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The Precision Medicine Approach in Oncology
Published in David E. Thurston, Ilona Pysz, Chemistry and Pharmacology of Anticancer Drugs, 2021
Toxicogenomic studies are highly dependent on a range of genomic technologies many of which have seen significant improvements in robustness, affordability, and speed of throughput during the past decade. However, data analysis is still one of the remaining key challenges in rendering data sets sufficiently comprehensive and statistically significant enough to be used for meaningful risk–benefit assessment. Therefore, in addition to bioinformatics, biostatistics methodologies are now playing an increasing role. Biostatistics is the application of mathematical methods to extract significant biomarker changes from complex biological data sets, and can support biological or clinical data mining with correlation, classification, regression, model building, and hypothesis testing. Assessing risk versus benefit using validated biomarkers ensures that thresholds are reached that have been established in previous studies. At present, most studies of this type still use classical markers for decision-making (e.g., serum creatinine levels for kidney damage), but new potential biomarkers can be validated in parallel and their measured values correlated with endpoints. Sometimes the same biomarker can be used for both safety and efficacy, and it is then a matter of using expression level to rank the effect in both the efficacy and toxicity windows.
Toxicogenomics
Published in Frank A. Barile, Barile’s Clinical Toxicology, 2019
Anirudh J. Chintalapati, Zacharoula Konsoula, Barile Frank A.
Toxicogenomics is a relatively new field oriented toward the response of an entire genome to toxicants or environmental stressors. Toxicogenomics encompasses three major objectives: to elucidate the connection between environmental stress and disease susceptibility; to establish proper biomarkers of disease and exposure to toxic substances; and to clarify the molecular mechanisms of toxicity. Toxicogenomics incorporates traditional toxicological and histopathologic endpoint-evaluation with the data surges derived from transcriptomics, proteomics, metabolomics, and metabonomics. The terminology of these terms is described in Table 12.1.
Toxicogenomics in Toxicologic Pathology
Published in Pritam S. Sahota, James A. Popp, Jerry F. Hardisty, Chirukandath Gopinath, Page R. Bouchard, Toxicologic Pathology, 2018
Arun R. Pandiri, David E. Malarkey, Mark J. Hoenerhoff
Toxicogenomics encompasses the generation, interpretation, and storage of information about genetic, epigenetic, and protein activity within particular cells, tissues, and/or organisms in response to toxic substances. Toxicogenomics data may comprise transcriptomics, epigenomics, proteomics, metabolomics, or a combination of one or more of these data. These large data are derived from the respective high throughput technologies such as DNA microarrays and RNASeq (transcriptomics), global methylation arrays or global bisulfite sequencing, Chip-Seq for global histone modifications, miRNA arrays (epigenomics), mass spectrometry, protein microarrays (proteomics), NMR-spectroscopy, and mass spectroscopy (metabonomics).
Development of an adverse outcome pathway for radiation-induced microcephaly via expert consultation and machine learning
Published in International Journal of Radiation Biology, 2022
Thomas Jaylet, Roel Quintens, Mohamed Abderrafi Benotmane, Jukka Luukkonen, Ignacia Braga Tanaka, Chrystelle Ibanez, Christelle Durand, Magdalini Sachana, Omid Azimzadeh, Christelle Adam-Guillermin, Knut Erik Tollefsen, Olivier Laurent, Karine Audouze, Olivier Armant
The integration of the effects observed at different levels of biological organization, central for the AOP framework, was identified as closely linked to the concept of systems biology. The existence of a high-throughput dataset describing the effects of IR on gene expression leading to microcephaly in the mouse embryonic brain (Mfossa et al. 2020) was discussed as an interesting approach to identify KEs and characterize the KERs, but such analysis was beyond the reach of the group. Instead, the screening of additional databases useful for AOP development, such as the Comparative Toxicogenomics Database (CTD), GeneCards, AOP-Wiki and PubMed databases were highlighted as useful approaches to capture and assess evidence systematically. The integration of these data to the results of the scoping review, also performed by the WG, was thus proposed as an innovative way to incorporate the existing knowledge to the microcephaly AOP and ensure its comprehensive assembly.
Assessing cancer hazards of bitumen emissions – a case study for complex petroleum substances
Published in Critical Reviews in Toxicology, 2018
Anthony J. Kriech, Ceinwen A. Schreiner, Linda V. Osborn, Anthony J. Riley
With much of the work addressing PAC mechanisms performed with individual well-characterized compounds, it is tempting to use additivity as the method for determining hazard from these complex substances. Recently, toxicogenomics has been used to address mode of action and points of departure for human health risk assessments. Labib et al. (2016 manuscript submitted; Labib, 2016 thesis) exposed MutaTM Mouse by oral gavage for 28 days to coal tar extract, or to a PAC mixture of 4 or 8 PACs found in coal tar. Three days after termination of exposure, microarrays were prepared to identify genes differentially expressed in lung tissue; cancer related pathways were identified and specific dose-response modeling was conducted to calculate gene/pathway benchmark doses [BMD]. Pathway BMD derived from coal tar were comparable to BMD from published coal tar-induced mouse lung incidence data but concentration addition modeling overestimated responses. Although this study addressed coal tar components, use of toxicogenomics with appropriate modeling could be useful in evaluating complex PAC substances and bitumen emissions concentrate specifically.
Isolation and molecular characterization of spermatogonia from male Sprague-Dawley rats exposed in utero and postnatally to dibutyl phthalate or acrylamide
Published in Toxicology Mechanisms and Methods, 2019
Nathália P. Souza, Lora L. Arnold, Karen L. Pennington, Merielen G. Nascimento e Pontes, Helio A. Miot, João Lauro V. de Camargo, Samuel M. Cohen
Therefore, the association of spermatogonia isolation and Real-Time PCR can be used to detect gene effects in testicular germ cells after chemical exposure and appears to be more sensitive than morphology alone. The use of gene expression analyses could lead to information on the toxicity mechanisms of substances and support human safety and risk assessments. The use of toxicogenomics in regulatory toxicology has received much attention lately and the technical procedures described in this manuscript might be useful for this novel approach to risk sciences.