TSCRE: a comprehensive database for tumor-specific cis-regulatory elements.

Cis-regulatory elements (CREs) and super cis-regulatory elements (SCREs) are non-coding DNA regions which influence the transcription of nearby genes and play critical roles in development. Dysregulated CRE and SCRE activities have been reported to alter the expression of oncogenes and tumor suppressors, thereby regulating cancer hallmarks. To address the strong need for a comprehensive catalogue of dysregulated CREs and SCREs in human cancers, we present TSCRE (http://tscre.zsqylab.com/), an open resource providing tumor-specific and cell type-specific CREs and SCREs derived from the re-analysis of publicly available histone modification profiles. Currently, TSCRE contains 1 864 941 dysregulated CREs and 68 253 dysregulated SCREs identified from 1366 human patient samples spanning 17 different cancer types and 9 histone marks. Over 95% of these elements have been validated in public resources. TSCRE offers comprehensive annotations for each element, including associated genes, expression patterns, clinical prognosis, somatic mutations, transcript factor binding sites, cancer-type specificity, and drug response. Additionally, TSCRE integrates pathway and transcript factor enrichment analyses for each study, enabling in-depth functional and mechanistic investigations. Furthermore, TSCRE provides an interactive interface for users to explore any CRE and SCRE of interest. We believe TSCRE will be a highly valuable platform for the community to discover candidate cancer biomarkers.

Lifetime healthcare expenses across demographic and cardiovascular risk groups: The application of a novel modeling strategy in a large multiethnic cohort study.

Objective: To understand the burden of healthcare expenses over the lifetime of individuals and evaluate differences among those with cardiovascular risk factors and among disadvantaged groups based on race/ethnicity and sex. Methods: We linked data from the longitudinal multiethnic Dallas Heart Study, which recruited participants between 2000 and 2002, with inpatient and outpatient claims from all hospitals in the Dallas-Fort Worth metroplex through December 2018, capturing encounter expenses. Race/ethnicity and sex, as well as five risk factors, hypertension, diabetes, hyperlipidemia, smoking, and overweight/obesity, were defined at cohort enrollment. For each individual, expenses were indexed to age and cumulated between 40 and 80 years of age. Lifetime expenses across exposures were evaluated as interactions in generalized additive models. Results: A total of 2184 individuals (mean age, 45±10 years; 61% women, 53% Black) were followed between 2000 and 2018. The mean modeled lifetime cumulative healthcare expenses were $442,629 (IQR, $423,850 to $461,408). In models that included 5 risk factors, Black individuals had $21,306 higher lifetime healthcare spending compared with non-Black individuals (P < .001), and men had modestly higher expenses than women ($5987, P < .001). Across demographic groups, the presence of risk factors was associated with progressively higher lifetime expenses, with significant independent association of diabetes ($28,075, P < .001), overweight/obesity ($8816, P < .001), smoking ($3980, P = .009), and hypertension ($528, P = .02) with excess spending. Conclusion: Our study suggests Black individuals have higher lifetime healthcare expenses, exaggerated by the substantially higher prevalence of risk factors, with differences emerging in older age.

Persistence on Novel Cardioprotective Antihyperglycemic Therapies in the United States.

Selected glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT-2is) have cardioprotective effects in patients with type 2 diabetes mellitus (T2D) and elevated cardiovascular risk. Prescription and consistent use of these medications are essential to realizing their benefits. In a nationwide deidentified United States administrative claims database of adults with T2D, the prescription practices of GLP-1RAs and SGLT-2i were evaluated across guideline-directed co-morbidity indications from 2018 to 2020. The monthly fill rates were assessed for 12 months after the initiation of therapy by calculating the proportion of days with consistent medication use. Of 587,657 subjects with T2D, 80,196 (13.6%) were prescribed GLP-1RAs and 68,149 (11.5%) SGLT-2i from 2018 to 2020, representing 12.9% and 11.6% of patients with indications for each medication, respectively. In new initiators, 1-year fill rate was 52.5% for GLP-1RAs and 52.9% for SGLT-2i, which was higher for patients with commercial insurance than those with Medicare Advantage plans for both GLP-1RAs (59.3% vs 51.0%, p <0.001) and SGLT-2i (63.4% vs 50.3%, p <0.001). After adjusting for co-morbidities, there were higher rates of prescription fills for patients with commercial insurance (odds ratio 1.17, 95% confidence interval 1.06 to 1.29 for GLP-1RAs, and 1.59 [1.42 to 1.77] for SGLT-2i); and higher income (odds ratio 1.09 [1.06 to 1.12] for GLP-1RAs, and 1.06 [1.03 to 1.1] for SGLT-2i). From 2018 to 2020, the use of GLP-1RAs and SGLT-2i remained limited to fewer than 1 in 8 patients with T2D and indications, with 1-year fill rates around 50%. The low and inconsistent use of these medications compromises their longitudinal health outcome benefits in a period of expanding indications for their use.

RPS: a comprehensive database of RNAs involved in liquid-liquid phase separation.

Liquid-liquid phase separation (LLPS) is critical for assembling membraneless organelles (MLOs) such as nucleoli, P-bodies, and stress granules, which are involved in various physiological processes and pathological conditions. While the critical role of RNA in the formation and the maintenance of MLOs is increasingly appreciated, there is still a lack of specific resources for LLPS-related RNAs. Here, we presented RPS (http://rps.renlab.org), a comprehensive database of LLPS-related RNAs in 20 distinct biomolecular condensates from eukaryotes and viruses. Currently, RPS contains 21,613 LLPS-related RNAs with three different evidence types, including 'Reviewed', 'High-throughput' and 'Predicted'. RPS provides extensive annotations of LLPS-associated RNA properties, including sequence features, RNA structures, RNA-protein/RNA-RNA interactions, and RNA modifications. Moreover, RPS also provides comprehensive disease annotations to help users to explore the relationship between LLPS and disease. The user-friendly web interface of RPS allows users to access the data efficiently. In summary, we believe that RPS will serve as a valuable platform to study the role of RNA in LLPS and further improve our understanding of the biological functions of LLPS.

MesKit: a tool kit for dissecting cancer evolution of multi-region tumor biopsies through somatic alterations.

BACKGROUND: Multi-region sequencing (MRS) has been widely used to analyze intra-tumor heterogeneity (ITH) and cancer evolution. However, comprehensive analysis of mutational data from MRS is still challenging, necessitating complicated integration of a plethora of computational and statistical approaches. FINDINGS: Here, we present MesKit, an R/Bioconductor package that can assist in characterizing genetic ITH and tracing the evolutionary history of tumors based on somatic alterations detected by MRS. MesKit provides a wide range of analysis and visualization modules, including ITH evaluation, metastatic route inference, and mutational signature identification. In addition, MesKit implements an auto-layout algorithm to generate phylogenetic trees based on somatic mutations. The application of MesKit for 2 reported MRS datasets of hepatocellular carcinoma and colorectal cancer identified known heterogeneous features and evolutionary patterns, together with potential driver events during cancer evolution. CONCLUSIONS: In summary, MesKit is useful for interpreting ITH and tracing evolutionary trajectory based on MRS data. MesKit is implemented in R and available at https://bioconductor.org/packages/MesKit under the GPL v3 license.

Single AAV-Mediated CRISPR-SaCas9 Inhibits HSV-1 Replication by Editing ICP4 in Trigeminal Ganglion Neurons.

Herpes simplex keratitis (HSK) is the most common cause of corneal blindness in developed nations, caused by primary or recurrent herpes simplex virus 1 (HSV-1) infection of the cornea. Latent infection of HSV-1, especially in the trigeminal ganglion (TG), causes recurrence of HSV-1 infection. As antiviral treatment is not effective on latent HSV-1, to test the possibility of inhibiting HSV-1 by SpCas9 (Streptococcus pyogenes Cas9) or SaCas9 (Staphylococcus aureus Cas9), ICP0 and ICP4, two important genes required for HSV-1 replication and reactivation, were chosen as targets. In Vero cells, SpCas9 and SaCas9 targeting ICP0 or ICP4 can effectively inhibit the proliferation of HSV-1 without affecting cell viability. No significant guide RNA (gRNA)-dependent off-targets were observed in the human genome by digenome sequencing and deep sequencing verification. Adeno-associated virus 1 (AAV1)-mediated delivery of SaCas9 inhibits HSV-1 replication by targeting ICP4 in mouse primary TG neuronal cells. SpCas9 and SaCas9 are able to inhibit HSV-1 infection in Vero cells and mouse TG neuronal cultures with high efficiency and good biosafety. AAV1-mediated delivery of SaCas9 shows great potential in treating HSK and inhibiting HSV-1 in TG neurons. Further investigations may be needed to test the inhibition of latent infections, which may result in the development of novel methods for treating viral diseases.

Identification and expression analysis of candidate chemosensory receptors based on the antennal transcriptome of Lissorhoptrus oryzophilus.

The rice water weevil Lissorhoptrus oryzophilus Kuschel (Coleoptera: Curculionidae) is a worldwide agricultural pest that causes serious damage to rice. The olfactory and gustatory behaviors of L. oryzophilus in locating host plants and oviposition sites mostly rely on the detection of chemical stimuli in the environment. To reveal such olfactory and gustatory systems, we performed a systematic analysis of major chemosensory receptor genes. The antennal transcriptome of adult female L. oryzophilus was sequenced and assembled using the Illumina sequencing platform. A total of 60 candidate chemosensory receptor genes were ultimately identified, including 41 putative odorant receptors (ORs), 10 ionotropic receptors (IRs) and 9 gustatory receptors (GRs). Relatedness with other species was predicted based on phylogenetic results, and specific chemosensory receptor genes were analyzed, including Orco, carbon dioxide receptors and sugar receptors. Furthermore, qRT-PCR analyses of chemosensory receptor genes showed 59 genes to be antenna-biased genes, whereas only 1 gene was predominantly expressed in non-olfactory tissues. Our research provides insight for understanding olfactory and gustatory systems in the antennae of L. oryzophilus and facilitating the discovery of novel strategies for controlling this pest.

lnCAR: A Comprehensive Resource for lncRNAs from Cancer Arrays.

Long noncoding RNAs (lncRNA) have emerged as promising biomarkers in cancer diagnosis, treatment, and prognosis. Recent studies suggest that a large number of coding gene expression microarray probes could be reannotated as lncRNAs. Microarray, once the most cutting-edge high-throughput gene expression technology, has been used for thousands of cancer studies and has brought invaluable resources for studying the functions of lncRNA in cancer development. However, a comprehensive lncRNA resource based on microarray data is still lacking. Here, we present lnCAR (lncRNAs from cancer arrays), a comprehensive open resource for providing expression profiles and prognostic landscape of lncRNAs derived from reannotation of public microarray data. Currently, lnCAR contains 52,300 samples for differential expression analysis and 12,883 samples for survival analysis from 10 cancer types. lnCAR allows users to interactively explore any annotated or novel lncRNAs. We believe lnCAR will serve as a valuable resource for the community focused on lncRNA research in cancer. SIGNIFICANCE: lnCAR, a new interactive tool of reannotated public cancer-related microarray data, provides expression profiles and prognostic landscapes of lncRNAs across thousands of samples and multiple cancer types.

Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development.

Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.

m6AVar: a database of functional variants involved in m6A modification.

Identifying disease-causing variants among a large number of single nucleotide variants (SNVs) is still a major challenge. Recently, N6-methyladenosine (m6A) has become a research hotspot because of its critical roles in many fundamental biological processes and a variety of diseases. Therefore, it is important to evaluate the effect of variants on m6A modification, in order to gain a better understanding of them. Here, we report m6AVar (http://m6avar.renlab.org), a comprehensive database of m6A-associated variants that potentially influence m6A modification, which will help to interpret variants by m6A function. The m6A-associated variants were derived from three different m6A sources including miCLIP/PA-m6A-seq experiments (high confidence), MeRIP-Seq experiments (medium confidence) and transcriptome-wide predictions (low confidence). Currently, m6AVar contains 16 132 high, 71 321 medium and 326 915 low confidence level m6A-associated variants. We also integrated the RBP-binding regions, miRNA-targets and splicing sites associated with variants to help users investigate the effect of m6A-associated variants on post-transcriptional regulation. Because it integrates the data from genome-wide association studies (GWAS) and ClinVar, m6AVar is also a useful resource for investigating the relationship between the m6A-associated variants and disease. Overall, m6AVar will serve as a useful resource for annotating variants and identifying disease-causing variants.