Recognition of histone covalent modifications by “reader” modules constitutes a major mechanism for epigenetic regulation. A recent upsurge of newly discovered histone lysine acylations, such as crotonylation (Kcr), butyrylation (Kbu), and propionylation (Kpr), greatly expands the coding potential of histone lysine modifications. Here we demonstrate that the histone acetylation-binding double PHD finger (DPF) domains of human MOZ (a.k.a. KAT6A) and DPF2 (a.k.a. BAF45d) accommodate a wide range of histone lysine acylations with the strongest preference for Kcr. Crystal structures of the DPF domain of MOZ in complex with H3K14cr, H3K14bu, and H3K14pr peptides reveal that these non-acetyl acylations are anchored in a hydrophobic “dead-end” pocket with selectivity for crotonylation arising from intimate encapsulation and amide-sensing hydrogen bonding network. Immunofluorescence and ChIP-qPCR show that MOZ and H3K14cr colocalize in a DPF-dependent manner. Our studies call attention to a new regulatory mechanism centered on histone crotonylation readout by DPF family members.

High-frequency point mutations of genes encoding histones have been identified recently as novel drivers in a number of tumors. Specifically, the H3K36M/I mutations were shown to be oncogenic in chondroblastomas and undifferentiated sarcomas by inhibiting H3K36 methyltransferases, including SETD2. Here we report the crystal structures of the SETD2 catalytic domain bound to H3K36M or H3K36I peptides with SAH (S-adenosylhomocysteine). In the complex structure, the catalytic domain adopts an open conformation, with the K36M/I peptide snuggly positioned in a newly formed substrate channel. Our structural and biochemical data reveal the molecular basis underying oncohistone recognition by and inhibition of SETD2.Supplemental material is available for this article.Received May 16, 2016; revised version accepted June 20, 2016. Histone post-translational modifications (PTMs) are linked to tumorigenesis, mostly via dysfunction of their regulators (e.g., readers, writers, and erasers) that are frequently mutated in tumors (Dawson and Kouzarides 2012). Recently, high-frequency mutations in genes encoding histones themselves, rather than the histone regulators, were identified in a number of cancer types. Exome sequencing studies have identified recurrent hot spot missense mutations in histone H3. Notably, these mutations are located at or adjacent to H3 lysine residues that undergo acetylation and/or methylation. For example, the H3K27M mutation was identified in the majority of pediatric diffuse intrinsic pontine gliomas (Schwartzentruber et al. 2012;Wu et al. 2012), and the H3K36M mutation was found to occur predominantly in chondroblastomas (Behjati et al. 2013) and rarely in other cancer types such as head and neck squamous cell carcinoma and colorectal cancer (Shah et al. 2014). In addition, the H3K36-neighboring G34 mutations, such as G34R/V and G34W/L, have been detected in pediatric non-brain stem gliomas (Schwartzentruber et al. 2012;Wu et al. 2012) and giant cell tumors of the bone (Behjati et al. 2013), respectively.Biochemical and cellular studies showed that H3K27M reduced global H3K27 methylation in vitro and in vivo by inhibiting the methyltransferase activity of polycombrepressive complex 2 (PRC2) (Chan et al. 2013;Lewis et al. 2013;Justin et al. 2016). Recently, we and others identified a similar "poisoning" mechanism underlying H3K36M-driven tumorigenesis involving the inactivation of H3K36 methyltransferases (Fang et al. 2016;Lu et al. 2016). H3K36 can be methylated by enzymes such as NSD1/2/3, ASH1L, and SETD2 (Wagner and Carpenter 2012). Among them, SETD2 serves as the major H3K36 methyltransferase that is able to generate the trimethylated H3K36 from the unmethylated, monomethylated, or dimethylated states in vitro and in cells (Edmunds et al. 2008;Hu et al. 2010). SETD2 plays important roles in cellular processes such as transcription elongation (Yoh et al. 2008), RNA splicing (de Almeida et al. 2011;Kim et al. 2011), and DNA damage repair (Li et al. 2013;Pai et al. 2014). However, due to the lack...

Somatic mutations on glycine 34 of histone H3 (H3G34) cause pediatric cancers, but the underlying oncogenic mechanism remains unknown. We demonstrate that substituting H3G34 with arginine, valine, or aspartate (H3G34R/V/D), which converts the non-side chain glycine to a large side chain-containing residue, blocks H3 lysine 36 (H3K36) dimethylation and trimethylation by histone methyltransferases, including SETD2, an H3K36-specific trimethyltransferase. Our structural analysis reveals that the H3 "G33-G34" motif is recognized by a narrow substrate channel, and that H3G34/R/V/D mutations impair the catalytic activity of SETD2 due to steric clashes that impede optimal SETD2-H3K36 interaction. H3G34R/V/D mutations also block H3K36me3 from interacting with mismatch repair (MMR) protein MutSα, preventing the recruitment of the MMR machinery to chromatin. Cells harboring H3G34R/V/D mutations display a mutator phenotype similar to that observed in MMR-defective cells. Therefore, H3G34R/V/D mutations promote genome instability and tumorigenesis by inhibiting MMR activity.

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Objective-Health utility decrements associated with diabetes complications are essential for calculating quality-adjusted life years (QALYs) in patients for use in economic evaluation of diabetes interventions. Previous studies mostly focused on assessing the impact of complications on health utility at event year based on cross-sectional data. This study aimed to separately estimate health utility decrements associated with current and previous diabetes complications.Research Design and Methods-The Health Utilities Index Mark 3 (HUI-3) was used to measure heath utility in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N=8,713). Five macrovascular complications (myocardial infarction (MI), congestive heart failure (CHF), stroke, angina, and revascularization surgery (RS)) and three microvascular complications (nephropathy (renal failure), retinopathy (severe vision loss), and neuropathy (severe pressure sensation loss)) were included in a set of alternative modelling approaches including ordinary least squares (OLS) model, fixed effects model and random effects model to estimate the complicationrelated health utility decrements.

For cancer diagnosis, many DNA methylation markers have been identified. However, few studies have tried to identify DNA methylation markers to diagnose diverse cancer types simultaneously, i.e., pan-cancers. In this study, we tried to identify DNA methylation markers to differentiate cancer samples from the respective normal samples in pan-cancers. We collected whole genome methylation data of 27 cancer types containing 10,140 cancer samples and 3386 normal samples, and divided all samples into five data sets, including one training data set, one validation data set and three test data sets. We applied machine learning to identify DNA methylation markers, and specifically, we constructed diagnostic prediction models by deep learning. We identified two categories of markers: 12 CpG markers and 13 promoter markers. Three of 12 CpG markers and four of 13 promoter markers locate at cancer-related genes. With the CpG markers, our model achieved an average sensitivity and specificity on test data sets as 92.8% and 90.1%, respectively. For promoter markers, the average sensitivity and specificity on test data sets were 89.8% and 81.1%, respectively. Furthermore, in cell-free DNA methylation data of 163 prostate cancer samples, the CpG markers achieved the sensitivity as 100%, and the promoter markers achieved 92%. For both marker types, the specificity of normal whole blood was 100%. To conclude, we identified methylation markers to diagnose pan-cancers, which might be applied to liquid biopsy of cancers.

Dynamic trafficking of G protein-coupled receptors (GPCRs) out of cilia is mediated by the BBSome. In concert with its membrane recruitment factor, the small GTPase ARL6/BBS3, the BBSome ferries GPCRs across the transition zone, a diffusion barrier at the base of cilia. Here, we present the near-atomic structures of the BBSome by itself and in complex with ARL6GTP, and we describe the changes in BBSome conformation induced by ARL6GTP binding. Modeling the interactions of the BBSome with membranes and the GPCR Smoothened (SMO) reveals that SMO, and likely also other GPCR cargoes, must release their amphipathic helix 8 from the membrane to be recognized by the BBSome.

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