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Multi-omics biomarkers in cadmium-related lung toxicity and carcinogenesis.

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Clinica chimica acta; international journal of clinical chemistry 📖 저널 OA 0% 2026 Vol.586() p. 120933 Heavy Metal Exposure and Toxicity
TL;DR A practical, stepwise translation pathway is suggested that emphasizes mechanistically informed multi-analyte panels, documented differences between exposure and effect biomarkers, future validation in exposed cohorts, and clinically relevant endpoints to facilitate routine laboratory implementation.
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PubMed DOI OpenAlex Semantic 마지막 보강 2026-04-30
OpenAlex 토픽 · Heavy Metal Exposure and Toxicity Aluminum toxicity and tolerance in plants and animals Chromium effects and bioremediation

Alharbi KS

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A practical, stepwise translation pathway is suggested that emphasizes mechanistically informed multi-analyte panels, documented differences between exposure and effect biomarkers, future validation i

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APA Khalid Saad Alharbi (2026). Multi-omics biomarkers in cadmium-related lung toxicity and carcinogenesis.. Clinica chimica acta; international journal of clinical chemistry, 586, 120933. https://doi.org/10.1016/j.cca.2026.120933
MLA Khalid Saad Alharbi. "Multi-omics biomarkers in cadmium-related lung toxicity and carcinogenesis.." Clinica chimica acta; international journal of clinical chemistry, vol. 586, 2026, pp. 120933.
PMID 41763445

Abstract

Cadmium exposure through smoking, occupational exposure, and pollution is linked to lung damage and cancer risk; however, most mechanistic studies remain limited to in vitro transformation and animal studies rather than large human cohorts. However, there are few clinically applicable biomarkers for early detection, risk assessment, and therapeutic monitoring. This review, centered on mechanisms, provides a summary and critical analysis of multi-omics biomarker evidence related to cadmium (Cd)-induced lung toxicity and carcinogenesis, with a particular focus on diagnostic laboratory medicine. We combine genomic and epigenomic signals (mutational signatures, cfDNA/ctDNA, methylation, and miRNA profiles) with proteomic and metabolomic readouts that represent inflammation, oxidative stress, extracellular matrix remodeling, and altered energy metabolism. In matrices (blood, urine, sputum, bronchoalveolar lavage, and extracellular vesicles), we emphasize key pre-analytical variables affecting measurements (collection tubes, processing delays, hemolysis, storage temperature, freeze-thaw cycles, and batch effects) rather than providing comprehensive experimental validation of the assays. Where appropriate, we comment on representative requirements for analytical performance and common pitfalls (limit of detection, precision, interference, calibration/traceability, and external quality assessment) of candidate biomarker classes; however, a comprehensive discussion of quantitative clinical performance measures (sensitivity, specificity, AUC, prospective validation) for most markers is lacking. Finally, we suggest a practical, stepwise translation pathway that emphasizes mechanistically informed multi-analyte panels, documented differences between exposure and effect biomarkers, future validation in exposed cohorts, and clinically relevant endpoints (reduction in lung function, incidence of malignancy, and response to treatment) to facilitate routine laboratory implementation. To demonstrate the clinical relevance and economic viability of controlling confounders and establishing decision limits, standard reporting of methods, rigorous control of confounders (particularly smoking and co-exposures), and explicit derivation of decision limits based on specific targeted applications (such as screening, surveillance, or monitoring of responses) should be prioritized over current evidence base achievements.

🏷️ 키워드 / MeSH