Integrated multi-omic analyses provide insight into colon adenoma susceptibility modulation by the gut microbiota
暂无分享,去创建一个
[1] Guoping Niu,et al. Identification of gene signatures associated with ulcerative colitis and the association with immune infiltrates in colon cancer , 2023, Frontiers in Immunology.
[2] Ling-Hui Li,et al. Enrichment of Prevotella intermedia in human colorectal cancer and its additive effects with Fusobacterium nucleatum on the malignant transformation of colorectal adenomas , 2022, Journal of Biomedical Science.
[3] N. Neff,et al. Design, construction, and in vivo augmentation of a complex gut microbiome , 2022, Cell.
[4] Xinxiang Li,et al. Integrated metagenomic and metabolomic analysis reveals distinct gut-microbiome-derived phenotypes in early-onset colorectal cancer , 2022, Gut.
[5] Maria Pires Pacheco,et al. The gut microbial metabolite formate exacerbates colorectal cancer progression , 2022, Nature Metabolism.
[6] S. Wong,et al. Altered gut metabolites and microbiota interactions are implicated in colorectal carcinogenesis and can be non-invasive diagnostic biomarkers , 2022, Microbiome.
[7] Paul Theodor Pyl,et al. Analysing high-throughput sequencing data in Python with HTSeq 2.0 , 2021, Bioinform..
[8] Mona Singh,et al. Metabolite discovery through global annotation of untargeted metabolomics data , 2021, Nature Methods.
[9] Tomoyoshi Soga,et al. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer , 2019, Nature Medicine.
[10] J. Pearson,et al. Integrative Genome-Scale DNA Methylation Analysis of a Large and Unselected Cohort Reveals 5 Distinct Subtypes of Colorectal Adenocarcinomas , 2019, Cellular and molecular gastroenterology and hepatology.
[11] C. Sears,et al. Impact of the gut microbiome on the genome and epigenome of colon epithelial cells: contributions to colorectal cancer development , 2019, Genome Medicine.
[12] C. Hutter,et al. The Cancer Genome Atlas: Creating Lasting Value beyond Its Data , 2018, Cell.
[13] M. Hornbrook,et al. Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data , 2017, Digestive Diseases and Sciences.
[14] V. Sperandio,et al. Bacterial Chat: Intestinal Metabolites and Signals in Host-Microbiota-Pathogen Interactions , 2017, Infection and Immunity.
[15] Adela Castelló,et al. Principal components analysis in clinical studies. , 2017, Annals of translational medicine.
[16] M. Wrona,et al. Metabolic Profiling of Hoodia, Chamomile, Terminalia Species and Evaluation of Commercial Preparations Using Ultrahigh-Performance Liquid Chromatography Quadrupole-Time-of-Flight Mass Spectrometry , 2017, Planta Medica.
[17] Adarsh Sankaran,et al. Unveiling the multiscale teleconnection between Pacific Decadal Oscillation and global surface temperature using time‐dependent intrinsic correlation analysis , 2017 .
[18] T. Hadden,et al. Bile acid: a potential inducer of colon cancer stem cells , 2016, Stem Cell Research & Therapy.
[19] Minoru Kanehisa,et al. KEGG: new perspectives on genomes, pathways, diseases and drugs , 2016, Nucleic Acids Res..
[20] Elizabeth P. Ryan,et al. Metabolomics and metabolic pathway networks from human colorectal cancers, adjacent mucosa, and stool , 2016, Cancer & metabolism.
[21] F. Ryan,et al. Tumour-associated and non-tumour-associated microbiota in colorectal cancer , 2016, Gut.
[22] Caroline H. Johnson,et al. Metabolomics: beyond biomarkers and towards mechanisms , 2016, Nature Reviews Molecular Cell Biology.
[23] D. Wishart. Emerging applications of metabolomics in drug discovery and precision medicine , 2016, Nature Reviews Drug Discovery.
[24] Wen-Ying Yu,et al. Dual inhibition of COX-2/5-LOX blocks colon cancer proliferation, migration and invasion in vitro. , 2016, Oncology reports.
[25] N. Barnich,et al. Gut microbiota imbalance and colorectal cancer. , 2016, World journal of gastroenterology.
[26] Han Wu,et al. Diagnostic and Prognostic Value of Serum Interleukin-6 in Colorectal Cancer , 2016, Medicine.
[27] J. Amos-Landgraf,et al. Differential susceptibility to colorectal cancer due to naturally occurring gut microbiota , 2015, Oncotarget.
[28] David S. Wishart,et al. MetaboAnalyst 3.0—making metabolomics more meaningful , 2015, Nucleic Acids Res..
[29] S. Givan,et al. Effects of Vendor and Genetic Background on the Composition of the Fecal Microbiota of Inbred Mice , 2015, PloS one.
[30] Kazuki Saito,et al. Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects. , 2015, Natural product reports.
[31] Feng-Sheng Wang,et al. Upregulation of TLRs and IL-6 as a Marker in Human Colorectal Cancer , 2014, International journal of molecular sciences.
[32] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[33] J. Amos-Landgraf,et al. The utility of Apc-mutant rats in modeling human colon cancer , 2014, Disease Models & Mechanisms.
[34] X. Liang,et al. Co-occurrence of driver and passenger bacteria in human colorectal cancer , 2014, Gut Pathogens.
[35] Jean-Eudes J. Dazard,et al. Metabolomics of Apc Min/+ mice genetically susceptible to intestinal cancer , 2014, BMC Systems Biology.
[36] Björn Usadel,et al. Trimmomatic: a flexible trimmer for Illumina sequence data , 2014, Bioinform..
[37] Stephanie L. Servetas,et al. Comparison of three next-generation sequencing platforms for metagenomic sequencing and identification of pathogens in blood , 2014, BMC Genomics.
[38] J. Petrosino,et al. The Gut Microbiome Modulates Colon Tumorigenesis , 2013, mBio.
[39] Edward L. Huttlin,et al. Candidate serum biomarkers for early intestinal cancer using 15N metabolic labeling and quantitative proteomics in the ApcMin/+ mouse. , 2013, Journal of proteome research.
[40] Joshua M. Stuart,et al. The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.
[41] Uwe Aickelin,et al. Supervised learning and anti-learning of colorectal cancer classes and survival rates from cellular biology parameters , 2013, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[42] E. Zoetendal,et al. Diet, microbiota, and microbial metabolites in colon cancer risk in rural Africans and African Americans. , 2013, The American journal of clinical nutrition.
[43] Cole Trapnell,et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions , 2013, Genome Biology.
[44] M. Neurath,et al. Interleukin-6 - A Key Regulator of Colorectal Cancer Development , 2012, International journal of biological sciences.
[45] J. Luban,et al. TRIM5 structure, HIV-1 capsid recognition, and innate immune signaling. , 2012, Current opinion in virology.
[46] David R. Kelley,et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks , 2012, Nature Protocols.
[47] M. Newton,et al. Monoallelic silencing and haploinsufficiency in early murine intestinal neoplasms , 2012, Proceedings of the National Academy of Sciences.
[48] C. Huttenhower,et al. Metagenomic biomarker discovery and explanation , 2011, Genome Biology.
[49] F. Toldrá,et al. Handbook of dairy foods analysis. , 2009 .
[50] W. R. Wikoff,et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites , 2009, Proceedings of the National Academy of Sciences.
[51] H. Bernstein,et al. Hydrophobic bile acids, genomic instability, Darwinian selection, and colon carcinogenesis , 2008, Clinical and experimental gastroenterology.
[52] R. Abagyan,et al. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. , 2006, Analytical chemistry.
[53] P. Dixon. VEGAN, a package of R functions for community ecology , 2003 .
[54] Jerilyn A. Walker,et al. Preparation of PCR-quality mouse genomic DNA with hot sodium hydroxide and tris (HotSHOT). , 2000, BioTechniques.
[55] J. Dickerson,et al. Bile acids and health: is fibre the answer? , 1996 .
[56] F. Nagengast,et al. Role of bile acids in colorectal carcinogenesis. , 1995, European journal of cancer.
[57] L. Sumner,et al. UHPLC-QTOF-MS/MS-SPE-NMR: A Solution to the Metabolomics Grand Challenge of Higher-Throughput, Confident Metabolite Identifications. , 2019, Methods in molecular biology.
[58] A. Jemal,et al. Cancer statistics, 2018 , 2018, CA: a cancer journal for clinicians.
[59] S. Bultman. Interplay between diet, gut microbiota, epigenetic events, and colorectal cancer. , 2017, Molecular nutrition & food research.
[60] Paul J. McMurdie,et al. Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses , 2016, F1000Research.
[61] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[62] Daniela M Witten,et al. Extensions of Sparse Canonical Correlation Analysis with Applications to Genomic Data , 2009, Statistical applications in genetics and molecular biology.
[63] E. Wynder,et al. Discussion of Current Bacteriological Investigations of the Relationships between Intestinal Flora, Diet, and Colon Cancer' , 2006 .