Engineered exosomes targeting MYC reverse the proneural-mesenchymal transition and extend survival of glioblastoma.

Dysregulated Myc signaling is a key oncogenic pathway in glioblastoma multiforme (GBM). Yet, effective therapeutic targeting of Myc continues to be challenging. Here, we demonstrate that exosomes generated from human bone marrow mesenchymal stem cells (MSCs) engineered to encapsulate siRNAs targeting Myc (iExo-Myc) localize to orthotopic GBM tumors in mice. Treatment of late stage GBM tumors with iExo-Myc inhibits proliferation and angiogenesis, suppresses tumor growth, and extends survival. Transcriptional profiling of tumors reveals that the mesenchymal transition and estrogen receptor signaling pathways are impacted by Myc inhibition. Single nuclei RNA sequencing (snRNA-seq) shows that iExo-Myc treatment induces transcriptional repression of multiple growth factor and interleukin signaling pathways, triggering a mesenchymal to proneural transition and shifting the cellular landscape of the tumor. These data confirm that Myc is an effective anti-glioma target and that iExo-Myc offers a feasible, readily translational strategy to inhibit challenging oncogene targets for the treatment of brain tumors.

Unique somatic variants in DNA from urine exosomes of individuals with bladder cancer.

Bladder cancer (BC), a heterogeneous disease characterized by high recurrence rates, is diagnosed and monitored by cystoscopy. Accurate clinical staging based on biopsy remains a challenge, and additional, objective diagnostic tools are needed urgently. We used exosomal DNA (exoDNA) as an analyte to examine cancer-associated mutations and compared the diagnostic utility of exoDNA from urine and serum of individuals with BC. In contrast to urine exosomes from healthy individuals, urine exosomes from individuals with BC contained significant amounts of DNA. Whole-exome sequencing of DNA from matched urine and serum exosomes, bladder tumors, and normal tissue (peripheral blood mononuclear cells) identified exonic and 3' UTR variants in frequently mutated genes in BC, detectable in urine exoDNA and matched tumor samples. Further analyses identified somatic variants in driver genes, unique to urine exoDNA, possibly because of the inherent intra-tumoral heterogeneity of BC, which is not fully represented in random small biopsies. Multiple variants were also found in untranslated portions of the genome, such as microRNA (miRNA)-binding regions of the KRAS gene. Gene network analyses revealed that exoDNA is associated with cancer, inflammation, and immunity in BC exosomes. Our findings show utility of exoDNA as an objective, non-invasive strategy to identify novel biomarkers and targets for BC.

Chromosomal Heterogeneity of the G-401 Rhabdoid Tumor Cell Line: Unusual Partial 7p Trisomy.

Rhabdoid tumor is a very aggressive and hardly curable pediatric malignancy. It commonly starts in the kidneys but also can occur in the brain, liver, and other organs. The treatment of this tumor usually involves a combination of surgery, radiation, and chemotherapy. Because this tumor is rare, there is still limited experience with a defined standard of care. Cytogenetic analysis is an important routine method to monitor chromosomal aberrations. We have analyzed metaphases of the G-401 rhabdoid tumor cell line. In these cells we have observed metaphases with derivative chromosome 12 arising from partial trisomy 7p. With increasing passage number the numbers of metaphases having this derivative chromosome 12 were found to be higher. In passage number 2 only one metaphase had this pathological chromosome 12. By passage number 10 and passage number 15 about 25 and 95% of this derivative chromosome 12 were found, respectively. We were able to subclone G-401 cells by limiting dilutions and successfully separated cells having apparently normal karyotypes from cells having derivative chromosome 12. Using the cell proliferation assay we showed that clones possessing the derivative chromosome 12 grew more rapidly than clones with normal chromosomes. The cell cycle analysis confirmed this observation. Overall, in this study we describe for the first time a 7p triplication in a rare rhabdoid tumor of kidney. Both types of clones described in this study could be used as a preclinical model to study the involvement of partial chromosome 7 alterations in the development of rhabdoid tumors.

Exploring the functional impact of alternative splicing on human protein isoforms using available annotation sources.

In recent years, the emphasis of scientific inquiry has shifted from whole-genome analyses to an understanding of cellular responses specific to tissue, developmental stage or environmental conditions. One of the central mechanisms underlying the diversity and adaptability of the contextual responses is alternative splicing (AS). It enables a single gene to encode multiple isoforms with distinct biological functions. However, to date, the functions of the vast majority of differentially spliced protein isoforms are not known. Integration of genomic, proteomic, functional, phenotypic and contextual information is essential for supporting isoform-based modeling and analysis. Such integrative proteogenomics approaches promise to provide insights into the functions of the alternatively spliced protein isoforms and provide high-confidence hypotheses to be validated experimentally. This manuscript provides a survey of the public databases supporting isoform-based biology. It also presents an overview of the potential global impact of AS on the human canonical gene functions, molecular interactions and cellular pathways.

XPO1 Inhibitor Selinexor Overcomes Intrinsic Ibrutinib Resistance in Mantle Cell Lymphoma via Nuclear Retention of IκB.

Inhibition of B-cell receptor (BCR) signaling through the BTK inhibitor, ibrutinib, has generated a remarkable response in mantle cell lymphoma (MCL). However, approximately one third of patients do not respond well to the drug, and disease relapse on ibrutinib is nearly universal. Alternative therapeutic strategies aimed to prevent and overcome ibrutinib resistance are needed. We compared and contrasted the effects of selinexor, a selective inhibitor of nuclear export, with ibrutinib in six MCL cell lines that display differential intrinsic sensitivity to ibrutinib. We found that selinexor had a broader antitumor activity in MCL than ibrutinib. MCL cell lines resistant to ibrutinib remained sensitive to selinexor. We showed that selinexor induced apoptosis/cell-cycle arrest and XPO-1 knockdown also retarded cell growth. Furthermore, downregulation of the NFκB gene signature, as opposed to BCR signature, was a common feature that underlies the response of MCL to both selinexor and ibrutinib. Meanwhile, unaltered NFκB was associated with ibrutinib resistance. Mechnistically, selinexor induced nuclear retention of IκB that was accompanied by the reduction of DNA-binding activity of NFκB, suggesting that NFκB is trapped in an inhibitory complex. Coimmunoprecipitation confirmed that p65 of NFκB and IκB were physically associated. In primary MCL tumors, we further demonstrated that the number of cells with IκB nuclear retention was linearly correlated with the degree of apoptosis. Our data highlight the role of NFκB pathway in drug response to ibrutinib and selinexor and show the potential of using selinexor to prevent and overcome intrinsic ibrutinib resistance through NFκB inhibition.

Chemokine expression in the early response to injury in human airway epithelial cells.

Basal airway epithelial cells (AEC) constitute stem/progenitor cells within the central airways and respond to mucosal injury in an ordered sequence of spreading, migration, proliferation, and differentiation to needed cell types. However, dynamic gene transcription in the early events after mucosal injury has not been studied in AEC. We examined gene expression using microarrays following mechanical injury (MI) in primary human AEC grown in submersion culture to generate basal cells and in the air-liquid interface to generate differentiated AEC (dAEC) that include goblet and ciliated cells. A select group of ~150 genes was in differential expression (DE) within 2-24 hr after MI, and enrichment analysis of these genes showed over-representation of functional categories related to inflammatory cytokines and chemokines. Network-based gene prioritization and network reconstruction using the PINTA heat kernel diffusion algorithm demonstrated highly connected networks that were richer in differentiated AEC compared to basal cells. Similar experiments done in basal AEC collected from asthmatic donor lungs demonstrated substantial changes in DE genes and functional categories related to inflammation compared to basal AEC from normal donors. In dAEC, similar but more modest differences were observed. We demonstrate that the AEC transcription signature after MI identifies genes and pathways that are important to the initiation and perpetuation of airway mucosal inflammation. Gene expression occurs quickly after injury and is more profound in differentiated AEC, and is altered in AEC from asthmatic airways. Our data suggest that the early response to injury is substantially different in asthmatic airways, particularly in basal airway epithelial cells.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

The functional domains for Bax∆2 aggregate-mediated caspase 8-dependent cell death.

Bax∆2 is a functional pro-apoptotic Bax isoform having alterations in its N-terminus, but sharing the rest of its sequence with Baxα. Bax∆2 is unable to target mitochondria due to the loss of helix α1. Instead, it forms cytosolic aggregates and activates caspase 8. However, the functional domain(s) responsible for BaxΔ2 behavior have remained elusive. Here we show that disruption of helix α1 makes Baxα mimic the behavior of Bax∆2. However, the other alterations in the Bax∆2 N-terminus have no significant impact on aggregation or cell death. We found that the hallmark BH3 domain is necessary but not sufficient for aggregation-mediated cell death. We also noted that the core region shared by Baxα and Bax∆2 is required for the formation of large aggregates, which is essential for BaxΔ2 cytotoxicity. However, aggregation by itself is unable to trigger cell death without the C-terminus. Interestingly, the C-terminal helical conformation, not its primary sequence, appears to be critical for caspase 8 recruitment and activation. As Bax∆2 shares core and C-terminal sequences with most Bax isoforms, our results not only reveal a structural basis for Bax∆2-induced cell death, but also imply an intrinsic potential for aggregate-mediated caspase 8-dependent cell death in other Bax family members.

Extracellular vesicles in gastrointestinal cancer in conjunction with microbiota: On the border of Kingdoms.

Extracellular vesicle (EV) production is a universal feature of metazoan cells as well as prokaryotes (bMVs - bacterial microvesicles). They are small vesicles with phospholipid membrane carrying proteins, DNA and different classes of RNAs and are heavily involved in intercellular communication acting as vectors of information to target cells. For the last decade, the interest in EV research has exponentially increased though thorough studies of their roles in various pathologies that was not previously possible due to technical limitations. This review focuses on research evaluating the role of EV production in gastrointestinal (GI) cancer development in conjunction with GI microbiota and inflammatory diseases. We also discuss recent studies on the promising role of EVs and their content as biomarkers for early diagnosis of GI cancers. The bMVs have also been implicated in the pathogenesis of GI chronic inflammatory diseases, however, possible role of bMVs in tumorigenesis remains underestimated. We propose that EVs from eukaryotic cells as well as from different microbial, fungi, parasitic species and edible plants in GI tract act as mediators of intracellular and inter-species communication, particularly facilitating tumor cell survival and multi-drug resistance. In conclusion, we suggest that matching sequences from EV proteomes (available from public databases) with known protein sequences of microbiome gut bacteria will be useful in identification of antigen mimicry between evolutionary conservative protein sequences. Using this approach we identified Bacteroides spp. pseudokinase with activation loop and homology to PDGFRα, providing a proof-of-concept strategy. We speculate that existence of microbial pseudokinase that 'mimics' PDGFRα may be related to PDGFRα and Bacteroides spp. roles in colorectal carcinogenesis that require further investigation.

Lynx: a knowledge base and an analytical workbench for integrative medicine.

Lynx (http://lynx.ci.uchicago.edu) is a web-based database and a knowledge extraction engine. It supports annotation and analysis of high-throughput experimental data and generation of weighted hypotheses regarding genes and molecular mechanisms contributing to human phenotypes or conditions of interest. Since the last release, the Lynx knowledge base (LynxKB) has been periodically updated with the latest versions of the existing databases and supplemented with additional information from public databases. These additions have enriched the data annotations provided by Lynx and improved the performance of Lynx analytical tools. Moreover, the Lynx analytical workbench has been supplemented with new tools for reconstruction of co-expression networks and feature-and-network-based prioritization of genetic factors and molecular mechanisms. These developments facilitate the extraction of meaningful knowledge from experimental data and LynxKB. The Service Oriented Architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.

Disease gene prioritization using network and feature.

Identifying high-confidence candidate genes that are causative for disease phenotypes, from the large lists of variations produced by high-throughput genomics, can be both time-consuming and costly. The development of novel computational approaches, utilizing existing biological knowledge for the prioritization of such candidate genes, can improve the efficiency and accuracy of the biomedical data analysis. It can also reduce the cost of such studies by avoiding experimental validations of irrelevant candidates. In this study, we address this challenge by proposing a novel gene prioritization approach that ranks promising candidate genes that are likely to be involved in a disease or phenotype under study. This algorithm is based on the modified conditional random field (CRF) model that simultaneously makes use of both gene annotations and gene interactions, while preserving their original representation. We validated our approach on two independent disease benchmark studies by ranking candidate genes using network and feature information. Our results showed both high area under the curve (AUC) value (0.86), and more importantly high partial AUC (pAUC) value (0.1296), and revealed higher accuracy and precision at the top predictions as compared with other well-performed gene prioritization tools, such as Endeavour (AUC-0.82, pAUC-0.083) and PINTA (AUC-0.76, pAUC-0.066). We were able to detect more target genes (9/18/19/27) on top positions (1/5/10/20) compared to Endeavour (3/11/14/23) and PINTA (6/10/13/18). To demonstrate its usability, we applied our method to a case study for the prediction of molecular mechanisms contributing to intellectual disability and autism. Our approach was able to correctly recover genes related to both disorders and provide suggestions for possible additional candidates based on their rankings and functional annotations.

An integrative computational approach for prioritization of genomic variants.

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.

Lynx web services for annotations and systems analysis of multi-gene disorders.

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform.

Lynx: a database and knowledge extraction engine for integrative medicine.

We have developed Lynx (http://lynx.ci.uchicago.edu)--a web-based database and a knowledge extraction engine, supporting annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Its underlying knowledge base (LynxKB) integrates various classes of information from >35 public databases and private collections, as well as manually curated data from our group and collaborators. Lynx provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization to assist the user in extracting meaningful knowledge from LynxKB and experimental data, whereas its service-oriented architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.

High-throughput translational medicine: challenges and solutions.

Recent technological advances in genomics now allow producing biological data at unprecedented tera- and petabyte scales. Yet, the extraction of useful knowledge from this voluminous data presents a significant challenge to a scientific community. Efficient mining of vast and complex data sets for the needs of biomedical research critically depends on seamless integration of clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships accumulated in a plethora of publicly available databases. Furthermore, such experimental data should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining. Translational projects require sophisticated approaches that coordinate and perform various analytical steps involved in the extraction of useful knowledge from accumulated clinical and experimental data in an orderly semiautomated manner. It presents a number of challenges such as (1) high-throughput data management involving data transfer, data storage, and access control; (2) scalable computational infrastructure; and (3) analysis of large-scale multidimensional data for the extraction of actionable knowledge.We present a scalable computational platform based on crosscutting requirements from multiple scientific groups for data integration, management, and analysis. The goal of this integrated platform is to address the challenges and to support the end-to-end analytical needs of various translational projects.

Microvesicles and intercellular communication in the context of parasitism.

There is a rapidly growing body of evidence that production of microvesicles (MVs) is a universal feature of cellular life. MVs can incorporate microRNA (miRNA), mRNA, mtDNA, DNA and retrotransposons, camouflage viruses/viral components from immune surveillance, and transfer cargo between cells. These properties make MVs an essential player in intercellular communication. Increasing evidence supports the notion that MVs can also act as long-distance vehicles for RNA molecules and participate in metabolic synchronization and reprogramming eukaryotic cells including stem and germinal cells. MV ability to carry on DNA and their general distribution makes them attractive candidates for horizontal gene transfer, particularly between multi-cellular organisms and their parasites; this suggests important implications for the co-evolution of parasites and their hosts. In this review, we provide current understanding of the roles played by MVs in intracellular pathogens and parasitic infections. We also discuss the possible role of MVs in co-infection and host shifting.

Copy number variants and infantile spasms: evidence for abnormalities in ventral forebrain development and pathways of synaptic function.

Infantile spasms (ISS) are an epilepsy disorder frequently associated with severe developmental outcome and have diverse genetic etiologies. We ascertained 11 subjects with ISS and novel copy number variants (CNVs) and combined these with a new cohort with deletion 1p36 and ISS, and additional published patients with ISS and other chromosomal abnormalities. Using bioinformatics tools, we analyzed the gene content of these CNVs for enrichment in pathways of pathogenesis. Several important findings emerged. First, the gene content was enriched for the gene regulatory network involved in ventral forebrain development. Second, genes in pathways of synaptic function were overrepresented, significantly those involved in synaptic vesicle transport. Evidence also suggested roles for GABAergic synapses and the postsynaptic density. Third, we confirm the association of ISS with duplication of 14q12 and maternally inherited duplication of 15q11q13, and report the association with duplication of 21q21. We also present a patient with ISS and deletion 7q11.3 not involving MAGI2. Finally, we provide evidence that ISS in deletion 1p36 may be associated with deletion of KLHL17 and expand the epilepsy phenotype in that syndrome to include early infantile epileptic encephalopathy. Several of the identified pathways share functional links, and abnormalities of forebrain synaptic growth and function may form a common biologic mechanism underlying both ISS and autism. This study demonstrates a novel approach to the study of gene content in subjects with ISS and copy number variation, and contributes further evidence to support specific pathways of pathogenesis.

The minimum information about a genome sequence (MIGS) specification.

With the quantity of genomic data increasing at an exponential rate, it is imperative that these data be captured electronically, in a standard format. Standardization activities must proceed within the auspices of open-access and international working bodies. To tackle the issues surrounding the development of better descriptions of genomic investigations, we have formed the Genomic Standards Consortium (GSC). Here, we introduce the minimum information about a genome sequence (MIGS) specification with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange. As part of its wider goals, the GSC also supports improving the 'transparency' of the information contained in existing genomic databases.

Interoperability of GADU in using heterogeneous grid resources for bioinformatics applications.

Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. The genome analysis and database update system (GADU) is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run jobs on different Grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual data system that makes high-throughput computational tools interoperable on heterogeneous Grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid. The paper will not go into the details of problems involved or the lessons learned in using individual Grid resources as it has already been published in our paper on genome analysis research environment (GNARE) and will focus primarily on the architecture that makes GADU resource independent and interoperable across heterogeneous Grid resources.