• Annex 1. State of validation of biomarkers.

      The Nofer Institute of Occupational Medicine, 2007
    • Appendix 1. DNA adducts.

      The Nofer Institute of Occupational Medicine, 2007
    • Appendix 2. Heterocyclic aromatic amines.

      The Nofer Institute of Occupational Medicine, 2007
    • Appendix 3. 1-Hydroxypyrene.

      The Nofer Institute of Occupational Medicine, 2007
    • Appendix 4. Oxidative damage to DNA.

      The Nofer Institute of Occupational Medicine, 2007
    • Bioactive components in foods.

      Manson, Margaret M.; Linseisen, Jakob; Rohrmann, Sabine; Sotiroudis, Theodore G.; Kyrtopoulos, Soterios A.; Hayes, John D.; Kelleher, Michael O.; Eggleston, Ian M.; de Kok, Theo M.; van Breda, Simone G.; et al. (The Nofer Institute of Occupational Medicine, 2007-04)
    • Challenges from new technologies and new biomarkers.

      Vineis, Paolo; Vermeulen, Roel; Geneletti, Sara; Minelli, Cosetta; Taioli, Emanuela; Thompson, John; Stromberg, Ulf; Kirsch-Volders, Micheline; Raluca, Mateuca; Matullo, Giuseppe (The Nofer Institute of Occupational Medicine, 2007)
    • Comments and suggestions for future work.

      The Nofer Institute of Occupational Medicine, 2007
    • Conclusions.

      Farmer, Peter (The Nofer Institute of Occupational Medicine, 2007)
    • Correlations among biomarkers.

      Gyorffy, Erika; Anna, Livia; Rudnai, Peter; Kovacs, Katalin; Schocket, Bernadette (The Nofer Institute of Occupational Medicine, 2006)
      An extensive literature survey on correlation of biomarkers resulted in the following preliminary conclusions: • No significant correlation between individual pairs of DNA adducts was found in a number of the 32P-postlabelling and immunoassay studies, indicating limited overlapping of the substrate specificity of the different DNA adduct methods. • Attempts to show correlations between a group of related DNA adduct structures and a chemically specific single DNA adduct structure by using the same type of methodology gave controversial results. These suggest the co-existence of both closely linked and independent metabolic activation pathways for complex mixtures of xenobiotics, and may also reflect differences in the kinetics of DNA adduct formation and elimination. • A larger number of studies revealed a positive correlation between DNA adduct levels in target and surrogate tissues than did not find a correlation. Correlation may depend on exposure dose and the metabolic capacity of the corresponding tissues. • In the majority of the studies there was a positive correlation between DNA adduct levels in tumour and normal tissues, suggesting similarities in the xenobiotic activation/elimination processes of the tumour and normal tissues. However, the levels of DNA adducts found suggested organ specificity. • There was a positive correlation for different urinary metabolites and urinary mutagenicity in most of the studies. • No correlation between DNA adducts and urinary polycyclic aromatic hydrocarbon metabolites was generally found, but stratification by genotype suggested that correlation might be present. • Correlation was more probable between structurally specified protein adducts and urinary polycyclic aromatic hydrocarbon metabolite 1-hydroxypyrene than with less specific xenobiotic-protein structures. • Stratification of the study population for confounding factors, such as smoking status, may reveal hidden correlations. • Cytogenetic biomarker studies also gave complex results. Examples of both positive correlation and lack of correlation with exposure markers were found. Molecular epidemiological studies of cancer that include exposure biomarkers have greatly increased in number in recent years, the rationale being to measure the biologically relevant aspect(s) of exposure. However, the use of biomarkers to measure exposure is not a panacea. Most biomarker-based studies, of both prospective and retrospective design, rely on a single biological sample. Most exposures in cancer epidemiology are time-related variables, and both carcinogenesis models and empirical evidence strongly point towards the importance of induction and latency periods in cancer onset, the need to separate the role of duration and intensity of exposure, and the decrease in effect after cessation of exposure. While most biomarkers measure recent exposure, it is possible to apply them in the measurement of temporal changes, e.g. by collecting repeated samples from subjects enrolled in prospective studies or from a sample of the original cohort. Another important parameter is the in vivo lifetime of the biomarker after it has been generated by a carcinogen exposure. Biomarker-based epidemiological results are subject to the methodological problems affecting all types of observational studies, namely bias and confounding. A further problem in the measurement of exposure biomarkers in retrospective studies is their possible dependence on the disease process. With the increasing use of biomarkers of dose and effect of carcinogens and the possible input of these data into the regulatory area, it is essential that the methodology be standardised and wherever possible internationally accepted protocols be established for this. The need to validate exposure biomarkers before their application in population-based studies arises from the variability in biomarker-based measurements of exposure, which can be due to interindividual sources (e.g. differences between exposed and unexposed individuals, usually the component of variability of primary interest), intraindividual sources (e.g. variability in hormonal levels) and observer sources, including measurement error. This is the domain of so-called transitional studies, which aim to characterise the biomarker itself rather than the underlying biological phenomenon. This is the area in which most work is needed in the near future: efforts such as the ECNIS Network of Excellence will be instrumental in providing a logical framework for the development and validation of biomarkers of exposure with the ultimate goal of their application in molecular epidemiological studies. • There was a positive correlation for different urinary metabolites and urinary mutagenicity in most of the studies. • No correlation between DNA adducts and urinary polycyclic aromatic hydrocarbon metabolites was generally found, but stratification by genotype suggested that correlation might be present. • Correlation was more probable between structurally specified protein adducts and urinary polycyclic aromatic hydrocarbon metabolite 1-hydroxypyrene than with less specific xenobiotic-protein structures. • Stratification of the study population for confounding factors, such as smoking status, may reveal hidden correlations. • Cytogenetic biomarker studies also gave complex results. Examples of both positive correlation and lack of correlation with exposure markers were found. Molecular epidemiological studies of cancer that include exposure biomarkers have greatly increased in number in recent years, the rationale being to measure the biologically relevant aspect(s) of exposure. However, the use of biomarkers to measure exposure is not a panacea. Most biomarker-based studies, of both prospective and retrospective design, rely on a single biological sample. Most exposures in cancer epidemiology are time-related variables, and both carcinogenesis models and empirical evidence strongly point towards the importance of induction and latency periods in cancer onset, the need to separate the role of duration and intensity of exposure, and the decrease in effect after cessation of exposure. While most biomarkers measure recent exposure, it is possible to apply them in the measurement of temporal changes, e.g. by collecting repeated samples from subjects enrolled in prospective studies or from a sample of the original cohort. Another important parameter is the in vivo lifetime of the biomarker after it has been generated by a carcinogen exposure. Biomarker-based epidemiological results are subject to the methodological problems affecting all types of observational studies, namely bias and confounding. A further problem in the measurement of exposure biomarkers in retrospective studies is their possible dependence on the disease process. With the increasing use of biomarkers of dose and effect of carcinogens and the possible input of these data into the regulatory area, it is essential that the methodology be standardised and wherever possible internationally accepted protocols be established for this. The need to validate exposure biomarkers before their application in population-based studies arises from the variability in biomarker-based measurements of exposure, which can be due to interindividual sources (e.g. differences between exposed and unexposed individuals, usually the component of variability of primary interest), intraindividual sources (e.g. variability in hormonal levels) and observer sources, including measurement error. This is the domain of so-called transitional studies, which aim to characterise the biomarker itself rather than the underlying biological phenomenon. This is the area in which most work is needed in the near future: efforts such as the ECNIS Network of Excellence will be instrumental in providing a logical framework for the development and validation of biomarkers of exposure with the ultimate goal of their application in molecular epidemiological studies.
    • DNA repair enzyme genotypes and their toxicologically relevant phenotypes.

      Aka, Peter; Mateuca, Raluca; Kirsch-Volders, Micheline (Nofer Institute of Occupational Medicine, 2008)
    • Dose response and potential thresholds in activation and inactivation of procarcinogens.

      Henderson, Colin J.; Paine, Mark J.I.; Friedberg, Thomas; Wolf, Charles Roland (Nofer Institute of Occupational Medicine, 2008)
    • Dose response and potential thresholds in DNA adduct formation.

      Segerback, Dan (Nofer Institute of Occupational Medicine, 2008)
    • Dose response and potential thresholds in gene expression.

      van Delft, Joost (Nofer Institute of Occupational Medicine, 2008)
    • Dose response and potential thresholds in proliferation and cell survival and death.

      Mateuca, Raluca; Decordier, Ilse; Cundari, Enrico; Kirsch-Volders, Micheline (Nofer Institute of Occupational Medicine, 2008)
    • Dose-response and potential thresholds in tumour development.

      Oesch, Franz; Weiss, Carsten; Dietrich, Cornelia; Oesch-Bartlomowicz, Barbara (Nofer Institute of Occupational Medicine, 2008)
    • The epidemiological theory: principles of biomarker validation.

      Vineis, Paolo; Gallo, Valentina (The Nofer Institute of Occupational Medicine, 2007)
    • Introduction.

      Akesson, Bjorn (The Nofer Institute of Occupational Medicine, 2007-04)
    • Introduction.

      Kyrtopoulos, Soterios (The Nofer Institute of Occupational Medicine, 2007)