can help to elucidate the potential association between the cervical microbiome and cervical cancer.
Experiment 1
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-3
Subjects
- Location of subjects
- South Korea
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Uterine cervixUterine cervix
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Cervical glandular intraepithelial neoplasia , Cervical carcinoma Cervical glandular intraepithelial neoplasia,cervical glandular intraepithelial neoplasia,cancer of cervix,cancer of the cervix,cancer of the uterine cervix,cancer of uterine cervix,carcinoma cervix uteri,carcinoma of cervix,carcinoma of cervix uteri,carcinoma of the cervix,carcinoma of the cervix uteri,carcinoma of the uterine cervix,carcinoma of uterine cervix,cervical cancer,cervical cancer, NOS,cervical carcinoma,cervix cancer,cervix carcinoma,cervix uteri carcinoma,uterine cervix cancer,uterine cervix carcinoma,Cervical carcinoma
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy controls
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- CIN2/3-CC
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- patients diagnosed with CIN2/3 or cervical cancer during screening of the cervical tract
- Group 0 sample size Number of subjects in the control (unexposed) group
- 50
- Group 1 sample size Number of subjects in the case (exposed) group
- 42
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- antibiotic therapy within 3 months
Lab analysis
- Sequencing type
- 16S
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Roche454
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- LEfSe
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- No
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- unchanged
- Chao1 Abundance-based estimator of species richness
- increased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- unchanged
- Richness Number of species
- increased
Signature 1
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-3
Source: figure 2
Description: Diferences in relative abundances of microbial taxa (genus and species) between groups by LEfSe analysis
Abundance in Group 1: increased abundance in CIN2/3-CC
Revision editor(s): WikiWorks, Peace Sandy
Signature 2
Reviewed Marked as Reviewed by Peace Sandy on 2024-2-3
Source: figure 2
Description: Diferences in relative abundances of microbial taxa (genus and species) between groups by LEfSe analysis
Abundance in Group 1: decreased abundance in CIN2/3-CC
| NCBI | Quality Control | Links |
|---|---|---|
| Gardnerella |
Revision editor(s): Peace Sandy, WikiWorks
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