Oncogenic Role of THOR, a Conserved Cancer/Testis Long Non-coding RNA.

Large-scale transcriptome sequencing efforts have vastly expanded the catalog of long non-coding RNAs (lncRNAs) with varying evolutionary conservation, lineage expression, and cancer specificity. Here, we functionally characterize a novel ultraconserved lncRNA, THOR (ENSG00000226856), which exhibits expression exclusively in testis and a broad range of human cancers. THOR knockdown and overexpression in multiple cell lines and animal models alters cell or tumor growth supporting an oncogenic role. We discovered a conserved interaction of THOR with IGF2BP1 and show that THOR contributes to the mRNA stabilization activities of IGF2BP1. Notably, transgenic THOR knockout produced fertilization defects in zebrafish and also conferred a resistance to melanoma onset. Likewise, ectopic expression of human THOR in zebrafish accelerated the onset of melanoma. THOR represents a novel class of functionally important cancer/testis lncRNAs whose structure and function have undergone positive evolutionary selection.

Steric Inhibition of 5' UTR Regulatory Elements Results in Upregulation of Human CFTR.

Cystic fibrosis (CF) is an autosomal recessive monogenic disease caused by mutations in the CFTR gene. Therapeutic approaches that are focused on correcting CFTR protein face the challenge of the heterogeneity in CFTR mutations and resulting defects. Thus, while several small molecules directed at CFTR show benefit in the clinic for subsets of CF patients, these drugs cannot treat all CF patients. Additionally, the clinical benefit from treatment with these modulators could be enhanced with novel therapies. To address this unmet need, we utilized an approach to increase CFTR protein levels through antisense oligonucleotide (ASO)-mediated steric inhibition of 5' UTR regulatory elements. We identified ASOs to upregulate CFTR protein expression and confirmed the regulatory role of the sites amenable to ASO-mediated upregulation. Two ASOs were investigated further, and both increased CFTR protein expression and function in cell lines and primary human bronchial epithelial cells with distinct CF genotypes. ASO treatment further increased CFTR function in almost all CF genotypes tested on top of treatment with the FDA approved drug Symdeko (ivacaftor and tezacaftor). Thus, we present a novel approach to CFTR therapeutic intervention, through ASO-mediated modulation of translation.

Antisense oligonucleotides targeting translation inhibitory elements in 5' UTRs can selectively increase protein levels.

A variety of diseases are caused by deficiencies in amounts or activity of key proteins. An approach that increases the amount of a specific protein might be of therapeutic benefit. We reasoned that translation could be specifically enhanced using trans-acting agents that counter the function of negative regulatory elements present in the 5' UTRs of some mRNAs. We recently showed that translation can be enhanced by antisense oligonucleotides (ASOs) that target upstream open reading frames. Here we report the amount of a protein can also be selectively increased using ASOs designed to hybridize to other translation inhibitory elements in 5' UTRs. Levels of human RNASEH1, LDLR, and ACP1 and of mouse ACP1 and ARF1 were increased up to 2.7-fold in different cell types and species upon treatment with chemically modified ASOs targeting 5' UTR inhibitory regions in the mRNAs encoding these proteins. The activities of ASOs in enhancing translation were sequence and position dependent and required helicase activity. The ASOs appear to improve the recruitment of translation initiation factors to the target mRNA. Importantly, ASOs targeting ACP1 mRNA significantly increased the level of ACP1 protein in mice, suggesting that this approach has therapeutic and research potentials.

Hepatotoxicity of high affinity gapmer antisense oligonucleotides is mediated by RNase H1 dependent promiscuous reduction of very long pre-mRNA transcripts.

High affinity antisense oligonucleotides (ASOs) containing bicylic modifications (BNA) such as locked nucleic acid (LNA) designed to induce target RNA cleavage have been shown to have enhanced potency along with a higher propensity to cause hepatotoxicity. In order to understand the mechanism of this hepatotoxicity, transcriptional profiles were collected from the livers of mice treated with a panel of highly efficacious hepatotoxic or non-hepatotoxic LNA ASOs. We observed highly selective transcript knockdown in mice treated with non-hepatotoxic LNA ASOs, while the levels of many unintended transcripts were reduced in mice treated with hepatotoxic LNA ASOs. This transcriptional signature was concurrent with on-target RNA reduction and preceded transaminitis. Remarkably, the mRNA transcripts commonly reduced by toxic LNA ASOs were generally not strongly associated with any particular biological process, cellular component or functional group. However, they tended to have much longer pre-mRNA transcripts. We also demonstrate that the off-target RNA knockdown and hepatotoxicity is attenuated by RNase H1 knockdown, and that this effect can be generalized to high affinity modifications beyond LNA. This suggests that for a certain set of ASOs containing high affinity modifications such as LNA, hepatotoxicity can occur as a result of unintended off-target RNase H1 dependent RNA degradation.

Integrated Safety Assessment of 2'-O-Methoxyethyl Chimeric Antisense Oligonucleotides in NonHuman Primates and Healthy Human Volunteers.

The common chemical and biological properties of antisense oligonucleotides provide the opportunity to identify and characterize chemical class effects across species. The chemical class that has proven to be the most versatile and best characterized is the 2'-O-methoxyethyl chimeric antisense oligonucleotides. In this report we present an integrated safety assessment of data obtained from controlled dose-ranging studies in nonhuman primates (macaques) and healthy human volunteers for 12 unique 2'-O-methoxyethyl chimeric antisense oligonucleotides. Safety was assessed by the incidence of safety signals in standardized laboratory tests for kidney and liver function, hematology, and complement activation; as well as by the mean test results as a function of dose level over time. At high doses a number of toxicities were observed in nonhuman primates. However, no class safety effects were identified in healthy human volunteers from this integrated data analysis. Effects on complement in nonhuman primates were not observed in humans. Nonhuman primates predicted safe doses in humans, but over predicted risk of complement activation and effects on platelets. Although limited to a single chemical class, comparisons from this analysis are considered valid and accurate based on the carefully controlled setting for the specified study populations and within the total exposures studied.

GOLGA8 increases bulk antisense oligonucleotide uptake and activity in mammalian cells.

Antisense oligonucleotides (ASOs) are short synthetic nucleic acids that recognize and bind to complementary RNA to modulate gene expression. It is well established that single-stranded, phosphorothioate-modified ASOs enter cells independent of carrier molecules, primarily via endocytic pathways, but that only a small portion of internalized ASO is released into the cytosol and/or nucleus, rendering the majority of ASO inaccessible to the targeted RNA. Identifying pathways that can increase the available ASO pool is valuable as a research tool and therapeutically. Here, we conducted a functional genomic screen for ASO activity by engineering GFP splice reporter cells and applying genome-wide CRISPR gene activation. The screen can identify factors that enhance ASO splice modulation activity. Characterization of hit genes uncovered GOLGA8, a largely uncharacterized protein, as a novel positive regulator enhancing ASO activity by ∼2-fold. Bulk ASO uptake is 2- to 5-fold higher in GOLGA8-overexpressing cells where GOLGA8 and ASOs are observed in the same intracellular compartments. We find GOLGA8 is highly localized to the trans-Golgi and readily detectable at the plasma membrane. Interestingly, overexpression of GOLGA8 increased activity for both splice modulation and RNase H1-dependent ASOs. Taken together, these results support a novel role for GOLGA8 in productive ASO uptake.

A multivalent and cross-protective vaccine strategy against arenaviruses associated with human disease.

Arenaviruses are the causative pathogens of severe hemorrhagic fever and aseptic meningitis in humans, for which no licensed vaccines are currently available. Pathogen heterogeneity within the Arenaviridae family poses a significant challenge for vaccine development. The main hypothesis we tested in the present study was whether it is possible to design a universal vaccine strategy capable of inducing simultaneous HLA-restricted CD8+ T cell responses against 7 pathogenic arenaviruses (including the lymphocytic choriomeningitis, Lassa, Guanarito, Junin, Machupo, Sabia, and Whitewater Arroyo viruses), either through the identification of widely conserved epitopes, or by the identification of a collection of epitopes derived from multiple arenavirus species. By inoculating HLA transgenic mice with a panel of recombinant vaccinia viruses (rVACVs) expressing the different arenavirus proteins, we identified 10 HLA-A02 and 10 HLA-A03-restricted epitopes that are naturally processed in human antigen-presenting cells. For some of these epitopes we were able to demonstrate cross-reactive CD8+ T cell responses, further increasing the coverage afforded by the epitope set against each different arenavirus species. Importantly, we showed that immunization of HLA transgenic mice with an epitope cocktail generated simultaneous CD8+ T cell responses against all 7 arenaviruses, and protected mice against challenge with rVACVs expressing either Old or New World arenavirus glycoproteins. In conclusion, the set of identified epitopes allows broad, non-ethnically biased coverage of all 7 viral species targeted by our studies.

Modeling of the water network at protein-RNA interfaces.

Water plays an important role in the mediation of biomolecular interactions. Thus, accurate prediction and evaluation of water-mediated interactions is an important element in the computational design of interfaces involving proteins, RNA, and DNA. Here, we use an algorithm (WATGEN) to predict the locations of interfacial water molecules for a data set of 224 protein-RNA interfaces. The accuracy of the prediction is validated against water molecules present in the X-ray structures of 105 of these complexes. The complexity of the water networks is deconvoluted through definition of the characteristics of each water molecule based on its bridging properties between the protein and RNA and on its depth in the interface with respect to the bulk solvent. This approach has the potential for scoring the water network for incorporation into the computational design of protein-RNA complexes.

Immune epitope database analysis resource (IEDB-AR).

We present a new release of the immune epitope database analysis resource (IEDB-AR, http://tools.immuneepitope.org), a repository of web-based tools for the prediction and analysis of immune epitopes. New functionalities have been added to most of the previously implemented tools, and a total of eight new tools were added, including two B-cell epitope prediction tools, four T-cell epitope prediction tools and two analysis tools.

Immunomic analysis of the repertoire of T-cell specificities for influenza A virus in humans.

Continuing antigenic drift allows influenza viruses to escape antibody-mediated recognition, and as a consequence, the vaccine currently in use needs to be altered annually. Highly conserved epitopes recognized by effector T cells may represent an alternative approach for the generation of a more universal influenza virus vaccine. Relatively few highly conserved epitopes are currently known in humans, and relatively few epitopes have been identified from proteins other than hemagglutinin and nucleoprotein. This prompted us to perform a study aimed at identifying a set of human T-cell epitopes that would provide broad coverage against different virus strains and subtypes. To provide coverage across different ethnicities, seven different HLA supertypes were considered. More than 4,000 peptides were selected from a panel of 23 influenza A virus strains based on predicted high-affinity binding to HLA class I or class II and high conservancy levels. Peripheral blood mononuclear cells from 44 healthy human blood donors were tested for reactivity against HLA-matched peptides by using gamma interferon enzyme-linked immunospot assays. Interestingly, we found that PB1 was the major target for both CD4(+) and CD8(+) T-cell responses. The 54 nonredundant epitopes (38 class I and 16 class II) identified herein provided high coverage among different ethnicities, were conserved in the majority of the strains analyzed, and were consistently recognized in multiple individuals. These results enable further functional studies of T-cell responses during influenza virus infection and provide a potential base for the development of a universal influenza vaccine.

A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus.

The value of predictive algorithms for identifying CD8+ T (T(CD8+))-cell epitopes has not been adequately tested experimentally. Here we demonstrate that conventional bioinformatic methods predict the vast majority of T(CD8+)-cell epitopes derived from vaccinia virus WR strain (VACV-WR) in the H-2(b) mouse model. This approach reveals the breadth of T-cell responses to vaccinia, a widely studied murine viral infection model, and may provide a tool for developing comprehensive antigenic maps of any complex pathogen.

ElliPro: a new structure-based tool for the prediction of antibody epitopes.

BACKGROUND: Reliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes. RESULTS: Here we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at http://tools.immuneepitope.org/tools/ElliPro. CONCLUSION: The results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.

Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines.

BACKGROUND: In an epitope-based vaccine setting, the use of conserved epitopes would be expected to provide broader protection across multiple strains, or even species, than epitopes derived from highly variable genome regions. Conversely, in a diagnostic and disease monitoring setting, epitopes that are specific to a given pathogen strain, for example, can be used to monitor responses to that particular infectious strain. In both cases, concrete information pertaining to the degree of conservancy of the epitope(s) considered is crucial. RESULTS: To assist in the selection of epitopes with the desired degree of conservation, we have developed a new tool to determine the variability of epitopes within a given set of protein sequences. The tool was implemented as a component of the Immune Epitope Database and Analysis Resources (IEDB), and is directly accessible at http://tools.immuneepitope.org/tools/conservancy. CONCLUSION: An epitope conservancy analysis tool was developed to analyze the variability or conservation of epitopes. The tool is user friendly, and is expected to aid in the design of epitope-based vaccines and diagnostics.

A community resource benchmarking predictions of peptide binding to MHC-I molecules.

Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, and chimpanzee MHC class I alleles. We use this data to establish a set of benchmark predictions with one neural network method and two matrix-based prediction methods extensively utilized in our groups. In general, the neural network outperforms the matrix-based predictions mainly due to its ability to generalize even on a small amount of data. We also retrieved predictions from tools publicly available on the internet. While differences in the data used to generate these predictions hamper direct comparisons, we do conclude that tools based on combinatorial peptide libraries perform remarkably well. The transparent prediction evaluation on this dataset provides tool developers with a benchmark for comparison of newly developed prediction methods. In addition, to generate and evaluate our own prediction methods, we have established an easily extensible web-based prediction framework that allows automated side-by-side comparisons of prediction methods implemented by experts. This is an advance over the current practice of tool developers having to generate reference predictions themselves, which can lead to underestimating the performance of prediction methods they are not as familiar with as their own. The overall goal of this effort is to provide a transparent prediction evaluation allowing bioinformaticians to identify promising features of prediction methods and providing guidance to immunologists regarding the reliability of prediction tools.

Predicting population coverage of T-cell epitope-based diagnostics and vaccines.

BACKGROUND: T cells recognize a complex between a specific major histocompatibility complex (MHC) molecule and a particular pathogen-derived epitope. A given epitope will elicit a response only in individuals that express an MHC molecule capable of binding that particular epitope. MHC molecules are extremely polymorphic and over a thousand different human MHC (HLA) alleles are known. A disproportionate amount of MHC polymorphism occurs in positions constituting the peptide-binding region, and as a result, MHC molecules exhibit a widely varying binding specificity. In the design of peptide-based vaccines and diagnostics, the issue of population coverage in relation to MHC polymorphism is further complicated by the fact that different HLA types are expressed at dramatically different frequencies in different ethnicities. Thus, without careful consideration, a vaccine or diagnostic with ethnically biased population coverage could result. RESULTS: To address this issue, an algorithm was developed to calculate, on the basis of HLA genotypic frequencies, the fraction of individuals expected to respond to a given epitope set, diagnostic or vaccine. The population coverage estimates are based on MHC binding and/or T cell restriction data, although the tool can be utilized in a more general fashion. The algorithm was implemented as a web-application available at http://epitope.liai.org:8080/tools/population. CONCLUSION: We have developed a web-based tool to predict population coverage of T-cell epitope-based diagnostics and vaccines based on MHC binding and/or T cell restriction data. Accordingly, epitope-based vaccines or diagnostics can be designed to maximize population coverage, while minimizing complexity (that is, the number of different epitopes included in the diagnostic or vaccine), and also minimizing the variability of coverage obtained or projected in different ethnic groups.

Curation of complex, context-dependent immunological data.

BACKGROUND: The Immune Epitope Database and Analysis Resource (IEDB) is dedicated to capturing, housing and analyzing complex immune epitope related data http://www.immuneepitope.org. DESCRIPTION: To identify and extract relevant data from the scientific literature in an efficient and accurate manner, novel processes were developed for manual and semi-automated annotation. CONCLUSION: Formalized curation strategies enable the processing of a large volume of context-dependent data, which are now available to the scientific community in an accessible and transparent format. The experiences described herein are applicable to other databases housing complex biological data and requiring a high level of curation expertise.

Structural prediction of peptides binding to MHC class I molecules.

Peptide binding to class I major histocompatibility complex (MHCI) molecules is a key step in the immune response and the structural details of this interaction are of importance in the design of peptide vaccines. Algorithms based on primary sequence have had success in predicting potential antigenic peptides for MHCI, but such algorithms have limited accuracy and provide no structural information. Here, we present an algorithm, PePSSI (peptide-MHC prediction of structure through solvated interfaces), for the prediction of peptide structure when bound to the MHCI molecule, HLA-A2. The algorithm combines sampling of peptide backbone conformations and flexible movement of MHC side chains and is unique among other prediction algorithms in its incorporation of explicit water molecules at the peptide-MHC interface. In an initial test of the algorithm, PePSSI was used to predict the conformation of eight peptides bound to HLA-A2, for which X-ray data are available. Comparison of the predicted and X-ray conformations of these peptides gave RMSD values between 1.301 and 2.475 A. Binding conformations of 266 peptides with known binding affinities for HLA-A2 were then predicted using PePSSI. Structural analyses of these peptide-HLA-A2 conformations showed that peptide binding affinity is positively correlated with the number of peptide-MHC contacts and negatively correlated with the number of interfacial water molecules. These results are consistent with the relatively hydrophobic binding nature of the HLA-A2 peptide binding interface. In summary, PePSSI is capable of rapid and accurate prediction of peptide-MHC binding conformations, which may in turn allow estimation of MHCI-peptide binding affinity.

Identification and Validation of PCAT14 as Prognostic Biomarker in Prostate Cancer.

Rapid advances in the discovery of long noncoding RNAs (lncRNAs) have identified lineage- and cancer-specific biomarkers that may be relevant in the clinical management of prostate cancer (PCa). Here we assembled and analyzed a large RNA-seq dataset, from 585 patient samples, including benign prostate tissue and both localized and metastatic PCa to discover and validate differentially expressed genes associated with disease aggressiveness. We performed Sample Set Enrichment Analysis (SSEA) and identified genes associated with low versus high Gleason score in the RNA-seq database. Comparing Gleason 6 versus 9+ PCa samples, we identified 99 differentially expressed genes with variable association to Gleason grade as well as robust expression in prostate cancer. The top-ranked novel lncRNA PCAT14, exhibits both cancer and lineage specificity. On multivariate analysis, low PCAT14 expression independently predicts for BPFS (P=.00126), PSS (P=.0385), and MFS (P=.000609), with trends for OS as well (P=.056). An RNA in-situ hybridization (ISH) assay for PCAT14 distinguished benign vs malignant cases, as well as high vs low Gleason disease. PCAT14 is transcriptionally regulated by AR, and endogenous PCAT14 overexpression suppresses cell invasion. Thus, Using RNA-sequencing data we identify PCAT14, a novel prostate cancer and lineage-specific lncRNA. PCAT14 is highly expressed in low grade disease and loss of PCAT14 predicts for disease aggressiveness and recurrence.

Targeting of repeated sequences unique to a gene results in significant increases in antisense oligonucleotide potency.

A new strategy for identifying potent RNase H-dependent antisense oligonucleotides (ASOs) is presented. Our analysis of the human transcriptome revealed that a significant proportion of genes contain unique repeated sequences of 16 or more nucleotides in length. Activities of ASOs targeting these repeated sites in several representative genes were compared to those of ASOs targeting unique single sites in the same transcript. Antisense activity at repeated sites was also evaluated in a highly controlled minigene system. Targeting both native and minigene repeat sites resulted in significant increases in potency as compared to targeting of non-repeated sites. The increased potency at these sites is a result of increased frequency of ASO/RNA interactions which, in turn, increases the probability of a productive interaction between the ASO/RNA heteroduplex and human RNase H1 in the cell. These results suggest a new, highly efficient strategy for rapid identification of highly potent ASOs.