Study of the Relationship between Microbiome and Colorectal Cancer Susceptibility Using 16SrRNA Sequencing

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Reviewed Marked as Reviewed by Fatima on 2022/03/14
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
Authors
Liu W, Zhang R, Shu R, Yu J, Li H, Long H, Jin S, Li S, Hu Q, Yao F, Zhou C, Huang Q, Hu X, Chen M, Hu W, Wang Q, Fang S, Wu Q
Journal
BioMed research international
Year
2020
A lot of previous studies have recently reported that the gut microbiota influences the development of colorectal cancer (CRC) in Western countries, but the role of the gut microbiota in Chinese population must be investigated fully. The goal of this study was to determine the role of the gut microbiome in the initiation and development of CRC. We collected fecal samples of 206 Chinese individuals: 59 with polyp (group P), 54 with adenoma (group A), 51 with colorectal cancer (group CC), and 42 healthy controls (group HC).16S ribosomal RNA (rRNA) was used to compare the microbiota community structures among healthy controls, patients with polyp, and those with adenoma or colorectal cancer. Our study proved that intestinal flora, as a specific indicator, showed significant differences in its diversity and composition. Sobs, Chao, and Ace indexes of group CC were significantly lower than those of the healthy control group (CC group: Sobs, Chao, and Ace indexes were 217.3 ± 69, 4265.1 ± 80.7, and 268.6 ± 78.1, respectively; HC group: Sobs, Chao, and Ace indexes were 228.8 ± 44.4, 272.9 ± 58.6, and 271.9 ± 57.2, respectively). When compared with the healthy individuals, the species richness and diversity of intestinal flora in patients with colorectal cancer were significantly reduced: PCA and PCoA both revealed that a significant separation in bacterial community composition between the CC group and HC group (with PCA using the first two principal component scores of PC1 14.73% and PC2 10.34% of the explained variance, respectively; PCoA : PC1 = 14%, PC2 = 9%, PC3 = 6%). Wilcox tests was used to analyze differences between the two groups, it reveals that Firmicutes (P=0.000356), Fusobacteria (P=0.000001), Proteobacteria (P=0.000796), Spirochaetes (P=0.013421), Synergistetes (P=0.005642) were phyla with significantly different distributions between cases and controls. The proportion of microorganism composition is varying at different stages of colon cancer development: Bacteroidetes (52.14%) and Firmicutes (35.88%) were enriched in the healthy individuals; on the phylum level, the abundance of Bacteroidetes (52.14%-53.92%-52.46%-47.06%) and Firmicutes (35.88%-29.73%-24.27%-25.36%) is decreasing with the development of health-polyp-adenomas-CRC, and the abundance of Proteobacteria (9.33%-12.31%-16.51%-22.37%) is increasing. PCA and PCOA analysis showed there was no significant (P < 0.05) difference in species similarity between precancerous and carcinogenic states. However, the composition of the microflora in patients with precancerous lesions (including patients with adenoma and polyp) was proved to have no significant disparity (P < 0.05). Our study provides insights into new angles to dig out potential biomarkers in diagnosis and treatment of colorectal cancer and to provide scientific advice for a healthy lifestyle for the sake of gut microbiota.

Experiment 1


Reviewed Marked as Reviewed by Fatima on 2022/03/14

Curated date: 2021/12/02

Curator: Itslanapark

Revision editor(s): Fatima, Itslanapark, Peace Sandy, LGeistlinger

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
Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
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
Healthy Controls (HC)
Group 1 name Corresponds to the case (exposed) group for case-control studies
Colorectal Cancer (CC)
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Patients who visited the department of gastroenterology of Tianyou hospital of Wuhan from January 2017 to December 2017 and received colonoscopy and histopathological examination were recruited to the study. Patients with colorectal adenocarcinoma were recorded as the colorectal cancer (CC) group.
Group 0 sample size Number of subjects in the control (unexposed) group
42
Group 1 sample size Number of subjects in the case (exposed) group
51
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
2 months

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V4-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
Mann-Whitney (Wilcoxon)
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

Chao1 Abundance-based estimator of species richness
decreased
Richness Number of species
decreased

Signature 1

Reviewed Marked as Reviewed by Fatima on 2022/03/14

Curated date: 2021/12/09

Curator: Itslanapark

Revision editor(s): Itslanapark

Source: Table 4

Description: Difference analysis at the phylum level between Colorectal Cancer and Healthy Controls. Wilcoxon tests were used to analyze differences in the abundance between the two groups. Significant differences were evaluated by False Discovery Rate.

Abundance in Group 1: increased abundance in Colorectal Cancer (CC)

NCBI Quality ControlLinks
Fusobacteriota
Pseudomonadota
Spirochaetota
Synergistota

Revision editor(s): Itslanapark

Signature 2

Reviewed Marked as Reviewed by Fatima on 2022/03/14

Curated date: 2021/12/10

Curator: Itslanapark

Revision editor(s): Itslanapark

Source: Table 4

Description: Difference analysis at the phylum level between Colorectal Cancer and Healthy Controls. Wilcoxon tests were used to analyze differences in the abundance between the two groups. Significant differences were evaluated by False Discovery Rate.

Abundance in Group 1: decreased abundance in Colorectal Cancer (CC)

NCBI Quality ControlLinks
Bacillota

Revision editor(s): Itslanapark