A comprehensive analysis of the microbiota composition and gene expression in colorectal cancer

Study information

Reviewed Marked as Reviewed by Claregrieve1 on 2023-4-16

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

33050883

DOI Digital object identifier for electronic documents.

10.1186/s12866-020-01938-w

URI

Authors

Zhang Q, Zhao H, Wu D, Cao D, Ma W

Journal

BMC microbiology

Year

2020

Keywords:

Colorectal cancer, Gene expression, Gut microflora, Pathways enrichment, Survival analysis

BACKGROUND: The dysregulation of gut microbiota is pivotal in colorectal carcinogenesis. Meanwhile, altered gut microbiome may affect the development of intestinal diseases through interaction with the host genes. However, the synergy between the altered gut microbiota composition and differential expression of specific genes in colorectal cancer (CRC) remains elusive. Thus, we integrated the data from 16S rRNA gene sequences and RNA sequences to investigate the potential relationship between genes and gut microbes in patients with CRC. RESULTS: Compared with normal samples, the presence of Proteobacteria and Fusobacteria increased considerably in CRC samples; conversely, the abundance of Firmicutes and Spirochaetes decreased markedly. In particular, the genera Fusobacterium, Catenibacterium, and Shewanella were only detected in tumor samples. Meanwhile, a closely interaction between Butyricimonas and Clostridium was observed in the microbiome network. Furthermore, a total of 246 (differentially expressed genes) DEGs were identified between tumor and normal tissues. Both DEGs and microbiota were involved in bile secretion and steroid hormone biosynthesis pathways. Finally, genes like cytochrome P450 family 3 subfamily A member 4 (CYP3A4) and ATP binding cassette subfamily G member 2 (ABCG2) enriched in these two pathways were connected with the prognosis of CRC, and CRC patients with low expression level of CYP3A4 and ABCG2 had longer survival time. CONCLUSION: Identifying the complicated interaction between gut microbiota and the DEGs contributed to further understand the pathogenesis of CRC, and these findings might enable better diagnosis and treatment of CRC patients.

Experiment 1

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Reviewed Marked as Reviewed by Claregrieve1 on 2023-4-16

Curated date: 2022/08/01

Curator: Jeshudy

Revision editor(s): Jeshudy, WikiWorks, Claregrieve1

Subjects

Location of subjects: China

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: Intestine Bowel,Intestinal tract,Intestine,intestine

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Colorectal cancer cancer of colorectum,cancer of large bowel,cancer of large intestine,cancer of the large bowel,colon cancer,colorectal cancer,colorectum cancer,CRC,large intestine cancer,malignant colorectal neoplasm,malignant colorectal tumor,malignant colorectum neoplasm,malignant large bowel neoplasm,malignant large bowel tumor,malignant large intestine neoplasm,malignant large intestine tumor,malignant neoplasm of colorectum,malignant neoplasm of large bowel,malignant neoplasm of large intestine,malignant neoplasm of the large bowel,malignant neoplasm of the large intestine,malignant tumor of large bowel,malignant tumor of large intestine,malignant tumor of the large bowel,malignant tumor of the large intestine,Colorectal cancer

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Control

Group 1 name Corresponds to the case (exposed) group for case-control studies: CRC

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Tumor specimens taken from patients with colorectal cancer

Group 0 sample size Number of subjects in the control (unexposed) group: 19

Group 1 sample size Number of subjects in the case (exposed) group: 19

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): None specified

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V3-V4

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: T-Test

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

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: unchanged

Chao1 Abundance-based estimator of species richness: unchanged

Simpson Estimator of species richness and species evenness: more weight on species evenness: unchanged

Signature 1

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Reviewed Marked as Reviewed by Claregrieve1 on 2023-4-16

Curated date: 2022/08/01

Curator: Jeshudy

Revision editor(s): Jeshudy, Claregrieve1

Source: Text

Description: Differential microbial abundance between CRC and control samples

Abundance in Group 1: increased abundance in CRC

NCBI	Quality Control	Links
Actinomycetota
Fusobacteriota
Fusobacterium
Bacteroides
Blautia

Revision editor(s): Jeshudy, Claregrieve1

Signature 2

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Reviewed Marked as Reviewed by Claregrieve1 on 2023-4-16

Curated date: 2022/08/01

Curator: Jeshudy

Revision editor(s): Jeshudy, Claregrieve1

Source: Text

Description: Differential microbial abundance between CRC and control samples

Abundance in Group 1: decreased abundance in CRC

NCBI	Quality Control	Links
Bacillota
Pseudomonadota

Revision editor(s): Jeshudy, Claregrieve1