Epithelial-to-mesenchymal transition (EMT) is an essential mechanism for development and wound healing, but in cancer it also mediates the progression and spread of aggressive tumors while increasing therapeutic resistance. Adoption of a mesenchymal state is also associated with increased iron uptake, but the relationship between EMT and the key regulators of cellular iron metabolism remains undefined. In this regard, the human adrenal cortical carcinoma SW13 cell line represents an invaluable research model as HDAC inhibitor treatment can convert them from an epithelial-like (SW13-) cell type to a mesenchymal-like (SW13+) subtype. In this study we establish SW13 cells as a model for exploring the link between iron and EMT. Increased iron accumulation following HDAC inhibitor mediated EMT is associated with decreased expression of the iron export protein ferroportin, enhanced ROS production, and reduced expression of antioxidant response genes. As availability of redox active iron and loss of lipid peroxide repair capacity are hallmarks of ferroptosis, a form of iron-mediated cell death, we next examined whether HDAC inhibitor treatment could augment ferroptosis sensitivity. Indeed, HDAC inhibitor treatment synergistically increased cell death following induction of ferroptosis. The exact mechanisms by which HDAC inhibition facilitates cell death following ferroptosis induction requires further study. As several HDAC inhibitors are already in use clinically for the treatment of certain cancer types, the findings from these studies have immediate implications for improving iron-targeted chemotherapeutic strategies.
The tumor suppressor gene TP53 is the most commonly mutated gene in human cancer. In addition to loss of tumor suppressor functions, mutations in TP53 promote cancer progression by altering cellular iron acquisition and metabolism. A newly identified role for TP53 in the coordination of iron homeostasis and cancer cell survival lies in the ability for TP53 to protect against ferroptosis, a form of iron-mediated cell death. The purpose of this study was to determine the extent to which TP53 mutation status affects the cellular response to ferroptosis induction. Using H1299 cells, which are null for TP53, we generated cell lines expressing either a tetracycline inducible wild-type (WT) TP53 gene, or a representative mutated TP53 gene from six exemplary “hotspot” mutations in the DNA binding domain (R273H, R248Q, R282W, R175H, G245S, and R249S). TP53 mutants (R273H, R248Q, R175H, G245S, and R249S) exhibited increased sensitivity ferroptosis compared to cells expressing WT TP53. As iron-mediated lipid peroxidation is critical for ferroptosis induction, we hypothesized that iron acquisition pathways would be upregulated in mutant TP53-expressing cells. However, only cells expressing the R248Q, R175H, and G245S TP53 mutation types exhibited statistically significant increases in spontaneous iron regulatory protein (IRP) RNA binding activity following ferroptosis activation. Moreover, changes in the expression of downstream IRP targets were inconsistent with the observed differences in sensitivity to ferroptosis. These findings reveal that canonical iron regulatory pathways are bypassed during ferroptotic cell death. These results also indicate that induction of ferroptosis may be an effective therapeutic approach for tumor cells expressing distinct TP53 mutation types.
The SLC39A8 gene encodes a divalent metal transporter, ZIP8. SLC39A8 is associated with pleiotropic effects across multiple tissues, including the brain. We determine the different brain magnetic resonance imaging (MRI) phenotypes associated with SLC39A8. We used a phenome-wide association study approach followed by joint and conditional association analysis. Using the summary statistics datasets from a brain MRI genome-wide association study on adult United Kingdom (UK) Biobank participants, we systematically selected all brain MRI phenotypes associated with single-nucleotide polymorphisms (SNPs) within 500 kb of the SLC39A8 genetic locus. For all significant brain MRI phenotypes, we used GCTA-COJO to determine the number of independent association signals and identify index SNPs for each brain MRI phenotype. Linkage equilibrium for brain phenotypes with multiple independent signals was confirmed by LDpair. We identified 24 brain MRI phenotypes that vary due to MRI type and brain region and contain a SNP associated with the SLC39A8 locus. Missense ZIP8 polymorphism rs13107325 was associated with 22 brain MRI phenotypes. Rare ZIP8 variants present in a published UK Biobank dataset are associated with 6 brain MRI phenotypes also linked to rs13107325. Among the 24 datasets, an additional 4 association signals were identified by GCTA-COJO and confirmed to be in linkage equilibrium with rs13107325 using LDpair. These additional association signals represent new probable causative SNPs in addition to rs13107325. This study provides leads into how genetic variation in SLC39A8, a trace mineral transport gene, is linked to brain structure differences and may affect brain development and nervous system function.
The tumor suppressor TP53 is the most commonly mutated gene in human cancers, and iron is necessary for cancer cell growth and proliferation, but there is a significant gap in knowledge for how the two cooperate to affect cellular physiology. Elucidating this role is complicated, however, because each TP53 mutation subtype exhibits unique phenotypic responses to changes in iron availability. The goal of this work was to determine how cells expressing distinct TP53 mutation subtypes respond to iron restriction. Utilizing a reverse genetics approach, we generated eight isogenic cell lines that either lacked TP53 expression, expressed wild-type TP53, or expressed one of the six most common TP53 “hotspot” mutations. We then employed isobaric peptide labeling and mass spectrometry to quantitively measure changes in global protein expression, both in response to induction of mutant TP53 expression, and in response to iron chelation. Our findings indicate that mutant TP53-dependent sensitivities to iron restriction are not driven by differences in responsiveness to iron chelation, but more so by mutant TP53-dependent differences in cellular antioxidant and lipid handling protein expression. These findings reinforce the importance of distinguishing between TP53 mutation subtypes when investigating approaches to target mutant TP53. We also identify unique TP53-dependent perturbances in protein expression patterns that could be exploited to improve iron-targeted chemotherapeutic strategies.
Objectives The SLC39A8 gene encodes a divalent metal transporter, ZIP8. ZIP8 polymorphisms are associated with pleiotropic effects including altered risks for schizophrenia. Our objective is to determine the different brain MRI phenotypes associated at or near the SLC39A8 (ZIP8) genetic locus using a phenome-wide association (PheWAS) approach followed by joint and conditional association analysis. Methods Using the summary statistics database containing brain MRI genome-wide association study (GWAS) data, we systematically selected all brain MRI phenotypes which were associated with single-nucleotide polymorphisms (SNPs) within 1 million bp of the SLC39A8 genetic locus, as defined as reaching a P-value significance cutoff of P < 5.0 × 10–8. For all brain MRI phenotypes reaching significance, we used GCTA-COJO to determine the number of independent association signals using settings of P < 1.0 × 10–5 and a window of 10 million base pairs. Using SNPclip and the European 1000 Genomes linkage panel with a linkage disequilibrium cutoff of r2 > 0.8, we identified SNP candidates at each index SNP. Linkage equilibrium for brain phenotypes with multiple independent signals was confirmed by LDpair. Results We identified 25 brain MRI phenotypes that vary due to MRI type and brain region that all contain a SNP associated with the SLC39A8 locus. All of these datasets have at least 1 index SNP directly labeling or in high linkage disequilibrium with rs13107325, which encodes a missense mutation in the SLC39A8 (ZIP8). Among the 25 datasets, an additional 4 association signals were identified by GCTA-COJO and confirmed to be in linkage equilibrium with rs13107325 using LDpair. For these additional association signals, probable causative SNPs were identified from the index SNP using SNPclip. Conclusions From the 25 brain MRI phenotypes, we identified new probable causative SNPs in addition to a previously reported missense SNP (rs13107325) associated with schizophrenia. This study provides leads into how SNPs in genes involved in trace metal transport influence brain structures and affect risks for schizophrenia. Funding Sources This work was funded by grants from the Oklahoma Center for the Advancement of Science and Technology and the Oklahoma Agricultural Experiment Station.
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