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Strong substrate affinity and high catalytic efficiency are persistently pursued to generate high‐performance nanozymes. Herein, with unique surface atomic configurations and distinct d‐orbital coupling features of different metal components, a class of highly efficient MnFeCoNiCu transition metal high‐entropy nanozymes (HEzymes) is prepared for the first time. Density functional theory calculations demonstrate that improved d‐orbital coupling between different metals increases the electron density near the Fermi energy level (EF) and shifts the position of the overall d‐band center with respect to EF, thereby boosting the efficiency of site‐to‐site electron transfer while also enhancing the adsorption of oxygen intermediates during catalysis. As such, the proposed HEzymes exhibit superior substrate affinities and catalytic efficiencies comparable to that of natural horseradish peroxidase (HRP). Finally, HEzymes with superb peroxidase (POD)‐like activity are used in biosensing and antibacterial applications. These results suggest that HEzymes have great potential as new‐generation nanozymes. [ABSTRACT FROM AUTHOR]

Metal aerogel with porous structure and interlocking pore channel can provide abundant active sites to boost the peroxidase (POD)-like activity for high-performance colorimetric analysis of food quality. Herein, CuBi bimetallic aerogels with different atomic ratio (Cu 1 Bi 9 , Cu 5 Bi 5 and Cu 9 Bi 1) were fabricated by a facile one-step reduction strategy, and the POD-like activity of the synthesized CuBi bimetallic aerogels was studied. The specific activity of Cu 9 Bi 1 aerogel was significantly enhanced due to the Bi-doping strategy. Through comparing the K m values we find that CuBi bimetallic aerogel can be used as a cheap alternative to equivalent noble metal materials for biosensor applications. Then, the optimized nanozyme was exploited to establish a colorimetric method for the total antioxidant capacity (TAC) by utilizing ascorbic acid (AA) as a representative antioxidant model. The linear range and limit of detection (LOD) were determined to be 300–900 μM and 59.4 μM, respectively, the wide detection range simplifies sample pre-treatment steps. Additionally, the method also demonstrated good feasibility for the TAC of food samples. The current study expands new fields for the application of metal aerogels and successfully developed macroscopic nanozymes with a convenient application, facile preparation and low cost. • Combining metal aerogel structures with peroxidase activity. • Introduced Bi element to enhance peroxidase activity and improve the structure. • CuBi bimetallic aerogels were fabricated by a facile one-step reduction strategy. • A rapid method for the total antioxidant capacity detection was constructed. • The measurement of actual samples such as fruits and beverages was realized. [ABSTRACT FROM AUTHOR]

Pulmonary lobe segmentation is an important prerequisite for accurately quantifying pulmonary damage in many pulmonary diseases and planning treatment. However, due to the incomplete lobar structures and morphological changes caused by diseases, the lobe segmentation still encounters great challenges. In this study, a Learnable Interpolation and Extrapolation Network (LIE‐Net) is proposed to form complete and consecutive fissure surfaces by learning to extract information of the fissures from existing fissure points and absent points (unsegmented points belonging to fissures) to predict the z coordinate of the absent fissure points. The completed pulmonary fissures are further used for accurate pulmonary lobe segmentation. Specifically, LIE‐Net takes the coordinate information of existing fissure points (their (x, y, z) coordinates) and absent fissure points (their (x, y) coordinates) as two independent inputs, and predicts the z coordinates of absent points. The proposed LIE‐Net makes voxel‐wise predictions based on the spatial structure characteristics of the lung fissure, and is able to provide a consecutive fissure surface in space. According to the evaluation of radiologists, the lobe segmentation performance was remarkably enhanced in approximately 76% of patients in our additional dataset after the application of LIE‐Net, especially for those cases with large‐scale missing fissures. [ABSTRACT FROM AUTHOR]

Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard. Despite tremendous efforts from the scientific community to conduct TF ChIP-seq experiments, the available data represent only a limited percentage of ChIP-seq experiments, considering all possible combinations of TFs and cell lines. In this study, we demonstrate a method for accurately predicting cell-specific TF binding for TF-cell line combinations based on only a small fraction (4%) of the combinations using available ChIP-seq data. The proposed model, termed TFImpute, is based on a deep neural network with a multi-task learning setting to borrow information across transcription factors and cell lines. Compared with existing methods, TFImpute achieves comparable accuracy on TF-cell line combinations with ChIP-seq data; moreover, TFImpute achieves better accuracy on TF-cell line combinations without ChIP-seq data. This approach can predict cell line specific enhancer activities in K562 and HepG2 cell lines, as measured by massively parallel reporter assays, and predicts the impact of SNPs on TF binding. [ABSTRACT FROM AUTHOR]

Motivation: RNA-seq has been widely used in transcriptome analysis to effectively measure gene expression levels. Although sequencing costs are rapidly decreasing, almost 70% of all the human RNA-seq samples in the gene expression omnibus do not have biological replicates and more unreplicated RNA-seq data were published than replicated RNA-seq data in 2011. Despite the large amount of single replicate studies, there is currently no satisfactory method for detecting differentially expressed genes when only a single biological replicate is available.Results: We present the GFOLD (generalized fold change) algorithm to produce biologically meaningful rankings of differentially expressed genes from RNA-seq data. GFOLD assigns reliable statistics for expression changes based on the posterior distribution of log fold change. In this way, GFOLD overcomes the shortcomings of P-value and fold change calculated by existing RNA-seq analysis methods and gives more stable and biological meaningful gene rankings when only a single biological replicate is available.Availability: The open source C/C++ program is available at http://www.tongji.edu.cn/∼zhanglab/GFOLD/index.htmlContact: xsliu@jimmy.harvard.edu or yzhang@tongji.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The new second generation sequencing technology revolutionizes many biology-related research fields and poses various computational biology challenges. One of them is transcriptome assembly based on RNA-Seq data, which aims at reconstructing all full-length mRNA transcripts simultaneously from millions of short reads. In this article, we consider three objectives in transcriptome assembly: the maximization of prediction accuracy, minimization of interpretation, and maximization of completeness. The first objective, the maximization of prediction accuracy, requires that the estimated expression levels based on assembled transcripts should be as close as possible to the observed ones for every expressed region of the genome. The minimization of interpretation follows the parsimony principle to seek as few transcripts in the prediction as possible. The third objective, the maximization of completeness, requires that the maximum number of mapped reads (or 'expressed segments' in gene models) be explained by (i.e., contained in) the predicted transcripts in the solution. Based on the above three objectives, we present IsoLasso, a new RNA-Seq based transcriptome assembly tool. IsoLasso is based on the well-known LASSO algorithm, a multivariate regression method designated to seek a balance between the maximization of prediction accuracy and the minimization of interpretation. By including some additional constraints in the quadratic program involved in LASSO, IsoLasso is able to make the set of assembled transcripts as complete as possible. Experiments on simulated and real RNA-Seq datasets show that IsoLasso achieves, simultaneously, higher sensitivity and precision than the state-of-art transcript assembly tools. [ABSTRACT FROM AUTHOR]

• CuBSA (Cu-bovine serum albumin nanoenzymes) was prepared by binding BSA to Cu2+. • CuBSA has a natural superoxide dismutase-like structure and excellent antioxidant capacity. • CuBSA has good bactericidal properties and is biocompatible. • Antimicrobial and antioxidant capabilities were obtained for composite films containing CuBSA. As monofunctional packaging becomes less able to satisfy the need for environmentally friendly convenience, functionalized packaging is becoming more and more significant in food applications. In this study, a biomimetic artificial nano-enzyme, bovine serum albumin (BSA) chelated with copper ions (CuBSA), was constructed by imitating the structure of natural superoxide dismutase (SOD). This novel CuBSA metallo-nanoenzyme possesses distinct SOD-like enzyme activity, antibacterial capabilities, as well as thermal stability and biocompatibility. With CuBSA as excellent filler, the carrageenan-based nanocomposite films were obtained, showing excellent performance in retarding enzymatic browning and inhibiting microbial attack on fresh-cut apples and figs, even stored at room temperature. More importantly, this new composite film is low-cost and simple to be synthesized for large-scale use. [ABSTRACT FROM AUTHOR]

Designing wound dressing materials with hemocompatibility, suitable mechanical properties, outstanding hemostatic effects and anti-inflammatory activity is of great practical significance for wound management. Herein, a hemostatic hydrogel loaded with Lycium barbarum L. polysaccharide (LBP)-functionalized ultrathin MMT nanosheets (L-MMT NSs) was fabricated for efficient hemostasis and wound healing. Loading the L-MMT NSs into polyvinyl alcohol (PVA), the obtained P-L-MMT hydrogel exhibited a 3D porous structure with good swelling properties, cytocompatibility, hemocompatibility, and anti-inflammatory activity. Importantly, in vivo investigations demonstrated that the P-L-MMT hydrogel exerts outstanding hemostasis activity in the hemorrhaging mouse liver model and reduces tissue damage caused by inflammation to shorten wound healing time. Altogether, the convenient exfoliation and functionalization of bulk MMT using LBPs make this inexpensive and rising nanostructure more attractive in the application of nanomedicine. Moreover, due to the synergy between hemostasis and anti-inflammation, this newly developed multifunctional P-L-MMT hydrogel represents a promising material in biomedical fields. [Display omitted] • LBPs functionalized ultrathin MMT nanosheets were efficiently obtained via liquid exfoliation. • The L-MMT-loaded PVA hydrogel shows 3D porous structure with good swelling property. • P-L-MMT hydrogel exhibited excellent hemostatic and anti-inflammatory activity. • The healing of inflammation-induced tissue damage in wound was facilitated. [ABSTRACT FROM AUTHOR]

The sensitive and on-site detection of highly pathogenic Escherichia coli O157:H7 (E. coli O157:H7) is of great importance to ensure public health. However, conventional methods for E. coli O157:H7 detection may suffer disadvantages such as high expense and time consumption. Herein, we reported a cost-effective colorimetric platform based on loop-mediated isothermal amplification (LAMP) for ultrasensitive and rapid detection of E. coli O157:H7. In this study, a novel quantitative colorimetric LAMP assay was established by in-situ measurement of hydroxy naphthol blue (HNB) color change with a designed portable device, which was applied to the amplification of the specific rfbE gene of E. coli O157:H7. As expected, this method featured a wide linear range (100-104 copies µL−1) with excellent linear regression analysis (R2 > 0.99) and possessed a record-low detection limit of 1 copy µL−1 to lower the risk of missed detection. The proposed strategy could be employed on drinking water samples with favorable recoveries and also demonstrated potential in the analysis of complex samples. This work exhibits the promising application prospect in on-site detection without the need for expensive instrumentation and seeks to provide an original paradigm for the rapid and sensitive detection of waterborne pathogens. • Quantify the LAMP reaction by in-situ measuring the absorbance. • Single-copy level detection of E. coli O157:H7 rfbE gene with a portable device. • On-site detection of E. coli O157:H7 in drinking water within 45 min. • As convenient as the visual detection method while more sensitive and reliable. • Better meet the field testing needs of E. coli O157:H7 in resource-poor areas. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate robustness of dual-energy CT (DECT) radiomics features of virtual unenhanced (VUE) image and virtual monoenergetic image (VMI) among different imaging platforms. Methods: A phantom with sixteen clinical-relevant densities was scanned on ten DECT platforms with comparable scan parameters. Ninety-four radiomic features were extracted via Pyradiomics from VUE images and VMIs at energy level of 70 keV (VMI70keV). Test–retest repeatability was assessed by Bland–Altman analysis. Inter-platform reproducibility of VUE images and VMI70keV was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD) among platforms, and by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) between platform pairs. The correlation between variability of CT number radiomics reproducibility was estimated. Results: 92.02% and 92.87% of features were repeatable between scan–rescans for VUE images and VMI70keV, respectively. Among platforms, 11.30% and 28.39% features of VUE images, and 15.16% and 28.99% features of VMI70keV were with CV < 10% and QCD < 10%. The average percentages of radiomics features with ICC > 0.90 and CCC > 0.90 between platform pairs were 10.00% and 9.86% in VUE images and 11.23% and 11.23% in VMI70keV. The CT number inter-platform reproducibility using CV and QCD showed negative correlations with percentage of the first-order radiomics features with CV < 10% and QCD < 10%, in both VUE images and VMI70keV (r2 0.3870–0.6178, all p < 0.001). Conclusions: The majority of DECT radiomics features were non-reproducible. The differences in CT number were considered as an indicator of inter-platform DECT radiomics variation. Critical relevance statement: The majority of radiomics features extracted from the VUE images and the VMI70keV were non-reproducible among platforms, while synchronizing energy levels of VMI to reduce the CT number value variability may be a potential way to mitigate radiomics instability. Key points: The repeatability of DECT radiomics features was high between scan–rescans. The inter-reproducibility of radiomics features in VUE images and VMI70keV was low. The differences in DECT techniques obviously altered the radiomics features. Synchronizing energy levels of VMI can potentially improve radiomics robustness. [ABSTRACT FROM AUTHOR]

Objectives: To compare image quality between a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT (DECT) and to assess the impact of these algorithms on radiomics robustness. Methods: A phantom with clinical-relevant densities was imaged on seven DECT scanners with the same voxel size using typical abdominal-pelvis examination protocols. On one DECT scanner, raw data were reconstructed using both conventional IR (adaptive statistical iterative reconstruction-V, ASIR-V) and DLIR. Nine sets of corresponding images were generated on other six DECT scanners using scanner-equipped conventional IR. Regions of interest were delineated through rigid registrations. Image quality was compared. Pyradiomics platform was used for radiomics feature extraction. Test-retest repeatability was assessed by Bland-Altman analysis for repeated scans. Inter-reconstruction algorithm reproducibility between conventional IR and DLIR was tested by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Inter-scanner reproducibility was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). Robust features were identified. Results: DLIR significantly improved image quality. Ninety-four radiomics features were extracted and nine features were considered as robust. 93.87% features were repeatable between repeated scans. ASIR-V images showed higher reproducibility to other conventional IR than DLIR (ICC mean, 0.603 vs 0.558, p = 0.001; CCC mean, 0.554 vs 0.510, p = 0.004). 7.45% and 26.83% features were reproducible among scanners evaluated by CV and QCD, respectively. Conclusions: DLIR improves quality of DECT images but may alter radiomics features compared to conventional IR. Nine robust DECT radiomics features were identified. Key Points: • DLIR improves DECT image quality in terms of signal-to-noise ratio and contrast-to-noise ratio compared with ASIR-V and showed the highest noise reduction rate and lowest peak frequency shift. • Most of radiomics features are repeatable between repeated DECT scans, while inter-reconstruction algorithm reproducibility between conventional IR and DLIR, and inter-scanner reproducibility, are low. • Although DLIR may alter radiomics features compared to IR algorithms, nine radiomics features survived repeatability and reproducibility analysis among DECT scanners and reconstruction algorithms, which allows further validation and clinical-relevant analysis. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate inter- and intra- scan mode and scanner repeatability and reproducibility of radiomics features within and between single-energy CT (SECT) and dual-energy CT (DECT). Methods: A standardized phantom with sixteen rods of clinical-relevant densities was scanned on seven DECT-capable scanners and three SECT-only scanners. The acquisition parameters were selected to present typical abdomen-pelvic examinations with the same voxel size. Images of SECT at 120 kVp and corresponding 120 kVp-like virtual monochromatic images (VMIs) in DECT which were generated according to scanners were analyzed. Regions of interest were drawn with rigid registrations to avoid variations due to segmentation. Radiomics features were extracted via Pyradiomics platform. Test-retest repeatability was evaluated by Bland-Altman analysis for repeated scans. Intra-scanner reproducibility for different scan modes was tested by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Inter-scanner reproducibility among different scanners for same scan mode was assessed by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). Results: The test-retest analysis presented that 92.91% and 87.02% of the 94 assessed features were repeatable for SECT 120kVp and DECT 120 kVp-like VMIs, respectively. The intra-scanner analysis for SECT 120kVp vs DECT 120 kVp-like VMIs demonstrated that 10.76% and 10.28% of features were with ICC > 0.90 and CCC > 0.90, respectively. The inter-scanner analysis showed that 17.09% and 27.73% of features for SECT 120kVp were with CV < 10% and QCD < 10%, and 15.16% and 32.78% for DECT 120 kVp-like VMIs, respectively. Conclusions: The majority of radiomics features were non-reproducible within and between SECT and DECT. Key Points: • Although the test-retest analysis showed high repeatability for radiomics features, the overall reproducibility of radiomics features within and between SECT and DECT was low. • Only about one-tenth of radiomics features extracted from SECT images and corresponding DECT images did match each other, even their average photon energy levels were considered alike, indicating that the scan mode potentially altered the radiomics features. • Less than one-fifth of radiomics features were reproducible among multiple SECT and DECT scanners, regardless of their fixed acquisition and reconstruction parameters, suggesting the necessity of scanning protocol adjustment and post-scan harmonization process. [ABSTRACT FROM AUTHOR]

[Display omitted] • "Edge in-situ heterogeneous" BiOI was synthesized. • BB exhibited the structures of both iodine defects and in-situ bismuth deposition. • The visible-light utilization and charge separation efficiency of BiOI were enhanced. • BB displayed excellent bactericidal ability and wound healing performance. The inherent narrow band gap of bismuth oxyiodide (BiOI) consistently leads to the rapid recombination of photogenerated carriers, significantly constraining its practical utility. To combat this shortcoming, we devise a Bi/BiOI 1−x (BB) nanosheet with edge heterostructure. It is modified by the introduction of both iodine defects and in-situ bismuth deposition through high-temperature calcination and solvothermal strategy. Notably, the in-situ deposition of bismuth enhances the visible-light absorption ability of BiOI. And the incorporation of iodine defects initiates a modification in the band position of BiOI, ultimately diminishing the electron-hole recombination rate effectively. More importantly, facilitated by the major work function of bismuth, a Schottky barrier is formed at the BB heterojunction interface, which effectively promotes the separation of photogenerated charges within BB. And the photocurrent intensity of BB is 4 times higher than that of pure BiOI. These ingenious designs result in a significant boost in the generation of reactive oxygen species (ROS) through the accumulation of electrons and holes on the surfaces of both Bi and BiOI 1−x. And BB photocatalyst shows an outstanding broad-spectrum bactericidal performance. The antibacterial rates against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) are 88.01% and 90.01%, respectively, which are increased by 80.6% and 83.8% compared with BiOI. Moreover, in vivo experiments provide compelling evidence for the BB photocatalyst's potential in promoting wound healing. The healing rate after BB treatment has already reached more than 95% on the fifth day. This work offers valuable insights on enhancing the sterilization performance of photocatalysts based on the synergistic effects of defect engineering and non-noble metal deposition. [ABSTRACT FROM AUTHOR]

A tannate-iron network-derived peroxidase-like catalyst loaded with Fe ions on carbon nitride (C 3 N 4) was reported for detection of total antioxidant capacity (TAC) in food in this study. Metal-phenolic networks (MPNs) was employed to form a low coordination compound on C 3 N 4 , and calcined catalyst formed hollow structure with abundant and uniform Fe sites and surface folds. CN-FeC exhibited significant peroxidase-like activity and high substrate affinity. The homogeneous distribution of amorphous Fe elements on the C 3 N 4 substrate provides more active sites, resulting in provided excellent catalytic activity to activate H 2 O 2 to ·OH, 1O 2 and O 2 ·–. The established CN-FeC/TMB/H 2 O 2 colorimetric system can detect AA in the concentration range of 5‐40 μM, with the detection limits of 1.40 μM, respectively. It has good accuracy for the detection of vitamin C tablets, beverages. Taken together, this work shows that metal-phenolic networks can be an effective way to achieve efficient utilization of metal atoms and provides a promising idea for metal-phenolic networks in nanoparticle enzyme performance enhancement. [Display omitted] [ABSTRACT FROM AUTHOR]

Gentiana straminea Maxim. exhibits various biological activities. However, the purification and functions of polysaccharides in Gentiana straminea Maxim. have never been reported. Herein, by proposing a flexible 3D graphene-based decoloration column (3DD column), Gentiana straminea Maxim. polysaccharide (GMP) was high-throughput obtained and its anti-inflammatory activity was investigated. Benefiting from the large macroporous network of 3D NH 2 -graphene oxide hydrogel with selective adsorption towards pigments, the 3DD column exhibits high decoloration ratio (96.41%). In addition, the 3DD column provides superior practical functionality as compared to the traditional approaches, which are time-consuming and need toxic solvents, and exhibiting widespread-application for the purification of polysaccharide from other common plant species. More importantly, the decolored GMP as a natural product has promising anti-inflammatory activity on RAW264.7 cells without negative impact on cell viability. Overall, this work reveals a new functional polysaccharides and provides a flexible approach for polysaccharide decoloration, exhibiting a promising prospect for natural polysaccharides in practical application of pharmaceutical. [Display omitted] • A high-throughput 3D graphene-based decoloration column is proposed. • 3DD column is nondestructive as regards the GMP. • Compared with traditional methods, 3DD column has superior practical functionality. • GMP exhibits excellent anti-inflammatory activity. [ABSTRACT FROM AUTHOR]

Motivation: With the rapid development of high-throughput sequencing technologies, the genome-wide profiling of nucleosome positioning has become increasingly affordable. Many future studies will investigate the dynamic behaviour of nucleosome positioning in cells that have different states or that are exposed to different conditions. However, a robust method to effectively identify the regions of differential nucleosome positioning (RDNPs) has not been previously available.Results: We describe a novel computational approach, DiNuP, that compares nucleosome profiles generated by high-throughput sequencing under various conditions. DiNuP provides a statistical P-value for each identified RDNP based on the difference of read distributions. DiNuP also empirically estimates the false discovery rate as a cutoff when two samples have different sequencing depths and differentiate reliable RDNPs from the background noise. Evaluation of DiNuP showed it to be both sensitive and specific for the detection of changes in nucleosome location, occupancy and fuzziness. RDNPs that were identified using publicly available datasets revealed that nucleosome positioning dynamics are closely related to the epigenetic regulation of transcription.Availability and implementation: DiNuP is implemented in Python and is freely available at http://www.tongji.edu.cn/∼zhanglab/DiNuP.Contact: yzhang@tongji.edu.cnSupplementary Information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Motivation Advances in high-throughput genotyping and sequencing technologies during recent years have revealed essential roles of non-coding regions in gene regulation. Genome-wide association studies (GWAS) suggested that a large proportion of risk variants are located in non-coding regions and remain unexplained by current expression quantitative trait loci catalogs. Interpreting the causal effects of these genetic modifications is crucial but difficult owing to our limited knowledge of how regulatory elements function. Although several computational methods have been designed to prioritize regulatory variants that substantially impact human phenotypes, few of them achieve consistently high performance even when large-scale multi-omic data are integrated. Results We propose a novel multi-task framework based on Bayesian deep neural networks, MtBNN, to quantify the deleterious impact of single nucleotide polymorphisms in non-coding genomic regions. With the high-efficiency provided by the multi-task Bayesian framework to integrate information from different sources, MtBNN is capable of extracting features from genomic sequences of large-scale chromatin-profiling data, such as chromatin accessibility and transcript factor binding affinities, and calculating the distribution of the probability that a non-coding variant disrupts regulatory activities. A series of comprehensive experiments show that MtBNN quantifies the functional impact of cis-regulatory variations with high accuracy, including expression quantitative trait locus, DNase I sensitivity quantitative trait locus and functional genetic variants located within ATAC-peaks that affect the accessibility of the corresponding peak and achieves significantly better performance than the existing methods. Moreover, MtBNN has applications in the discovery of potentially causal disease-associated single-nucleotide polymorphisms (SNPs), thus helping fine-map the GWAS SNPs. Availability and implementation Code can be downloaded from https://github.com/Zoesgithub/MtBNN. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Summary: Recurrent mutations in histone-modifying enzymes imply key roles in tumorigenesis, yet their functional relevance is largely unknown. Here, we show that JARID1B, encoding a histone H3 lysine 4 (H3K4) demethylase, is frequently amplified and overexpressed in luminal breast tumors and a somatic mutation in a basal-like breast cancer results in the gain of unique chromatin binding and luminal expression and splicing patterns. Downregulation of JARID1B in luminal cells induces basal genes expression and growth arrest, which is rescued by TGFβ pathway inhibitors. Integrated JARID1B chromatin binding, H3K4 methylation, and expression profiles suggest a key function for JARID1B in luminal cell-specific expression programs. High luminal JARID1B activity is associated with poor outcome in patients with hormone receptor-positive breast tumors. [ABSTRACT FROM AUTHOR]