mEnrich-seq: methylation-guided enrichment sequencing of bacterial taxa of interest from microbiome.

Metagenomics has enabled the comprehensive study of microbiomes. However, many applications would benefit from a method that sequences specific bacterial taxa of interest, but not most background taxa. We developed mEnrich-seq (in which 'm' stands for methylation and seq for sequencing) for enriching taxa of interest from metagenomic DNA before sequencing. The core idea is to exploit the self versus nonself differentiation by natural bacterial DNA methylation and rationally choose methylation-sensitive restriction enzymes, individually or in combination, to deplete host and background taxa while enriching targeted taxa. This idea is integrated with library preparation procedures and applied in several applications to enrich (up to 117-fold) pathogenic or beneficial bacteria from human urine and fecal samples, including species that are hard to culture or of low abundance. We assessed 4,601 bacterial strains with mapped methylomes so far and showed broad applicability of mEnrich-seq. mEnrich-seq provides microbiome researchers with a versatile and cost-effective approach for selective sequencing of diverse taxa of interest.

The repertoire of copy number alteration signatures in human cancer.

Copy number alterations (CNAs) are a predominant source of genetic alterations in human cancer and play an important role in cancer progression. However comprehensive understanding of the mutational processes and signatures of CNA is still lacking. Here we developed a mechanism-agnostic method to categorize CNA based on various fragment properties, which reflect the consequences of mutagenic processes and can be extracted from different types of data, including whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) array. The 14 signatures of CNA have been extracted from 2778 pan-cancer analysis of whole genomes WGS samples, and further validated with 10 851 the cancer genome atlas SNP array dataset. Novel patterns of CNA have been revealed through this study. The activities of some CNA signatures consistently predict cancer patients' prognosis. This study provides a repertoire for understanding the signatures of CNA in cancer, with potential implications for cancer prognosis, evolution and etiology.

TLimmuno2: predicting MHC class II antigen immunogenicity through transfer learning.

Major histocompatibility complex (MHC) class II molecules play a pivotal role in antigen presentation and CD4+ T cell response. Accurate prediction of the immunogenicity of MHC class II-associated antigens is critical for vaccine design and cancer immunotherapies. However, current computational methods are limited by insufficient training data and algorithmic constraints, and the rules that govern which peptides are truly recognized by existing T cell receptors remain poorly understood. Here, we build a transfer learning-based, long short-term memory model named 'TLimmuno2' to predict whether epitope-MHC class II complex can elicit T cell response. Through leveraging binding affinity data, TLimmuno2 shows superior performance compared with existing models on independent validation datasets. TLimmuno2 can find real immunogenic neoantigen in real-world cancer immunotherapy data. The identification of significant MHC class II neoantigen-mediated immunoediting signal in the cancer genome atlas pan-cancer dataset further suggests the robustness of TLimmuno2 in identifying really immunogenic neoantigens that are undergoing negative selection during cancer evolution. Overall, TLimmuno2 is a powerful tool for the immunogenicity prediction of MHC class II presented epitopes and could promote the development of personalized immunotherapies.

LncRNA LUESCC promotes esophageal squamous cell carcinoma by targeting the miR-6785-5p/NRSN2 axis.

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent gastrointestinal malignancies with high mortality worldwide. Emerging evidence indicates that long noncoding RNAs (lncRNAs) are involved in human cancers, including ESCC. However, the detailed mechanisms of lncRNAs in the regulation of ESCC progression remain incompletely understood. LUESCC was upregulated in ESCC tissues compared with adjacent normal tissues, which was associated with gender, deep invasion, lymph node metastasis, and poor prognosis of ESCC patients. LUESCC was mainly localized in the cytoplasm of ESCC cells. Knockdown of LUESCC inhibited cell proliferation, colony formation, migration, and invasion in vitro and suppressed tumor growth in vivo. Mechanistic investigation indicated that LUESCC functions as a ceRNA by sponging miR-6785-5p to enhance NRSN2 expression, which is critical for the malignant behaviors of ESCC. Furthermore, ASO targeting LUESCC substantially suppressed ESCC both in vitro and in vivo. Collectively, these data demonstrate that LUESCC may exerts its oncogenic role by sponging miR-6785-5p to promote NRSN2 expression in ESCC, providing a potential diagnostic marker and therapeutic target for ESCC patients.

Singlet oxygen induces cell wall thickening and stomatal density reducing by transcriptome reprogramming.

Singlet oxygen (1O2) has a very short half-life of 10-5 s; however, it is a strong oxidant that causes growth arrest and necrotic lesions on plants. Its signaling pathway remains largely unknown. The Arabidopsis flu (fluorescent) mutant accumulates a high level of 1O2 and shows drastic changes in nuclear gene expression. Only two plastid proteins, EX1 (executer 1) and EX2 (executer 2), have been identified in the singlet oxygen signaling. Here, we found that the transcription factor abscisic acid insensitive 4 (ABI4) binds the promoters of genes responsive to 1O2-signals. Inactivation of the ABI4 protein in the flu/abi4 double mutant was sufficient to compromise the changes of almost all 1O2-responsive-genes and rescued the lethal phenotype of flu grown under light/dark cycles, similar to the flu/ex1/ex2 triple mutant. In addition to cell death, we reported for the first time that 1O2 also induces cell wall thickening and stomatal development defect. Contrastingly, no apparent growth arrest was observed for the flu mutant under normal light/dim light cycles, but the cell wall thickening (doubled) and stomatal density reduction (by two-thirds) still occurred. These results offer a new idea for breeding stress tolerant plants.

Impact of Pt(hkl) Electrode Surface Structure on the Electrical Double Layer Capacitance.

The classical theory of the electrical double layer (EDL) does not consider the effects of the electrode surface structure on the EDL properties. Moreover, the best agreement between the traditional EDL theory and experiments has been achieved so far only for a very limited number of ideal systems, such as liquid metal mercury electrodes, for which it is challenging to operate with specific surface structures. In the case of solid electrodes, the predictive power of classical theory is often not acceptable for electrochemical energy applications, e.g., in supercapacitors, due to the effects of surface structure, electrode composition, and complex electrolyte contributions. In this work, we combine ab initio molecular dynamics (AIMD) simulations and electrochemical experiments to elucidate the relationship between the structure of Pt(hkl) surfaces and the double-layer capacitance as a key property of the EDL. Flat, stepped, and kinked Pt single crystal facets in contact with acidic HClO4 media are selected as our model systems. We demonstrate that introducing specific defects, such as steps, can substantially reduce the EDL capacitances close to the potential of zero charge (PZC). Our AIMD simulations reveal that different Pt facets are characterized by different net orientations of the water dipole moment at the interface. That allows us to rationalize the experimentally measured (inverse) volcano-shaped capacitance as a function of the surface step density.

Detection of Helicobacter pylori Infection in Human Gastric Fluid Through Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms.

Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H. pylori diagnosis. In this study, we propose a novel technique for accurately detecting H. pylori infection through machine learning analysis of surface-enhanced Raman scattering (SERS) spectra of gastric fluid samples that were noninvasively collected from human stomachs via the string test. One hundred participants were recruited to collect gastric fluid samples noninvasively. Therefore, 12,000 SERS spectra (n = 120 spectra/participant) were generated for building machine learning models evaluated by standard metrics in model performance assessment. According to the results, the Light Gradient Boosting Machine algorithm exhibited the best prediction capacity and time efficiency (accuracy = 99.54% and time = 2.61 seconds). Moreover, the Light Gradient Boosting Machine model was blindly tested on 2,000 SERS spectra collected from 100 participants with unknown H. pylori infection status, achieving a prediction accuracy of 82.15% compared with qPCR results. This novel technique is simple and rapid in diagnosing H. pylori infection, potentially complementing current H. pylori diagnostic methods.

PCSK9 Inhibitor Added to High-Intensity Statin Therapy to Prevent Cardiovascular Events in Patients with Acute Coronary Syndrome after Percutaneous Coronary Intervention: A Randomized, Double- Blind, Placebo-Controlled, Multicenter SHAWN Study.

BACKGROUND: It is currently uncertain whether the combination of a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor and high-intensity statin treatment can effectively reduce cardiovascular events in patients with acute coronary syndrome (ACS) who have undergone percutaneous coronary intervention (PCI) for culprit lesions. METHODS: This study protocol describes a double-blind, randomized, placebo-controlled, multicenter study aiming to investigate the efficacy and safety of combining a PCSK9 inhibitor with high-intensity statin therapy in patients with ACS following PCI. A total of 1212 patients with ACS and multiple lesions will be enrolled and randomly assigned to receive either PCSK9 inhibitor plus high-intensity statin therapy or high-intensity statin monotherapy. The randomization process will be stratified by sites, diabetes, initial presentation and use of stable (≥4 weeks) statin treatment at presentation. PCSK 9 inhibitor or its placebo is injected within 4 hours after PCI for the culprit lesion. The primary endpoint is the composite of cardiovascular death, myocardial infarction, stroke, re-hospitalization due to ACS or heart failure, or any ischemia-driven coronary revascularization at one-year follow-up between two groups. Safety endpoints mean PCSK 9 inhibitor and statin intolerance. CONCLUSION: The SHAWN study has been specifically designed to evaluate the effectiveness and safety of adding a PCSK9 inhibitor to high-intensity statin therapy in patients who have experienced ACS following PCI. The primary objective of this study is to generate new evidence regarding the potential benefits of combining a PCSK9 inhibitor with high-intensity statin treatment in reducing cardiovascular events among these patients.

Discovering multiple types of DNA methylation from bacteria and microbiome using nanopore sequencing.

Bacterial DNA methylation occurs at diverse sequence contexts and plays important functional roles in cellular defense and gene regulation. Existing methods for detecting DNA modification from nanopore sequencing data do not effectively support de novo study of unknown bacterial methylomes. In this work, we observed that a nanopore sequencing signal displays complex heterogeneity across methylation events of the same type. To enable nanopore sequencing for broadly applicable methylation discovery, we generated a training dataset from an assortment of bacterial species and developed a method, named nanodisco ( https://github.com/fanglab/nanodisco ), that couples the identification and fine mapping of the three forms of methylation into a multi-label classification framework. We applied it to individual bacteria and the mouse gut microbiome for reliable methylation discovery. In addition, we demonstrated the use of DNA methylation for binning metagenomic contigs, associating mobile genetic elements with their host genomes and identifying misassembled metagenomic contigs.

Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization.

Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.

Oridonin attenuates liver ischemia-reperfusion injury by suppressing PKM2/NLRP3-mediated macrophage pyroptosis.

BACKGROUND: The NOD-like receptor protein 3 (NLRP3) mediated pyroptosis of macrophages is closely associated with liver ischemia reperfusion injury (IRI). As a covalent inhibitor of NLRP3, Oridonin (Ori), has strong anti-inflammasome effect, but its effect and mechanisms for liver IRI are still unknown. METHODS: Mice and liver macrophages were treated with Ori, respectively. Co-IP and LC-MS/MS analysis of the interaction between PKM2 and NLRP3 in macrophages. Liver damage was detected using H&E staining. Pyroptosis was detected by WB, TEM, and ELISA. RESULTS: Ori ameliorated liver macrophage pyroptosis and liver IRI. Mechanistically, Ori inhibited the interaction between pyruvate kinase M2 isoform (PKM2) and NLRP3 in hypoxia/reoxygenation（H/R）-induced macrophages, while the inhibition of PKM2/NLRP3 reduced liver macrophage pyroptosis and liver IRI. CONCLUSION: Ori exerted protective effects on liver IRI via suppressing PKM2/NLRP3-mediated liver macrophage pyroptosis, which might become a potential therapeutic target in the clinic.

Intelligent ultrafast total-body PET for sedation-free pediatric [18F]FDG imaging.

PURPOSE: This study aims to develop deep learning techniques on total-body PET to bolster the feasibility of sedation-free pediatric PET imaging. METHODS: A deformable 3D U-Net was developed based on 245 adult subjects with standard total-body PET imaging for the quality enhancement of simulated rapid imaging. The developed method was first tested on 16 children receiving total-body [18F]FDG PET scans with standard 300-s acquisition time with sedation. Sixteen rapid scans (acquisition time about 3 s, 6 s, 15 s, 30 s, and 75 s) were retrospectively simulated by selecting the reconstruction time window. In the end, the developed methodology was prospectively tested on five children without sedation to prove the routine feasibility. RESULTS: The approach significantly improved the subjective image quality and lesion conspicuity in abdominal and pelvic regions of the generated 6-s data. In the first test set, the proposed method enhanced the objective image quality metrics of 6-s data, such as PSNR (from 29.13 to 37.09, p < 0.01) and SSIM (from 0.906 to 0.921, p < 0.01). Furthermore, the errors of mean standardized uptake values (SUVmean) for lesions between 300-s data and 6-s data were reduced from 12.9 to 4.1% (p < 0.01), and the errors of max SUV (SUVmax) were reduced from 17.4 to 6.2% (p < 0.01). In the prospective test, radiologists reached a high degree of consistency on the clinical feasibility of the enhanced PET images. CONCLUSION: The proposed method can effectively enhance the image quality of total-body PET scanning with ultrafast acquisition time, leading to meeting clinical diagnostic requirements of lesion detectability and quantification in abdominal and pelvic regions. It has much potential to solve the dilemma of the use of sedation and long acquisition time that influence the health of pediatric patients.

Sedation-free pediatric [18F]FDG imaging on totalbody PET/CT with the assistance of artificial intelligence.

PURPOSE: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer's biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC). METHODS: This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach. RESULTS: Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns). CONCLUSIONS: This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.

Pre-therapy PET-based voxel-wise dosimetry prediction by characterizing intra-organ heterogeneity in PSMA-directed radiopharmaceutical theranostics.

BACKGROUND AND OBJECTIVE: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET. METHODS: 23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map. RESULTS: Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach. CONCLUSION: Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.

Phase Separation Enhanced PROTAC for Highly Efficient Protein Degradation.

Biomacromolecular condensates formed via phase separation establish compartments for the enrichment of specific compositions, which is also used as a biological tool to enhance molecule condensation, thereby increasing the efficiency of biological processes. Proteolysis-targeting chimeras (PROTACs) have been developed as powerful tools for targeted protein degradation in cells, offering a promising approach for therapies for different diseases. Herein, we introduce an intrinsically disordered region in the PROTAC (denoted PSETAC), which led to the formation of droplets of target proteins in the cells and increased degradation efficiency compared with PROTAC without phase separation. Further, using a nucleus targeting intrinsically disordered domain, the PSETAC was able to target and degrade nuclear-located proteins. Finally, we demonstrated intracellular delivery of PSETAC using lipid nanoparticle-encapsulated mRNA (mRNA-LNP) for the degradation of the endogenous target protein. This study established the PSETAC mRNA-LNP method as a potentially translatable, safe therapeutic strategy for the development of clinical applications based on PROTAC.

Dissociable neural correlates of trait and ability emotional intelligence: a resting-state fMRI study.

Emotional intelligence (EI) is one's ability to monitor one's own and other's emotions and the use of emotional information to enhance thought and action. Previous behavioral studies have shown that EI is separable into trait EI and ability EI, which are known to have distinct characteristics at the behavioral level. A relevant and unanswered question is whether both forms of EI have a dissociable neural basis. Previous studies have individually explored the neural underpinnings of trait EI and ability EI, but there has been no direct comparison of the neural mechanisms underlying these two types of emotional intelligence. The present study addresses this question by using resting-state fMRI to examine the correlational pattern between the regional amplitude of low-frequency fluctuations (ALFF) of the brain and individuals' trait EI and ability EI scores. We found that trait EI scores were positively correlated with the ALFF in the bilateral superior temporal gyrus, and negatively correlated with the ALFF in the ventral medial prefrontal cortex. In contrast, ability EI scores were positively correlated with the ALFF in the insula. Taken together, these results provide preliminary evidence of dissociable neural substrates between trait EI and ability EI.

Rare and common coding variants in lipid metabolism-related genes and their association with coronary artery disease.

BACKGROUND: Coronary artery disease (CAD) is a complex disease that is influenced by environmental and genetic factors. In this study, we aimed to investigate the relationship between coding variants in lipid metabolism-related genes and CAD in a Chinese Han population. METHODS: A total of 252 individuals were recruited for this study, including 120 CAD patients and 132 healthy control individuals. Rare and common coding variants in 12 lipid metabolism-related genes (ANGPTL3, ANGPTL4, APOA1, APOA5, APOC1, APOC3, CETP, LDLR, LIPC, LPL, PCSK9 and SCARB1) were detected via next-generation sequencing (NGS)-based targeted sequencing. Associations between common variants and CAD were evaluated by Fisher's exact test. A gene-based association test of rare variants was performed by the sequence kernel association test-optimal (SKAT-O test). RESULTS: We found 51 rare variants and 17 common variants in this study. One common missense variant, LIPC rs6083, was significantly associated with CAD after Bonferroni correction (OR = 0.47, 95% CI = 0.29-0.76, p = 1.9 × 10- 3). Thirty-three nonsynonymous rare variants were identified, including two novel variants located in the ANGPTL4 (p.Gly47Glu) and SCARB1 (p.Leu233Phe) genes. We did not find a significant association between rare variants and CAD via gene-based analysis via the SKAT-O test. CONCLUSIONS: Targeted sequencing is a powerful tool for identifying rare and common variants in CAD. The common missense variant LIPC rs6083 confers protection against CAD. The clinical relevance of rare variants in CAD aetiology needs to be investigated in larger sample sizes in the future.

Value of the Air Bronchogram Sign and Other Computed Tomography Findings in the Early Diagnosis of Lung Adenocarcinoma.

OBJECTIVES: The present study aims to explore the application value of the air bronchogram (AB) sign and other computed tomography (CT) signs in the early diagnosis of lung adenocarcinoma (LUAD). METHOD: The pathological information and CT images of 130 patients diagnosed with N0 and M0 solitary pulmonary nodules (diameter ≤3 cm) and treated with surgical resection in our hospital between June 2021 and June 2022 were analyzed. RESULTS: The patients were divided into the benign pulmonary nodule (BPN) group (14 cases), the AIS group (30 cases), the MIA group (10 cases), and the IAC group (76 cases). Among the 116 patients with AIS and LUAD, 96 showed an AB sign. Among the 14 patients with BPN, only 4 patients showed an AB sign. The average CT value and maximum diameter were significantly higher in the IAC group than in the AIS and MIA groups. In the BPN group, 5 patients had an average CT value of >80 HU. Among all LUAD-based groups, there was only 1 patient with a CT value of >60 HU. CONCLUSIONS: The identification of the AB sign based on CT imaging facilitates the differentiation between benign and malignant nodules. The CT value and maximum diameter of pulmonary adenocarcinoma nodules increase with the increase of the malignancy degree. The nodule type, CT value, and maximum diameter are useful for predicting the pathological type and prognosis. If the average CT value of pulmonary nodules is >80 HU, LUAD may be excluded.

Locally advanced breast cancer patients should be cautious about the immediate breast reconstruction after mastectomy: a pooling analysis of safety and efficacy.

BACKGROUND: The purpose of this study was to compare safety and efficacy outcomes between immediate breast reconstruction (IBR) and mastectomy alone in locally advanced breast cancer patients. METHODS: We conducted a comprehensive literature search of PUBMED, EMBASE, and Cochrane databases. The primary outcomes evaluated were overall survival, disease-free survival, and local recurrence. The secondary outcome was the incidence of surgical complications. All data were analyzed using Review Manager 5.3. RESULTS: Sixteen studies, involving 15,364 participants were included in this meta-analysis. Pooled data demonstrated that patients underwent IBR were more likely to experience surgical complications than those underwent mastectomy alone (HR: 3.96, 95%CI [1.07,14.67], p = 0.04). No significant difference was found in overall survival (HR: 0.94, 95%CI [0.73,1.20], p = 0.62), disease-free survival (HR: 1.03, 95%CI [0.83,1.27], p = 0.81), or breast cancer specific survival (HR: 0.93, 95%CI [0.71,1.21], p = 0.57) between IBR group and Non-IBR group. CONCLUSIONS: Our study demonstrates that IBR after mastectomy does not affect the overall survival and disease-free survival of locally advanced breast cancer patients. However, IBR brings with it a nonnegligible higher risk of complications and needs to be fully evaluated and carefully decided.

Copy number signature analysis tool and its application in prostate cancer reveals distinct mutational processes and clinical outcomes.

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool "sigminer" has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis.