Colorectal tumour mucosa microbiome is enriched in oral pathogens and defines three subtypes that correlate with markers of tumour progression

Zwinsová, Barbora; Petrov, Viacheslav; Hrivňáková, Martina; Smatana, Stanislav; Micenková, Lenka; Kazdová, Natálie; Popovici, Vlad; Hrstka, Roman; Šefr, Roman; Bencsiková, Beatrix; Zdražilová-Dubská, Lenka; Brychtová, Veronika; Nenutil, Rudolf; Vídeňská, Petra; Budinská, Eva

doi:10.3390/cancers13194799

Article (Scientific journals)

Colorectal tumour mucosa microbiome is enriched in oral pathogens and defines three subtypes that correlate with markers of tumour progression

Zwinsová, Barbora; Petrov, Viacheslav; Hrivňáková, Martina et al.

2021 • In Cancers, 13 (19), p. 4799

Peer Reviewed verified by ORBi

Permalink
https://hdl.handle.net/2268/291246

DOI
10.3390/cancers13194799

Files (1)Send to Details Statistics Bibliography Similar publications

Files

Full Text

cancers-13-04799-v3.pdf

Author postprint (4.67 MB)

Download

All documents in ORBi are protected by a user license.

Send to

RIS BibTex APA Chicago Permalink X Linkedin

Details

Keywords :

16S rRNA gene; Colorectal cancer; Microbial subtypes; Tumour microbiome; Oncology; Cancer Research

Abstract :

[en] Long-term dysbiosis of the gut microbiome has a significant impact on colorectal cancer (CRC) progression and explains part of the observed heterogeneity of the disease. Even though the shifts in gut microbiome in the normal-adenoma-carcinoma sequence were described, the landscape of the microbiome within CRC and its associations with clinical variables remain under-explored. We performed 16S rRNA gene sequencing of paired tumour tissue, adjacent visually normal mucosa and stool swabs of 178 patients with stage 0–IV CRC to describe the tumour microbiome and its association with clinical variables. We identified new genera associated either with CRC tumour mucosa or CRC in general. The tumour mucosa was dominated by genera belonging to oral patho-gens. Based on the tumour microbiome, we stratified CRC patients into three subtypes, significantly associated with prognostic factors such as tumour grade, sidedness and TNM staging, BRAF mutation and MSI status. We found that the CRC microbiome is strongly correlated with the grade, location and stage, but these associations are dependent on the microbial environment. Our study opens new research avenues in the microbiome CRC biomarker detection of disease progression while identifying its limitations, suggesting the need for combining several sampling sites (e.g., stool and tumour swabs).

Disciplines :

Microbiology

Author, co-author :

Zwinsová, Barbora ; Research Centre for Applied Molecular Oncology (RECAMO), Department, Masaryk Memorial Cancer Institute, University, Brno, Czech Republic ; Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Brno, Czech Republic ; Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic

Petrov, Viacheslav ; Université de Liège - ULiège > GIGA > GIGA Medical Genomics - Unit of Animal Genomics

Hrivňáková, Martina; Research Centre for Applied Molecular Oncology (RECAMO), Department, Masaryk Memorial Cancer Institute, University, Brno, Czech Republic ; Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Brno, Czech Republic

Smatana, Stanislav; Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Brno, Czech Republic ; Faculty of Information Technology, IT4Innovations Centre of Excellence, Brno University of Technology, Brno, Czech Republic

Micenková, Lenka; Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Brno, Czech Republic

Kazdová, Natálie; Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Brno, Czech Republic

Popovici, Vlad; Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Brno, Czech Republic

Hrstka, Roman ; Research Centre for Applied Molecular Oncology (RECAMO), Department, Masaryk Memorial Cancer Institute, University, Brno, Czech Republic

Šefr, Roman; Research Centre for Applied Molecular Oncology (RECAMO), Department, Masaryk Memorial Cancer Institute, University, Brno, Czech Republic

Bencsiková, Beatrix; Research Centre for Applied Molecular Oncology (RECAMO), Department, Masaryk Memorial Cancer Institute, University, Brno, Czech Republic

More authors (5 more)

Language :

English

Title :

Colorectal tumour mucosa microbiome is enriched in oral pathogens and defines three subtypes that correlate with markers of tumour progression

Publication date :

October 2021

Journal title :

Cancers

eISSN :

2072-6694

Publisher :

MDPI

Volume :

Issue :

Pages :

4799

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.mdpi.com/2072-6694/13/19/4799/pdf

European Projects :

H2020 - 825410 - ONCOBIOME - Gut OncoMicrobiome Signatures (GOMS) associated with cancer incidence, prognosis and prediction of treatment response.

Funders :

MZCR - Ministerstvo zdravotnictví České republiky
EU - European Union

Funding text :

Funding: Authors thanks to Research Infrastructure RECETOX RI (No LM2018121) financed by the Ministry of Education, Youth and Sports, and Operational Programme Research, Development and Innovation - project CETOCOEN EXCELLENCE (No CZ.02.1.01/0.0/0.0/17_043/0009632) for supportive background. This work received funding from the Ministry of Health of the Czech Republic (project AZV 16-31966A) and the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825410. This publication reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains. Computational resources were supplied by the project "e-Infrastruktura CZ" (e-INFRA LM2018140) provided within the program Projects of Large Research, Development, and Innovations Infrastructures. The work was supported by the project BBMRI-CZ no. LM2018125.Authors thanks to Research Infrastructure RECETOX RI (No LM2018121) financed by the Ministry of Education, Youth and Sports, and Operational Programme Research, Development and Innovation-project CETOCOEN EXCELLENCE (No CZ.02.1.01/0.0/0.0/17_043/0009632) for supportive background. This work received funding from the Ministry of Health of the Czech Republic (project AZV 16-31966A) and the European Union?s Horizon 2020 research and innovation programme under grant agreement No 825410. This publication reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains. Computational resources were supplied by the project "e-Infrastruktura CZ" (e-INFRA LM2018140) provided within the program Projects of Large Research, Development, and Innovations Infrastructures. The work was supported by the project BBMRI-CZ no. LM2018125.The authors acknowledge the help of the volunteers enrolled in this study. We thank the ONCOBIOME researchers for their insight and suggestions.

Available on ORBi :

since 24 May 2022

Statistics

Number of views

35 (6 by ULiège)

Number of downloads

25 (1 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

OpenAlex citations

Bibliography

Ferlay, J.; Colombet, M.; Soerjomataram, I.; Dyba, T.; Randi, G.; Bettio, M.; Gavin, A.; Visser, O.; Bray, F. Cancer incidence and mortality patterns in Europe: Estimates for 40 countries and 25 major cancers in 2018. Eur. J. Cancer 2018, 103, 356–387, doi:10.1016/j.ejca.2018.07.005.
Punt, C.J.A.; Koopman, M.; Vermeulen, L. From tumour heterogeneity to advances in precision treatment of colorectal cancer. Nat. Rev. Clin. Oncol. 2017, 14, 235–246, doi:10.1038/nrclinonc.2016.171.
Van Der Jeught, K.; Xu, H.-C.; Li, Y.-J.; Lu, X.-B.; Ji, G. Drug resistance and new therapies in colorectal cancer. World J. Gastro-enterol. 2018, 24, 3834–3848, doi:10.3748/wjg.v24.i34.3834.
Ahn, J.; Sinha, R.; Pei, Z.; Dominianni, C.; Wu, J.; Shi, J.; Goedert, J.J.; Hayes, R.; Yang, L. Human Gut Microbiome and Risk for Colorectal Cancer. J. Natl. Cancer Inst. 2013, 105, 1907–1911, doi:10.1093/jnci/djt300.
Arthur, J.; Perez-Chanona, E.; Mühlbauer, M.; Tomkovich, S.; Uronis, J.M.; Fan, T.-J.; Campbell, B.J.; Abujamel, T.; Dogan, B.; Rogers, A.B.; et al. Intestinal Inflammation Targets Cancer-Inducing Activity of the Microbiota. Science 2012, 338, 120–123, doi:10.1126/science.1224820.
Balamurugan, R.; Rajendiran, E.; George, S.; Samuel, G.V.; Ramakrishna, B. Real-time polymerase chain reaction quantification of specific butyrate-producing bacteria,DesulfovibrioandEnterococcus faecalisin the feces of patients with colorectal cancer. J. Gastroenterol. Hepatol. 2008, 23, 1298–1303, doi:10.1111/j.1440-1746.2008.05490.x.
Chen, J.; Young, S.M.; Allen, C.; Seeber, A.; Péli-Gulli, M.-P.; Panchaud, N.; Waller, A.; Ursu, O.; Yao, T.; Golden, J.E.; et al. Identification of a Small Molecule Yeast TORC1 Inhibitor with a Multiplex Screen Based on Flow Cytometry. ACS Chem. Biol. 2012, 7, 715–722, doi:10.1021/cb200452r.
Chen, W.; Liu, F.; Ling, Z.; Tong, X.; Xiang, C. Human Intestinal Lumen and Mucosa-Associated Microbiota in Patients with Colorectal Cancer. PLoS ONE 2012, 7, e39743, doi:10.1371/journal.pone.0039743.
Cipe, G.; Idiz, U.O.; Firat, D.; Bektasoglu, H. Relationship between intestinal microbiota and colorectal cancer. World J. Gastro-intest. Oncol. 2015, 7, 233–240, doi:10.4251/wjgo.v7.i10.233.
Kostic, A.; Chun, E.; Robertson, L.; Glickman, J.N.; Gallini, C.A.; Michaud, M.; Clancy, T.E.; Chung, D.C.; Lochhead, P.; Hold, G.; et al. Fusobacterium nucleatum Potentiates Intestinal Tumorigenesis and Modulates the Tumor-Immune Microenviron-ment. Cell Host Microbe 2013, 14, 207–215, doi:10.1016/j.chom.2013.07.007.
Lu, Y.; Chen, J.; Zheng, J.; Hu, G.; Wang, J.; Huang, C.; Lou, L.; Wang, X.; Zeng, Y. Mucosal adherent bacterial dysbiosis in patients with colorectal adenomas. Sci. Rep. 2016, 6, 26337, doi:10.1038/srep26337.
Marchesi, J.R.; Dutilh, B.E.; Hall, N.; Peters, W.H.M.; Roelofs, R.; Boleij, A.; Tjalsma, H. Towards the Human Colorectal Cancer Microbiome. PLoS ONE 2011, 6, e20447, doi:10.1371/journal.pone.0020447.
Nakatsu, G.; Li, X.; Zhou, H.; Sheng, J.; Wong, S.H.; Wu, W.K.K.; Ng, S.C.; Tsoi, H.; Dong, Y.; Zhang, N.; et al. Gut mucosal microbiome across stages of colorectal carcinogenesis. Nat. Commun. 2015, 6, 8727, doi:10.1038/ncomms9727.
Rubinstein, M.R.; Wang, X.; Liu, W.; Hao, Y.; Cai, G.; Han, Y.W. Fusobacterium nucleatum Promotes Colorectal Carcinogenesis by Modulating E-Cadherin/β-Catenin Signaling via its FadA Adhesin. Cell Host Microbe 2013, 14, 195–206, doi:10.1016/j.chom.2013.07.012.
Sobhani, I.; Tap, J.; Roudot-Thoraval, F.; Roperch, J.P.; Letulle, S.; Langella, P.; Corthier, G.; Van Nhieu, J.T.; Furet, J.-P. Microbial Dysbiosis in Colorectal Cancer (CRC) Patients. PLoS ONE 2011, 6, e16393, doi:10.1371/journal.pone.0016393.
Viljoen, K.S.; Dakshinamurthy, A.; Goldberg, P.; Blackburn, J.M. Quantitative Profiling of Colorectal Cancer-Associated Bacteria Reveals Associations between Fusobacterium spp., Enterotoxigenic Bacteroides fragilis (ETBF) and Clinicopathological Features of Colorectal Cancer. PLoS ONE 2015, 10, e0119462, doi:10.1371/journal.pone.0119462.
Wang, T.; Cai, G.; Qiu, Y.; Fei, N.; Zhang, M.; Pang, X.; Jia, W.; Cai, S.; Zhao, L. Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers. ISME J. 2011, 6, 320–329, doi:10.1038/ismej.2011.109.
Wu, N.; Yang, X.; Zhang, R.; Li, J.; Xiao, X.; Hu, Y.; Chen, Y.; Yang, F.; Lu, N.; Wang, Z.; et al. Dysbiosis Signature of Fecal Microbiota in Colorectal Cancer Patients. Microb. Ecol. 2013, 66, 462–470, doi:10.1007/s00248-013-0245-9.
Yang, J.; McDowell, A.; Kim, E.K.; Seo, H.; Lee, W.H.; Moon, C.-M.; Kym, S.-M.; Lee, D.H.; Park, Y.S.; Jee, Y.-K.; et al. Development of a colorectal cancer diagnostic model and dietary risk assessment through gut microbiome analysis. Exp. Mol. Med. 2019, 51, 1–15, doi:10.1038/s12276-019-0313-4.
Yu, J.; Feng, Q.; Wong, S.H.; Zhang, D.; Liang, Q.Y.; Qin, Y.; Tang, L.; Zhao, H.; Stenvang, J.; Li, Y.; et al. Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer. Gut 2017, 66, 70–78, doi:10.1136/gutjnl-2015-309800.
Zackular, J.P.; Baxter, N.; Iverson, K.D.; Sadler, W.D.; Petrosino, J.F.; Chen, G.Y.; Schloss, P.D. The Gut Microbiome Modulates Colon Tumorigenesis. mBio 2013, 4, e00692-13, doi:10.1128/mbio.00692-13.
Zackular, J.; Rogers, M.; Ruffin, M.; Schloss, P.D. The Human Gut Microbiome as a Screening Tool for Colorectal Cancer. Cancer Prev. Res. 2014, 7, 1112–1121, doi:10.1158/1940-6207.capr-14-0129.
Vaupel, P.; Harrison, L. Tumor Hypoxia: Causative Factors, Compensatory Mechanisms, and Cellular Response. Oncologist 2004, 9 (Suppl. S5), 4–9, doi:10.1634/theoncologist.9-90005-4.
Louis, P.; Hold, G.; Flint, H.J. The gut microbiota, bacterial metabolites and colorectal cancer. Nat. Rev. Microbiol. 2014, 12, 661– 672, doi:10.1038/nrmicro3344.
Tlaskalova-Hogenova, H.; Vannucci, L.; Klimesova, K.; Stepankova, R.; Krizan, J.; Kverka, M. Microbiome and Colorectal Car-cinoma. Cancer J. 2014, 20, 217–224, doi:10.1097/ppo.0000000000000052.
Xiao, Y.; Freeman, G.J. The Microsatellite Instable Subset of Colorectal Cancer Is a Particularly Good Candidate for Checkpoint Blockade Immunotherapy. Cancer Discov. 2015, 5, 16–18, doi:10.1158/2159-8290.cd-14-1397.
Tjalsma, H.; Boleij, A.; Marchesi, J.R.; Dutilh, B.E. A bacterial driver–passenger model for colorectal cancer: Beyond the usual suspects. Nat. Rev. Genet. 2012, 10, 575–582, doi:10.1038/nrmicro2819.
Pennisi, E. Cancer Therapies Use a Little Help from Microbial Friends. Science 2013, 342, 921, doi:10.1126/science.342.6161.921.
Thomas, A.M.; Manghi, P.; Asnicar, F.; Pasolli, E.; Armanini, F.; Zolfo, M.; Beghini, F.; Manara, S.; Karcher, N.; Pozzi, C.; et al. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with cho-line degradation. Nat. Med. 2019, 25, 667–678, doi:10.1038/s41591-019-0405-7.
Feng, Q.; Liang, S.; Jia, H.; Stadlmayr, A.; Tang, L.; Lan, Z.; Zhang, D.; Xia, H.; Xu, X.; Jie, Z.; et al. Gut microbiome development along the colorectal adenoma–carcinoma sequence. Nat. Commun. 2015, 6, 6528, doi:10.1038/ncomms7528.
Dejea, C.M.; Wick, E.C.; Hechenbleikner, E.M.; White, J.R.; Welch, J.L.M.; Rossetti, B.J.; Peterson, S.N.; Snesrud, E.C.; Borisy, G.G.; Lazarev, M.; et al. Microbiota organization is a distinct feature of proximal colorectal cancers. Proc. Natl. Acad. Sci. USA 2014, 111, 18321–18326, doi:10.1073/pnas.1406199111.
Zeller, G.; Tap, J.; Voigt, A.Y.; Sunagawa, S.; Kultima, J.R.; Costea, P.I.; Amiot, A.; Böhm, J.; Brunetti, F.; Habermann, N.; et al. Potential of fecal microbiota for early-stage detection of colorectal cancer. Mol. Syst. Biol. 2014, 10, 766, doi:10.15252/msb.20145645.
Yang, Y.; Cai, Q.; Shu, X.; Steinwandel, M.D.; Blot, W.J.; Zheng, W.; Long, J. Prospective study of oral microbiome and colorectal cancer risk in low-income and African American populations. Int. J. Cancer 2019, 144, 2381–2389, doi:10.1002/ijc.31941.
Liu, C.; Zhang, Y.; Shang, Y.; Wu, B.; Yang, E.; Luo, Y.-Y.; Li, X. Intestinal bacteria detected in cancer and adjacent tissue from patients with colorectal cancer. Oncol. Lett. 2018, 17, 1115–1127, doi:10.3892/ol.2018.9714.
Pu, L.Z.C.T.; Yamamoto, K.; Honda, T.; Nakamura, M.; Yamamura, T.; Hattori, S.; Burt, A.D.; Singh, R.; Hirooka, Y.; Fujishiro, M. Microbiota profile is different for early and invasive colorectal cancer and is consistent throughout the colon. J. Gastroenterol. Hepatol. 2020, 35, 433–437, doi:10.1111/jgh.14868.
Flemer, B.; Lynch, D.B.; Brown, J.M.R.; Jeffery, I.; Ryan, F.; Claesson, M.; O’Riordain, M.; Shanahan, F.; O’Toole, P.W. Tumour-associated and non-tumour-associated microbiota in colorectal cancer. Gut 2017, 66, 633–643, doi:10.1136/gutjnl-2015-309595.
Egao, Z.; Eguo, B.; Egao, R.; Ezhu, Q.; Eqin, H. Microbiota disbiosis is associated with colorectal cancer. Front. Microbiol. 2015, 6, 20, doi:10.3389/fmicb.2015.00020.
Li, E.; Hamm, C.M.; Gulati, A.S.; Sartor, R.B.; Chen, H.; Wu, X.; Zhang, T.; Rohlf, F.J.; Zhu, W.; Gu, C.; et al. Inflammatory Bowel Diseases Phenotype, C. difficile and NOD2 Genotype Are Associated with Shifts in Human Ileum Associated Microbial Com-position. PLoS ONE 2012, 7, e26284, doi:10.1371/journal.pone.0026284.
Han, S.; Wu, W.; Da, M.; Xu, J.; Zhuang, J.; Zhang, L.; Zhang, X.; Yang, X. Adequate Lymph Node Assessments and Investigation of Gut Microorganisms and Microbial Metabolites in Colorectal Cancer. OTT 2020, 13, 1893–1906, doi:10.2147/OTT.S242017.
Wu, Y.; Shi, L.; Li, Q.; Wu, J.; Peng, W.; Li, H.; Chen, K.; Ren, Y.; Fu, X. Microbiota Diversity in Human Colorectal Cancer Tissues Is Associated with Clinicopathological Features. Nutr. Cancer 2019, 71, 214–222, doi:10.1080/01635581.2019.1578394.
Apprill, A.; McNally, S.; Parsons, R.; Weber, L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 2015, 75, 129–137, doi:10.3354/ame01753.
Caporaso, J.G.; Lauber, C.L.; Walters, W.A.; Berg-Lyons, D.; Lozupone, C.A.; Turnbaugh, P.J.; Fierer, N.; Knight, R. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 2011, 108, 4516–4522, doi:10.1073/pnas.1000080107.
Callahan, B.J.; McMurdie, P.; Rosen, M.J.; Han, A.W.; Johnson, A.J.A.; Holmes, S. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 2016, 13, 581–583, doi:10.1038/nmeth.3869.
Aronesty, E. Comparison of Sequencing Utility Programs. TOBIOIJ 2013, 7, 1–8, doi:10.2174/1875036201307010001.
Pruesse, E.; Quast, C.; Knittel, K.; Fuchs, B.M.; Ludwig, W.; Peplies, J.; Glöckner, F.O. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007, 35, 7188–7196, doi:10.1093/nar/gkm864.
Edgar, R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010, 26, 2460–2461, doi:10.1093/bioin-formatics/btq461.
Caporaso, J.G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F.; Costello, E.K.; Fierer, N.; Peña, A.G.; Goodrich, J.K.; Gordon, J.I.; et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 2010, 7, 335–336, doi:10.1038/nmeth.f.303.
Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410, doi:10.1016/s0022-2836(05)80360-2.
Lozupone, C.; Knight, R. UniFrac: A New Phylogenetic Method for Comparing Microbial Communities. Appl. Environ. Micro-biol. 2005, 71, 8228–8235, doi:10.1128/aem.71.12.8228-8235.2005.
Douglas, G.M.; Maffei, V.J.; Zaneveld, J.R.; Yurgel, S.N.; Brown, J.R.; Taylor, C.M.; Huttenhower, C.; Langille, M.G.I. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 2020, 38, 685–688, doi:10.1038/s41587-020-0548-6.
Aitchison, J. The Statistical Analysis of Compositional Data. J. R. Stat. Soc. Ser. B Methodol. 1982, 44, 139–160, doi:10.1111/j.2517-6161.1982.tb01195.x.
Gloor, G.B.; Wu, J.R.; Pawlowsky-Glahn, V.; Egozcue, J.J. It’s all relative: Analyzing microbiome data as compositions. Ann. Epidemiol. 2016, 26, 322–329, doi:10.1016/j.annepidem.2016.03.003.
Martín-Fernández, J.-A.; Hron, K.; Templ, M.; Filzmoser, P.; Palarea-Albaladejo, J. Bayesian-multiplicative treatment of count zeros in compositional data sets. Stat. Model. Int. J. 2015, 15, 134–158, doi:10.1177/1471082x14535524.
Tsilimigras, M.C.; Fodor, A.A. Compositional data analysis of the microbiome: Fundamentals, tools, and challenges. Ann. Epi-demiol. 2016, 26, 330–335, doi:10.1016/j.annepidem.2016.03.002.
Oaksen, J.; Blanchet, F.G.; Friendly, M.; Kindt, R.; Legendre, P.; McGlinn, D.; Minchin, P.R.; O’Hara, R.B.; Simpson, G.L.; Soly-mos, P.; et al. Vegan: Community Ecology Package. R Package. 2019. Available online: http://cran.rproject.org/package=vegan (accessed on 4 July 2020).
Comas-Cufí, M.. R Package. 2020. Available online: https://rdrr.io/cran/coda.base/(accessed on 4 July 2020.
Kloke, J.D.; McKean, J.W. Rfit: Rank-Based Estimation for Linear Models. R J. 2012, 4, 57–64.
Benjamini, Y.; Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J. R. Stat. Soc. Ser. B Methodol. 1995, 57, 289–300, doi:10.1111/j.2517-6161.1995.tb02031.x.
Gu, Z.; Gu, L.; Eils, R.; Schlesner, M.; Brors, B. circlize implements and enhances circular visualization in R. Bioinformatics 2014, 30, 2811–2812, doi:10.1093/bioinformatics/btu393.
Gu, Z.; Eils, R.; Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinfor-matics 2016, 32, 2847–2849, doi:10.1093/bioinformatics/btw313.
Warnes, G.R.; Bolker, B.; Bonebakker, L.; Gentleman, R.; Liaw, W.H.A.; Lumley, T.; Maechler, M.; Magnusson, A.; Moeller, S.; Schwartz, M.; et al. Gplots: Various R Programming Tools for Plotting Data; R Package. 2020. Available online: https://rdrr.io/cran/gplots/(accessed on 4 July 2020).
Wickham, H. Ggplot2: Elegant Graphics for Data Analysis, 2nd. ed.; Springer: Cham, Switzerland, 2016; ISBN 978-3-319-24277-4.
Wray, C.M.; Ziogas, A.; Hinojosa, M.W.; Le, H.; Stamos, M.J.; Zell, J.A. Tumor Subsite Location Within the Colon Is Prognostic for Survival After Colon Cancer Diagnosis. Dis. Colon Rectum 2009, 52, 1359–1366, doi:10.1007/dcr.0b013e3181a7b7de.
Pasolli, E.; Schiffer, L.; Manghi, P.; Renson, A.; Obenchain, V.; Truong, D.T.; Beghini, F.; Malik, F.; Ramos, M.; Dowd, J.; et al. Accessible, curated metagenomic data through ExperimentHub. Nat. Methods 2017, 14, 1023–1024, doi:10.1038/nmeth.4468.
De Almeida, C.V.; Lulli, M.; Di Pilato, V.; Schiavone, N.; Russo, E.; Nannini, G.; Baldi, S.; Borrelli, R.; Bartolucci, G.; Menicatti, M.; et al. Differential Responses of Colorectal Cancer Cell Lines to Enterococcus faecalis’ Strains Isolated from Healthy Donors and Colorectal Cancer Patients. JCM 2019, 8, 388, doi:10.3390/jcm8030388.
Gupta, A.; Dhakan, D.B.; Maji, A.; Saxena, R.; Visnu Prasoodanan, P.K.; Mahajan, S.; Pulikkan, J.; Kurian, J.; Gomez, A.M.; Scaria, J.; et al. Association of Flavonifractor plautii, a Flavonoid-Degrading Bacterium, with the Gut Microbiome of Colorectal Cancer Patients in India. mSystems 2019, 4, doi:10.1128/msystems.00438-19.
Ai, D.; Pan, H.; Li, X.; Gao, Y.; Liu, G.; Xia, L.C. Identifying Gut Microbiota Associated with Colorectal Cancer Using a Zero-Inflated Lognormal Model. Front. Microbiol. 2019, 10, 826, doi:10.3389/fmicb.2019.00826.
Ito, M.; Kanno, S.; Nosho, K.; Sukawa, Y.; Mitsuhashi, K.; Kurihara, H.; Igarashi, H.; Takahashi, T.; Tachibana, M.; Takahashi, H.; et al. Association ofFusobacterium nucleatumwith clinical and molecular features in colorectal serrated pathway. Int. J. Cancer 2015, 137, 1258–1268, doi:10.1002/ijc.29488.
Bahmani, S.; Azarpira, N.; Moazamian, E. Anti-colon cancer activity of Bifidobacterium metabolites on colon cancer cell line SW742. Turk. J. Gastroenterol. 2019, 30, 835–842, doi:10.5152/tjg.2019.18451.
Mangifesta, M.; Mancabelli, L.; Milani, C.; Gaiani, F.; De’Angelis, N.; De’Angelis, G.L.; Van Sinderen, D.; Ventura, M.; Turroni, F. Mucosal microbiota of intestinal polyps reveals putative biomarkers of colorectal cancer. Sci. Rep. 2018, 8, 1–9, doi:10.1038/s41598-018-32413-2.
Parisa, A.; Roya, G.; Mahdi, R.; Shabnam, R.; Maryam, E.; Malihe, T. Anti-cancer effects of Bifidobacterium species in colon cancer cells and a mouse model of carcinogenesis. PLoS ONE 2020, 15, e0232930, doi:10.1371/journal.pone.0232930.
Sivan, A.; Corrales, L.; Hubert, N.; Williams, J.B.; Aquino-Michaels, K.; Earley, Z.M.; Benyamin, F.W.; Lei, Y.M.; Jabri, B.; Alegre, M.-L.; et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 2015, 350, 1084–1089, doi:10.1126/science.aac4255.
Koncina, E.; Haan, S.; Rauh, S.; Letellier, E. Prognostic and Predictive Molecular Biomarkers for Colorectal Cancer: Updates and Challenges. Cancers 2020, 12, 319, doi:10.3390/cancers12020319.
Guinney, J.; Dienstmann, R.; Wang, X.; De Reyniès, A.; Schlicker, A.; Soneson, C.; Marisa, L.; Roepman, P.; Nyamundanda, G.; Angelino, P.; et al. The consensus molecular subtypes of colorectal cancer. Nat. Med. 2015, 21, 1350–1356, doi:10.1038/nm.3967.
Koliarakis, I.; Messaritakis, I.; Nikolouzakis, T.K.; Hamilos, G.; Souglakos, J.; Tsiaoussis, J. Oral Bacteria and Intestinal Dysbiosis in Colorectal Cancer. Int. J. Mol. Sci. 2019, 20, 4146, doi:10.3390/ijms20174146.
Long, X.; Wong, C.C.; Tong, L.; Chu, E.S.H.; Szeto, C.H.; Go, M.Y.Y.; Coker, O.O.; Chan, A.W.H.; Chan, F.K.; Sung, J.J.Y.; et al. Peptostreptococcus anaerobius promotes colorectal carcinogenesis and modulates tumour immunity. Nat. Microbiol. 2019, 4, 2319–2330, doi:10.1038/s41564-019-0541-3.
Abed, J.; Emgård, J.E.; Zamir, G.; Faroja, M.; Almogy, G.; Grenov, A.; Sol, A.; Naor, R.; Pikarsky, E.; Atlan, K.A.; et al. Fap2 Mediates Fusobacterium nucleatum Colorectal Adenocarcinoma Enrichment by Binding to Tumor-Expressed Gal-GalNAc. Cell Host Microbe 2016, 20, 215–225, doi:10.1016/j.chom.2016.07.006.
Zou, X.; Feng, B.; Dong, T.; Yan, G.; Tan, B.; Shen, H.; Huang, A.; Zhang, X.; Zhang, M.; Yang, P.; et al. Up-regulation of type I collagen during tumorigenesis of colorectal cancer revealed by quantitative proteomic analysis. J. Proteom. 2013, 94, 473–485, doi:10.1016/j.jprot.2013.10.020.
Takahashi, N. Microbial ecosystem in the oral cavity: Metabolic diversity in an ecological niche and its relationship with oral diseases. Int. Congr. Ser. 2005, 1284, 103–112, doi:10.1016/j.ics.2005.06.071.
Eley, B.M.; Cox, S.W. Proteolytic and hydrolytic enzymes from putative periodontal pathogens: characterization, molecular genetics, effects on host defenses and tissues and detection in gingival crevice fluid. Periodontol. 2000 2003, 31, 105–124, doi:10.1034/j.1600-0757.2003.03107.x.
Potempa, J.; Sroka, A.; Imamura, T.; Travis, J. Gingipains, the major cysteine proteinases and virulence factors of Porphyromo-nas gingivalis: Structure, function and assembly of multidomain protein complexes. Curr. Protein Pept. Sci. 2003, 4, 397–407, doi:10.2174/1389203033487036.
Gonçalves, L.F.H.; Fermiano, D.; Feres, M.; Figueiredo, L.C.; Teles, F.R.P.; Mayer, M.P.A.; Faveri, M. Levels ofSelenomonasspe-cies in generalized aggressive periodontitis. J. Periodontal Res. 2012, 47, 711–718, doi:10.1111/j.1600-0765.2012.01485.x.
Scher, J.U.; Ubeda, C.; Equinda, M.; Khanin, R.; Buischi, Y.; Viale, A.; Lipuma, L.; Attur, M.; Pillinger, M.; Weissmann, G.; et al. Periodontal disease and the oral microbiota in new-onset rheumatoid arthritis. Arthritis Rheum. 2012, 64, 3083–3094, doi:10.1002/art.34539.
Herbert, B.A.; Novince, C.M.; Kirkwood, K.L. Aggregatibacter actinomycetemcomitans, a potent immunoregulator of the periodontal host defense system and alveolar bone homeostasis. Mol. Oral Microbiol. 2016, 31, 207–227, doi:10.1111/omi.12119.
Lin, W.-R.; Chen, Y.-S.; Liu, Y.-C. Cellulitis and Bacteremia Caused by Bergeyella zoohelcum. J. Formos. Med. Assoc. 2007, 106, 573–576, doi:10.1016/s0929-6646(07)60008-4.
Peel, M.M.; Hornidge, K.A.; Luppino, M.; Stacpoole, A.M.; Weaver, R.E. Actinobacillus spp. and related bacteria in infected wounds of humans bitten by horses and sheep. J. Clin. Microbiol. 1991, 29, 2535–2538, doi:10.1128/jcm.29.11.2535-2538.1991.
Sohn, K.M.; Huh, K.; Baek, J.-Y.; Kim, Y.-S.; Kang, C.-I.; Peck, K.R.; Lee, N.Y.; Song, J.-H.; Ko, K.S.; Chung, D.R. A new causative bacteria of infective endocarditis, Bergeyella cardium sp. nov. Diagn. Microbiol. Infect. Dis. 2015, 81, 213–216, doi:10.1016/j.diag-microbio.2014.12.001.
Friis-Møller, A.; Christensen, J.J.; Fussing, V.; Hesselbjerg, A.; Christiansen, J.; Bruun, B. Clinical Significance and Taxonomy of Actinobacillus hominis. J. Clin. Microbiol. 2001, 39, 930–935, doi:10.1128/jcm.39.3.930-935.2001.
Zha, Z.; Lv, Y.; Tang, H.; Li, T.; Miao, Y.; Cheng, J.; Wang, G.; Tan, Y.; Zhu, Y.; Xing, X.; et al. An orally administered butyrate-releasing xylan derivative reduces inflammation in dextran sulphate sodium-induced murine colitis. Int. J. Biol. Macromol. 2020, 156, 1217–1233, doi:10.1016/j.ijbiomac.2019.11.159.
Kelly, T.N.; Bazzano, L.A.; Ajami, N.J.; He, H.; Zhao, J.; Petrosino, J.F.; Correa, A.; He, J. Gut Microbiome Associates with Life-time Cardiovascular Disease Risk Profile Among Bogalusa Heart Study Participants. Circ. Res. 2016, 119, 956–964, doi:10.1161/circresaha.116.309219.
Niederseer, D.; Bracher, I.; Stadlmayr, A.; Huber-Schönauer, U.; Plöderl, M.; Obeid, S.; Schmied, C.; Hammerl, S.; Stickel, F.; Lederer, D.; et al. Association between Cardiovascular Risk and Diabetes with Colorectal Neoplasia: A Site-Specific Analysis. J. Clin. Med. 2018, 7, 484, doi:10.3390/jcm7120484.
Mei, Q.-X.; Huang, C.-L.; Luo, S.-Z.; Zhang, X.-M.; Zeng, Y.; Lu, Y.-Y. Characterization of the duodenal bacterial microbiota in patients with pancreatic head cancer vs. healthy controls. Pancreatology 2018, 18, 438–445, doi:10.1016/j.pan.2018.03.005.
Gao, R.; Kong, C.; Huang, L.; Li, H.; Qu, X.; Liu, Z.; Lan, P.; Wang, J.; Qin, H. Mucosa-associated microbiota signature in colo-rectal cancer. Eur. J. Clin. Microbiol. Infect. Dis. 2017, 36, 2073–2083, doi:10.1007/s10096-017-3026-4.
Xi, Y.; Yuefen, P.; Wei, W.; Quan, Q.; Jing, Z.; Jiamin, X.; Shuwen, H. Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer. J. Transl. Med. 2019, 17, 1–22, doi:10.1186/s12967-019-2102-1.
Kamphuis, J.; Mercier-Bonin, M.; Eutamène, H.; Théodorou, V. Mucus organisation is shaped by colonic content; a new view. Sci. Rep. 2017, 7, 1–13, doi:10.1038/s41598-017-08938-3.
Paone, P.; Cani, P.D. Mucus barrier, mucins and gut microbiota: The expected slimy partners? Gut 2020, 69, 2232–2243, doi:10.1136/gutjnl-2020-322260.
Luu, T.H.; Michel, C.; Bard, J.-M.; Dravet, F.; Nazih, H.; Bobin-Dubigeon, C. Intestinal Proportion ofBlautiasp. is Associated with Clinical Stage and Histoprognostic Grade in Patients with Early-Stage Breast Cancer. Nutr. Cancer 2017, 69, 267–275, doi:10.1080/01635581.2017.1263750.
Wu, A.H.; Tseng, C.; Vigen, C.; Yu, Y.; Cozen, W.; Garcia, A.A.; Spicer, D. Gut microbiome associations with breast cancer risk factors and tumor characteristics: A pilot study. Breast Cancer Res. Treat. 2020, 182, 451–463, doi:10.1007/s10549-020-05702-6.
Zhuang, H.; Cheng, L.; Wang, Y.; Zhang, Y.-K.; Zhao, M.-F.; Liang, G.-D.; Zhang, M.-C.; Li, Y.-G.; Zhao, J.-B.; Gao, Y.-N.; et al. Dysbiosis of the Gut Microbiome in Lung Cancer. Front. Cell. Infect. Microbiol. 2019, 9, 112, doi:10.3389/fcimb.2019.00112.
Budinska, E.; Popovici, V.; Tejpar, S.; D’Ario, G.; Lapique, N.; Sikora, K.O.; Di Narzo, A.F.; Yan, P.; Hodgson, J.G.; Weinrich, S.; et al. Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer. J. Pathol. 2013, 231, 63–76, doi:10.1002/path.4212.
He, Z.; Gharaibeh, R.Z.; Newsome, R.C.; Pope, J.L.; Dougherty, M.; Tomkovich, S.; Pons, B.; Mirey, G.; Vignard, J.; Hendrixson, D.R.; et al. Campylobacter jejuni promotes colorectal tumorigenesis through the action of cytolethal distending toxin. Gut 2019, 68, 289–300, doi:10.1136/gutjnl-2018-317200.
Drewes, J.L.; White, J.R.; Dejea, C.M.; Fathi, P.; Iyadorai, T.; Vadivelu, J.; Roslani, A.C.; Wick, E.C.; Mongodin, E.F.; Loke, M.F.; et al. High-resolution bacterial 16S rRNA gene profile meta-analysis and biofilm status reveal common colorectal cancer con-sortia. npj Biofilms Microbiomes 2017, 3, 1–12, doi:10.1038/s41522-017-0040-3.
Kaplan, C.W.; Lux, R.; Haake, S.K.; Shi, W. TheFusobacterium nucleatumouter membrane protein RadD is an arginine-inhibit-able adhesin required for inter-species adherence and the structured architecture of multispecies biofilm. Mol. Microbiol. 2009, 71, 35–47, doi:10.1111/j.1365-2958.2008.06503.x.
Tomkovich, S.; Dejea, C.M.; Winglee, K.; Drewes, J.L.; Chung, L.; Housseau, F.; Pope, J.L.; Gauthier, J.; Sun, X.; Mühlbauer, M.; et al. Human colon mucosal biofilms from healthy or colon cancer hosts are carcinogenic. J. Clin. Investig. 2019, 129, 1699–1712, doi:10.1172/jci124196.
Jorth, P.; Turner, K.H.; Gumus, P.; Nizam, N.; Buduneli, N.; Whiteley, M. Metatranscriptomics of the Human Oral Microbiome during Health and Disease. mBio 2014, 5, e01012-14, doi:10.1128/mbio.01012-14.
Liu, Y.; Geng, R.; Liu, L.; Jin, X.; Yan, W.; Zhao, F.; Wang, S.; Guo, X.; Ghimire, G.; Wei, Y. Gut Microbiota-Based Algorithms in the Prediction of Metachronous Adenoma in Colorectal Cancer Patients Following Surgery. Front. Microbiol. 2020, 11, 1106, doi:10.3389/fmicb.2020.01106.
Alexander, J.L.; Wilson, I.D.; Teare, J.; Marchesi, J.; Nicholson, J.K.; Kinross, J. Gut microbiota modulation of chemotherapy efficacy and toxicity. Nat. Rev. Gastroenterol. Hepatol. 2017, 14, 356–365, doi:10.1038/nrgastro.2017.20.
Chew, S.-S.; Tan, L.T.-H.; Law, J.W.-F.; Pusparajah, P.; Goh, B.-H.; Ab Mutalib, N.S.; Lee, L.-H. Targeting Gut Microbial Bio-films—A Key to Hinder Colon Carcinogenesis? Cancers 2020, 12, 2272, doi:10.3390/cancers12082272.
Kim, G.W.; Kim, Y.-S.; Lee, S.H.; Park, S.G.; Kim, D.H.; Cho, J.Y.; Hahm, K.B.; Hong, S.P.; Yoo, J.-H. Periodontitis is associated with an increased risk for proximal colorectal neoplasms. Sci. Rep. 2019, 9, 7528, doi:10.1038/s41598-019-44014-8.
Horz, H.-P.; Scheer, S.; Huenger, F.; Vianna, M.E.; Conrads, G. Selective isolation of bacterial DNA from human clinical speci-mens. J. Microbiol. Methods 2008, 72, 98–102, doi:10.1016/j.mimet.2007.10.007.
Walker, S.P.; Tangney, M.; Claesson, M. Sequence-Based Characterization of Intratumoral Bacteria—A Guide to Best Practice. Front. Oncol. 2020, 10, 179, doi:10.3389/fonc.2020.00179.
Heravi, F.S.; Zakrzewski, M.; Vickery, K.; Hu, H. Host DNA depletion efficiency of microbiome DNA enrichment methods in infected tissue samples. J. Microbiol. Methods 2020, 170, 105856, doi:10.1016/j.mimet.2020.105856.