GSK-3 Inhibitor Elraglusib Enhances Tumor-Infiltrating Immune Cell Activation in Tumor Biopsies and Synergizes with Anti-PD-L1 in a Murine Model of Colorectal Cancer.

Glycogen synthase kinase-3 (GSK-3) is a serine/threonine kinase that has been implicated in numerous oncogenic processes. GSK-3 inhibitor elraglusib (9-ING-41) has shown promising preclinical and clinical antitumor activity across multiple tumor types. Despite promising early-phase clinical trial results, there have been limited efforts to characterize the potential immunomodulatory properties of elraglusib. We report that elraglusib promotes immune cell-mediated tumor cell killing of microsatellite stable colorectal cancer (CRC) cells. Mechanistically, elraglusib sensitized CRC cells to immune-mediated cytotoxicity and enhanced immune cell effector function. Using western blots, we found that elraglusib decreased CRC cell expression of NF-κB p65 and several survival proteins. Using microarrays, we discovered that elraglusib upregulated the expression of proapoptotic and antiproliferative genes and downregulated the expression of cell proliferation, cell cycle progression, metastasis, TGFß signaling, and anti-apoptotic genes in CRC cells. Elraglusib reduced CRC cell production of immunosuppressive molecules such as VEGF, GDF-15, and sPD-L1. Elraglusib increased immune cell IFN-γ secretion, which upregulated CRC cell gasdermin B expression to potentially enhance pyroptosis. Elraglusib enhanced immune effector function resulting in augmented granzyme B, IFN-γ, TNF-α, and TRAIL production. Using a syngeneic, immunocompetent murine model of microsatellite stable CRC, we evaluated elraglusib as a single agent or combined with immune checkpoint blockade (anti-PD-1/L1) and observed improved survival in the elraglusib and anti-PD-L1 group. Murine responders had increased tumor-infiltrating T cells, augmented granzyme B expression, and fewer regulatory T cells. Murine responders had reduced immunosuppressive (VEGF, VEGFR2) and elevated immunostimulatory (GM-CSF, IL-12p70) cytokine plasma concentrations. To determine the clinical significance, we then utilized elraglusib-treated patient plasma samples and found that reduced VEGF and BAFF and elevated IL-1 beta, CCL22, and CCL4 concentrations correlated with improved survival. Using paired tumor biopsies, we found that tumor-infiltrating immune cells had a reduced expression of inhibitory immune checkpoints (VISTA, PD-1, PD-L2) and an elevated expression of T-cell activation markers (CTLA-4, OX40L) after elraglusib treatment. These results address a significant gap in knowledge concerning the immunomodulatory mechanisms of GSK-3 inhibitor elraglusib, provide a rationale for the clinical evaluation of elraglusib in combination with immune checkpoint blockade, and are expected to have an impact on additional tumor types, besides CRC.

Detecting m6A methylation regions from Methylated RNA Immunoprecipitation Sequencing.

MOTIVATION: The post-transcriptional epigenetic modification on mRNA is an emerging field to study the gene regulatory mechanism and their association with diseases. Recently developed high-throughput sequencing technology named Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) enables one to profile mRNA epigenetic modification transcriptome wide. A few computational methods are available to identify transcriptome-wide mRNA modification, but they are either limited by over-simplified model ignoring the biological variance across replicates or suffer from low accuracy and efficiency. RESULTS: In this work, we develop a novel statistical method, based on an empirical Bayesian hierarchical model, to identify mRNA epigenetic modification regions from MeRIP-seq data. Our method accounts for various sources of variations in the data through rigorous modeling and applies shrinkage estimation by borrowing information from transcriptome-wide data to stabilize the parameter estimation. Simulation and real data analyses demonstrate that our method is more accurate, robust and efficient than the existing peak calling methods. AVAILABILITY AND IMPLEMENTATION: Our method TRES is implemented as an R package and is freely available on Github at https://github.com/ZhenxingGuo0015/TRES. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Simulation, power evaluation and sample size recommendation for single-cell RNA-seq.

MOTIVATION: Determining the sample size for adequate power to detect statistical significance is a crucial step at the design stage for high-throughput experiments. Even though a number of methods and tools are available for sample size calculation for microarray and RNA-seq in the context of differential expression (DE), this topic in the field of single-cell RNA sequencing is understudied. Moreover, the unique data characteristics present in scRNA-seq such as sparsity and heterogeneity increase the challenge. RESULTS: We propose POWSC, a simulation-based method, to provide power evaluation and sample size recommendation for single-cell RNA-sequencing DE analysis. POWSC consists of a data simulator that creates realistic expression data, and a power assessor that provides a comprehensive evaluation and visualization of the power and sample size relationship. The data simulator in POWSC outperforms two other state-of-art simulators in capturing key characteristics of real datasets. The power assessor in POWSC provides a variety of power evaluations including stratified and marginal power analyses for DEs characterized by two forms (phase transition or magnitude tuning), under different comparison scenarios. In addition, POWSC offers information for optimizing the tradeoffs between sample size and sequencing depth with the same total reads. AVAILABILITY AND IMPLEMENTATION: POWSC is an open-source R package available online at https://github.com/suke18/POWSC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dissecting differential signals in high-throughput data from complex tissues.

MOTIVATION: Samples from clinical practices are often mixtures of different cell types. The high-throughput data obtained from these samples are thus mixed signals. The cell mixture brings complications to data analysis, and will lead to biased results if not properly accounted for. RESULTS: We develop a method to model the high-throughput data from mixed, heterogeneous samples, and to detect differential signals. Our method allows flexible statistical inference for detecting a variety of cell-type specific changes. Extensive simulation studies and analyses of two real datasets demonstrate the favorable performance of our proposed method compared with existing ones serving similar purpose. AVAILABILITY AND IMPLEMENTATION: The proposed method is implemented as an R package and is freely available on GitHub (https://github.com/ziyili20/TOAST). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: genomics with bigger data and wider applications.

The sixth International Conference on Intelligent Biology and Medicine (ICIBM) took place in Los Angeles, California, USA on June 10-12, 2018. This conference featured eleven regular scientific sessions, four tutorials, one poster session, four keynote talks, and four eminent scholar talks. The scientific program covered a wide range of topics from bench to bedside, including 3D Genome Organization, reconstruction of large scale evolution of genomes and gene functions, artificial intelligence in biological and biomedical fields, and precision medicine. Both method development and application in genomic research continued to be a main component in the conference, including studies on genetic variants, regulation of transcription, genetic-epigenetic interaction at both single cell and tissue level and artificial intelligence. Here, we write a summary of the conference and also briefly introduce the four high quality papers selected to be published in BMC Genomics that cover novel methodology development or innovative data analysis.

Two-phase differential expression analysis for single cell RNA-seq.

Motivation: Single-cell RNA-sequencing (scRNA-seq) has brought the study of the transcriptome to higher resolution and makes it possible for scientists to provide answers with more clarity to the question of 'differential expression'. However, most computational methods still stick with the old mentality of viewing differential expression as a simple 'up or down' phenomenon. We advocate that we should fully embrace the features of single cell data, which allows us to observe binary (from Off to On) as well as continuous (the amount of expression) regulations. Results: We develop a method, termed SC2P, that first identifies the phase of expression a gene is in, by taking into account of both cell- and gene-specific contexts, in a model-based and data-driven fashion. We then identify two forms of transcription regulation: phase transition, and magnitude tuning. We demonstrate that compared with existing methods, SC2P provides substantial improvement in sensitivity without sacrificing the control of false discovery, as well as better robustness. Furthermore, the analysis provides better interpretation of the nature of regulation types in different genes. Availability and implementation: SC2P is implemented as an open source R package publicly available at https://github.com/haowulab/SC2P. Supplementary information: Supplementary data are available at Bioinformatics online.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: bioinformatics towards translational applications.

The 2018 International Conference on Intelligent Biology and Medicine (ICIBM 2018) was held on June 10-12, 2018, in Los Angeles, California, USA. The conference consisted of a total of eleven scientific sessions, four tutorials, one poster session, four keynote talks and four eminent scholar talks, which covered a wild range of aspects of bioinformatics, medical informatics, systems biology and intelligent computing. Here, we summarize nine research articles selected for publishing in BMC Bioinformatics.

Mitonuclear Interactions Mediate Transcriptional Responses to Hypoxia in Drosophila.

Among the major challenges in quantitative genetics and personalized medicine is to understand how gene × gene interactions (G × G: epistasis) and gene × environment interactions (G × E) underlie phenotypic variation. Here, we use the intimate relationship between mitochondria and oxygen availability to dissect the roles of nuclear DNA (nDNA) variation, mitochondrial DNA (mtDNA) variation, hypoxia, and their interactions on gene expression in Drosophila melanogaster. Mitochondria provide an important evolutionary and medical context for understanding G × G and G × E given their central role in integrating cellular signals. We hypothesized that hypoxia would alter mitonuclear communication and gene expression patterns. We show that first order nDNA, mtDNA, and hypoxia effects vary between the sexes, along with mitonuclear epistasis and G × G × E effects. Females were generally more sensitive to genetic and environmental perturbation. While dozens to hundreds of genes are altered by hypoxia in individual genotypes, we found very little overlap among mitonuclear genotypes for genes that were significantly differentially expressed as a consequence of hypoxia; excluding the gene hairy. Oxidative phosphorylation genes were among the most influenced by hypoxia and mtDNA, and exposure to hypoxia increased the signature of mtDNA effects, suggesting retrograde signaling between mtDNA and nDNA. We identified nDNA-encoded genes in the electron transport chain (succinate dehydrogenase) that exhibit female-specific mtDNA effects. Our findings have important implications for personalized medicine, the sex-specific nature of mitonuclear communication, and gene × gene coevolution under variable or changing environments.

PROPER: comprehensive power evaluation for differential expression using RNA-seq.

MOTIVATION: RNA-seq has become a routine technique in differential expression (DE) identification. Scientists face a number of experimental design decisions, including the sample size. The power for detecting differential expression is affected by several factors, including the fraction of DE genes, distribution of the magnitude of DE, distribution of gene expression level, sequencing coverage and the choice of type I error control. The complexity and flexibility of RNA-seq experiments, the high-throughput nature of transcriptome-wide expression measurements and the unique characteristics of RNA-seq data make the power assessment particularly challenging. RESULTS: We propose prospective power assessment instead of a direct sample size calculation by making assumptions on all of these factors. Our power assessment tool includes two components: (i) a semi-parametric simulation that generates data based on actual RNA-seq experiments with flexible choices on baseline expressions, biological variations and patterns of DE; and (ii) a power assessment component that provides a comprehensive view of power. We introduce the concepts of stratified power and false discovery cost, and demonstrate the usefulness of our method in experimental design (such as sample size and sequencing depth), as well as analysis plan (gene filtering). AVAILABILITY: The proposed method is implemented in a freely available R software package PROPER. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data.

Recent developments in RNA-sequencing (RNA-seq) technology have led to a rapid increase in gene expression data in the form of counts. RNA-seq can be used for a variety of applications, however, identifying differential expression (DE) remains a key task in functional genomics. There have been a number of statistical methods for DE detection for RNA-seq data. One common feature of several leading methods is the use of the negative binomial (Gamma-Poisson mixture) model. That is, the unobserved gene expression is modeled by a gamma random variable and, given the expression, the sequencing read counts are modeled as Poisson. The distinct feature in various methods is how the variance, or dispersion, in the Gamma distribution is modeled and estimated. We evaluate several large public RNA-seq datasets and find that the estimated dispersion in existing methods does not adequately capture the heterogeneity of biological variance among samples. We present a new empirical Bayes shrinkage estimate of the dispersion parameters and demonstrate improved DE detection.

Target-Oriented Reference Construction for supervised cell-type identification in scRNA-seq.

Cell-type identification is the most crucial step in single cell RNA-seq (scRNA-seq) data analysis, for which the supervised cell-type identification method is a desired solution due to the accuracy and efficiency. The performance of such methods is highly dependent on the quality of the reference data. Even though there are many supervised cell-type identification tools, there is no method for selecting and constructing reference data. Here we develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing reference given target dataset in scRNA-seq supervised cell-type identification. TORC alleviates the differences in data distribution and cell-type composition between reference and target. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell-type identification from TORC. TORC is freely available at https://github.com/weix21/TORC.

Removing technical variability in RNA-seq data using conditional quantile normalization.

The ability to measure gene expression on a genome-wide scale is one of the most promising accomplishments in molecular biology. Microarrays, the technology that first permitted this, were riddled with problems due to unwanted sources of variability. Many of these problems are now mitigated, after a decade's worth of statistical methodology development. The recently developed RNA sequencing (RNA-seq) technology has generated much excitement in part due to claims of reduced variability in comparison to microarrays. However, we show that RNA-seq data demonstrate unwanted and obscuring variability similar to what was first observed in microarrays. In particular, we find guanine-cytosine content (GC-content) has a strong sample-specific effect on gene expression measurements that, if left uncorrected, leads to false positives in downstream results. We also report on commonly observed data distortions that demonstrate the need for data normalization. Here, we describe a statistical methodology that improves precision by 42% without loss of accuracy. Our resulting conditional quantile normalization algorithm combines robust generalized regression to remove systematic bias introduced by deterministic features such as GC-content and quantile normalization to correct for global distortions.

[Efficiency of O'Leary-Sant symptom index and problem index in the diagnosis of interstitial cystitis].

OBJECTIVE: To evaluate the efficiency of O'Leary-Sant problem index and symptom index (OPSI) in the diagnosis of interstitial cystitis (IC). METHODS: A total of 82 patients, initially diagnosed as IC, with urinary frequency, urgency and pain on pubic area during bladder filling phase from January 2008 to March 2013 were enrolled.OPSI was used to evaluate their symptoms. They were eventually divided into IC and non-IC groups according to the clinical diagnosis. The scores of OPSI, interstitial cystitis problem index (ICPI) and interstitial cystitis symptom index (ICSI) were compared between two groups. And the ROC curve was plotted to screen the diagnostic specificity and sensitivity. RESULTS: Among them, 58 were diagnosed with IC and the rest with non-IC. The average score of OPSI for groups IC and non-IC were 24.7 ± 6.9 and 23.2 ± 7.8 respectively (P = 0.403). And the ICPI score for two groups were 11.7 ± 3.2 and 10.2 ± 3.7 (P = 0.070) and the ICSI score 13.0 ± 4.0 and 13.1 ± 4.3 (P = 0.975) respectively.No significant differences existed between two groups. If an OPSI score of 12 or greater for diagnosing IC, the sensitivity was 98% and specificity 8%. Because of a high sensitivity, OPSI was a useful indicator for screening IC patients from others.In the ROC curve, acreage under curve for OPSI, ICPI, ICSI were 0.548 ± 0.071, 0.622 ± 0.069 and 0.492 ± 0.070 respectively. These three indices were not good indicators for diagnosing IC. CONCLUSIONS: The O'Leary-Sant symptom index and problem index has a high sensitivity but a low specificity in the diagnosis of IC. Therefore it should not be used to differentiate interstitial cystitis. A cutoff OPSI value of 12 may be used for differentiation.

Analyzing mRNA Epigenetic Sequencing Data with TRESS.

RNA epigenetics has emerged as an active topic to study gene regulation mechanisms. In this regard, the MeRIP-seq technology allows profiling transcriptome-wide mRNA modifications, in particular m6A. The primary goals for the analysis of MeRIP-seq data are the identification of m6A-methylated regions under each condition and across different biological conditions. Here we describe detailed procedures to guide researchers in MeRIP-seq data analyses by providing step-by-step instructions of the dedicated bioconductor package TRESS.

Overexpression of the WWE domain of RNF146 modulates poly-(ADP)-ribose dynamics at sites of DNA damage.

Protein poly-ADP-ribosylation (PARylation) is a post-translational modification formed by transfer of successive units of ADP-ribose to target proteins to form poly-ADP-ribose (PAR) chains. PAR plays a critical role in the DNA damage response (DDR) by acting as a signaling platform to promote the recruitment of DNA repair factors to the sites of DNA damage that bind via their PAR-binding domains (PBDs). Several classes of PBD families have been recognized, which identify distinct parts of the PAR chain. Proteins encoding PBDs play an essential role in conveying the PAR-mediated signal through their interaction with PAR chains, which mediates many cellular functions, including the DDR. The WWE domain identifies the iso-ADP-ribose moiety of the PAR chain. We recently described the WWE domain of RNF146 as a robust genetically encoded probe, when fused to EGFP, for detection of PAR in live cells. Here, we evaluated other PBD candidates as molecular PAR probes in live cells, including several other WWE domains and an engineered macrodomain. In addition, we demonstrate unique PAR dynamics when tracked by different PAR binding domains, a finding that that can be exploited for modulation of the PAR-dependent DNA damage response.

GSK-3 inhibitor elraglusib enhances tumor-infiltrating immune cell activation in tumor biopsies and synergizes with anti-PD-L1 in a murine model of colorectal cancer.

Inhibition of GSK-3 using small-molecule elraglusib has shown promising preclinical antitumor activity. Using in vitro systems, we found that elraglusib promotes immune cell-mediated tumor cell killing, enhances tumor cell pyroptosis, decreases tumor cell NF-κB-regulated survival protein expression, and increases immune cell effector molecule secretion. Using in vivo systems, we observed synergy between elraglusib and anti-PD-L1 in an immunocompetent murine model of colorectal cancer. Murine responders had more tumor-infiltrating T-cells, fewer tumor-infiltrating Tregs, lower tumorigenic circulating cytokine concentrations, and higher immunostimulatory circulating cytokine concentrations. To determine the clinical significance, we utilized human plasma samples from patients treated with elraglusib and correlated cytokine profiles with survival. Using paired tumor biopsies, we found that CD45+ tumor-infiltrating immune cells had lower expression of inhibitory immune checkpoints and higher expression of T-cell activation markers in post-elraglusib patient biopsies. These results introduce several immunomodulatory mechanisms of GSK-3 inhibition using elraglusib, providing a rationale for the clinical evaluation of elraglusib in combination with immunotherapy. Statement of significance: Pharmacologic inhibition of GSK-3 using elraglusib sensitizes tumor cells, activates immune cells for increased anti-tumor immunity, and synergizes with anti-PD-L1 immune checkpoint blockade. These results introduce novel biomarkers for correlations with response to therapy which could provide significant clinical utility and suggest that elraglusib, and other GSK-3 inhibitors, should be evaluated in combination with immune checkpoint blockade.

Accurate genome-scale percentage DNA methylation estimates from microarray data.

DNA methylation is a key regulator of gene function in a multitude of both normal and abnormal biological processes, but tools to elucidate its roles on a genome-wide scale are still in their infancy. Methylation sensitive restriction enzymes and microarrays provide a potential high-throughput, low-cost platform to allow methylation profiling. However, accurate absolute methylation estimates have been elusive due to systematic errors and unwanted variability. Previous microarray preprocessing procedures, mostly developed for expression arrays, fail to adequately normalize methylation-related data since they rely on key assumptions that are violated in the case of DNA methylation. We develop a normalization strategy tailored to DNA methylation data and an empirical Bayes percentage methylation estimator that together yield accurate absolute methylation estimates that can be compared across samples. We illustrate the method on data generated to detect methylation differences between tissues and between normal and tumor colon samples.

[Identification of lower urinary tract voiding dysfunction in females by using video-urodynamic study].

OBJECTIVE: To assess the value of video-urodynamic study (VUD) in the identification of lower urinary tract voiding dysfunction in female. METHODS: A total of 126 female patients with sign and symptoms of lower urinary tract voiding dysfunction underwent VUD from December 2008 to January 2011 in Beijing Chaoyang Hospital. The causes of voiding dysfunction were analyzed based on VUD findings. RESULTS: Neurogenic voiding dysfunction was found in 30 patients (23.8%), non-neurogenic voiding dysfunction was found in 96 patients (76.2%). The 72 patients suffered from recurrent urinary tract infection (57.1%) and 23 patients suffered from hydronephrosis (18.3%). Based on special characteristics of video-urodynamic study, a total of 126 patients were classified as: (1) Bladder outlet obstruction (BOO) was found in 65 patients. Of them, bladder neck obstruction in 40 patients (61.5%), their VUD showed "high pressure-low flow" obstructive curve and synchronic image showed bladder neck did not open in a funnel shape and no contrast was found in urethra. Distal urethral stricture in 22 patients (33.8%), VUD showed "high pressure-low flow" obstructive curve and synchronic image showed bladder neck open in a funnel shape, proximal urethra dilated and no contrast was found in distal urethral. Urethral sphincter obstruction in 3 patients (including detrusor-sphincter dyssynergia in 1 and sphincterismus in 2 patients), VUD showed "high pressure-low flow" obstructive curve and synchronic image showed bladder neck open in a funnel shape, sphincteric urethra did not open, proximal urethra dilated and no contrast was found in distal urethral. (2) Detrusor areflexia (DA) was found in 39 patients (2 patients with hydronephrosis), the VUD finding was: no voluntary detrusor contraction in voiding phase, and abdominal pressure voiding pattern. (3) OAB was found in 3 patients, which VUD findings was frequent involuntary detrusor contraction at storage period with or without urine leakage. (4) Low compliance bladder was found in 17 patients (13.5%), 16 patients with hydronephrosis, the VUD showed that increased bladder storage pressure with significantly decreased bladder safe capacity and compliance, appearance of the bladder as "Christmas tree", with or without ureteral reflux. (5) And stress urinary incontinence (SUI) was in 2. CONCLUSIONS: The main causes of female BOO may be non-neurogenic conditions or organic obstruction. VUD would offer valuable information for confirmed diagnosis of voiding dysfunction in female patients.

Liparismacrosepala (Orchidaceae), a new species from southwest China with its phylogenetic position.

A new orchid species, Liparismacrosepala, is illustrated and described from Yunnan Province, China, based on morphological and molecular analyses. This plant is characterised by the ovoid-fusiform, slightly compressed pseudobulbs with 4 or 5 leaves with slightly crisped margins on their apical half, dorsal sepal heart-shaped, lip with a bituberculate basal callus and a thickened folded lateral lobe on each side, centrally with one cavity with slightly raised margins, the column with a single pair of broadly triangular, obtuse wings. Maximum Likelihood and Bayesian Inference analyses of combined nrITS and plastid matK DNA sequences place this species in section Cestichis.

Chromosome-wide mapping of DNA methylation patterns in normal and malignant prostate cells reveals pervasive methylation of gene-associated and conserved intergenic sequences.

BACKGROUND: DNA methylation has been linked to genome regulation and dysregulation in health and disease respectively, and methods for characterizing genomic DNA methylation patterns are rapidly emerging. We have developed/refined methods for enrichment of methylated genomic fragments using the methyl-binding domain of the human MBD2 protein (MBD2-MBD) followed by analysis with high-density tiling microarrays. This MBD-chip approach was used to characterize DNA methylation patterns across all non-repetitive sequences of human chromosomes 21 and 22 at high-resolution in normal and malignant prostate cells. RESULTS: Examining this data using computational methods that were designed specifically for DNA methylation tiling array data revealed widespread methylation of both gene promoter and non-promoter regions in cancer and normal cells. In addition to identifying several novel cancer hypermethylated 5' gene upstream regions that mediated epigenetic gene silencing, we also found several hypermethylated 3' gene downstream, intragenic and intergenic regions. The hypermethylated intragenic regions were highly enriched for overlap with intron-exon boundaries, suggesting a possible role in regulation of alternative transcriptional start sites, exon usage and/or splicing. The hypermethylated intergenic regions showed significant enrichment for conservation across vertebrate species. A sampling of these newly identified promoter (ADAMTS1 and SCARF2 genes) and non-promoter (downstream or within DSCR9, C21orf57 and HLCS genes) hypermethylated regions were effective in distinguishing malignant from normal prostate tissues and/or cell lines. CONCLUSIONS: Comparison of chromosome-wide DNA methylation patterns in normal and malignant prostate cells revealed significant methylation of gene-proximal and conserved intergenic sequences. Such analyses can be easily extended for genome-wide methylation analysis in health and disease.