The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Measuring the exposome: A powerful basis for evaluating environmental exposures and cancer risk
Abstract
Advances in laboratory sciences offer much in the challenge to unravel the complex etiology of cancer and to therefore provide an evidence‐base for prevention. One area where improved measurements are particularly important to epidemiology is exposure assessment; this requirement has been highlighted through the concept of the exposome. In addition, the ability to observe genetic and epigenetic alterations in individuals exposed to putative risk factors also affords an opportunity to elucidate underlying mechanisms of carcinogenesis, which in turn may allow earlier detection and more refined molecular classification of disease. In this context the application of omics technologies to large population‐based studies and their associated biobanks raise exciting new avenues of research. This review considers the areas of genomics, transcriptomics, epigenomics and metabolomics and the evidence to date that people exposed to well‐defined factors (for example, tobacco, diet, occupational exposures, environmental pollutants) have specific omics profiles. Although in their early stages of development these approaches show promising evidence of distinct exposure‐derived biological effects and indicate molecular pathways that may be particularly relevant to the carcinogenic process subsequent to environmental and lifestyle exposures. Such an interdisciplinary approach is vital if the full benefits of advances in laboratory sciences and investments in large‐scale prospective cohort studies are to be realized in relation to cancer prevention. Environ. Mol. Mutagen. 54:480‐499, 2013. © 2013 Wiley Periodicals, Inc.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020
p53 Mutations in Human Cancers
Hollstein, M., Sidransky, D., Vogelstein, B., & Harris, C. C. (1991) · Science · doi:10.1126/science.1905840 · Cited by 8,018
Newgard, C. B., An, J., Bain, J. R., Muehlbauer, M. J., Stevens, R. D., Lien, L. F., Haqq, A. M., Shah, S. H., Arlotto, M., Slentz, C. A., et al. (2009) · Cell Metabolism · doi:10.1016/j.cmet.2009.02.002 · Cited by 3,165
Wild, C. P. (2005) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-05-0456 · Cited by 2,562
Self-citationEpigenetics and the environment: emerging patterns and implications
Feil, R., & Fraga, M. F. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3142 · Cited by 1,929
A comprehensive catalogue of somatic mutations from a human cancer genome
Pleasance, E. D., Cheetham, R. K., Stephens, P. J., McBride, D. J., Humphray, S. J., Greenman, C. D., Varela, I., Lin, M.-L., Ordóñez, G. R., Bignell, G. R., et al. (2010) · Nature · doi:10.1038/nature08658 · Cited by 1,696
Personal omics profiling reveals dynamic molecular and medical phenotypes
Chen, R., Mias, G. I., Li-Pook-Than, J., Jiang, L., Lam, H. Y. K., Chen, R., Miriami, E., Karczewski, K. J., Hariharan, M., Dewey, F. E., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.009 · Cited by 1,291
Human metabolic phenotype diversity and its association with diet and blood pressure
Holmes, E., Loo, R. L., Stamler, J., Bictash, M., Yap, I. K. S., Chan, Q., Ebbels, T., De Iorio, M., Brown, I. J., Veselkov, K. A., et al. (2008) · Nature · doi:10.1038/nature06882 · Cited by 1,054
Rhee, E. P., Cheng, S., Larson, M. G., Walford, G. A., Lewis, G. D., McCabe, E., Yang, E., Farrell, L., Fox, C. S., O’Donnell, C. J., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci44442 · Cited by 647
Huffman, K. M., Shah, S. H., Stevens, R. D., Bain, J. R., Muehlbauer, M., Slentz, C. A., Tanner, C. J., Kuchibhatla, M., Houmard, J. A., Newgard, C. B., et al. (2009) · Diabetes Care · doi:10.2337/dc08-2075 · Cited by 410
Cited by
The food metabolome: a window over dietary exposure
Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.076133 · Cited by 519
Self-citationEarly-onset colorectal cancer: initial clues and current views
Hofseth, L. J., Hebert, J. R., Chanda, A., Chen, H., Love, B. L., Pena, M. M., Murphy, E. A., Sajish, M., Sheth, A., Buckhaults, P. J., et al. (2020) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-019-0253-4 · Cited by 428
Gut microbiome and its role in colorectal cancer
Rebersek, M. (2021) · BMC Cancer · doi:10.1186/s12885-021-09054-2 · Cited by 355
Influence of environmental exposure on human epigenetic regulation
Marsit, C. J. (2015) · Journal of Experimental Biology · doi:10.1242/jeb.106971 · Cited by 253
Lochhead, P., Chan, A. T., Nishihara, R., Fuchs, C. S., Beck, A. H., Giovannucci, E., & Ogino, S. (2015) · Modern Pathology · doi:10.1038/modpathol.2014.81 · Cited by 206
Metadata
- Authors
- Wild, C. P., Scalbert, A., & Herceg, Z.
- Venue
- Environmental and Molecular Mutagenesis
- Publisher
- Wiley
- Published
- 2013-05-16
- Volume
- 54
- Issue
- 7
- Pages
- 480-499
- ISSN
- 0893-6692 (ISSN-L)
- 1098-2280
- OpenAlex
- W2150352109
- Cited by
- 227
- References
- 23
- FWCI
- 14.73
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Measuring the exposome: A powerful basis for evaluating environmental exposures and cancer risk. https://app.cochat.ai/papers/10.1002/em.21777
- The paper
- Wild, C. P., Scalbert, A., & Herceg, Z. (2013). Measuring the exposome: A powerful basis for evaluating environmental exposures and cancer risk. Environmental and Molecular Mutagenesis. https://doi.org/10.1002/em.21777
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
