Exploring mechanisms of diet-colon cancer associations through candidate molecular interaction networks

David Westergaard, Jun Li, Kasper Jensen, Irene Kouskoumvekaki, Gianni Panagiotou

    Research output: Contribution to journalJournal articleResearchpeer-review

    248 Downloads (Pure)

    Abstract

    Background: Epidemiological studies in the recent years have investigated the relationship between dietary habits and disease risk demonstrating that diet has a direct effect on public health. Especially plant-based diets-fruits, vegetables and herbs-are known as a source of molecules with pharmacological properties for treatment of several malignancies. Unquestionably, for developing specific intervention strategies to reduce cancer risk there is a need for a more extensive and holistic examination of the dietary components for exploring the mechanisms of action and understanding the nutrient-nutrient interactions. Here, we used colon cancer as a proof-of-concept for understanding key regulatory sites of diet on the disease pathway. Results: We started from a unique vantage point by having a database of 158 plants positively associated to colon cancer reduction and their molecular composition (similar to 3,500 unique compounds). We generated a comprehensive picture of the interaction profile of these edible and non-edible plants with a predefined candidate colon cancer target space consisting of similar to 1,900 proteins. This knowledge allowed us to study systematically the key components in colon cancer that are targeted synergistically by phytochemicals and identify statistically significant and highly correlated protein networks that could be perturbed by dietary habits. Conclusion: We propose here a framework for interrogating the critical targets in colon cancer processes and identifying plant-based dietary interventions as important modifiers using a systems chemical biology approach. Our methodology for better delineating prevention of colon cancer by nutritional interventions relies heavily on the availability of information about the small molecule constituents of our diet and it can be expanded to any other disease class that previous evidence has linked to lifestyle.
    Original languageEnglish
    JournalB M C Genomics
    Volume15
    Issue number1
    ISSN1471-2164
    DOIs
    Publication statusPublished - 2014

    Keywords

    • dietray pattern
    • disease pathway
    • drug discovery
    • molecular interaction network
    • colon cancer Colonic Neoplasms (MeSH) digestive system disease, neoplastic disease pathology, diet therapy, genetics, prevention and control, etiology
    • Plantae (Plants) - Plantae [11000] plant common medicinal plant
    • Primates Mammalia Vertebrata Chordata Animalia (Animals, Chordates, Humans, Mammals, Primates, Vertebrates) - Hominidae [86215] human common
    • Rodentia Mammalia Vertebrata Chordata Animalia (Animals, Chordates, Mammals, Nonhuman Vertebrates, Nonhuman Mammals, Rodents, Vertebrates) - Muridae [86375] Rattus norvegicus species Mus musculus species
    • gene
    • phytochemical
    • protein network
    • 03502, Genetics - General
    • 03504, Genetics - Plant
    • 03506, Genetics - Animal
    • 03508, Genetics - Human
    • 12502, Pathology - General
    • 12512, Pathology - Therapy
    • 13202, Nutrition - General studies, nutritional status and methods
    • 14006, Digestive system - Pathology
    • 24004, Neoplasms - Pathology, clinical aspects and systemic effects
    • 51504, Plant physiology - Nutrition
    • 54000, Pharmacognosy and pharmaceutical botany
    • Biochemistry and Molecular Biophysics
    • Human Medicine, Medical Sciences
    • Pharmacology
    • chemoinformatics method mathematical and computer techniques
    • Gastroenterology
    • Molecular Genetics
    • Nutrition
    • Oncology
    • Pharmacognosy
    • BIOTECHNOLOGY
    • GENETICS
    • COLORECTAL-CANCER
    • INTEGRATION
    • PREVENTION
    • PREDICTION
    • METABOLISM

    Fingerprint Dive into the research topics of 'Exploring mechanisms of diet-colon cancer associations through candidate molecular interaction networks'. Together they form a unique fingerprint.

    Cite this