Development and validation of a quantitative Proximity Extension Assay instrument with 21 proteins associated with cardiovascular risk (CVD-21).

BACKGROUND: Treatment of cardiovascular diseases (CVD) is a substantial burden to healthcare systems worldwide. New tools are needed to improve precision of treatment by optimizing the balance between efficacy, safety, and cost. We developed a high-throughput multi-marker decision support instrument which simultaneously quantifies proteins associated with CVD. METHODS AND FINDINGS: Candidate proteins independently associated with different clinical outcomes were selected from clinical studies by the screening of 368 circulating biomarkers. We then custom-designed a quantitative PEA-panel with 21 proteins (CVD-21) by including recombinant antigens as calibrator samples for normalization and absolute quantification of the proteins. The utility of the CVD-21 tool was evaluated in plasma samples from a case-control cohort of 4224 patients with chronic coronary syndrome (CCS) using multivariable Cox regression analyses and machine learning techniques. The assays in the CVD-21 tool gave good precision and high sensitivity with lower level of determination (LOD) between 0.03-0.7 pg/ml for five of the biomarkers. The dynamic range for the assays was sufficient to accurately quantify the biomarkers in the validation study except for troponin I, which in the modeling was replaced by high-sensitive cardiac troponin T (hs-TnT). We created seven different multimarker models, including a reference model with NT-proBNP, hs-TnT, GDF-15, IL-6, and cystatin C and one model with only clinical variables, for the comparison of the discriminative value of the CVD-21 tool. All models with biomarkers including hs-TnT provided similar discrimination for all outcomes, e.g. c-index between 0.68-0.86 and outperformed models using only clinical variables. Most important prognostic biomarkers were MMP-12, U-PAR, REN, VEGF-D, FGF-23, TFF3, ADM, and SCF. CONCLUSIONS: The CVD-21 tool is the very first instrument which with PEA simultaneously quantifies 21 proteins with associations to different CVD. Novel pathophysiologic and prognostic information beyond that of established biomarkers were identified by a number of proteins.

Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis.

Understanding the dynamics of the human proteome is crucial for developing biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. The Proximity Extension Assay (PEA) is a technology that translates protein information into actionable knowledge by linking protein-specific antibodies to DNA-encoded tags. In this report we demonstrate how we have combined the unique PEA technology with an innovative and automated sample preparation and high-throughput sequencing readout enabling parallel measurement of nearly 1500 proteins in 96 samples generating close to 150,000 data points per run. This advancement will have a major impact on the discovery of new biomarkers for disease prediction and prognosis and contribute to the development of the rapidly evolving fields of wellness monitoring and precision medicine.

High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer.

Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I-IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.

Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay.

Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.

A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer.

BACKGROUND: Over 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening. METHODS: In the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n = 106), endometrial cancer (n = 74), benign ovarian tumors (n = 150) and healthy population controls (n = 399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n = 280), endometrial cancer (n = 228), women with benign ovarian tumors (n = 76) and healthy controls (n = 57). RESULTS: In the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III-IV with a sensitivity of 0.88 and specificity of 0.92 (AUC = 0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p = 9.56e-22). Also, population controls could be distinguished from ovarian cancer stage III-IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC = 0.89). CONCLUSION: The PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination. FUNDING: The Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.

Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells.

Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell's phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment.

Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability.

Medical research is developing an ever greater need for comprehensive high-quality data generation to realize the promises of personalized health care based on molecular biomarkers. The nucleic acid proximity-based methods proximity ligation and proximity extension assays have, with their dual reporters, shown potential to relieve the shortcomings of antibodies and their inherent cross-reactivity in multiplex protein quantification applications. The aim of the present study was to develop a robust 96-plex immunoassay based on the proximity extension assay (PEA) for improved high throughput detection of protein biomarkers. This was enabled by: (1) a modified design leading to a reduced number of pipetting steps compared to the existing PEA protocol, as well as improved intra-assay precision; (2) a new enzymatic system that uses a hyper-thermostabile enzyme, Pwo, for uniting the two probes allowing for room temperature addition of all reagents and improved the sensitivity; (3) introduction of an inter-plate control and a new normalization procedure leading to improved inter-assay precision (reproducibility). The multiplex proximity extension assay was found to perform well in complex samples, such as serum and plasma, and also in xenografted mice and resuspended dried blood spots, consuming only 1 µL sample per test. All-in-all, the development of the current multiplex technique is a step toward robust high throughput protein marker discovery and research.

Detection of serological biomarkers by proximity extension assay for detection of colorectal neoplasias in symptomatic individuals.

BACKGROUND: Although the potential of biomarkers to aid in early detection of colorectal cancer (CRC) is recognized and numerous biomarker candidates have been reported in the literature, to date only few molecular markers have been approved for daily clinical use. METHODS: In order to improve the translation of biomarkers from the bench to clinical practice we initiated a biomarker study focusing on a novel technique, the proximity extension assay, with multiplexing capability and the possible additive effect obtained from biomarker panels. We performed a screening of 74 different biomarkers in plasma derived from a case-control sample set consisting of symptomatic individuals representing CRC patients, patients with adenoma, patients with non-neoplastic large bowel diseases and healthy individuals. RESULTS: After statistical evaluation we found 12 significant indicators of CRC and the receiver operating characteristic (ROC) curve of Carcinoembryonic antigen (CEA), Transferrin Receptor-1 (TFRC), Macrophage migration inhibitory factor (MIF), Osteopontin (OPN/SPP1) and cancer antigen 242 (CA242) showed additive effect. This biomarker panel identified CRC patients with a sensitivity of 56% at 90% specificity and thus the performance is sufficiently high to further investigate this combination of five proteins as serological biomarkers for detection of CRC. Furthermore, when applying the indicators to identify early-stage CRC a combination of CEA, TFRC and CA242 resulted in a ROC curve with an area under the curve of 0.861. CONCLUSIONS: Five plasma protein biomarkers were found to be potential CRC discriminators and three of these were additionally found to be discriminators of early-stage CRC. These explorative data in symptomatic individuals demonstrates the feasibility of the multiplex proximity extension assay for screening of potential serological protein biomarkers and warrants independent analyses in a larger sample cohort, including asymptomatic individuals, to further validate the performances of our CRC biomarker panel.

Homogeneous antibody-based proximity extension assays provide sensitive and specific detection of low-abundant proteins in human blood.

Convenient and well-performing protein detection methods for a wide range of targets are in great demand for biomedical research and future diagnostics. Assays without the need for washing steps while still unaffected when analyzing complex biological samples are difficult to develop. Herein, we report a well-characterized nucleic acid proximity-based assay using antibodies, called Proximity Extension Assay (PEA), showing good performance in plasma samples. Target-specific antibody pairs are linked to DNA strands that upon simultaneous binding to the target analyte create a real-time PCR amplicon in a proximity-dependent manner enabled by the action of a DNA polymerase. 3'Exonuclease-capable polymerases were found to be clearly superior in sensitivity over non-3'exonuclease ones. A PEA was set up for IL-8 and GDNF in a user-friendly, homogenous assay displaying femtomolar detection sensitivity, good recovery in human plasma, high specificity and up to 5-log dynamic range in 1 µL samples. Furthermore, we have illustrated the use of a macro-molecular crowding matrix in combination with this homogeneous assay to drive target binding for low-affinity antibodies, thereby improving the sensitivity and increasing affinity reagent availability by lowering assay development dependency on high-affinity antibodies. Assay performance was also confirmed for a multiplex version of PEA.

Multiplexed homogeneous proximity ligation assays for high-throughput protein biomarker research in serological material.

A high throughput protein biomarker discovery tool has been developed based on multiplexed proximity ligation assays in a homogeneous format in the sense of no washing steps. The platform consists of four 24-plex panels profiling 74 putative biomarkers with sub-pm sensitivity each consuming only 1 µl of human plasma sample. The system uses either matched monoclonal antibody pairs or the more readily available single batches of affinity purified polyclonal antibodies to generate the target specific reagents by covalently linking with unique nucleic acid sequences. These paired sequences are united by DNA ligation upon simultaneous target binding forming a PCR amplicon. Multiplex proximity ligation assays thereby converts multiple target analytes into real-time PCR amplicons that are individually quantified using microfluidic high capacity qPCR in nano liter volumes. The assay shows excellent specificity, even in multiplex, by its dual recognition feature, its proximity requirement, and most importantly by using unique sequence specific reporter fragments on both antibody-based probes. To illustrate the potential of this protein detection technology, a pilot biomarker research project was performed using biobanked plasma samples for the detection of colorectal cancer using a multivariate signature.

TiArA: a virtual appliance for the analysis of Tiling Array data.

BACKGROUND: Genomic tiling arrays have been described in the scientific literature since 2003, yet there is a shortage of user-friendly applications available for their analysis. METHODOLOGY/PRINCIPAL FINDINGS: Tiling Array Analyzer (TiArA) is a software program that provides a user-friendly graphical interface for the background subtraction, normalization, and summarization of data acquired through the Affymetrix tiling array platform. The background signal is empirically measured using a group of nonspecific probes with varying levels of GC content and normalization is performed to enforce a common dynamic range. CONCLUSIONS/SIGNIFICANCE: TiArA is implemented as a standalone program for Linux systems and is available as a cross-platform virtual machine that will run under most modern operating systems using virtualization software such as Sun VirtualBox or VMware. The software is available as a Debian package or a virtual appliance at http://purl.org/NET/tiara.

Universal influenza DNA vaccine encoding conserved CD4+ T cell epitopes protects against lethal viral challenge in HLA-DR transgenic mice.

The goal of the present study was to design a vaccine that would provide universal protection against infection of humans with diverse influenza A viruses. Accordingly, protein sequences from influenza A virus strains currently in circulation (H1N1, H3N2), agents of past pandemics (H1N1, H2N2, H3N2) and zoonotic infections of man (H1N1, H5N1, H7N2, H7N3, H7N7, H9N2) were evaluated for the presence of amino acid sequences, motifs, that are predicted to mediate peptide epitope binding with high affinity to the most frequent HLA-DR allelic products. Peptides conserved among diverse influenza strains were then synthesized, evaluated for binding to purified HLA-DR molecules and for their capacity to induce influenza-specific immune recall responses using human donor peripheral blood mononuclear cells (PBMC). Accordingly, 20 epitopes were selected for further investigation based on their conservancy among diverse influenza strains, predicted population coverage in diverse ethnic groups and capacity to recall influenza-specific responses. A DNA plasmid encoding the epitopes was constructed using amino acid spacers between epitopes to promote optimum processing and presentation. Immunogenicity of the DNA vaccine was measured using HLA-DR4 transgenic mice and the TriGrid in vivo electroporation device. Vaccination resulted in peptide-specific immune responses, augmented HA-specific antibody responses and protection of HLA-DR4 transgenic mice from lethal PR8 influenza virus challenge. These studies demonstrate the utility of this vaccine format and the contribution of CD4(+) T cell responses to protection against influenza infection.

Definition of epitopes and antigens recognized by vaccinia specific immune responses: their conservation in variola virus sequences, and use as a model system to study complex pathogens.

In the last few years, a wealth of information has become available relating to the targets of vaccinia virus (VACV)-specific CD4(+) T cell, CD8(+) T cell and antibody responses. Due to the large size of its genome, encoding more than 200 different proteins, VACV represents a useful model system to study immunity to complex pathogens. Our data demonstrate that both cellular and humoral responses target a large number of antigens and epitopes. This broad spectrum of targets is detected in both mice and humans. CD4(+) T cell responses target late and structural antigens, while CD8(+) T cells preferentially recognize early antigens. While both CD4(+) and CD8(+) T cell responses target different types of antigens, the antigens recognized by T(H) cells are highly correlated with those recognized by antibody responses. We further show that protein abundance and antibody recognition can be used to predict antigens recognized by CD4(+) T cell responses, while early expression at the mRNA level predicts antigens targeted by CD8(+) T cells. Finally, we find that the vast majority of VACV epitopes are conserved in variola virus (VARV), thus suggesting that the epitopes defined herein also have relevance for the efficacy of VACV as a smallpox vaccine.

Of mice and humans: how good are HLA transgenic mice as a model of human immune responses?

BACKGROUND: Previous studies have defined vaccinia virus (VACV)-derived T cell epitopes in VACV-infected human leukocyte antigen-A*0201 (HLA-A2.1) transgenic (Tg) mice and A2.1-positive human Dryvax vaccinees. A total of 14 epitopes were detected in humans and 16 epitopes in A2.1 Tg mice; however, only two epitopes were independently reported in both systems. This limited overlap raised questions about the suitability of using HLA Tg mice as a model system to map human T cell responses to a complex viral pathogen. The present study was designed to investigate this issue in more detail. RESULTS: Re-screening the panel of 28 A2.1-restricted epitopes in additional human vaccinees and in A2.1 Tg mice revealed that out of the 28 identified epitopes, 13 were detectable in both systems, corresponding to a 46% concordance rate. Interestingly, the magnitude of responses in Tg mice against epitopes originally identified in humans is lower than for epitopes originally detected in mice. Likewise, responses in humans against epitopes originally detected in Tg mice are of lower magnitude. CONCLUSION: These data suggest that differences in immunodominance patterns might explain the incomplete response overlap, and that with limitations; HLA Tg mice represent a relevant and suitable model system to study immune responses against complex pathogens.

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.

Kinetic analysis of a complete poxvirus transcriptome reveals an immediate-early class of genes.

Vaccinia virus is the prototypic orthopoxvirus and was the vaccine used to eradicate smallpox, yet the expression profiles of many of its genes remain unknown. Using a genome tiling array approach, we simultaneously measured the expression levels of all 223 annotated vaccinia virus genes during infection and determined their kinetics. For 95% of these genes, significant transcript levels were detected. Most remarkably, classification of the genes by their expression profiles revealed 35 genes exhibiting immediate-early expression. Although a similar kinetic class has been described for other virus families, to our knowledge, this is the first demonstration of its existence in orthopoxviruses. Despite expression levels higher than for genes in the other three kinetic classes, the functions of more than half of these remain unknown. Additionally, genes within each kinetic class were spatially grouped together in the genome. This genome-wide picture of transcription alters our understanding of how orthopoxviruses regulate gene expression.

Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries.

BACKGROUND: It has been previously shown that combinatorial peptide libraries are a useful tool to characterize the binding specificity of class I MHC molecules. Compared to other methodologies, such as pool sequencing or measuring the affinities of individual peptides, utilizing positional scanning combinatorial libraries provides a baseline characterization of MHC molecular specificity that is cost effective, quantitative and unbiased. RESULTS: Here, we present a large-scale application of this technology to 19 different human and mouse class I alleles. These include very well characterized alleles (e.g. HLA A*0201), alleles with little previous data available (e.g. HLA A*3201), and alleles with conflicting previous reports on specificity (e.g. HLA A*3001). For all alleles, the positional scanning combinatorial libraries were able to elucidate distinct binding patterns defined with a uniform approach, which we make available here. We introduce a heuristic method to translate this data into classical definitions of main and secondary anchor positions and their preferred residues. Finally, we validate that these matrices can be used to identify candidate MHC binding peptides and T cell epitopes in the vaccinia virus and influenza virus systems, respectively. CONCLUSION: These data confirm, on a large scale, including 15 human and 4 mouse class I alleles, the efficacy of the positional scanning combinatorial library approach for describing MHC class I binding specificity and identifying high affinity binding peptides. These libraries were shown to be useful for identifying specific primary and secondary anchor positions, and thereby simpler motifs, analogous to those described by other approaches. The present study also provides matrices useful for predicting high affinity binders for several alleles for which detailed quantitative descriptions of binding specificity were previously unavailable, including A*3001, A*3201, B*0801, B*1501 and B*1503.

A quantitative analysis of the variables affecting the repertoire of T cell specificities recognized after vaccinia virus infection.

Many components contribute to immunodominance in the response to a complex virus, but their relative importance is unclear. This was addressed using vaccinia virus and HLA-A*0201 as the model system. A comprehensive analysis of 18 viral proteins recognized by CD8(+) T cell responses demonstrated that approximately one-fortieth of all possible 9- to 10-mer peptides were high-affinity HLA-A*0201 binders. Peptide immunization and T cell recognition data generated from 90 peptides indicated that about one-half of the binders were capable of eliciting T cell responses, and that one-seventh of immunogenic peptides are generated by natural processing. Based on these results, we estimate that vaccinia virus encodes approximately 150 dominant and subdominant epitopes restricted in by HLA-A*0201. However, of all these potential epitopes, only 15 are immunodominant and actually recognized in vivo during vaccinia virus infection of HLA-A*0201 transgenic mice. Neither peptide-binding affinity, nor complex stability, nor TCR avidity, nor amount of processed epitope appeared to strictly correlate with immunodominance status. Additional experiments suggested that vaccinia infection impairs the development of responses directed against subdominant epitopes. This suggested that additional factors, including immunoregulatory mechanisms, restrict the repertoire of T cell specificities after vaccinia infection by a factor of at least 10.

Severe defect in thymic development in an insertional mutant mouse model.

Transgenic mice were generated expressing NK1.1, an NK cell-associated receptor, under control of the human CD2 promoter. Unexpectedly, one of the founder lines, Tg66, showed a marked defect in thymic development characterized by disorganized architecture and small size. Mapping of the transgene insertion by fluorescence in situ hybridization revealed integration in chromosome 2, band G. Already from postnatal day 3, the thymic architecture was disturbed with a preferential loss of cortical thymic epithelial cells, a feature that became more pronounced over time. Compared with wild-type mice, total thymic cell numbers decreased dramatically between 10 and 20 days of age. Thymocytes isolated from adult Tg66 mice were predominantly immature double-negative cells, indicating a block in thymic development at an early stage of differentiation. Consequently, Tg66 mice had reduced numbers of peripheral CD4(+) and CD8(+) T cells. Bone marrow from Tg66 mice readily reconstituted thymi of irradiated wild-type as well as RAG-deficient mice. This indicates that the primary defect in Tg66 mice resided in nonhemopoietic stromal cells of the thymus. The phenotype is observed in mice heterozygous for the insertion and does not resemble any known mutations affecting thymic development. Preliminary studies in mice homozygous for transgene insertion reveal a more accelerated and pronounced phenotype suggesting a semidominant effect. The Tg66 mice may serve as a useful model to identify genes regulating thymic epithelial cell differentiation, thymic development, and function.

Ab and T cell epitopes of influenza A virus, knowledge and opportunities.

The Immune Epitope Database and Analysis Resources (IEDB) (www.immuneepitope.org) was recently developed to capture epitope related data. IEDB also hosts various bioinformatics tools that can be used to identify novel epitopes as well as to analyze and visualize existing epitope data. Herein, a comprehensive analysis was undertaken (i) to compile and inventory existing knowledge regarding influenza A epitopes and (ii) to determine possible cross-reactivities of identified epitopes among avian H5N1 and human influenza strains. At present, IEDB contains >600 different epitopes derived from 58 different strains and 10 influenza A proteins. By using the IEDB analysis resources, conservancy analyses were performed, and several conserved and possibly cross-reactive epitopes were identified. Significant gaps in the current knowledge were also revealed, including paucity of Ab epitopes in comparison with T cell epitopes, limited number of epitopes reported for avian influenza strains/subtypes, and limited number of epitopes reported from proteins other than hemagglutinin and nucleoprotein. This analysis provides a resource for researchers to access existing influenza epitope data. At the same time, the analysis illustrates gaps in our collective knowledge that should inspire directions for further study of immunity against the influenza A virus.