The DOI matches its Crossref record; 97 of the 98 references it cites were found in a registry or an index.
Potential of fecal microbiota for early-stage detection of colorectal cancer
Open accessAbstract
Several bacterial species have been implicated in the development of colorectal carcinoma (CRC), but CRC-associated changes of fecal microbiota and their potential for cancer screening remain to be explored. Here, we used metagenomic sequencing of fecal samples to identify taxonomic markers that distinguished CRC patients from tumor-free controls in a study population of 156 participants. Accuracy of metagenomic CRC detection was similar to the standard fecal occult blood test (FOBT) and when both approaches were combined, sensitivity improved > 45% relative to the FOBT, while maintaining its specificity. Accuracy of metagenomic CRC detection did not differ significantly between early- and late-stage cancer and could be validated in independent patient and control populations (N = 335) from different countries. CRC-associated changes in the fecal microbiome at least partially reflected microbial community composition at the tumor itself, indicating that observed gene pool differences may reveal tumor-related host-microbe interactions. Indeed, we deduced a metabolic shift from fiber degradation in controls to utilization of host carbohydrates and amino acids in CRC patients, accompanied by an increase of lipopolysaccharide metabolism.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“studies of fecal microbiomes that used either 16s rRNA or shotgun metagenomic sequencing found that F nucleatum to be increased in fecal samples from patients with CRC or adenoma compared with controls (Table 1).15, 18, 35–39”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [36]
In the citing paper
“The protein AvrA, produced by Salmonella, promotes inflammation and colon tumor development by activating beta-catenin signaling to STAT3.36, 180”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [36]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Jemal, A., Bray, F., Ferlay, J., Ward, E., & Forman, D. (2011) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.20107 · Cited by 55,044
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., et al. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.01541-09 · Cited by 21,481
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.00062-07 · Cited by 20,145
Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega
Sievers, F., Wilm, A., Dineen, D., Gibson, T., Karplus, K., Li, W.-Z., Lopez, R., McWilliam, H., Remmert, M., Söding, J., et al. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.75 · Cited by 15,576
pROC: an open-source package for R and S+ to analyze and compare ROC curves
Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C., & Müller, M. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-77 · Cited by 13,697
An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
Flagged first, then by citations
1 of the 98 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 201–300 of 1,000
Ševčíková, A., Izoldova, N., Števurková, V., Kasperova, B., Chovanec, M., Čierniková, S., & Mego, M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23010488 · Cited by 109
Tarallo, S., Ferrero, G., Gallo, G., Francavilla, A., Clerico, G. F., Luc, A. R., Manghi, P., Thomas, A. M., Vineis, P., Segata, N., et al. (2019) · mSystems · doi:10.1128/msystems.00289-19 · Cited by 104
Inchingolo, A. D., Malcangi, G., Semjonova, A., Inchingolo, A. M., Patano, A., Coloccia, G., Ceci, S., Marinelli, G., Pede, C. D., Ciocia, A. M., et al. (2022) · Children · doi:10.3390/children9071014 · Cited by 113
Towards predicting the environmental metabolome from metagenomics with a mechanistic model
Garza, D. R., Verk, M. C. V., Huynen, M. A., & Dutilh, B. E. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0124-8 · Cited by 97
Fecal Microbial Transplantation for Diseases Beyond Recurrent Clostridium Difficile Infection
D’Haens, G., & Jobin, C. (2019) · Gastroenterology · doi:10.1053/j.gastro.2019.04.053 · Cited by 104
Integrative Analysis of Fecal Metagenomics and Metabolomics in Colorectal Cancer
Clos‐Garcia, M., García‐Etxebarria, K., Alonso, C., Iruarrizaga‐Lejarreta, M., D’Amato, M., Crespo, A., Iglesias, Á., Cubiella, J., Bujanda, L., & Falcón‐Pérez, J. M. (2020) · Cancers · doi:10.2139/ssrn.3520024 · Cited by 99
Richer gut microbiota with distinct metabolic profile in HIV infected Elite Controllers
Vesterbacka, J., Rivera, J., Noyan, K., Parera, M., Neogi, U., Calle, M. L., Paredes, R., Sönnerborg, A. B., Noguera-Julián, M., & Nowak, P. (2017) · Scientific Reports · doi:10.1038/s41598-017-06675-1 · Cited by 97
Taxonomy-aware feature engineering for microbiome classification
Oudah, M., & Henschel, A. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2205-3 · Cited by 99
Knoll, R. L., Forslund, S. K., Kultima, J. R., Meyer, C. U., Kullmer, U., Sunagawa, S., Bork, P., & Gehring, S. (2016) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00293.2016 · Cited by 98
Self-citationOral microbiome and pancreatic cancer
Wei, A.-L., Mao, L., Li, G., Wang, X., Hu, W.-M., Li, Z., Yuan, J., Liu, H.-Y., Zhou, L.-L., Li, K., et al. (2020) · World Journal of Gastroenterology · doi:10.3748/wjg.v26.i48.7679 · Cited by 95
Ren, Y., Zhuang, Z.-Y., Xie, Y.-H., Yang, P., Xia, T., Xie, Y., Liu, Z.-H., Kang, Z., Leng, X.-X., Lu, S., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.07.012 · Cited by 101
Pathogenic functions of host microbiota
Rath, S., Rud, T., Karch, A., Pieper, D. H., & Vital, M. (2018) · Microbiome · doi:10.1186/s40168-018-0542-0 · Cited by 98
Molecular mechanism of ATF6 in unfolded protein response and its role in disease
Lei, Y., Yu, H., Ding, S., Liu, H., Liu, C., & Fu, R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e25937 · Cited by 102
Yeoh, Y. K., Sun, Y., Ip, L., Wang, L., Chan, F. K. L., Miao, Y., & Ng, S. C. (2022) · Scientific Reports · doi:10.1038/s41598-022-12721-4 · Cited by 102
The impact of the intestinal microbiota in therapeutic responses against cancer
Goubet, A., Daillère, R., Routy, B., Derosa, L., Roberti, P. M., & Zitvogel, L. (2018) · Comptes Rendus Biologies · doi:10.1016/j.crvi.2018.03.004 · Cited by 94
Human gastric microbiota transplantation recapitulates premalignant lesions in germ-free mice
Kwon, S.-K., Park, J. C., Kim, K. H., Yoon, J., Cho, Y., Lee, B., Lee, J.-J., Jeong, H., Oh, Y., Kim, S., et al. (2021) · Gut · doi:10.1136/gutjnl-2021-324489 · Cited by 95
Gut Microbiome in Colorectal Cancer: Clinical Diagnosis and Treatment
Liu, Y., Lau, H. C.-H., Cheng, W. Y., & Yu, J. Q. (2022) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2022.07.002 · Cited by 108
The Denture-Associated Oral Microbiome in Health and Stomatitis
Shi, B., Wu, T., McLean, J. S., Edlund, A., Young, Y., He, X., Lv, H., Zhou, X., Shi, W., Li, H., et al. (2016) · mSphere · doi:10.1128/msphere.00215-16 · Cited by 97
Assessment of fecal DNA extraction protocols for metagenomic studies
Yang, F., Sun, J., Luo, H., Ren, H., Zhou, H., Lin, Y., Han, M., Chen, B., Liao, H., Brix, S., et al. (2020) · GigaScience · doi:10.1093/gigascience/giaa071 · Cited by 88
Carcinogenic microbiota and its role in colorectal cancer development
Karpiński, T. M. M., Ożarowski, M., & Stasiewicz, M. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2022.01.004 · Cited by 93
Enterotypes of the human gut mycobiome
Lai, S., Yan, Y., Pu, Y., Lin, S., Qiu, J., Jiang, B., Keller, M. I., Wang, M., Bork, P., Chen, W., et al. (2023) · Microbiome · doi:10.1186/s40168-023-01586-y · Cited by 95
Gut microbiome of Moroccan colorectal cancer patients
Allali, I., Boukhatem, N., Bouguenouch, L., Hardi, H., Boudouaya, H. A., Cadenas, M. B., Ouldim, K., Amzazi, S., Azcárate-Peril, M. A., & Ghazal, H. (2018) · Medical Microbiology and Immunology · doi:10.1007/s00430-018-0542-5 · Cited by 90
Pathogens and Carcinogenesis: A Review
Hatta, M. N. A., Hanif, E. A. M., Chin, S., & Neoh, H. (2021) · Biology · doi:10.3390/biology10060533 · Cited by 94
NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language
Coelho, L. P., Alves, R., Monteiro, P., Huerta‐Cepas, J., Freitas, A. T., & Bork, P. (2019) · Microbiome · doi:10.1186/s40168-019-0684-8 · Cited by 86
Advances in tests for colorectal cancer screening and diagnosis
Chan, S. C. H., & Liang, Q. (2022) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2022.2065197 · Cited by 86
Dalal, N., Jalandra, R., Sharma, M., Prakash, H., Makharia, G. K., Solanki, P. R., Singh, R. K., & Kumar, A. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.110648 · Cited by 94
Oral microbiome and history of smoking and colorectal cancer
Kato, I., Vasquez, A. A., Moyerbrailean, G. A., Land, S. J., Sun, J., Lin, H., & Ram, J. L. (2016) · Journal of Epidemiological Research · doi:10.5430/jer.v2n2p92 · Cited by 87
The ColoCare Study: A Paradigm of Transdisciplinary Science in Colorectal Cancer Outcomes
Ulrich, C. M., Gigic, B., Böhm, J., Ose, J., Viskochil, R. H., Schneider, M. A., Colditz, G. A., Figueiredo, J. C., Grady, W. M., Li, C. I., et al. (2018) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-18-0773 · Cited by 86
Self-citationNovielli, P., Romano, D., Magarelli, M., Bitonto, P. D., Diacono, D., Chiatante, A., Lopalco, G., Sabella, D. V. A., Venerito, V., Filannino, P., et al. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1348974 · Cited by 94
Gut microbiota and hypertension: From pathogenesis to new therapeutic strategies
Kang, Y., & Cai, Y. (2017) · Clinics and Research in Hepatology and Gastroenterology · doi:10.1016/j.clinre.2017.09.006 · Cited by 84
Burns, M. B., Montassier, E., Abrahante, J. E., Priya, S., Niccum, D. E., Khoruts, A., Starr, T. K., Knights, D., & Blekhman, R. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007376 · Cited by 87
The Role of Microbiota in Gastrointestinal Cancer and Cancer Treatment: Chance or Curse?
Smet, A., Kupčinskas, J., Link, A., Hold, G. L., & Bornschein, J. (2021) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2021.08.013 · Cited by 87
Zhang, Y., Yu, X., Yu, E., Wang, N., Cai, Q.-C., Shuai, Q., Yan, F., Jiang, L., Wang, H., Liu, J., et al. (2018) · BMC Microbiology · doi:10.1186/s12866-018-1232-6 · Cited by 82
SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis
Volant, S., Lechat, P., Woringer, P., Motreff, L., Campagne, P., Malabat, C., Kennedy, S., & Ghozlane, A. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03666-4 · Cited by 92
Ma, Y., Zhang, Y., Jiang, H., Xiang, S., Zhao, Y., Xiao, M., Du, F., Ji, H., Kaboli, P. J., Wu, X., et al. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.599734 · Cited by 84
$W_{d}^{*}$-test: robust distance-based multivariate analysis of variance
Hamidi, B., Wallace, K., Vasu, C., & Alekseyenko, A. V. (2019) · Microbiome · doi:10.1186/s40168-019-0659-9 · Cited by 81
The Human Microbiome in Relation to Cancer Risk: A Systematic Review of Epidemiologic Studies
Huybrechts, I., Zouiouich, S., Loobuyck, A., Vandenbulcke, Z., Vogtmann, E., Pisanu, S., Iguacel, I., Scalbert, A., Indave, I., Smelov, V., et al. (2020) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-20-0288 · Cited by 80
Illescas, O., Rodríguez‐Sosa, M., & Gariboldi, M. (2021) · Nutrients · doi:10.3390/nu13072234 · Cited by 88
Martin‐Gallausiaux, C., Salesse, L., Garcia-Weber, D., Marinelli, L., Béguet-Crespel, F., Brochard, V., Gléau, C. L., Jamet, A., Dore, J. M., Blottière, H. M., et al. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2295384 · Cited by 85
Kumar, B., Lorusso, E., Fosso, B., & Pesole, G. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1343572 · Cited by 93
Bundgaard‐Nielsen, C., Baandrup, U. T., Nielsen, L. P., & Sørensen, S. (2019) · BMC Cancer · doi:10.1186/s12885-019-5571-y · Cited by 84
Crosstalk between gut microbiota and Sirtuin-3 in colonic inflammation and tumorigenesis
Zhang, Y., Wang, X.-L., Zhou, M., Kang, C., Lang, H.-D., Chen, M.-T., Hui, S.-C., Wang, B., & Mi, M.-T. (2018) · Experimental & Molecular Medicine · doi:10.1038/s12276-017-0002-0 · Cited by 78
Andreu-Sánchez, S., Blanco-Míguez, A., Wang, D., Golzato, D., Manghi, P., Heidrich, V., Fackelmann, G., Zhernakova, D. V., Kurilshikov, A., Valles-Colomer, M., et al. (2025) · Cell · doi:10.1016/j.cell.2025.04.014 · Cited by 81
A systematic review of microbiome-derived biomarkers for early colorectal cancer detection
Zwezerijnen-Jiwa, F. H., Sivov, H., Paizs, P., Zafeiropoulou, K., & Kinross, J. K. (2022) · Neoplasia · doi:10.1016/j.neo.2022.100868 · Cited by 87
Bars‐Cortina, D., Ramon, E., Rius‐Sansalvador, B., Guinó, E., García‐Serrano, A., Mach, N., Khannous‐Lleiffe, O., Saus, E., Gabaldón, T., Ibáñez‐Sanz, G., et al. (2024) · BMC Genomics · doi:10.1186/s12864-024-10621-7 · Cited by 92
Microbiota as a mediator of cancer progression and therapy
Pope, J. L., Tomkovich, S., Yang, Y., & Jobin, C. (2016) · Translational research · doi:10.1016/j.trsl.2016.07.021 · Cited by 80
Akaçin, İ., Ersoy, Ş., Doluca, O., & Güngörmüşler, M. (2022) · Microbiological Research · doi:10.1016/j.micres.2022.127154 · Cited by 88
Leveraging explainable AI for gut microbiome-based colorectal cancer classification
Rynazal, R., Fujisawa, K., Shiroma, H., Salim, F., Mizutani, S., Shiba, S., Yachida, S., & Yamada, T. (2023) · Genome biology · doi:10.1186/s13059-023-02858-4 · Cited by 78
Self-citationMetaProb: accurate metagenomic reads binning based on probabilistic sequence signatures
Girotto, S., Pizzi, C., & Comin, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw466 · Cited by 79
Ai, L., Tian, H., Chen, Z., Chen, H., Xu, J., & Fang, J. (2017) · Oncotarget · doi:10.18632/oncotarget.14488 · Cited by 78
Mima, K., Ogino, S., Nakagawa, S., Sawayama, H., Kinoshita, K., Krashima, R., Ishimoto, T., Imai, K., Iwatsuki, M., Hashimoto, D., et al. (2017) · Surgical Oncology · doi:10.1016/j.suronc.2017.07.011 · Cited by 80
Wang, X., Wang, J. P., Rao, B., & Deng, L. (2017) · Experimental and Therapeutic Medicine · doi:10.3892/etm.2017.4367 · Cited by 78
RetractedYeoh, Y. K., Chen, Z., Wong, M. C. S., Hui, M., Yu, J., Ng, S. C., Sung, J. J. �., Chan, F. K. L., & Chan, P. K. S. (2020) · Gut · doi:10.1136/gutjnl-2019-319635 · Cited by 74
Huang, P., Ji, F., Cheung, A. H. K., Fu, K., Zhou, Q., Ding, X. Q., Chen, D., Lin, Y., Wang, L., Jiao, Y., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.07.001 · Cited by 81
Abavisani, M., Khoshrou, A., Foroushan, S. K., Ebadpour, N., & Sahebkar, A. (2024) · Current Research in Biotechnology · doi:10.1016/j.crbiot.2024.100211 · Cited by 75
Fusobacterium’s link to colorectal neoplasia sequenced: A systematic review and future insights
Hussan, H., Clinton, S. K., Roberts, K., & Bailey, M. T. (2017) · World Journal of Gastroenterology · doi:10.3748/wjg.v23.i48.8626 · Cited by 76
Over 50,000 Metagenomically Assembled Draft Genomes for the Human Oral Microbiome Reveal New Taxa
Zhu, J., Tian, L., Chen, P., Han, M., Song, L., Tong, X., Sun, X., Yang, F., Lin, Z., Liu, X., et al. (2021) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.05.001 · Cited by 76
The Human Mucosal Mycobiome and Fungal Community Interactions
Witherden, E. A., Shoaie, S., Hall, R. A., & Moyes, D. L. (2017) · Journal of Fungi · doi:10.3390/jof3040056 · Cited by 74
Microbiome: Effects of Ageing and Diet
Salazar, N., González, S., Nogacka, A. M., Ríos-Covián, D., Arboleya, S., Gueimonde, M., & Reyes‐Gavilán, C. G. D. L. (2019) · Current Issues in Molecular Biology · doi:10.21775/cimb.036.033 · Cited by 75
Sheng, Q., Du, H., Cheng, X., Cheng, X.-B., Tang, Y., Pan, L., Wang, Q., & Lin, J. (2019) · Oncology Letters · doi:10.3892/ol.2019.10841 · Cited by 70
Inter-species Metabolic Interactions in an In-vitro Minimal Human Gut Microbiome of Core Bacteria
Shetty, S. A., Kuipers, B., Atashgahi, S., Aalvink, S., Smidt, H., & de Vos, W. M. (2022) · npj Biofilms and Microbiomes · doi:10.1038/s41522-022-00275-2 · Cited by 72
Ullah, I., Yang, L., Yin, F., Sun, Y., Li, X., Li, J., & Wang, X. (2022) · Cancers · doi:10.3390/cancers14225545 · Cited by 81
Zhang, Y., Wu, H., Xu, R., Wang, Y., Chen, L., & Wei, C. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.167730 · Cited by 77
Gunter, M. J., Alhomoud, S. J., Arnold, M., Brenner, H., Burn, J., Casey, G., Chan, A. T., Cross, A. J., Giovannucci, E. L., Hoover, R. N., et al. (2019) · Annals of Oncology · doi:10.1093/annonc/mdz044 · Cited by 73
Yang, J., Li, D., Yang, Z., Dai, W., Feng, X., Liu, Y., Jiang, Y., Li, P., Li, Y., Tang, B., et al. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1712986 · Cited by 78
Quantifying technical confounders in microbiome studies
Bartolomaeus, T. U. P., Birkner, T., Bartolomaeus, H., Löber, U., Avery, E. G., Mähler, A., Weber, D., Kochlik, B., Balogh, A., Wilck, N., et al. (2020) · Cardiovascular Research · doi:10.1093/cvr/cvaa128 · Cited by 70
Véziant, J., Villéger, R., Barnich, N., & Bonnet, M. (2021) · Cancers · doi:10.3390/cancers13092215 · Cited by 76
Vanhaecke, T., Bretin, O., Poirel, M., & Tap, J. (2021) · Journal of Nutrition · doi:10.1093/jn/nxab312 · Cited by 80
Self-citationJust Add Data: automated predictive modeling for knowledge discovery and feature selection
Tsamardinos, I., Charonyktakis, P., Παπουτσόγλου, Γ., Borboudakis, G., Lakiotaki, K., Zenklusen, J. C., Juhl, H. H., Chatzaki, Ε., & Lagani, V. (2022) · npj Precision Oncology · doi:10.1038/s41698-022-00274-8 · Cited by 95
Yang, T.-W., Lee, W.-H., Tu, S.-J., Huang, W.-C., Chen, H., Sun, T.-H., Tsai, M.-C., Wang, C., Chen, H., Huang, C., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-45588-z · Cited by 81
Zhang, J., Lacroix, C., Wortmann, E., Ruscheweyh, H., Sunagawa, S., Sturla, S. J., & Schwab, C. (2019) · BMC Microbiology · doi:10.1186/s12866-019-1483-x · Cited by 71
Self-citationVaginal Microbiota and Cytokine Levels Predict Preterm Delivery in Asian Women
Kumar, M., Murugesan, S., Singh, P., Saadaoui, M., Elhag, D. A., Terranegra, A., Kabeer, B. S. A., Marr, A. K., Kino, T., Brummaier, T., et al. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.639665 · Cited by 73
Chen, J., Wang, A., & Wang, Q. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04199-0 · Cited by 73
Mannucci, A., & Goel, A. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02174-w · Cited by 75
Tan, R., Jin, M., Shao, Y., Yin, J., Li, H., Chen, T., Shi, D., Zhou, S., Lǐ, J., & Yang, D. (2022) · Gut Microbes · doi:10.1080/19490976.2021.2022442 · Cited by 74
Applying multi‐omics toward tumor microbiome research
Zhang, N., Kandalai, S., Zhou, X., Hossain, F., & Zheng, Q. (2023) · iMeta · doi:10.1002/imt2.73 · Cited by 70
Senthakumaran, T., Moen, A. E. F., Tannæs, T. M., Endres, A., Brackmann, S. A., Rounge, T. B., Bemanian, V., & Tunsjø, H. S. (2023) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-023-04551-7 · Cited by 73
A Pilot Study: Changes of Gut Microbiota in Post-surgery Colorectal Cancer Patients
Cong, J., Zhu, H., Liu, D., Li, T., Zhang, C., Zhu, J., Lv, H., Liu, K., Hao, C., Tian, Z., et al. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.02777 · Cited by 71
Liu, X., Cheng, Y., Shao, L., & Ling, Z. (2020) · BioMed Research International · doi:10.1155/2020/2948282 · Cited by 71
lefser: implementation of metagenomic biomarker discovery tool, LEfSe, in R
Khleborodova, A., Gamboa-Tuz, S. D., Ramos, M., Segata, N., Waldron, L., & Oh, S. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae707 · Cited by 69
Alterations of circulating bacterial DNA in colorectal cancer and adenoma: A proof-of-concept study
Xiao, Q., Lu, W., Kong, X., Shao, Y. W., Hu, Y., Wang, A., Bao, H., Cao, R., Liu, K., Wang, X., et al. (2020) · Cancer Letters · doi:10.1016/j.canlet.2020.11.030 · Cited by 70
Li, S., Guo, R., Zhang, Y., Li, P., Chen, F., Wang, X., Li, J., Jie, Z., Lv, Q., Jin, H., et al. (2021) · iScience · doi:10.1016/j.isci.2022.104418 · Cited by 70
Wang, B., Wang, X., Wang, Z., Zhu, K., & Wu, W. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1102547 · Cited by 73
Bergsten, E., Mestivier, D., Donnadieu, F., Pédron, T., Barau, C., Tsoumtsa, L. L., Mettouchi, A., Lemichez, E., Gorgette, O., Chamaillard, M., et al. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2265138 · Cited by 75
Self-citationCholecystectomy Damages Aging-Associated Intestinal Microbiota Construction
Wang, W., Wang, J., Li, J., Yan, P., Jin, Y., Zhang, R., Yue, W., Guo, Q., & Geng, J. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.01402 · Cited by 70
Zhao, D., Liu, H., Zheng, Y., He, Y., Lu, D., & Lyu, C. (2018) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-018-1930-0 · Cited by 66
Li, M., Liu, J., Zhu, J., Wang, H., Sun, C., Gao, N., Zhao, X., & Chen, W. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2205386 · Cited by 75
Osman, M. A., Neoh, H., Mutalib, N. A., Chin, S., & Jamal, R. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00767 · Cited by 71
Implications of gut microbiota-mediated epigenetic modifications in intestinal diseases
Zhang, Q., Liu, Y., Li, Y., Bai, G., Pang, J., Wu, M., Li, J., Zhao, X., & Xia, Y. (2025) · Gut Microbes · doi:10.1080/19490976.2025.2508426 · Cited by 73
Zhang, X., Zhu, X., Cao, Y., Fang, J., Hong, J., & Chen, H. (2019) · Cancer Medicine · doi:10.1002/cam4.1850 · Cited by 65
Ai, D., Pan, H., Han, R., Li, X., Liu, G., & Xia, L. C. (2019) · Genes · doi:10.3390/genes10020112 · Cited by 65
Resistome expansion in disease-associated human gut microbiomes
Fredriksen, S., de Warle, S., van Baarlen, P., Boekhorst, J., & Wells, J. M. (2023) · Microbiome · doi:10.1186/s40168-023-01610-1 · Cited by 70
Bacterial Signaling at the Intestinal Epithelial Interface in Inflammation and Cancer
Coleman, O. I., & Haller, D. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01927 · Cited by 66
Metagenomic analysis reveals mechanisms of atrazine biodegradation promoted by tree species
Aguiar, L. M., Souza, M. D. F., de Laia, M. L., Melo, J. D. O., da Costa, M. R., Gonçalves, J. F., Silva, D. V., & dos Santos, J. B. (2020) · Environmental Pollution · doi:10.1016/j.envpol.2020.115636 · Cited by 65
Ding, X., Lan, W., Yan, A., Li, Y., Katayama, Y., & Gu, J. (2021) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.114041 · Cited by 66
Duan, D., Wang, M., Han, J., Li, M., Wang, Z., Zhou, S., Xin, W., & Li, X. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1509117 · Cited by 78
She, R., Li, T.-T., Luo, D., Li, J., Yin, L.-Y., Li, H., Liu, Y.-M., Li, X.-Z., & Yan, Q. (2017) · Current Microbiology · doi:10.1007/s00284-017-1294-y · Cited by 64
Normalization of the microbiota in patients after treatment for colonic lesions
Sze, M. A., Baxter, N. T., Ruffin, M. T., Rogers, M. A. M., & Schloss, P. D. (2017) · Microbiome · doi:10.1186/s40168-017-0366-3 · Cited by 63
Oral and Gut Microbial Carbohydrate-Active Enzymes Landscape in Health and Disease
Onyango, S. O., Juma, J., Paepe, K. D., & de Wiele, T. V. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.653448 · Cited by 65
A systemic review of the role of enterotoxic Bacteroides fragilis in colorectal cancer
Scott, N. E., Whittle, E., Jeraldo, P., & Chia, N. (2022) · Neoplasia · doi:10.1016/j.neo.2022.100797 · Cited by 64
Metadata
- Authors
- Zeller, G., Tap, J., Voigt, A. Y., Sunagawa, S., Kultima, J. R., Costea, P. I., Amiot, A., Böhm, J., Brunetti, F., Habermann, N., Hercog, R., Koch, M., Luciani, A., Mende, D. R., Schneider, M. A., Schrotz‐King, P., Tournigand, C., Tran Van Nhieu, J., Yamada, T., Zimmermann, J., Benes, V., Kloor, M., Ulrich, C. M., von Knebel Doeberitz, M., Sobhani, I., & Bork, P.
- Affiliations
- European Molecular Biology Laboratory (DE)
- Université Paris-Est Créteil (FR)
- German Cancer Research Center (DE)
- University Hospital Heidelberg (DE)
- Tokyo Institute of Technology (JP)
- Corresponding author
- Sobhani, Iradj
- ORCID
- Venue
- Molecular Systems Biology
- Published
- 2014-11-01
- Volume
- 10
- Issue
- 11
- Pages
- 766-766
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC4299606
- OpenAlex
- W2130725058
- Cited by
- 1,375
- References
- 98
- Citations by year
- 2026: 131 · 2025: 168 · 2024: 162 · 2023: 134 · 2022: 160 · 2021: 140 · 2020: 134 · 2019: 97 · 2018: 82 · 2017: 85 · 2016: 59 · 2015: 20 · 2014: 1
- FWCI
- 22.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
- HAL (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- European Research Council (268985)
- METACARDIS (FP7‐HEALTH‐2012‐INNOVATION‐I‐305312)
- International Human Microbiome Standards (HEALTH‐F4‐2010‐261376)
- French LNCC 2004 grant
- ACD grants
- PHRC 2009 Vatnimad grant
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
- Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
- Keywords
- colorectal cancer, fecal microbiota, early cancer detection, cancer screening, metagenomics, fecal occult blood test, microbial biomarkers, host-microbe interactions, fiber degradation
- MeSH terms
- Feces, Humans, Occult Blood, Sensitivity and Specificity, Colorectal Neoplasms, Case-Control Studies, Early Detection of Cancer, Metagenomics, Molecular Typing, Microbiota
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
