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Nutrition and Metabolism Branch (NME)

Research


Research in NME is currently structured around six teams that work in an integrated and collaborative way:

Hormones and metabolism

Team Leader: Sabina Rinaldi

The overarching aim of this team is to advance research on the role of hormones and metabolism in cancer etiology, building on established molecular epidemiology research on hormone-dependent cancers (with an emphasis on cancers of the breast, endometrium, ovary, and thyroid). This research programme is based on the application of cutting-edge laboratory-based technologies to large-scale epidemiological studies. Crucial support for the team’s activities is provided by the laboratory facilities that have been specifically tailored to the application of novel molecular technologies to epidemiological studies. Currently, major activities include measurements of hormones, inflammatory factors, fatty acids, and endogenous metabolites, analysed by a variety of assays (immunoassays, gas chromatography–mass spectrometry [GC-MS], liquid chromatography–mass spectrometry [LC-MS]) in samples from large-scale epidemiological studies. Technological development is also a major focus and is crucial to support evolving research.

Onco-metabolomics

Team Leaders: Pekka Keski-Rahkonen and Mazda Jenab

NME is internationally recognized in the application of metabolomics to large-scale epidemiological and human intervention studies on cancer, with expertise in laboratory-based metabolomics, bioinformatics, and cancer-nutrition-metabolic epidemiology. The onco-metabolomics team implements modern, state-of-the-art LC-MS-based analytical techniques to assess, measure, and identify metabolites in various biospecimens (blood, urine, stool, tissues) and to study metabolite variations associated with cancer outcomes. The team also undertakes studies to identify novel biomarkers of dietary, lifestyle, and environmental exposures for cancer risk factors that may help to improve the accuracy of exposure measurement in cancer epidemiological and intervention studies. The team actively develops and implements new laboratory- and bioinformatics-based methodologies, emphasizing annotation and biological interpretation of the metabolome. Areas of major research interest include identification of novel biomarkers of diet, metabolic mechanisms of cancer development (e.g. gut barrier functionality, the gut–liver axis, microbiome dysbiosis, bile acid metabolism), novel exogenous or endogenous exposures (e.g. glycation products and dicarbonyl stress, polyphenols), and the microbial exposome.

Lifestyle exposure and interventions

Team Leader: Inge Huybrechts

The overall goal of this team is to leverage lifestyle research (e.g. nutrition, physical activity, sedentary behavior, sleep, and stress research) to enhance the understanding of the causes of lifestyle-related cancers and identify pathways to prevention. A major focus of the team is the development and dissemination of innovative methods of exposure assessment as well as sustainable evidence-based lifestyle interventions that will help researchers and other relevant stakeholders to support their communities with tailored lifestyle recommendations and effective behaviour change strategies for cancer prevention. This is achieved through three integrated objectives:
  • enhancement of databases of current epidemiological studies with innovative lifestyle behaviour indicators to enable cutting-edge research on understudied lifestyle concepts (e.g. food biodiversity and processing, meal timing, circadian rhythm, and stress);
  • development of new observational studies (cohort and case–control design) in high-, middle-, and low-income settings, considering the emerging lifestyle transitions, to elucidate causal relationships between lifestyle behaviours and cancer risk (e.g. IARC-International Initiative for Pediatrics and Nutrition [IIPAN] programme on nutrition and childhood cancer); and
  • development of sustainable cost-effective and wide-reaching lifestyle behaviour change interventions, and evaluation of their efficacy for cancer prevention; these intervention strategies make use of teachable moments, such as during cancer screening, to reach high-risk population groups during periods when they may be more receptive and motivated for lifestyle behaviour changes (e.g. the LIFE-SCREEN intervention currently being evaluated in the colorectal cancer screening programme in France).

Biostatistics and data integration

Team Leaders: Vivian Viallon and Pietro Ferrari

This team provides statistical support to research conducted within NME and oversees the management of epidemiological data, in particular molecular, lifestyle, cancer end-points, and vital status within the EPIC cohort and other NME studies. Appropriate use of statistical methodology across IARC is also promoted via direct support and training/seminars. The team also leads the development, implementation, and application of biostatistical and bioinformatic techniques for the analysis and integration of lifestyle and molecular data, including metabolomics, proteomics, genetics, and epigenetic data within cancer epidemiology studies. Specific current projects include the development of statistical methods for the normalization, pre-processing, and analysis of metabolomics data, discovery of novel biomarkers of diet using untargeted metabolomic data, identification of -omics signatures of lifestyle and their relationship with cancer, and research on healthy lifestyle patterns and cancer risk. The team also leads a major programme of research on alcohol and cancer, with a focus on understudied cancers, mechanisms underlying the alcohol–cancer link, and alcohol consumption patterns throughout the life-course and cancer.

Nutrition and cancer multimorbidity

Team Leader: Heinz Freisling

This team investigates how nutrition, obesity, and metabolic dysfunction interact with cardiometabolic diseases, including cardiovascular diseases and type 2 diabetes, in relation to cancer incidence. nutrition, obesity, and metabolic dysfunction interact with cardiometabolic diseases, including cardiovascular diseases and type 2 diabetes, in relation to cancer incidence. The co-occurrence of chronic diseases in individuals, such as cardiometabolic diseases and cancer, defined as multimorbidity, is becoming increasingly common. Multimorbidity could be due to common risk factors among chronic conditions, such as obesity, physical inactivity, or unhealthy diets, but it could also be caused by shared biological pathways. Furthermore, metabolic consequences of cardiometabolic diseases may have incremental impacts on cancer risk. However, these interrelationships still need to be elucidated in robust population-based settings. The role of lifestyle factors and the occurrence of morbid conditions that affect survival in people living with cancer is also an area of research for the team.

Metabolic epidemiology

Team Leader: Neil Murphy

This team conducts collaborative research using diverse but complementary analytical methods, including traditional and molecular epidemiological approaches, such as Mendelian randomization, gene–environment interaction, metabolomics, proteomics, and molecular pathological analyses. Projects are conducted using data from worldwide prospective cohorts, clinical databases, and consortia. The research focuses mainly on identifying etiological risk factors for gastrointestinal cancers, specifically examining how obesity, diabetes, physical inactivity, and related metabolic abnormalities influence cancer development, and molecular epidemiological approaches are used to uncover the mediating biological pathways. The team recently initiated a portfolio of studies to investigate the etiology of early-onset colorectal cancer (diagnosed before age 50 years), for which the rising incidence rates remain unexplained. This research is conducted within the NCI Cohort Consortium project (the Colorectal Cancer Pooling Project [C2P2]), in which associations of emerging and established risk factors with early-onset colorectal cancer are being investigated. The team also leverages data from clinical databases and genetic consortia to identify causal relationships between putative risk factors and the development of early-onset colorectal cancer.

 

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