ArticleJournal of proteomics & bioinformatics2014
Proteomics-Based Identification of Differentially Abundant Proteins from Human Keratinocytes Exposed to Arsenic Trioxide.
Article in Journal of proteomics & bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Deficient arsenic methylation and global proteomic reprogramming in human keratinocytes during arsenic-induced skin carcinogenesis.Archives of toxicology · 2026Article
- Identification and Characterization of Oxidative Stress and Endoplasmic Reticulum Stress-Related Genes in Esophageal Cancer.Journal of Cancer · 2025Article
- Anti-ferroptoticJournal of gastrointestinal oncology · 2023Article
- Temporal Modulation of Differential Alternative Splicing in HaCaT Human Keratinocyte Cell Line Chronically Exposed to Arsenic for up to 28 Wk.Environmental health perspectives · 2022Article
- State of the science review of the health effects of inorganic arsenic: Perspectives for future research.Environmental toxicology · 2019Review
- Label-Free Proteomic Approach to Characterize Protease-Dependent and -Independent Effects of sarA Inactivation on the Staphylococcus aureus Exoproteome.Journal of proteome research · 2018Article
- Transferrin receptor 1 in cancer: a new sight for cancer therapy.American journal of cancer research · 2018Review
- Integration of microRNAome, proteomics and metabolomics to analyze arsenic-induced malignant cell transformation.Oncotarget · 2017Article
- Integrated proteomics and metabolomics analysis of rat testis: Mechanism of arsenic-induced male reproductive toxicity.Scientific reports · 2016Article
- Differential expression of serum proteins in rats subchronically exposed to arsenic identified by iTRAQ-based proteomic technology-14-3-3 ζ protein to serve as a potential biomarker.Toxicology research · 2016Article
- From Normal Skin to Squamous Cell Carcinoma: A Quest for Novel Biomarkers.Disease markers · 2016Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
introductionArsenic is a widely distributed environmental toxicant that can cause multi-tissue pathologies. Proteomic assays allow for the identification of biological processes modulated by arsenic in diverse tissue types.
methodThe altered abundance of proteins from HaCaT human keratinocyte cell line exposed to arsenic was quantified using a label-free LC-MS/MS mass spectrometry workflow. Selected proteomics results were validated using western blot and RT-PCR. A functional annotation analytics strategy that included visual analytical integration of heterogeneous data sets was developed to elucidate functional categories. The annotations integrated were mainly tissue localization, biological process and gene family.
resultThe abundance of 173 proteins was altered in keratinocytes exposed to arsenic; in which 96 proteins had increased abundance while 77 proteins had decreased abundance. These proteins were also classified into 69 Gene Ontology biological process terms. The increased abundance of transferrin receptor protein (TFRC) was validated and also annotated to participate in response to hypoxia. A total of 33 proteins (11 increased abundance and 22 decreased abundance) were associated with 18 metabolic process terms. The Glutamate--cysteine ligase catalytic subunit (GCLC), the only protein annotated with the term sulfur amino acid metabolism process, had increased abundance while succinate dehydrogenase [ubiquinone] iron-sulfur subunit, mitochondrial precursor (SDHB), a tumor suppressor, had decreased abundance.
conclusionA list of 173 differentially abundant proteins in response to arsenic trioxide was grouped using three major functional annotations covering tissue localization, biological process and protein families. A possible explanation for hyperpigmentation pathologies observed in arsenic toxicity is that arsenic exposure leads to increased iron uptake in the normally hypoxic human skin. The proteins mapped to metabolic process terms and differentially abundant are candidates for evaluating metabolic pathways perturbed by arsenicals.
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