Significance: Iron and oxygen are intimately linked: iron is an essential nutrient utilized as a cofactor in enzymes for oxygen transport, oxidative phosphorylation, and metabolite oxidation. However, excess labile iron facilitates the formation of oxygen-derived free radicals capable of damaging biomolecules. Therefore, biological utilization of iron is a tightly regulated process. The nuclear factor (erythroid-derived 2)-like 2 (NRF2) transcription factor, which can respond to oxidative and electrophilic stress, regulates several genes involved in iron metabolism.Recent Advances: The bulk of NRF2 transcription factor research has focused on its roles in detoxification and cancer prevention. Recent works have identified that several genes involved in heme synthesis, hemoglobin catabolism, iron storage, and iron export are under the control of NRF2. Constitutive NRF2 activation and subsequent deregulation of iron metabolism have been implicated in cancer development: NRF2-mediated upregulation of the iron storage protein ferritin or heme oxygenase 1 can lead to enhanced proliferation and therapy resistance. Of note, NRF2 activation and alterations to iron signaling in cancers may hinder efforts to induce the iron-dependent cell death process known as ferroptosis.Critical Issues: Despite growing recognition of NRF2 as a modulator of iron signaling, exactly how iron metabolism is altered due to NRF2 activation in normal physiology and in pathologic conditions remains imprecise; moreover, the roles of NRF2-mediated iron signaling changes in disease progression are only beginning to be uncovered.Future Directions: Further studies are necessary to connect NRF2 activation with physiological and pathological changes to iron signaling and oxidative stress.

Urea destabilizes helical and folded conformations of nucleic acids and proteins, as well as protein-nucleic acid complexes. To understand these effects, extend previous characterizations of interactions of urea with protein functional groups, and thereby develop urea as a probe of conformational changes in protein and nucleic acid processes, we obtain chemical potential derivatives (μ23 = dμ2/dm3) quantifying interactions of urea (component 3) with nucleic acid bases, base analogs, nucleosides and nucleotide monophosphates (component 2) using osmometry and hexanol-water distribution assays. Dissection of these μ23 yields interaction potentials quantifying interactions of urea with unit surface areas of nucleic acid functional groups (heterocyclic aromatic ring, ring methyl, carbonyl and phosphate O, amino N, sugar (C,O)); urea interacts favorably with all these groups, relative to interactions with water. Interactions of urea with heterocyclic aromatic rings and attached methyl groups (as on thymine) are particularly favorable, as previously observed for urea-homocyclic aromatic ring interactions. Urea m-values determined for double helix formation by DNA dodecamers near 25°C are in the range 0.72 to 0.85 kcal mol−1 m−1 and exhibit little systematic dependence on nucleobase composition (17–42% GC). Interpretation of these results using the urea interaction potentials indicates that extensive (60–90%) stacking of nucleobases in the separated strands in the transition region is required to explain the m-value. Results for RNA and DNA dodecamers obtained at higher temperatures, and literature data, are consistent with this conclusion. This demonstrates the utility of urea as a quantitative probe of changes in surface area (ΔASA) in nucleic acid processes.

Identification and characterization of somatic mutations in cancer have important prognostication and treatment implications. Genes encoding the Nuclear factor (erythroid-derived 2)-like 2 (NRF2) transcription factor and its negative regulator, Kelch-like ECH-associated protein 1 (KEAP1), are frequently mutated in cancer. These mutations drive constitutive NRF2 activation and correlate with poor prognosis. Despite its apparent significance, a comprehensive catalogue of somatic NRF2 mutations across different tumor types is still lacking. Here, we catalogue NRF2 mutations in The Cancer Genome Atlas (TCGA) database. 226 unique NRF2-mutant tumors were identified from 10,364 cases. NRF2 mutations were found in 21 out of the 33 tumor types. A total of 11 hotspots were identified. Of these, mutation to the R34 position was most frequent. Notably, R34 and D29 mutations were overrepresented in bladder, lung, and uterine cancers. Analyses of corresponding RNA sequencing data using a de novo derived gene expression classifier showed that the R34 mutations drive constitutive NRF2 activation with a selection pressure biased against the formation of R34L. Of all R34 mutants, R34L conferred the least degree of protein stabilization, suggesting a pro-tumor NRF2 half-life threshold. Our findings offer a comprehensive catalogue of NRF2 mutations in cancer that can help prognostication and NRF2 research.

Edited by Xiao-Fan WangThe nuclear factor (erythroid 2)-like (NRF) transcription factors are a subset of cap'n'collar transcriptional regulators. They consist of three members, NRF1, NRF2, and NRF3, that regulate the expression of genes containing antioxidant-response elements (AREs) in their promoter regions. Although all NRF members regulate ARE-containing genes, each is associated with distinct roles. A comprehensive study of differential and overlapping DNA-binding and transcriptional activities of the NRFs has not yet been conducted. Here, we performed chromatin immunoprecipitation (ChIP)-exo sequencing, an approach that combines ChIP with exonuclease treatment to pinpoint regulatory elements in DNA with high precision, in conjunction with RNA-sequencing to define the transcriptional targets of each NRF member. Our approach, done in three U2OS cell lines, identified 31 genes that were regulated by all three NRF members, 27 that were regulated similarly by all three, and four genes that were differentially regulated by at least one NRF member. We also found genes that were up-or down-regulated by only one NRF member, with 84, 84, and 22 genes that were regulated by NRF1, NRF2, and NRF3, respectively. Analysis of the ARE motifs identified in ChIP peaks revealed that NRF2 prefers binding to AREs flanked by GC-rich regions and that NRF1 prefers AT-rich flanking regions. Thus, sequence preference, likely in combination with upstream signaling events, determines NRF member activation under specific cellular contexts. Our analysis provides a comprehensive description of differential and overlapping gene regulation by the transcriptional regulators NRF1, NRF2, and NRF3.