Microbiome in Colorectal Cancer: How to Get from Meta-omics to Mechanism?

Ternes, Dominik; Karta, Jessica; Tsenkova, Mina; Wilmes, Paul; Haan, Serge; Letellier, Elisabeth

doi:10.1016/j.tim.2020.05.013

Cited by 20 publications

(25 citation statements)

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“…It is unexpected and needs further validation that Faecalibacterium/ Prausnitzii was identified as enriched in non-responders compared to responders (Figure 3) and also enriched in non-responders before nCRT compared to after nCRT (Supplementary Figure 5), since Faecalibacterium/Prausnitzii was suggested to be positively correlated with CD8+ T cell infiltrate in the tumor and favorable responses to anti-PD-1 immunotherapy (Gopalakrishnan and Spencer, 2018). Besides, several bacteria taxa including Clostridium IV and Haemophilus, which were identified as enriched in non-responders, were previously shown to be associated with colorectal cancer patients (Yu et al, 2017;Ternes et al, 2020). Other than the compositional differences of gut microbiota between responders and non-responders, PICRUSt algorithm was utilized to predict functional differences.…”

Section: Discussionmentioning

confidence: 87%

“…The changes in gut microbiome induced by chemotherapy and radiotherapy may contribute to the development of mucositis, particularly diarrhea (Touchefeu et al, 2014). Several bacteria taxa identified were shown to be enriched in colorectal cancer patients (Ternes et al, 2020), including Porphyromonas, Parvimonas, Gemella identified by LefSe (Figure 2), Peptostreptococcus identified by STAMP as enriched before nCRT (Table 2), and Splanchnicus identified as enriched after nCRT by STAMP (Table 3). Prausnitzii, as identified by STAMP as enriched before nCRT, was shown to be reduced in colorectal cancer patients (Burns et al, 2015;Nakatsu et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…It is speculated that factors beyond clinical stage, tumor genomics and germline polymorphism etc (Pezzolo et al, 2015;Dayde et al, 2017) may influence therapeutic responses and toxicities, including host factors such as differential composition of the patients' gut microbiome (Qin et al, 2010;Arumugam et al, 2011;Koren et al, 2013). Several species of commensal bacteria were shown to play potential roles in colorectal carcinogenesis (Yu et al, 2017;Garrett, 2019;Thomas et al, 2019;Wirbel and Pyl, 2019;Wong and Yu, 2019;Ternes et al, 2020;Yang et al, 2020). More strikingly, commensal bacteria were shown to modulate cancer responses to therapy, including chemotherapy and immunotherapy (Iida et al, 2013;Viaud et al, 2013;Roy and Trinchieri, 2017;Gopalakrishnan and Spencer, 2018;Matson et al, 2018;Routy and Le Chatelier, 2018) and to be correlated with toxicities of chemotherapy or radiotherapy (Husebye et al, 1995;Crawford and Gordon, 2005;Manichanh et al, 2008;Wedlake et al, 2008;Wallace et al, 2010;Nam et al, 2013;Ferreira et al, 2014;Wallace et al, 2015;Wang et al, 2015;Reis Ferreira et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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The Gut Microbiome Is Associated With Therapeutic Responses and Toxicities of Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients—A Pilot Study

Shi

Shen

Zou

et al. 2020

Front. Cell. Infect. Microbiol.

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Responses to neoadjuvant chemoradiotherapy (nCRT) and therapy-related toxicities in rectal cancer vary among patients. To provide the individualized therapeutic option for each patient, predictive markers of therapeutic responses and toxicities are in critical need. We aimed to identify the association of gut microbiome with and its potential predictive value for therapeutic responses and toxicities. In the present study, we collected fecal microbiome samples from patients with rectal cancer at treatment initiation and just after nCRT. Taxonomic profiling via 16S ribosomal RNA gene sequencing was performed on all samples. Patients were classified as responders versus non-responders. Patients were grouped into no or mild diarrhea and severe diarrhea. STAMP and high-dimensional class comparisons via linear discriminant analysis of effect size (LEfSe) were used to compare the compositional differences between groups. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was utilized to predict differences in metabolic function between groups. Ten patients were classified as responders and 12 patients were classified as non-responders. Fourteen patients experienced no or mild diarrhea and 8 patients experienced severe diarrhea. Several bacteria taxa with significantly different relative abundances before and after nCRT were identified. Similarly, several baseline bacteria taxa and predicted pathways with significantly different relative abundances between responders and non-responders or between patients no or mild diarrhea and severe diarrhea were identified. Specifically, Shuttleworthia was identified as enriched in responders and several bacteria taxa in the Clostridiales order etc. were identified as enriched in non-responders. Pathways including fatty acid metabolism were predicted to be enriched in responders. In addition, Bifidobacterium, Clostridia, and Bacteroides etc. were identified as enriched in patients with no or mild diarrhea. Pathways including primary bile acid biosynthesis were predicted to be enriched in patients with no or mild diarrhea. Together, the microbiota and pathway markers identified in this study may be utilized to predict the therapeutic responses and therapy-related toxicities of nCRT in patients with rectal cancer. More patient data is needed to verify the current findings and the results of metagenomic, metatranscriptomic, and metabolomic analyses will further mine key biomarkers at the compositional and functional level.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Gut Microbiome Is Associated With Therapeutic Responses and Toxicities of Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients—A Pilot Study

Shi

Shen

Zou

et al. 2020

Front. Cell. Infect. Microbiol.

View full text Add to dashboard Cite

show abstract

“…There is emerging evidence that gut pathological microbial imbalance or dysbiosis occurs in patients with colorectal cancer [1][2][3][4][5]. Changes in the intestinal microbiome can promote chronic in ammatory conditions and the production of carcinogenic molecules, subsequently increasing the risk of colorectal cancer.…”

Section: Introductionmentioning

confidence: 99%

“…These bacteria include Fusobacterium, Peptostreptococcus, Porphyromonas, Prevotella, Parvimonas, Bacteroides, Gemella and the oral microbiome. Their metabolism or immune modulation may directly or indirectly affect the colonial mucosal cells, causing colonic carcinogenesis [2][3][4][5]. However, how gut microbial dysbiosis may be involved in cancer pathogenesis remains undescribed.…”

Section: Introductionmentioning

confidence: 99%

The Gut Microbiota Composition in Patients with Right- and Left-Sided Colorectal Cancer and After Curative Colectomy, as Analyzed by 16S rRNA Gene Amplicon Sequencing

Suga

Mizutani

Fukui

et al. 2022

Preprint

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Background Gut pathological microbial imbalance or dysbiosis is closely associated with colorectal cancer. Although there are observable differences in molecular and clinical characteristics between right-sided and left-sided colon cancer, their gut microbiome differences have not been thoroughly investigated. Furthermore, subsequent changes in microbiota status after partial colectomy remain unknown. We examined the human gut microbiota composition to determine its relationship with colon cancer and partial colon resection according to the location. Methods Stool samples from forty-one subjects (10 in the control group, 10 in the right-sided colon cancer [RCC] group, 6 in the sigmoid colon cancer [SCC] group, 9 in right colon resection [RCR] group and 6 in sigmoid colon resection [SCR] group) were collected, and DNA was extracted. After terminal restriction fragment length polymorphism (T-RFLP) analysis, the samples were subjected to 16S rRNA gene amplicon sequencing and metagenome analysis. Results T-RFLP analysis showed a reduced ratio of Clostridial clusters XIVa in SCC patients and Clostridial clusters IX in RCC patients, although these changes were not seen in RCR or SCR patients. 16S rRNA gene amplicon sequencing demonstrated that the diversity of the gut microbiota in the RCC group was higher than that in the control group and that in the SCR group was significantly higher than that in the RCR group. Principal coordinate analysis (PCoA) revealed significant differences according to the group. Analysis of the microbiota revealed that Firmicutes was significantly dominant in the RCC group and that the SCC group had a higher abundance of Verrucomicrobia. At the genus level, linear discriminant analysis effect size (LEfSe) revealed several bacteria, such as Ruminococcaceae, Streptococcaceae, Clostridiaceae, Gemellaceae, and Desulfovibrio, in the RCC group and several oral microbiomes in the SCC group. Metagenome analysis revealed that cholesterol transport- and metabolism-related enzymes were specifically upregulated in the RCC group and that cobalamin metabolism-related enzymes were downregulated in the SCC group. Conclusion Gut microbial properties differ between right and sigmoid colon cancer patients and between right hemicolectomy and sigmoidectomy patients and may contribute to clinical manifestations.

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Assessment of extracellular vesicle isolation methods from human stool supernatant

Northrop-Albrecht

Taylor

Huang

et al. 2022

J of Extracellular Vesicle

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Extracellular vesicles (EVs) are of growing interest due to their potential diagnostic, disease surveillance, and therapeutic applications. While several studies have evaluated EV isolation methods in various biofluids, there are few if any data on these techniques when applied to stool. The latter is an ideal biospecimen for studying EVs and colorectal cancer (CRC) because the release of tumour markers by luminal exfoliation into stool occurs earlier than vascular invasion. Since EV release is a conserved mechanism, bacteria in stool contribute to the overall EV population. In this study, we assessed five EV separation methods (ultracentrifugation [UC], precipitation [EQ‐O, EQ‐TC], size exclusion chromatography [SEC], and ultrafiltration [UF]) for total recovery, reproducibility, purity, RNA composition, and protein expression in stool supernatant. CD63, TSG101, and ompA proteins were present in EV fractions from all methods except UC. Human (18s) and bacterial (16s) rRNA was detected in stool EV preparations. Enzymatic treatment prior to extraction is necessary to avoid non‐vesicular RNA contamination. Ultrafiltration had the highest recovery, RNA, and protein yield. After assessing purity further, SEC was the isolation method of choice. These findings serve as the groundwork for future studies that use high throughput omics technologies to investigate the potential of stool‐derived EVs as a source for novel biomarkers for early CRC detection.

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Microbiome in Colorectal Cancer: How to Get from Meta-omics to Mechanism?

Cited by 20 publications

References 0 publications

The Gut Microbiome Is Associated With Therapeutic Responses and Toxicities of Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients—A Pilot Study

The Gut Microbiome Is Associated With Therapeutic Responses and Toxicities of Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients—A Pilot Study

The Gut Microbiota Composition in Patients with Right- and Left-Sided Colorectal Cancer and After Curative Colectomy, as Analyzed by 16S rRNA Gene Amplicon Sequencing

Assessment of extracellular vesicle isolation methods from human stool supernatant

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