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Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer
Open accessAbstract
Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10−5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics. Cross-study analysis defines fecal microbial species associated with colorectal cancer.
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“The lack of solid cross-study reproducible microbial biomarkers of ICI response is not attributable to analytical choices, as applying the same meta-analysis methods in the context of colorectal cancer confirmed the strong and consistent biomarkers across cohorts described elsewhere13,14.”
From Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma (2022) · cites this paper as [13]
In the citing paper
“This signature, identified using both supervised machine learning and a meta-analysis, included the bacterial species Solobacterium moorei, Fusobacterium nucleatum, Parvimonas micra, Peptostreptococcus stomatis, Peptostreptococcus anaerobius and Gemella morbillorum”
From Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy (2023) · cites this paper as [49]
In the citing paper
“Several taxonomic features associated with sequence variants of cutC were also found to be enriched in patients with CRC, including Hungatella hathewayi, Clostridium asparagiforme, Klebsiella oxytoca, and E coli.”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [146]
In the citing paper
“A meta-analysis of metagenomes of fecal samples146 found patients with CRC to have higher levels of 2 bacterial genes that regulate TMA synthesis: choline TMA-lyase (cutC) and choline TMA-lyase-activating enzyme (cutD).”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [146]
In the citing paper
“Moreover, the bai operon, encoding 7α-dehydroxylation in Clostridium spp. required for synthesis of secondary bile acids, was found to be enriched in metagenomes of fecal samples from patients with CRC.146”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [146]
In the citing paper
“A recent analysis of 8 geographically and technically diverse fecal shotgun metagenomic studies found evidence for increased production of secondary bile acids in patients with CRC, indicating a metabolic link between cancer-associated microbes and a fat- and meat-rich diet. 146”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [146]
In the citing paper
“This pattern has been found previously both with MetaPhlAn 2 (Thomas et al., 2019) and with mOTUs2 (Wirbel et al., 2019), in large part due to low-level detection of typically oral microbes in addition to the baseline gut microbiome during CRC.”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Wirbel et al., 2019
In the citing paper
“Nearly all microbial-based cancer diagnostics are sequencing-based and have focused on tumors within the aerodigestive tract (31), such as colorectal (118–121), pancreatic (122, 123), and lung cancer (124–126).”
From The microbiome and human cancer (2021) · cites this paper as [118]
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Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
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
MUSCLE: multiple sequence alignment with high accuracy and high throughput
Edgar, R. C. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh340 · Cited by 44,662
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
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
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Self-citationPeng, H., Long, F., & Ding, C. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.159 · Cited by 10,818
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,944
Cited by
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Items 101–200 of 998
Xia, X., Wu, W. K. K., Wong, S. H., Liu, D., Kwong, T. N. Y., Nakatsu, G., Yan, P. S., Chuang, Y., Chan, M. W. Y., Coker, O. O., et al. (2020) · Microbiome · doi:10.1186/s40168-020-00847-4 · Cited by 155
Fusobacterium nucleatum secretes amyloid-like FadA to enhance pathogenicity
Meng, Q., Gao, Q., Mehrazarin, S., Tangwanichgapong, K., Wang, Y., Huang, Y., Pan, Y., Robinson, S. T., Liu, Z., Zangiabadi, A., et al. (2021) · EMBO Reports · doi:10.15252/embr.202152891 · Cited by 153
Tito, R. Y., Verbandt, S., Vázquez, M. A., Lahti, L., Verspecht, C., Lloréns‐Rico, V., Vieira‐Silva, S., Arts, J., Falony, G., Dekker, E., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02963-2 · Cited by 163
The effect of physical exercise on anticancer immunity
Fiuza‐Luces, C., Valenzuela, P. L., Gálvez, B. G., Ramírez, M. R., López‐Soto, A., Simpson, R. J., & Lucía, A. (2023) · Nature reviews. Immunology · doi:10.1038/s41577-023-00943-0 · Cited by 164
Strain-level epidemiology of microbial communities and the human microbiome
Yan, Y., Nguyen, L. H., Franzosa, E. A., & Huttenhower, C. (2020) · Genome Medicine · doi:10.1186/s13073-020-00765-y · Cited by 152
Ralser, A., Dietl, A., Jarosch, S., Engelsberger, V., Wanisch, A., Janssen, K., Middelhoff, M. A., Vieth, M. W., Quante, M., Haller, D., et al. (2023) · Gut · doi:10.1136/gutjnl-2022-328075 · Cited by 155
Machine learning approaches in microbiome research: challenges and best practices
Παπουτσόγλου, Γ., Tarazona, S., Lopes, M. B., Klammsteiner, T., Ibrahimi, E., Eckenberger, J., Novielli, P., Tonda, A. P., Mihajlović, A., Shigdel, R., et al. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1261889 · Cited by 153
Noninvasive, microbiome-based diagnosis of inflammatory bowel disease
Zheng, J., Sun, Q., Zhang, M., Liu, C., Su, Q., Zhang, L., Xu, Z., Lu, W., Ching, J. Y. L., Tang, W., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03280-4 · Cited by 155
Lin, Y., Lau, H. C.-H., Liu, Y., Kang, X., Wang, Y., Ting, N. L.-N., Kwong, T. N.-Y., Han, J., Liu, W., Liu, C., et al. (2022) · Gastroenterology · doi:10.1053/j.gastro.2022.06.038 · Cited by 142
Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy
Thomas, A. M., Fidelle, M., Routy, B., Kroemer, G., Wargo, J. A., Segata, N., & Zitvogel, L. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00785-8 · Cited by 141
Self-citationA metagenomic strategy for harnessing the chemical repertoire of the human microbiome
Sugimoto, Y., Camacho, F. R., Wang, S., Chankhamjon, P., Odabas, A., Biswas, A. G., Jeffrey, P. D., & Donia, M. S. (2019) · Science · doi:10.1126/science.aax9176 · Cited by 143
Intestinal microbiota and its association with colon cancer and red/processed meat consumption
Abu‐Ghazaleh, N., Chua, W. J., & Gopalan, V. (2020) · Journal of Gastroenterology and Hepatology · doi:10.1111/jgh.15042 · Cited by 155
Bacteriophages and their potential for treatment of gastrointestinal diseases
Duan, Y., Young, R., & Schnabl, B. (2021) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-021-00536-z · Cited by 150
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Drewes, J. L., Chen, J., Markham, N. O., Knippel, R. J., Domingue, J. C., Tam, A. J., Chan, J. L., Kim, L., McMann, M., Stevens, C. M., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-1273 · Cited by 139
Jia, B., Park, D., Hahn, Y., & Jeon, C. O. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1748261 · Cited by 139
Gao, R., Wu, C., Zhu, Y., Kong, C., Zhu, Y., Gao, Y., Zhang, X., Yang, R., Zhong, H., Xiong, X., et al. (2022) · Gastroenterology · doi:10.1053/j.gastro.2022.06.069 · Cited by 137
K., V., Sharma, A. K., Mahajan, S., Dhakan, D. B., Maji, A., Scaria, J., & Sharma, V. K. (2021) · npj Biofilms and Microbiomes · doi:10.1038/s41522-021-00248-x · Cited by 139
Ruscheweyh, H., Milanese, A., Paoli, L., Karcher, N., Clayssen, Q., Keller, M. I., Wirbel, J., Bork, P., Mende, D. R., Zeller, G., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01410-z · Cited by 130
Self-citationMa, X., Zhou, Z., Zhang, X., Fan, M., Hong, Y., Feng, Y., Dong, Q., Diao, H., & Wang, G. (2020) · Cell Biology and Toxicology · doi:10.1007/s10565-020-09518-4 · Cited by 131
Liu, W., Zhang, R., Shu, R., Yu, J., Li, H., Long, H., Jin, S., Li, S., Hu, Q., Yao, F., et al. (2020) · BioMed Research International · doi:10.1155/2020/7828392 · Cited by 135
Breast and gut microbiome in health and cancer
Zhang, J., Xia, Y., & Sun, J. (2020) · Genes & Diseases · doi:10.1016/j.gendis.2020.08.002 · Cited by 130
Piccinno (2025) · doi:10.1038/s41591-025-03693-9 · Cited by 133
Self-citationWolf, P. G., Cowley, E. S., Breister, A. M., Matatov, S., Lucio, L., Polak, P., Ridlon, J. M., Gaskins, H. R., & Anantharaman, K. (2022) · Microbiome · doi:10.1186/s40168-022-01242-x · Cited by 126
Yan, Q., Li, S., Yan, Q., Huo, X., Wang, C., Wang, X., Sun, Y., Zhao, W., Yu, Z., Zhang, Y., et al. (2024) · Cell · doi:10.1016/j.cell.2024.04.043 · Cited by 127
Cancer research using organoid technology
Kretzschmar, K. (2021) · Journal of Molecular Medicine · doi:10.1007/s00109-020-01990-z · Cited by 120
Bile salt hydrolase in non-enterotoxigenic Bacteroides potentiates colorectal cancer
Sun, L., Zhang, Y., Cai, J., Rimal, B., Rocha, E. R., Coleman, J. P., Zhang, C., Nichols, R. G., Luo, Y., Kim, B., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36089-9 · Cited by 130
Montalban‐Arques, A., & Scharl, M. M. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.09.050 · Cited by 118
Gut Microbiota in Intestinal and Liver Disease
Jones, R. M., & Neish, A. S. (2020) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathol-030320-095722 · Cited by 117
Probiotics: A Promising Candidate for Management of Colorectal Cancer
Tripathy, A., Dash, J., Kancharla, S., Kolli, P., Mahajan, D., Senapati, S., & Jena, M. K. (2021) · Cancers · doi:10.3390/cancers13133178 · Cited by 118
Machine Learning and Artificial Intelligence in the Multi-Omics Approach to Gut Microbiota
Rozera, T., Pasolli, E., Segata, N., & Ianiro, G. (2025) · Gastroenterology · doi:10.1053/j.gastro.2025.02.035 · Cited by 112
Self-citationEffects of caloric restriction on the gut microbiome are linked with immune senescence
Sbierski‐Kind, J., Grenkowitz, S., Schlickeiser, S., Sandforth, A., Friedrich, M., Kunkel, D., Glauben, R., Brachs, S., Mai, K., Thürmer, A., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01249-4 · Cited by 116
Zhang, Y., Lu, R., Wu, S., Chatterjee, I., Zhou, D., Xia, Y., & Sun, J. (2020) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2020.05.010 · Cited by 113
What Is Metagenomics Teaching Us, and What Is Missed?
New, F. N., & Brito, I. (2020) · Annual Review of Microbiology · doi:10.1146/annurev-micro-012520-072314 · Cited by 124
International consensus statement on microbiome testing in clinical practice
Porcari, S., Mullish, B. H., Asnicar, F., Ng, S. C., Zhao, L., Hansen, R., O’Toole, P. W., Raes, J., Hold, G. L., Putignani, L., et al. (2024) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(24)00311-x · Cited by 131
Self-citationThe Cancer Microbiome: Recent Highlights and Knowledge Gaps
Knippel, R. J., Drewes, J. L., & Sears, C. L. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0324 · Cited by 112
Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics
Purushothaman, S., Meola, M., & Egli, A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23179834 · Cited by 121
Intracellular bacteria in cancer—prospects and debates
Schorr, L., Mathies, M., Elinav, E., & Puschhof, J. (2023) · npj Biofilms and Microbiomes · doi:10.1038/s41522-023-00446-9 · Cited by 116
Avuthu, N., & Guda, C. (2022) · Microbiology Spectrum · doi:10.1128/spectrum.00013-22 · Cited by 114
Podlesny, D., Durdevic, M., Paramsothy, S., Kaakoush, N. O., Högenauer, C., Gorkiewicz, G., Walter, J., & Fricke, W. F. (2022) · Cell Reports Medicine · doi:10.1016/j.xcrm.2022.100711 · Cited by 111
Rosendahl Huber, A., Pleguezuelos-Manzano, C., Puschhof, J., Ubels, J., Boot, C., Saftien, A., Verheul, M., Trabut, L. T., Groenen, N., van Roosmalen, M., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.02.009 · Cited by 106
Kendong, S. M. A., Ali, R. A. R., Nawawi, K. N. M., Ahmad, H. F., & Mokhtar, N. M. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.744606 · Cited by 113
Significance of the gut microbiome in multistep colorectal carcinogenesis
Mizutani, S., Yamada, T., & Yachida, S. (2020) · Cancer Science · doi:10.1111/cas.14298 · Cited by 103
Self-citationGut microbial DL-endopeptidase alleviates Crohn’s disease via the NOD2 pathway
Gao, J., Zhao, X., Hu, S., Huang, Z., Hu, M., Jin, S., Lu, B., Sun, K., Wang, Z., Fu, J., et al. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2022.08.002 · Cited by 107
Mouradov, D., Greenfield, P. A., Li, S., In, E.-J., Storey, C., Sakthianandeswaren, A., Georgeson, P., Buchanan, D. D., Ward, R. L., Hawkins, N. J., et al. (2023) · Gastroenterology · doi:10.1053/j.gastro.2023.03.205 · Cited by 105
Iacucci, M., Santacroce, G., Majumder, S., Morael, J., Zammarchi, I., Maeda, Y., Ryan, D., Sabatino, A. D., Rescigno, M., Aburto, M. R., et al. (2024) · Gut · doi:10.1136/gutjnl-2023-331579 · Cited by 110
Gut microbiota-derived metabolites in CRC progression and causation
Dalal, N., Jalandra, R., Bayal, N., Yadav, A. K., Harshulika, Sharma, M., Makharia, G. K., Kumar, P., Singh, R. K., Solanki, P. R., et al. (2021) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-021-03729-w · Cited by 105
Functional and evolutionary significance of unknown genes from uncultivated taxa
del Río, Á. R., Giner‐Lamia, J., Cantalapiedra, C. P., Botas, J., Deng, Z., Hernández-Plaza, A., Palmer, M. M., Santamaría‐Hernando, S., Rodríguez‐Herva, J. J., Ruscheweyh, H., et al. (2023) · Nature · doi:10.1038/s41586-023-06955-z · Cited by 110
Self-citationTarallo, 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
Self-citationNguyen, L. H., Cao, Y., Hur, J., Mehta, R. S., Sikavi, D. R., Wang, Y., Ma, W., Wu, K., Song, M., Giovannucci, E. L., et al. (2021) · Gastroenterology · doi:10.1053/j.gastro.2021.07.008 · Cited by 109
The microbiome of the buffalo digestive tract
Feng, T., Wang, T., Gao, N., Liu, Z., Cui, K., Duan, Y., Wu, S., Luo, Y., Li, Z., Yang, C., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28402-9 · Cited by 102
Fiber, Fat, and Colorectal Cancer: New Insight into Modifiable Dietary Risk Factors
Ocvirk, S., Wilson, A. S., Appolonia, C. N., Thomas, T. K., & O’Keefe, S. J. (2019) · Current Gastroenterology Reports · doi:10.1007/s11894-019-0725-2 · Cited by 104
Probiotics and postbiotics in colorectal cancer: Prevention and complementary therapy
Kvaková, M., Kamlárová, A., Štofilová, J., Benetinová, V., & Bertková, I. (2022) · World Journal of Gastroenterology · doi:10.3748/wjg.v28.i27.3370 · Cited by 110
He, R., Li, P., Wang, J., Cui, B., Zhang, F., & Zhao, F. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2100197 · Cited by 98
Large-scale microbiome data integration enables robust biomarker identification
Xiao, L., Zhang, F., & Zhao, F. (2022) · Nature Computational Science · doi:10.1038/s43588-022-00247-8 · Cited by 101
Role of Gut Microbiota and Probiotics in Colorectal Cancer: Onset and Progression
Torres-Maravilla, E., Boucard, A.-S., Mohseni, A. H., Taghinezhad‐S, S., Cortes‐Perez, N. G., & Bermúdez‐Humarán, L. G. (2021) · Microorganisms · doi:10.3390/microorganisms9051021 · Cited by 98
Gut Microbiota and Colorectal Cancer Development: A Closer Look to the Adenoma-Carcinoma Sequence
Vacante, M., Ciuni, R., Basile, F., & Biondi, A. (2020) · Biomedicines · doi:10.3390/biomedicines8110489 · Cited by 98
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
The adhesin RadD enhances Fusobacterium nucleatum tumour colonization and colorectal carcinogenesis
Zhang, L., Leng, X.-X., Qi, J., Wang, N., Han, J., Tao, Z., Zhuang, Z.-Y., Ren, Y., Xie, Y., Jiang, S., et al. (2024) · Nature Microbiology · doi:10.1038/s41564-024-01784-w · Cited by 98
Wang, Z., Yang, Y., Yan, Z., Liu, H., Chen, B., Liang, Z., Wang, F., Miller, B. E., Tal‐Singer, R., Yi, X., et al. (2020) · The ISME Journal · doi:10.1038/s41396-020-0727-y · Cited by 96
Yang, J. H., Wei, H., Lin, Y., Chu, E. S., Zhou, Y., Gou, H., Guo, S., Lau, H. C.-H., Cheung, A. H. K., Chen, H., et al. (2023) · Gastroenterology · doi:10.1053/j.gastro.2023.10.012 · Cited by 98
Han, D., Gao, P., Li, R., Tan, P., Xie, J., Zhang, R., & Li, J. (2020) · Journal of Advanced Research · doi:10.1016/j.jare.2020.07.010 · Cited by 93
Caspi, M., Wittenstein, A., Kazelnik, M., Shor-Nareznoy, Y., & Rosin‐Arbesfeld, R. (2020) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2020.12.010 · Cited by 92
Inamura, K., Hamada, T., Bullman, S., Ugai, T., Yachida, S., & Ogino, S. (2022) · Gut · doi:10.1136/gutjnl-2022-327209 · Cited by 97
Self-citationHuang, X., Hu, M., Sun, T., Li, J., Zhou, Y., Yan, Y., Xuan, B., Wang, J., Xiong, H., Ji, L., et al. (2023) · Cell Host & Microbe · doi:10.1016/j.chom.2023.10.005 · Cited by 94
A key genetic factor governing arabinan utilization in the gut microbiome alleviates constipation
Zhang, C., Yu, L., Ma, C., Jiang, S., Zhang, Y., Wang, S., Tian, F., Xue, Y., Zhao, J., Zhang, H., et al. (2023) · Cell Host & Microbe · doi:10.1016/j.chom.2023.10.011 · Cited by 98
Microbiome distinctions between the CRC carcinogenic pathways
DeDecker, L. C., Coppedge, B., Avelar‐Barragan, J., Karnes, W. E., & Whiteson, K. (2021) · Gut Microbes · doi:10.1080/19490976.2020.1854641 · Cited by 91
The human microbiome and cancer: a diagnostic and therapeutic perspective
Kandalai, S., Li, H., Zhang, N., Peng, H., & Zheng, Q. (2023) · Cancer Biology & Therapy · doi:10.1080/15384047.2023.2240084 · Cited by 96
Yang, Y., Gharaibeh, R. Z., Newsome, R. C., & Jobin, C. (2020) · Nature Cancer · doi:10.1038/s43018-020-0078-7 · Cited by 94
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VanEvery, H., Franzosa, E. A., Nguyen, L. H., & Huttenhower, C. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00529-x · Cited by 86
The Role of Diet and Lifestyle in Early-Onset Colorectal Cancer: A Systematic Review
Puzzono, M., Mannucci, A., Grannò, S., Zuppardo, R. A., Galli, A., Danese, S., & Cavestro, G. M. (2021) · Cancers · doi:10.3390/cancers13235933 · Cited by 92
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
Fu, T., Huan, T., Rahman, G., Zhi, H., Xu, Z. Z., Oh, T. G., Guo, J. P., Coulter, S., Tripathi, A., Martino, C., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112997 · Cited by 94
Perillo, F., Amoroso, C., Strati, F., Giuffrè, M. R., Díaz‐Basabe, A., Lattanzi, G., & Facciotti, F. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21155389 · Cited by 88
Kaźmierczak-Siedlecka, K., Roviello, G., Catalano, M., & Połom, K. (2021) · Nutrients · doi:10.3390/nu13082674 · Cited by 89
Mucins, gut microbiota, and postbiotics role in colorectal cancer
Pothuraju, R., Chaudhary, S., Rachagani, S., Kaur, S., Roy, H. K., Bouvet, M., & Batra, S. K. (2021) · Gut Microbes · doi:10.1080/19490976.2021.1974795 · Cited by 89
Gut microbiome response to a modern Paleolithic diet in a Western lifestyle context
Barone, M., Turroni, S., Rampelli, S., Soverini, M., D’Amico, F., Biagi, E., Brigidi, P., Troiani, E., & Candela, M. (2019) · PLoS ONE · doi:10.1371/journal.pone.0220619 · Cited by 94
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
Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome
Kindschuh, W. F., Baldini, F., Liu, M. C., Gerson, K. D., Liao, J., Lee, H. H., Anton, L., Gajer, P., Ravel, J., Levy, M., et al. (2023) · Nature Microbiology · doi:10.1038/s41564-022-01293-8 · Cited by 90
Ocvirk, S., Wilson, A. S., Posma, J. M., Li, J. V., Koller, K. R., Day, G. M., Flanagan, C. A., Otto, E., Sacco, P. E., Sacco, F. D., et al. (2019) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqz301 · Cited by 84
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
Robust airway microbiome signatures in acute respiratory failure and hospital-acquired pneumonia
Montassier, E., Kitsios, G. D., Radder, J. E., Bastard, Q. L., Kelly, B. J., Panzer, A. R., Lynch, S. V., Calfee, C. S., Dickson, R. P., & Roquilly, A. (2023) · Nature Medicine · doi:10.1038/s41591-023-02617-9 · Cited by 88
Xie, M., Yuan, K., Zhang, Y., Zhang, Y., Zhang, R., Gao, J., Wei, W., Jiang, L., Li, T., Ding, Y., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.07.012 · Cited by 85
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
Self-citationFidelle, M., Yonekura, S., Picard, M., Cogdill, A. P., Hollebecque, A., Roberti, M. P., & Zitvogel, L. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.600886 · Cited by 87
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
Li, L., He, S., Liao, B., Wang, M., Lin, H., Hu, B., Lan, X., Shu, Z., Zhang, C., Yu, M., et al. (2024) · Research · doi:10.34133/research.0364 · Cited by 79
Optimal deep learning based fusion model for biomedical image classification
Mansour, R. F., Alfaer, N. M., Abdel‐Khalek, S., Abdelhaq, M., Saeed, R. A., & Alsaqour, R. A. (2021) · Expert Systems · doi:10.1111/exsy.12764 · Cited by 83
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
Niccolai, E., Russo, E., Baldi, S., Ricci, F., Nannini, G., Pedone, M., Stingo, F. C., Taddei, A., Ringressi, M. N., Bechi, P., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2020.573158 · Cited by 79
Sharing of Antimicrobial Resistance Genes between Humans and Food Animals
Cao, H., Bougouffa, S., Park, T.-J., Lau, A., Tong, M.-K., Chow, K., & Ho, P. (2022) · mSystems · doi:10.1128/msystems.00775-22 · Cited by 79
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-citationPardini, B., Ferrero, G., Tarallo, S., Gallo, G., Francavilla, A., Licheri, N., Trompetto, M., Clerico, G. F., Senore, C., Peyre, S., et al. (2023) · Gastroenterology · doi:10.1053/j.gastro.2023.05.037 · Cited by 80
Self-citationMas-Lloret, J., Obón‐Santacana, M., Ibáñez‐Sanz, G., Guinó, E., Pato, M. L., Rodríguez‐Moranta, F., Mata, A., García‐Rodríguez, A., Moreno, V. R., & Pimenoff, V. N. (2020) · Scientific Data · doi:10.1038/s41597-020-0427-5 · Cited by 82
Yeoh, 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
Microbial metabolites in colorectal tumorigenesis and cancer therapy
Liu, Y., Lau, H. C.-H., & Yu, J. Q. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2203968 · Cited by 84
Zhu, X., Hu, M., Huang, X., Li, L., Lin, X., Shao, X., Li, J., Du, X., Zhang, X., Sun, R., et al. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2024.12.013 · Cited by 83
Genome-Scale Metabolic Modeling of the Human Microbiome in the Era of Personalized Medicine
Heinken, A., Basile, A., Hertel, J., Thinnes, C. C., & Thiele, I. (2021) · Annual Review of Microbiology · doi:10.1146/annurev-micro-060221-012134 · Cited by 76
Tomofuji, Y., Maeda, Y., Oguro-Igashira, E., Kishikawa, T., Yamamoto, K., Sonehara, K., Motooka, D., Matsumoto, Y., Matsuoka, H., Yoshimura, M., et al. (2021) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2021-220687 · Cited by 75
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
Metadata
- Authors
- Wirbel, J., Pyl, P. T., Kartal, E., Zych, K., Kashani, A., Milanese, A., Fleck, J. S., Voigt, A. Y., Palleja, A., Ponnudurai, R., Sunagawa, S., Coelho, L. P., Schrotz-King, P., Vogtmann, E., Habermann, N., Niméus, E., Thomas, A. M., Manghi, P., Gandini, S., Serrano, D., Mizutani, S., Shiroma, H., Shiba, S., Shibata, T., Yachida, S., Yamada, T., Waldron, L., Naccarati, A., Segata, N., Sinha, R., Ulrich, C. M., Brenner, H., Arumugam, M., Bork, P., & Zeller, G.
- Affiliations
- European Molecular Biology Laboratory (DE)
- University of Copenhagen (DK)
- ETH Zurich (CH)
- Shanghai Medical College of Fudan University (CN)
- National Cancer Institute (US)
- Lund University (SE)
- Universidade de São Paulo (BR)
- University of Trento (IT)
- European Institute of Oncology (IT)
- Tokyo Institute of Technology (JP)
- National Cancer Center Research Institute (JP)
- Institute of Medical Science, The University of Tokyo (JP)
- City University of New York (US)
- Italian institute for Genomic Medicine (IT)
- University of Utah (US)
- German Cancer Research Center (DE)
- Corresponding author
- Arumugam, Manimozhiyan
- Zeller, Georg
- ORCID
- Wirbel, Jakob
- Pyl, Paul Theodor
- Kartal, Ece
- Zych, Konrad
- Milanese, Alessio
- Fleck, Jonas S.
- Voigt, Anita Y.
- Palleja, Albert
- Sunagawa, Shinichi
- Coelho, Luis Pedro
- Schrotz-King, Petra
- Vogtmann, Emily
- Niméus, Emma
- Thomas, Andrew M.
- Manghi, Paolo
- Gandini, Sara
- Serrano, Davide
- Mizutani, Sayaka
- Shiroma, Hirotsugu
- Shiba, Satoshi
- Shibata, Tatsuhiro
- Yachida, Shinichi
- Yamada, Takuji
- Waldron, Levi
- Naccarati, Alessio
- Segata, Nicola
- Sinha, Rashmi
- Ulrich, Cornelia M.
- Brenner, Hermann
- Arumugam, Manimozhiyan
- Bork, Peer
- Zeller, Georg
- Venue
- Nature Medicine
- Published
- 2019-04
- Volume
- 25
- Issue
- 4
- Pages
- 679-689
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- PMC
- PMC7984229
- OpenAlex
- W2927453907
- Semantic Scholar
- 62b9cf8262232a54b36b08e6822fc0e815ce909a
- Cited by
- 1,373
- References
- 85
- Citations by year
- 2026: 214 · 2025: 215 · 2024: 224 · 2023: 189 · 2022: 176 · 2021: 169 · 2020: 143 · 2019: 41
- FWCI
- 11.74
- Type
- journal article
- Language
- en
- Open access
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- University of Southern Denmark Research Portal (University of Southern Denmark) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Iris (University of Trento) (submittedVersion, other-oa)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Funders
- Deutsches Krebsforschungszentrum
- Huntsman Cancer Foundation
- Eidgenössische Technische Hochschule Zürich
- Novo Nordisk
- Helmut Horten Stiftung
- National Institutes of Health
- Japan Society for the Promotion of Science (16H06279, 18K15800)
- National Cancer Institute (R01CA189184, R01CA207371, ZIACP010198, P30CA042014, U01CA206110)
- H2020 European Research Council (669830, 716575)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Infectious Diseases › Clostridium difficile and Clostridium perfringens research
- Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
- Keywords
- colorectal cancer, gut microbiota, fecal metagenome, microbial signatures, cross-study comparison, protein degradation, carbohydrate degradation, secondary bile acids, cancer diagnosis
- MeSH terms
- Gastrointestinal Microbiome, Adenoma, Aged, Feces, Female, Humans, Male, Middle Aged, Models, Biological, Species Specificity, Biomarkers, Tumor, Colorectal Neoplasms, Reproducibility of Results, Cohort Studies, Databases, Genetic, Metagenome
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