Untargeted lipidomic features associated with colorectal cancer in a prospective cohort

[1]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[2]  S. O'keefe Diet, microorganisms and their metabolites, and colon cancer , 2016, Nature Reviews Gastroenterology &Hepatology.

[3]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[4]  Li Li,et al.  A genome-wide systems analysis reveals strong link between colorectal cancer and trimethylamine N-oxide (TMAO), a gut microbial metabolite of dietary meat and fat , 2015, BMC Genomics.

[5]  C. Ulrich,et al.  Plasma choline metabolites and colorectal cancer risk in the Women's Health Initiative Observational Study. , 2014, Cancer research.

[6]  Kevin F Krenitsky,et al.  Reduction of novel circulating long-chain fatty acids in colorectal cancer patients is independent of tumor burden and correlates with age , 2010, BMC gastroenterology.

[7]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[8]  Chun-Nan Hsu,et al.  Weakly supervised learning of biomedical information extraction from curated data , 2016, BMC Bioinformatics.

[9]  Paolo Vineis,et al.  Evaluating Ultra-long-Chain Fatty Acids as Biomarkers of Colorectal Cancer Risk , 2016, Cancer Epidemiology, Biomarkers & Prevention.

[10]  S. Neumann,et al.  CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets. , 2012, Analytical chemistry.

[11]  P. Schloss,et al.  The Human Gut Microbiome as a Screening Tool for Colorectal Cancer , 2014, Cancer Prevention Research.

[12]  Pedro Larrañaga,et al.  A review of feature selection techniques in bioinformatics , 2007, Bioinform..

[13]  Yeisoo Yu,et al.  Uncovering the novel characteristics of Asian honey bee, Apis cerana, by whole genome sequencing , 2015, BMC Genomics.

[14]  Michael Karin,et al.  Inflammation and colon cancer. , 2010, Gastroenterology.

[15]  R. Brand,et al.  Prediagnostic Serum Biomarkers as Early Detection Tools for Pancreatic Cancer in a Large Prospective Cohort Study , 2014, PloS one.

[16]  Robin P Boushey,et al.  Colorectal cancer epidemiology: incidence, mortality, survival, and risk factors. , 2009, Clinics in colon and rectal surgery.

[17]  Ying Zhang,et al.  HMDB: the Human Metabolome Database , 2007, Nucleic Acids Res..

[18]  E. Riboli,et al.  Plasma methionine, choline, betaine, and dimethylglycine in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC). , 2014, Annals of oncology : official journal of the European Society for Medical Oncology.

[19]  Shengwu Xiong,et al.  InDel marker detection by integration of multiple softwares using machine learning techniques , 2016, BMC Bioinformatics.

[20]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[21]  H. P. Benton,et al.  XCMS 2 : Processing Tandem Mass Spectrometry Data for Metabolite Identification and Structural Characterization , 2008 .

[22]  W. Byrdwell,et al.  Dual parallel liquid chromatography with dual mass spectrometry (LC2/MS2) for a total lipid analysis. , 2008, Frontiers in bioscience : a journal and virtual library.

[23]  Kevin F Krenitsky,et al.  Reduced levels of hydroxylated, polyunsaturated ultra long-chain fatty acids in the serum of colorectal cancer patients: implications for early screening and detection , 2010, BMC medicine.

[24]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[25]  S Neumann,et al.  RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data. , 2014, Analytical chemistry.

[26]  Ralf Tautenhahn,et al.  CAMERA: An integrated strategy for compound spectra extraction and annotation of LC/MS data sets , 2013 .

[27]  S. Neumann,et al.  Metabolite profiling and beyond: approaches for the rapid processing and annotation of human blood serum mass spectrometry data , 2013, Analytical and Bioanalytical Chemistry.

[28]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[29]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[30]  Robert C. G. Martin,et al.  Environmental Exposures, Tumor Heterogeneity, and Colorectal Cancer Outcomes , 2014, Current Colorectal Cancer Reports.

[31]  N. Gassler,et al.  Modifier-concept of colorectal carcinogenesis: lipidomics as a technical tool in pathway analysis. , 2010, World journal of gastroenterology.

[32]  Paolo Vineis,et al.  Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition. , 2005, Journal of the National Cancer Institute.

[33]  Stephen M. Rappaport,et al.  Genetic Factors Are Not the Major Causes of Chronic Diseases , 2016, PloS one.

[34]  Risk , 2020, Journal of paediatrics and child health.

[35]  W. Stone,et al.  The role of antioxidants and pro-oxidants in colon cancer. , 2014, World journal of gastrointestinal oncology.

[36]  N E Day,et al.  European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection , 2002, Public Health Nutrition.

[37]  K. Czene,et al.  Attributable risks of familial cancer from the Family-Cancer Database. , 2002, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[38]  Augustin Scalbert,et al.  compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC-MS Data Sets. , 2017, Analytical chemistry.

[39]  Brian J. Bennett,et al.  Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease , 2011, Nature.

[40]  Talwar Vsm Lt Col Pankaj Manual of Assisted Reproductive Technologies and Clinical Embryology , 2012 .

[41]  K. Shinohara,et al.  Perceived Parental Rejection Mediates the Influence of Serotonin Transporter Gene (5-HTTLPR) Polymorphisms on Impulsivity in Japanese Adults , 2012, PloS one.

[42]  F. Clavel-Chapelon,et al.  Blood lipid and lipoprotein concentrations and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition , 2011, Gut.

[43]  Paul C. Boutros,et al.  The parameter sensitivity of random forests , 2016, BMC Bioinformatics.

[44]  P. Rothwell,et al.  Effect of daily aspirin on long-term risk of death due to cancer: analysis of individual patient data from randomised trials , 2011, The Lancet.

[45]  B. Ogretmen,et al.  Sphingolipid metabolism in cancer signalling and therapy , 2017, Nature Reviews Cancer.

[46]  T. Takenawa,et al.  A Novel Serum Metabolomics-Based Diagnostic Approach for Colorectal Cancer , 2012, PloS one.

[47]  Yanlei Ma,et al.  Association between vitamin D and risk of colorectal cancer: a systematic review of prospective studies. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[48]  R. Abagyan,et al.  XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. , 2006, Analytical chemistry.

[49]  R. Sinha,et al.  Meat consumption and risk of colorectal cancer. , 2005, JAMA.

[50]  Ahmedin Jemal,et al.  Global patterns and trends in colorectal cancer incidence and mortality , 2016, Gut.

[51]  Joshua D. Knowles,et al.  Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry , 2011, Nature Protocols.

[52]  Paolo Vineis,et al.  The Blood Exposome and Its Role in Discovering Causes of Disease , 2014, Environmental health perspectives.

[53]  Christopher G. Adda,et al.  Rapid and comprehensive 'shotgun' lipidome profiling of colorectal cancer cell derived exosomes. , 2015, Methods.

[54]  Claudio R. Santos,et al.  Lipid metabolism in cancer , 2012, The FEBS journal.

[55]  T. Ebbels,et al.  Optimized preprocessing of ultra-performance liquid chromatography/mass spectrometry urinary metabolic profiles for improved information recovery. , 2011, Analytical chemistry.

[56]  D. Goodenowe,et al.  Low-serum GTA-446 anti-inflammatory fatty acid levels as a new risk factor for colon cancer , 2012, International journal of cancer.

[57]  R. Sinha,et al.  A prospective study of serum metabolites and colorectal cancer risk , 2014, Cancer.

[58]  Douglas B. Kell,et al.  Statistical strategies for avoiding false discoveries in metabolomics and related experiments , 2007, Metabolomics.

[59]  K. Sigler,et al.  Odd-numbered very-long-chain fatty acids from the microbial, animal and plant kingdoms. , 2009, Progress in lipid research.

[60]  Francis R. Bach,et al.  Bolasso: model consistent Lasso estimation through the bootstrap , 2008, ICML '08.

[61]  M. Singer,et al.  BMI and waist circumference as predictors of lifetime colon cancer risk in Framingham Study adults , 2004, International Journal of Obesity.

[62]  F. Clavel-Chapelon,et al.  Metabolic Syndrome and Risks of Colon and Rectal Cancer: The European Prospective Investigation into Cancer and Nutrition Study , 2011, Cancer Prevention Research.

[63]  Hendriek C Boshuizen,et al.  Cigarette smoking and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition study. , 2011, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[64]  Amy M. Sheflin,et al.  Stool Microbiome and Metabolome Differences between Colorectal Cancer Patients and Healthy Adults , 2013, PloS one.

[65]  Jan Alexander,et al.  The role of red and processed meat in colorectal cancer development: a perspective. , 2014, Meat science.

[66]  S. O'keefe,et al.  Diet, microbiota, and dysbiosis: a 'recipe' for colorectal cancer. , 2016, Food & function.

[67]  G. Siuzdak,et al.  XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization. , 2008, Analytical chemistry.

[68]  Wolfgang Schramm,et al.  Team , 2018, Spaces of Intensity.

[69]  Tao Jiang,et al.  Accurate inference of isoforms from multiple sample RNA-Seq data , 2015, BMC Genomics.

[70]  Herbert H Hill,et al.  Metabolomics of colorectal cancer: past and current analytical platforms , 2013, Analytical and Bioanalytical Chemistry.

[71]  Colin A. Smith LC / MS Preprocessing and Analysis with xcms , 2005 .

[72]  E. Rimm,et al.  Proportion of colon cancer risk that might be preventable in a cohort of middle-aged US men , 2004, Cancer Causes & Control.

[73]  R. Abagyan,et al.  METLIN: A Metabolite Mass Spectral Database , 2005, Therapeutic drug monitoring.

[74]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .