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1.  Ultraspecific and Highly Sensitive Nucleic Acid Detection by Integrating a DNA Catalytic Network with a Label-Free Microcavity 
Nucleic acid detection with label-free biosensors circumvents costly fluorophore functionalization steps associated with conventional assays by utilizing transducers of impressive ultimate detection limits. Despite this technological prowess, molecular recognition at a surface limits the biosensors’ sensitivity, specificity, and reusability. It is therefore imperative to integrate novel molecular approaches with existing label-free transducers to overcome those limitations. Here, we demonstrate this concept by integrating a DNA strand displacement circuit with a micron-scale whispering gallery mode (WGM) microsphere biosensor. The integrated biosensor exhibits at least 25-fold improved nucleic acid sensitivity, and sets a new record for label-free microcavity biosensors by detecting 80 pM (32 fmol) of a 22nt oligomer; this improvement results from the catalytic behavior of the circuit. Furthermore, the integrated sensor exhibits extremely high specificity; single nucleotide variants yield 40- to 100-fold lower signal. Finally, the same physical sensor was demonstrated to alternatingly detect 2 different nucleic acid sequences through 5 cycles of detection, showcasing both its reusability and its versatility.
PMCID: PMC4096343  PMID: 24585636
2.  IFN-γ production in response to in vitro stimulation with collagen type II in rheumatoid arthritis is associated with HLA-DRB1*0401 and HLA-DQ8 
Arthritis Research  1999;2(1):75-84.
IFN-γ was measured in supernatants after in vitro stimulation of peripheral blood mononuclear cells with collagen type II (CII), purified protein derivative or influenza virus. IFN-γ production in response to CII was similar in rheumatoid arthritis (RA) patients and healthy control individuals. The IFN-γ response to purified protein derivative and influenza virus was lower in RA patients, reflecting a general T-cell hyporesponsiveness in RA. After recalculating the response to CII taking this hyporesponsiveness into account the CII response was higher in RA patients, and was associated with human leucocyte antigen (HLA)-DRB1*0401 and HLA-DQA1*0301-DQB1*0302 (HLA-DQ8). Rheumatoid arthritis patients with elevated serum levels of immunoglobulin (Ig)G anti-CII antibodies had lower CII-induced IFN-γ production than patients with low anti-CII levels. The relative increase in CII-reactivity in RA patients as compared with healthy control individuals, and the association of a higher response with RA-associated HLA haplotypes, suggest the existence of a potentially pathogenic cellular reactivity against CII in RA.
Despite much work over past decades, whether antigen-specific immune reactions occur in rheumatoid arthritis (RA) and to what extent such reactions are directed towards joint-specific autoantigens is still questionable. One strong indicator for antigenic involvement in RA is the fact that certain major histocompatibility complex (MHC) class II genotypes [human leucocyte antigen (HLA)-DR4 and HLA-DR1] predispose for the development of the disease [1]. In the present report, collagen type II (CII) was studied as a putative autoantigen on the basis of both clinical and experimental data that show an increased frequency of antibodies to CII in RA patients [2,3,4] and that show that CII can induce experimental arthritis [5].
It is evident from the literature that RA peripheral blood mononuclear cells (PBMCs) respond poorly to antigenic stimulation [6,7,8], and in particular evidence for a partial tolerization to CII has been presented [9]. The strategy of the present work has accordingly been to reinvestigate T-cell reactivity to CII in RA patients, to relate it to the response to commonly used recall antigens and to analyze IFN-γ responses as an alternative to proliferative responses.
To study cellular immune reactivity to CII in patients with RA and in healthy control individuals and to correlate this reactivity to HLA class II genotypes and to the presence of antibodies to CII in serum.
Forty-five patients who met the 1987 American College of Rheumatology classification criteria for RA [10] and 25 healthy control individuals of similar age and sex were included. Twenty-six of these patients who had low levels of anti-CII in serum were randomly chosen, whereas 19 patients with high anti-CII levels were identified by enzyme-linked immunosorbent assay (ELISA)-screening of 400 RA sera.
Heparinized blood was density gradient separated and PBMCs were cultured at 1 × 106/ml in RPMI-10% fetal calf serum with or without antigenic stimulation: native or denatured CII (100 μ g/ml), killed influenza virus (Vaxigrip, Pasteur Mérieux, Lyon, France; diluted 1 : 1000) or purified protein derivative (PPD; 10 μ g/ml). CII was heat-denatured in 56°C for 30 min.
Cell supernatants were collected after 7days and IFN-γ contents were analyzed using ELISA. HLA-DR and HLA-DQ genotyping was performed utilizing a polymerase chain reaction-based technique with sequence-specific oligonucleotide probe hybridization. Nonparametric statistical analyses were utilized throughout the study.
PBMCs from both RA patients and healthy control individuals responded with inteferon-γ production to the same degree to stimulation with native and denatured CII (Fig. 1a), giving median stimulation indexes with native CII of 4.6 for RA patients and 5.4 for healthy control individuals, and with denatured CII of 2.9 for RA patients and 2.6 for healthy control individuals. RA patients with elevated levels of anti-CII had a weaker IFN-γ response to both native and denatured CII than did healthy control individuals (P = 0.02 and 0.04, respectively).
Stimulation with the standard recall antigens PPD and killed influenza virus yielded a median stimulation index with PPD of 10.0 for RA patients and 51.3 for healthy control individuals and with influenza of 12.3 for RA patients and 25.7 for healthy, control individuals. The RA patients displayed markedly lower responsiveness to both PPD and killed influenza virus than did healthy control individuals (Fig. 1b). IFN-γ responses to all antigens were abrogated when coincubating with antibodies blocking MHC class II.
The low response to PPD and killed influenza virus in RA patients relative to that of healthy control individuals reflects a general downregulation of antigen-induced responsiveness of T cells from RA patients [6,7,8]. That no difference between the RA group and the control group was recorded in CII-induced IFN-γ production therefore indicates that there may be an underlying increased responsiveness to CII in RA patients, which is obscured by the general downregulation of T-cell responsiveness in these patients. In order to address this possibility, we calculated the fraction between individual values for the CII-induced IFN-γ production and the PPD-induced and killed influenza virus-induced IFN-γ production, and compared these fractions. A highly significant difference between the RA and healthy control groups was apparent after stimulation with both native CII and denatured CII when expressing the response as a fraction of that with PPD (Fig. 2a). Similar data were obtained using killed influenza virus-stimulated IFN-γ values as the denominator (Fig. 2b).
When comparing the compensated IFN-γ response to denatured CII stimulation between RA patients with different HLA genotypes, highly significant differences were evident, with HLA-DRB1*0401 patients having greater CII responsiveness than patients who lacked this genotype (Fig. 3a). HLA-DQ8 positive patients also displayed a high responsiveness to CII as compared with HLA-DQ8 negative RA patients (Fig. 3b). These associations between the relative T-cell reactivity to denatured CII and HLA class II genotypes were not seen in healthy control individuals. Similar results were achieved using influenza as denominator (P = 0.02 for HLA-DRB1*0401 and P = 0.01 for HLA-DQ8).
No reports have previously systematically taken the general T-cell hyporesponsiveness in RA into account when investigating specific T-cell responses in this disease. In order to address this issue we used the T-cell responses to PPD and killed influenza virus as reference antigens. This was made on the assumption that exposure to these antigens is similar in age-matched and sex-matched groups of RA patients and healthy control individuals. The concept of a general hyporesponsiveness in RA T cells has been documented in several previous reports, in which both nominal antigens [6,7,8] and mitogens [11,12,13] have been used. The fact that a similar functional downregulation in RA PBMCs was obtained with both PPD and killed influenza virus as reference antigens strengthens the validity of our approach.
We identified an association between the IFN-γ response to CII and HLA-DRB1*0401 and HLA-DQ8 in the RA patient group, which is of obvious interest because both these MHC class II alleles have been associated with high responsiveness to CII in transgenic mice that express these human MHC class II molecules [14,15]. There was no association between high anti-CII levels and shared epitope (HLA-DRB1*0401 or HLA-DRB1*0404).
CII, a major autoantigen candidate in RA, can elicit an IFN-γ response in vitro that is associated with HLA-DRB1*0401 and HLA-DQ8 in RA patients. This study, with a partly new methodological approach to a classical problem in RA, has provided some additional support to the notion that CII may be a target autoantigen of importance for a substantial group of RA patients. Continued efforts to identify mechanisms behind the general hyporesponsiveness to antigens in RA, as well as the mechanisms behind the potential partial anergy to CII, may provide us with better opportunities to study the specificity and pathophysiological relevance of anti-CII reactivity in RA.
PMCID: PMC17806  PMID: 11219392
collagen type II; human leucocyte antigen-DR; IFN-γ; rheumatoid arthritis; T cell
3.  Ultra-high resolution HLA genotyping and allele discovery by highly multiplexed cDNA amplicon pyrosequencing 
BMC Genomics  2012;13:378.
High-resolution HLA genotyping is a critical diagnostic and research assay. Current methods rarely achieve unambiguous high-resolution typing without making population-specific frequency inferences due to a lack of locus coverage and difficulty in exon-phase matching. Achieving high-resolution typing is also becoming more challenging with traditional methods as the database of known HLA alleles increases.
We designed a cDNA amplicon-based pyrosequencing method to capture 94% of the HLA class I open-reading-frame with only two amplicons per sample, and an analogous method for class II HLA genes, with a primary focus on sequencing the DRB loci. We present a novel Galaxy server-based analysis workflow for determining genotype. During assay validation, we performed two GS Junior sequencing runs to determine the accuracy of the HLA class I amplicons and DRB amplicon at different levels of multiplexing. When 116 amplicons were multiplexed, we unambiguously resolved 99%of class I alleles to four- or six-digit resolution, as well as 100% unambiguous DRB calls. The second experiment, with 271 multiplexed amplicons, missed some alleles, but generated high-resolution, concordant typing for 93% of class I alleles, and 96% for DRB1 alleles. In a third, preliminary experiment we attempted to sequence novel amplicons for other class II loci with mixed success.
The presented assay is higher-throughput and higher-resolution than existing HLA genotyping methods, and suitable for allele discovery or large cohort sampling. The validated class I and DRB primers successfully generated unambiguously high-resolution genotypes, while further work is needed to validate additional class II genotyping amplicons.
PMCID: PMC3575390  PMID: 22866951
HLA; Genotyping; Roche/454; Pyrosequencing; Galaxy; Tissue typing; Cellular immunity; Multiplexing
4.  Allele Polymorphism and Haplotype Diversity of HLA-A, -B and -DRB1 Loci in Sequence-Based Typing for Chinese Uyghur Ethnic Group 
PLoS ONE  2010;5(11):e13458.
Previous studies indicate that the frequency distributions of HLA alleles and haplotypes vary from one ethnic group to another or between the members of the same ethnic group living in different geographic areas. It is necessary and meaningful to study the high-resolution allelic and haplotypic distributions of HLA loci in different groups.
Methodology/Principal Findings
High-resolution HLA typing for the Uyghur ethnic minority group using polymerase chain reaction-sequence-based-typing method was first reported. HLA-A, -B and -DRB1 allelic distributions were determined in 104 unrelated healthy Uyghur individuals and haplotypic frequencies and linkage disequilibrium parameters for HLA loci were estimated using the maximum-likelihood method. A total of 35 HLA-A, 51 HLA-B and 33 HLA-DRB1 alleles were identified at the four-digit level in the population. High frequency alleles were HLA-A*1101 (13.46%), A*0201 (12.50%), A*0301 (10.10%); HLA-B*5101(8.17%), B*3501(6.73%), B*5001 (6.25%); HLA-DRB1*0701 (16.35%), DRB1*1501 (8.65%) and DRB1*0301 (7.69%). The two-locus haplotypes at the highest frequency were HLA-A*3001-B*1302 (2.88%), A*2402-B*5101 (2.86%); HLA-B*5001-DRB1*0701 (4.14%) and B*0702-DRB1*1501 (3.37%). The three-locus haplotype at the highest frequency was HLA-A*3001-B*1302-DRB1*0701(2.40%). Significantly high linkage disequilibrium was observed in six two-locus haplotypes, with their corresponding relative linkage disequilibrium parameters equal to 1. Neighbor-joining phylogenetic tree between the Uyghur group and other previously reported populations was constructed on the basis of standard genetic distances among the populations calculated using the four-digit sequence-level allelic frequencies at HLA-A, HLA-B and HLA-DRB1 loci. The phylogenetic analyses reveal that the Uyghur group belongs to the northwestern Chinese populations and is most closely related to the Xibe group, and then to Kirgiz, Hui, Mongolian and Northern Han.
The present findings could be useful to elucidate the genetic background of the population and to provide valuable data for HLA matching in clinical bone marrow transplantation, HLA-linked disease-association studies, population genetics, human identification and paternity tests in forensic sciences.
PMCID: PMC2973946  PMID: 21079793
5.  Statistical Resolution of Ambiguous HLA Typing Data 
PLoS Computational Biology  2008;4(2):e1000016.
High-resolution HLA typing plays a central role in many areas of immunology, such as in identifying immunogenetic risk factors for disease, in studying how the genomes of pathogens evolve in response to immune selection pressures, and also in vaccine design, where identification of HLA-restricted epitopes may be used to guide the selection of vaccine immunogens. Perhaps one of the most immediate applications is in direct medical decisions concerning the matching of stem cell transplant donors to unrelated recipients. However, high-resolution HLA typing is frequently unavailable due to its high cost or the inability to re-type historical data. In this paper, we introduce and evaluate a method for statistical, in silico refinement of ambiguous and/or low-resolution HLA data. Our method, which requires an independent, high-resolution training data set drawn from the same population as the data to be refined, uses linkage disequilibrium in HLA haplotypes as well as four-digit allele frequency data to probabilistically refine HLA typings. Central to our approach is the use of haplotype inference. We introduce new methodology to this area, improving upon the Expectation-Maximization (EM)-based approaches currently used within the HLA community. Our improvements are achieved by using a parsimonious parameterization for haplotype distributions and by smoothing the maximum likelihood (ML) solution. These improvements make it possible to scale the refinement to a larger number of alleles and loci in a more computationally efficient and stable manner. We also show how to augment our method in order to incorporate ethnicity information (as HLA allele distributions vary widely according to race/ethnicity as well as geographic area), and demonstrate the potential utility of this experimentally. A tool based on our approach is freely available for research purposes at
Author Summary
At the core of the human adaptive immune response is the train-to-kill mechanism in which specialized immune cells are sensitized to recognize small peptides from foreign sources (e.g., from HIV or bacteria). Following this sensitization, these immune cells are then activated to kill other cells which display this same peptide (and which contain this same foreign peptide). However, in order for sensitization and killing to occur, the foreign peptide must be “paired up” with one of the infected person's other specialized immune molecules—an HLA molecule. The way in which peptides interact with these HLA molecules defines if and how an immune response will be generated. There is a huge repertoire of such HLA molecules, with almost no two people having the same set. Furthermore, a person's HLA type can determine their susceptibility to disease, or the success of a transplant, for example. However, obtaining high quality HLA data for patients is often difficult because of the great cost and specialized laboratories required, or because the data are historical and cannot be retyped with modern methods. Therefore, we introduce a statistical model which can make use of existing high-quality HLA data, to infer higher-quality HLA data from lower-quality data.
PMCID: PMC2289775  PMID: 18392148
6.  High-throughput multiplex HLA genotyping by next-generation sequencing using multi-locus individual tagging 
BMC Genomics  2014;15(1):864.
Unambiguous human leukocyte antigen (HLA) typing is important in transplant matching and disease association studies. High-resolution HLA typing that is not restricted to the peptide-binding region can decrease HLA allele ambiguities. Cost and technology constraints have hampered high-throughput and efficient high resolution unambiguous HLA typing. We have developed a method for HLA genotyping that preserves the very high-resolution that can be obtained by next-generation sequencing (NGS) but also achieves substantially increased efficiency. Unambiguous HLA-A, B, C and DRB1 genotypes can be determined for 96 individuals in a single run of the Illumina MiSeq.
Long-range amplification of full-length HLA genes from four loci was performed in separate polymerase chain reactions (PCR) using primers and PCR conditions that were optimized to reduce co-amplification of other HLA loci. Amplicons from the four HLA loci of each individual were then pooled and subjected to enzymatic library generation. All four loci of an individual were then tagged with one unique index combination. This multi-locus individual tagging (MIT) method combined with NGS enabled the four loci of 96 individuals to be analyzed in a single 500 cycle sequencing paired-end run of the Illumina-MiSeq. The MIT-NGS method generated sequence reads from the four loci were then discriminated using commercially available NGS HLA typing software. Comparison of the MIT-NGS with Sanger sequence-based HLA typing methods showed that all the ambiguities and discordances between the two methods were due to the accuracy of the MIT-NGS method.
The MIT-NGS method enabled accurate, robust and cost effective simultaneous analyses of four HLA loci per sample and produced 6 or 8-digit high-resolution unambiguous phased HLA typing data from 96 individuals in a single NGS run.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-864) contains supplementary material, which is available to authorized users.
PMCID: PMC4196003  PMID: 25283548
HLA; NGS; HLA typing; Illumina MiSeq
7.  High-Throughput High-Resolution Class I HLA Genotyping in East Africa 
PLoS ONE  2010;5(5):e10751.
HLA, the most genetically diverse loci in the human genome, play a crucial role in host-pathogen interaction by mediating innate and adaptive cellular immune responses. A vast number of infectious diseases affect East Africa, including HIV/AIDS, malaria, and tuberculosis, but the HLA genetic diversity in this region remains incompletely described. This is a major obstacle for the design and evaluation of preventive vaccines. Available HLA typing techniques, that provide the 4-digit level resolution needed to interpret immune responses, lack sufficient throughput for large immunoepidemiological studies. Here we present a novel HLA typing assay bridging the gap between high resolution and high throughput. The assay is based on real-time PCR using sequence-specific primers (SSP) and can genotype carriers of the 49 most common East African class I HLA-A, -B, and -C alleles, at the 4-digit level. Using a validation panel of 175 samples from Kampala, Uganda, previously defined by sequence-based typing, the new assay performed with 100% sensitivity and specificity. The assay was also implemented to define the HLA genetic complexity of a previously uncharacterized Tanzanian population, demonstrating its inclusion in the major East African genetic cluster. The availability of genotyping tools with this capacity will be extremely useful in the identification of correlates of immune protection and the evaluation of candidate vaccine efficacy.
PMCID: PMC2873994  PMID: 20505773
8.  An Integrated Tool to Study MHC Region: Accurate SNV Detection and HLA Genes Typing in Human MHC Region Using Targeted High-Throughput Sequencing 
PLoS ONE  2013;8(7):e69388.
The major histocompatibility complex (MHC) is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb) of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community.
PMCID: PMC3722289  PMID: 23894464
9.  Human Leukocyte Antigen Typing Using a Knowledge Base Coupled with a High-Throughput Oligonucleotide Probe Array Analysis 
Human leukocyte antigens (HLA) are important biomarkers because multiple diseases, drug toxicity, and vaccine responses reveal strong HLA associations. Current clinical HLA typing is an elimination process requiring serial testing. We present an alternative in situ synthesized DNA-based microarray method that contains hundreds of thousands of probes representing a complete overlapping set covering 1,610 clinically relevant HLA class I alleles accompanied by computational tools for assigning HLA type to 4-digit resolution. Our proof-of-concept experiment included 21 blood samples, 18 cell lines, and multiple controls. The method is accurate, robust, and amenable to automation. Typing errors were restricted to homozygous samples or those with very closely related alleles from the same locus, but readily resolved by targeted DNA sequencing validation of flagged samples. High-throughput HLA typing technologies that are effective, yet inexpensive, can be used to analyze the world’s populations, benefiting both global public health and personalized health care.
PMCID: PMC4245923  PMID: 25505899
HLA typing; HLA disease association; population typing
10.  Inference of high resolution HLA types using genome-wide RNA or DNA sequencing reads 
BMC Genomics  2014;15(1):325.
Accurate HLA typing at amino acid level (four-digit resolution) is critical in hematopoietic and organ transplantations, pathogenesis studies of autoimmune and infectious diseases, as well as the development of immunoncology therapies. With the rapid adoption of genome-wide sequencing in biomedical research, HLA typing based on transcriptome and whole exome/genome sequencing data becomes increasingly attractive due to its high throughput and convenience. However, unlike targeted amplicon sequencing, genome-wide sequencing often employs a reduced read length and coverage that impose great challenges in resolving the highly homologous HLA alleles. Though several algorithms exist and have been applied to four-digit typing, some deliver low to moderate accuracies, some output ambiguous predictions. Moreover, few methods suit diverse read lengths and depths, and both RNA and DNA sequencing inputs. New algorithms are therefore needed to leverage the accuracy and flexibility of HLA typing at high resolution using genome-wide sequencing data.
We have developed a new algorithm named PHLAT to discover the most probable pair of HLA alleles at four-digit resolution or higher, via a unique integration of a candidate allele selection and a likelihood scoring. Over a comprehensive set of benchmarking data (a total of 768 HLA alleles) from both RNA and DNA sequencing and with a broad range of read lengths and coverage, PHLAT consistently achieves a high accuracy at four-digit (92%-95%) and two-digit resolutions (96%-99%), outcompeting most of the existing methods. It also supports targeted amplicon sequencing data from Illumina Miseq.
PHLAT significantly leverages the accuracy and flexibility of high resolution HLA typing based on genome-wide sequencing data. It may benefit both basic and applied research in immunology and related fields as well as numerous clinical applications.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-325) contains supplementary material, which is available to authorized users.
PMCID: PMC4035057  PMID: 24884790
HLA typing; Transcriptome sequencing; Exome sequencing; Whole genome sequencing; Hematopoietic transplantation; Autoimmune disease; Immunoncology; Human genetics
11.  Prediction of HLA Class II Alleles Using SNPs in an African Population 
PLoS ONE  2012;7(6):e40206.
Despite the importance of the human leukocyte antigen (HLA) gene locus in research and clinical practice, direct HLA typing is laborious and expensive. Furthermore, the analysis requires specialized software and expertise which are unavailable in most developing country settings. Recently, in silico methods have been developed for predicting HLA alleles using single nucleotide polymorphisms (SNPs). However, the utility of these methods in African populations has not been systematically evaluated.
Methodology/Principal Findings
In the present study, we investigate prediction of HLA class II (HLA-DRB1 and HLA-DQB1) alleles using SNPs in the Wolaita population, southern Ethiopia. The subjects comprised 297 Ethiopians with genome-wide SNP data, of whom 188 had also been HLA typed and were used for training and testing the model. The 109 subjects with SNP data alone were used for empirical prediction using the multi-allelic gene prediction method. We evaluated accuracy of the prediction, agreement between predicted and HLA typed alleles, and discriminative ability of the prediction probability supplied by the model. We found that the model predicted intermediate (two-digit) resolution for HLA-DRB1 and HLA-DQB1 alleles at accuracy levels of 96% and 87%, respectively. All measures of performance showed high accuracy and reliability for prediction. The distribution of the majority of HLA alleles in the study was similar to that previously reported for the Oromo and Amhara ethnic groups from Ethiopia.
We demonstrate that HLA class II alleles can be predicted from SNP genotype data with a high level of accuracy at intermediate (two-digit) resolution in an African population. This finding offers new opportunities for HLA studies of disease epidemiology and population genetics in developing countries.
PMCID: PMC3386230  PMID: 22761960
12.  Co-evolution of Human Leukocyte Antigen (HLA) Class I Ligands with Killer-Cell Immunoglobulin-Like Receptors (KIR) in a Genetically Diverse Population of Sub-Saharan Africans 
PLoS Genetics  2013;9(10):e1003938.
Interactions between HLA class I molecules and killer-cell immunoglobulin-like receptors (KIR) control natural killer cell (NK) functions in immunity and reproduction. Encoded by genes on different chromosomes, these polymorphic ligands and receptors correlate highly with disease resistance and susceptibility. Although studied at low-resolution in many populations, high-resolution analysis of combinatorial diversity of HLA class I and KIR is limited to Asian and Amerindian populations with low genetic diversity. At the other end of the spectrum is the West African population investigated here: we studied 235 individuals, including 104 mother-child pairs, from the Ga-Adangbe of Ghana. This population has a rich diversity of 175 KIR variants forming 208 KIR haplotypes, and 81 HLA-A, -B and -C variants forming 190 HLA class I haplotypes. Each individual we studied has a unique compound genotype of HLA class I and KIR, forming 1–14 functional ligand-receptor interactions. Maintaining this exceptionally high polymorphism is balancing selection. The centromeric region of the KIR locus, encoding HLA-C receptors, is highly diverse whereas the telomeric region encoding Bw4-specific KIR3DL1, lacks diversity in Africans. Present in the Ga-Adangbe are high frequencies of Bw4-bearing HLA-B*53:01 and Bw4-lacking HLA-B*35:01, which otherwise are identical. Balancing selection at key residues maintains numerous HLA-B allotypes having and lacking Bw4, and also those of stronger and weaker interaction with LILRB1, a KIR-related receptor. Correspondingly, there is a balance at key residues of KIR3DL1 that modulate its level of cell-surface expression. Thus, capacity to interact with NK cells synergizes with peptide binding diversity to drive HLA-B allele frequency distribution. These features of KIR and HLA are consistent with ongoing co-evolution and selection imposed by a pathogen endemic to West Africa. Because of the prevalence of malaria in the Ga-Adangbe and previous associations of cerebral malaria with HLA-B*53:01 and KIR, Plasmodium falciparum is a candidate pathogen.
Author Summary
Natural killer cells are white blood cells with critical roles in human health that deliver front-line immunity against pathogens and nurture placentation in early pregnancy. Controlling these functions are cell-surface receptors called KIR that interact with HLA class I ligands expressed on most cells of the body. KIR and HLA are both products of complex families of variable genes, but present on separate chromosomes. Many HLA and KIR variants and their combinations associate with resistance to specific infections and pregnancy syndromes. Previously we identified basic components of the system necessary for individual and population survival. Here, we explore the system at its most genetically diverse by studying the Ga-Adangbe population from Ghana in West Africa. Co-evolution of KIR receptors with their HLA targets is ongoing in the Ga-Adangbe, with every one of 235 individuals studied having a unique set of KIR receptors and HLA class I ligands. In addition, one critical combination of receptor and ligand maintains alternative forms that either can or cannot interact with their ‘partner.’ This balance resembles that induced by malfunctioning variants of hemoglobin that confer resistance to malaria, a candidate disease for driving diversity and co-evolution of KIR and HLA class I in the Ga-Adangbe.
PMCID: PMC3814319  PMID: 24204327
13.  In Silico Analysis of Six Known Leishmania major Antigens and In Vitro Evaluation of Specific Epitopes Eliciting HLA-A2 Restricted CD8 T Cell Response 
As a potent CD8+ T cell activator, peptide vaccine has found its way in vaccine development against intracellular infections and cancer, but not against leishmaniasis. The first step toward a peptide vaccine is epitope mapping of different proteins according to the most frequent HLA types in a population.
Methods and Findings
Six Leishmania (L.) major-related candidate antigens (CPB,CPC,LmsTI-1,TSA,LeIF and LPG-3) were screened for potential CD8+ T cell activating 9-mer epitopes presented by HLA-A*0201 (the most frequent HLA-A allele). Online software including SYFPEITHI, BIMAS, EpiJen, Rankpep, nHLApred, NetCTL and Multipred were used. Peptides were selected only if predicted by almost all programs, according to their predictive scores. Pan-A2 presentation of selected peptides was confirmed by NetMHCPan1.1. Selected peptides were pooled in four peptide groups and the immunogenicity was evaluated by in vitro stimulation and intracellular cytokine assay of PBMCs from HLA-A2+ individuals recovered from L. major. HLA-A2− individuals recovered from L. major and HLA-A2+ healthy donors were included as control groups. Individual response of HLA-A2+ recovered volunteers as percent of CD8+/IFN-γ+ T cells after in vitro stimulation against peptide pools II and IV was notably higher than that of HLA-A2− recovered individuals. Based on cutoff scores calculated from the response of HLA-A2− recovered individuals, 31.6% and 13.3% of HLA-A2+ recovered persons responded above cutoff in pools II and IV, respectively. ELISpot and ELISA results confirmed flow cytometry analysis. The response of HLA-A2− recovered individuals against peptide pools I and III was detected similar and even higher than HLA-A2+ recovered individuals.
Using in silico prediction we demonstrated specific response to LmsTI-1 (pool II) and LPG-3- (pool IV) related peptides specifically presented in HLA-A*0201 context. This is among the very few reports mapping L. major epitopes for human HLA types. Studies like this will speed up polytope vaccine idea towards leishmaniasis.
Author Summary
Leishmaniasis is currently a serious health as well as economic problem in underdeveloped and developing countries in Africa, Asia, the Near and Middle East, Central and South America and the Mediterranean region. Cutaneous leishmaniasis is highly endemic in Iran, remarkably in Isfahan, Fars, Khorasan, Khozestan and Kerman provinces. Since effective prevention is not available and current curative therapy is expensive, often poorly tolerated and not always effective, alternative therapies including vaccination against leishmaniasis are of priority to overcome the problem. Although Th1 dominant response is so far considered as a pre-requisite for the immune system to overcome the infection, CD8+ T cell response could also be considered as a potent arm of immune system fighting against intracellular Leishmania. Polytope vaccine strategy may open up a new way in vaccine design against leishmaniasis, since they act as a potent tool to stimulate multi-CD8 T cell responses. Clearly there is a substantial need to evaluate the promising epitopes from different proteins of Leishmania parasite species. Some new immunoinformatic tools are now available to speed up this process, and we have shown here that in silico prediction can effectively evaluate HLA class I-restricted epitopes out of Leishmania proteins.
PMCID: PMC3167772  PMID: 21909442
14.  A real-time PCR assay for the rapid identification of the autoimmune disease-associated allele HLA-DQB1*0602 
Tissue antigens  2009;73(4):335-340.
Many autoimmune diseases share a genetic association with the presence or absence of HLA-DQB1*0602, including type I diabetes, multiple sclerosis, and narcolepsy. High resolution HLA typing to determine the presence of this allele is cumbersome and expensive by currently available techniques. We present a real-time PCR assay for the identification of HLA-DQB1*0602, using sequence-specific primers and probes, that provides rapid and sensitive identification of this allele, involves minimal hands-on time, and provides a major cost savings compared to existing methods. The assay allows the simultaneous determination of both the presence and the number of copies of this allele. Since there is no post-PCR handling, the risk of contamination is avoided. We have validated the assay using 44 blinded and 32 unblinded samples, previously typed by standard techniques, which were identified with 100% accuracy, sensitivity, and specificity. Further, using a narcolepsy cohort of 734 subjects, we demonstrated the robustness of the assay to analyze DNA isolated from buccal swabs, demonstrating the applicability of this assay as an alternative approach to traditional HLA typing methods.
PMCID: PMC3027491  PMID: 19317743
Genotyping; HLA-DQB1*0602; HLA typing; Multiple Sclerosis; Narcolepsy; QPCR-SSPP; Real-time PCR; Systemic Lupus Erythematosus; TaqMan; Type 1 Diabetes Mellitus
15.  Association of HLA-DQB1∗05:02 and DRB1∗16 Alleles with Late-Onset, Nonthymomatous, AChR-Ab-Positive Myasthenia Gravis 
Autoimmune Diseases  2012;2012:541760.
An association of several HLA alleles with myasthenia gravis (MG) has been reported. Aim of this work was to analyze the HLA allele profile in a survey of 76 unselected Italian MG patients and in a subgroup characterized by disease onset after the age of 50 years, absence of thymoma, and presence of antiacetylcholine receptor antibodies. We defined this subgroup by the acronym LOAb. Typing was performed at low resolution for HLA-A, -B, and -DRB1 loci with sequence-specific oligonucleotide probe (PCR-SSO); at high resolution for HLA-DQB1 locus by PCR with sequence-specific primers (PCR-SSPS). HLA allele frequencies were compared with 100 healthy controls. No correlation was observed between MG and the studied HLA class I alleles. On the contrary, a strong positive association was found for the HLA class II alleles DQB1∗05:02 (Pc = 0.00768) and DRB1∗16 (Pc = 0.0211) in the LOAb subgroup (n = 27) of MG patients. Association between DQB1∗05:02 and some subtypes of MG has been previously reported but not in patients with the LOAb characteristics. Therefore, the HLA allele DQB1∗05:02 might be considered as a susceptibility marker for LOAb among Italians.
PMCID: PMC3474207  PMID: 23091703
16.  Ambiguous allele combinations in HLA Class I and Class II sequence-based typing: when precise nucleotide sequencing leads to imprecise allele identification 
Sequence-based typing (SBT) is one of the most comprehensive methods utilized for HLA typing. However, one of the inherent problems with this typing method is the interpretation of ambiguous allele combinations which occur when two or more different allele combinations produce identical sequences. The purpose of this study is to investigate the probability of this occurrence. We performed HLA-A,-B SBT for Exons 2 and 3 on 676 donors. Samples were analyzed with a capillary sequencer. The racial distribution of the donors was as follows: 615-Caucasian, 13-Asian, 23-African American, 17-Hispanic and 8-Unknown. 672 donors were analyzed for HLA-A locus ambiguities and 666 donors were analyzed for HLA-B locus ambiguities. At the HLA-A locus a total of 548 total ambiguous allele combinations were identified (548/1344 = 41%). Most (278/548 = 51%) of these ambiguities were due to the fact that Exon 4 analysis was not performed. At the HLA-B locus 322 total ambiguous allele combinations were found (322/1332 = 24%). The HLA-B*07/08/15/27/35/44 antigens, common in Caucasians, produced a large portion of the ambiguities (279/322 = 87%). A large portion of HLA-A and B ambiguous allele combinations can be addressed by utilizing a group-specific primary amplification approach to produce an unambiguous homozygous sequence. Therefore, although the prevalence of ambiguous allele combinations is high, if the resolution of these ambiguities is clinically warranted, methods exist to compensate for this problem.
PMCID: PMC517951  PMID: 15363110
HLA; Histocompatibility; genotyping
17.  Accurate HLA type inference using a weighted similarity graph 
BMC Bioinformatics  2010;11(Suppl 11):S10.
The human leukocyte antigen system (HLA) contains many highly variable genes. HLA genes play an important role in the human immune system, and HLA gene matching is crucial for the success of human organ transplantations. Numerous studies have demonstrated that variation in HLA genes is associated with many autoimmune, inflammatory and infectious diseases. However, typing HLA genes by serology or PCR is time consuming and expensive, which limits large-scale studies involving HLA genes. Since it is much easier and cheaper to obtain single nucleotide polymorphism (SNP) genotype data, accurate computational algorithms to infer HLA gene types from SNP genotype data are in need. To infer HLA types from SNP genotypes, the first step is to infer SNP haplotypes from genotypes. However, for the same SNP genotype data set, the haplotype configurations inferred by different methods are usually inconsistent, and it is often difficult to decide which one is true.
In this paper, we design an accurate HLA gene type inference algorithm by utilizing SNP genotype data from pedigrees, known HLA gene types of some individuals and the relationship between inferred SNP haplotypes and HLA gene types. Given a set of haplotypes inferred from the genotypes of a population consisting of many pedigrees, the algorithm first constructs a weighted similarity graph based on a new haplotype similarity measure and derives constraint edges from known HLA gene types. Based on the principle that different HLA gene alleles should have different background haplotypes, the algorithm searches for an optimal labeling of all the haplotypes with unknown HLA gene types such that the total weight among the same HLA gene types is maximized. To deal with ambiguous haplotype solutions, we use a genetic algorithm to select haplotype configurations that tend to maximize the same optimization criterion. Our experiments on a previously typed subset of the HapMap data show that the algorithm is highly accurate, achieving an accuracy of 96% for gene HLA-A, 95% for HLA-B, 97% for HLA-C, 84% for HLA-DRB1, 98% for HLA-DQA1 and 97% for HLA-DQB1 in a leave-one-out test.
Our algorithm can infer HLA gene types from neighboring SNP genotype data accurately. Compared with a recent approach on the same input data, our algorithm achieved a higher accuracy. The code of our algorithm is available to the public for free upon request to the corresponding authors.
PMCID: PMC3024871  PMID: 21172045
18.  A novel single cDNA amplicon pyrosequencing method for high-throughput, cost-effective sequence-based HLA class-I genotyping 
Human immunology  2010;71(10):1011-1017.
HLA genotype influences the immune response to pathogens and transplanted tissues; accurate HLA genotyping is critical for clinical and research applications. Sequence-based HLA typing is limited by the cost of Sanger sequencing genomic DNA and resolving cis/trans ambiguities, hindering both studies correlating high-resolution genotype with clinical outcomes, and population-specific allele frequency surveys. We present an assay for sequence-based HLA genotyping by Titanium read length clonal Roche/454 pyrosequencing of a single, universally diagnostic PCR amplicon from HLA class-I cDNA that captures the majority of exons 2, 3 and 4 used for traditional sequence-based typing. The amplicon is predicted to unambiguously resolve 85% of known alleles. A panel of 48 previously HLA-typed samples was assayed with this method, demonstrating 100% non-null allele typing concordance. We show this technique can multiplex at least 768 patients per sequencing run with multiplex identifier sequence bar-coding. Unprecedented typing throughput results from a novel single cDNA-PCR amplicon strategy requiring only one PCR amplification per sample. This method dramatically reduces cost for genotyping of large cohorts.
PMCID: PMC3191540  PMID: 20650293
Pyrosequencing; HLA; sequence-based typing; multiplexing; high-throughput
19.  High Resolution Human Leukocyte Antigen Class I Allele Frequencies and HIV-1 Infection Associations in Chinese Han and Uyghur Cohorts 
PLoS ONE  2012;7(12):e50656.
Host immunogenetic factors such as HLA class I polymorphism are important to HIV-1 infection risk and AIDS progression. Previous studies using high-resolution HLA class I profile data of Chinese populations appeared insufficient to provide information for HIV-1 vaccine development and clinical trial design. Here we reported HLA class I association with HIV-1 susceptibility in a Chinese Han and a Chinese Uyghur cohort.
Methodology/Principal Findings
Our cohort included 327 Han and 161 Uyghur ethnic individuals. Each cohort included HIV-1 seropositive and HIV-1 seronegative subjects. Four-digit HLA class I typing was performed by sequencing-based typing and high-resolution PCR-sequence specific primer. We compared the HLA class I allele and inferred haplotype frequencies between HIV-1 seropositive and seronegative groups. A neighbor-joining tree between our cohorts and other populations was constructed based on allele frequencies of HLA-A and HLA-B loci. We identified 58 HLA-A, 75 HLA-B, and 32 HLA-Cw distinct alleles from our cohort and no novel alleles. The frequency of HLA-B*5201 and A*0301 was significantly higher in the Han HIV-1 negative group. The frequency of HLA-B*5101 was significantly higher in the Uyghur HIV-1 negative group. We observed statistically significant increases in expectation-maximization (EM) algorithm predicted haplotype frequencies of HLA-A*0201-B*5101 in the Uyghur HIV-1 negative group, and of Cw*0304-B*4001 in the Han HIV-1 negative group. The B62s supertype frequency was found to be significantly higher in the Han HIV-1 negative group than in the Han HIV-1 positive group.
At the four-digit level, several HLA class I alleles and haplotypes were associated with lower HIV-1 susceptibility. Homogeneity of HLA class I and Bw4/Bw6 heterozygosity were not associated with HIV-1 susceptibility in our cohort. These observations contribute to the Chinese HLA database and could prove useful in the development of HIV-1 vaccine candidates.
PMCID: PMC3520934  PMID: 23251376
20.  Rapid, scalable and highly automated HLA genotyping using next-generation sequencing: a transition from research to diagnostics 
BMC Genomics  2013;14:221.
Human leukocyte antigen matching at allelic resolution is proven clinically significant in hematopoietic stem cell transplantation, lowering the risk of graft-versus-host disease and mortality. However, due to the ever growing HLA allele database, tissue typing laboratories face substantial challenges. In light of the complexity and the high degree of allelic diversity, it has become increasingly difficult to define the classical transplantation antigens at high-resolution by using well-tried methods. Thus, next-generation sequencing is entering into diagnostic laboratories at the perfect time and serving as a promising tool to overcome intrinsic HLA typing problems. Therefore, we have developed and validated a scalable automated HLA class I and class II typing approach suitable for diagnostic use.
A validation panel of 173 clinical and proficiency testing samples was analysed, demonstrating 100% concordance to the reference method. From a total of 1,273 loci we were able to generate 1,241 (97.3%) initial successful typings. The mean ambiguity reduction for the analysed loci was 93.5%. Allele assignment including intronic sequences showed an improved resolution (99.2%) of non-expressed HLA alleles.
We provide a powerful HLA typing protocol offering a short turnaround time of only two days, a fully integrated workflow and most importantly a high degree of typing reliability. The presented automated assay is flexible and can be scaled by specific primer compilations and the use of different 454 sequencing systems. The workflow was successfully validated according to the policies of the European Federation for Immunogenetics. Next-generation sequencing seems to become one of the new methods in the field of Histocompatibility.
PMCID: PMC3639865  PMID: 23557197
21.  Human leukocyte antigen alleles, genotypes and haplotypes frequencies in renal transplant donors and recipients from West Central India 
Indian Journal of Human Genetics  2013;19(2):219-232.
Human leukocyte antigen (HLA) is comprised of a highly polymorphic set of genes which determines the histocompatibility of organ transplantation. The present study was undertaken to identify HLA class I and class II allele, genotype and haplotype frequencies in renal transplant recipients and donors from West Central India.
HLA typing was carried out using Polymerase Chain Reaction-Sequence Specific Primer in 552 live related and unrelated renal transplant recipients and donors.
The most frequent HLA class I and class II alleles and their frequencies in recipients were HLA-AFNx0101 (0.1685) and AFNx0102 (0.1649), HLA-BFNx0135 (0.1322), and HLA-DR beta 1 (DRB 1)FNx0115 (0.2192), whereas in donors, these were HLA-AFNx0102 (0.1848) and AFNx0101 (0.1667), HLA-BFNx0135 (0.1359), and HLA-DRB1FNx0115 (0.2409). The two-locus haplotype statistical analysis revealed HLA-AFNx0102-B61 as the most common haplotype with the frequency of 0.0487 and 0.0510 in recipients and donors, respectively. Further, among the three locus haplotypes HLA-AFNx0133-BFNx0144-DRB1FNx0107 and HLA-AFNx0102-BFNx0161-DRB1FNx0115 were the most common haplotypes with frequencies 0.0362 and 0.0326, respectively in recipients and 0.0236 and 0.0323, respectively in donors. Genotype frequency revealed a high prevalence of genotype HLA-AFNx0102/AFNx0124 in recipients (0.058) compared to donors (0.0109) whereas low prevalence of HLA-AFNx0101/AFNx0102 in recipients (0.0435) than in donors (0.0797). The phylogenetic and principal component analysis of HLA allele and haplotype frequency distribution revealed genetic similarities of various ethnic groups. Further, case control analysis provides preliminary evidence of association of HLA-A genotype (P < 0.05) with renal failure.
This study will be helpful in suitable donor search besides providing valuable information for population genetics and HLA disease association analysis.
PMCID: PMC3758731  PMID: 24019626
Allele; genotype; haplotype; human leukocyte antigens frequencies; polymorphism; renal transplant
22.  Cost-efficient high-throughput HLA typing by MiSeq amplicon sequencing 
BMC Genomics  2014;15:63.
A close match of the HLA alleles between donor and recipient is an important prerequisite for successful unrelated hematopoietic stem cell transplantation. To increase the chances of finding an unrelated donor, registries recruit many hundred thousands of volunteers each year. Many registries with limited resources have had to find a trade-off between cost and resolution and extent of typing for newly recruited donors in the past. Therefore, we have taken advantage of recent improvements in NGS to develop a workflow for low-cost, high-resolution HLA typing.
We have established a straightforward three-step workflow for high-throughput HLA typing: Exons 2 and 3 of HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 are amplified by PCR on Fluidigm Access Array microfluidic chips. Illumina sequencing adapters and sample specific tags are directly incorporated during PCR. Upon pooling and cleanup, 384 samples are sequenced in a single Illumina MiSeq run. We developed “neXtype” for streamlined data analysis and HLA allele assignment. The workflow was validated with 1140 samples typed at 6 loci. All neXtype results were concordant with the Sanger sequences, demonstrating error-free typing of more than 6000 HLA loci. Current capacity in routine operation is 12,000 samples per week.
The workflow presented proved to be a cost-efficient alternative to Sanger sequencing for high-throughput HLA typing. Despite the focus on cost efficiency, resolution exceeds the current standards of Sanger typing for donor registration.
PMCID: PMC3909933  PMID: 24460756
Human leukocyte antigen; HLA typing; NGS; Dual indexing; 4-primer approach; Amplicon-based sequencing; Fluidigm Access Array; Illumina MiSeq
23.  Signature-Based Small Molecule Screening Identifies Cytosine Arabinoside as an EWS/FLI Modulator in Ewing Sarcoma 
PLoS Medicine  2007;4(4):e122.
The presence of tumor-specific mutations in the cancer genome represents a potential opportunity for pharmacologic intervention to therapeutic benefit. Unfortunately, many classes of oncoproteins (e.g., transcription factors) are not amenable to conventional small-molecule screening. Despite the identification of tumor-specific somatic mutations, most cancer therapy still utilizes nonspecific, cytotoxic drugs. One illustrative example is the treatment of Ewing sarcoma. Although the EWS/FLI oncoprotein, present in the vast majority of Ewing tumors, was characterized over ten years ago, it has never been exploited as a target of therapy. Previously, this target has been intractable to modulation with traditional small-molecule library screening approaches. Here we describe a gene expression–based approach to identify compounds that induce a signature of EWS/FLI attenuation. We hypothesize that screening small-molecule libraries highly enriched for FDA-approved drugs will provide a more rapid path to clinical application.
Methods and Findings
A gene expression signature for the EWS/FLI off state was determined with microarray expression profiling of Ewing sarcoma cell lines with EWS/FLI-directed RNA interference. A small-molecule library enriched for FDA-approved drugs was screened with a high-throughput, ligation-mediated amplification assay with a fluorescent, bead-based detection. Screening identified cytosine arabinoside (ARA-C) as a modulator of EWS/FLI. ARA-C reduced EWS/FLI protein abundance and accordingly diminished cell viability and transformation and abrogated tumor growth in a xenograft model. Given the poor outcomes of many patients with Ewing sarcoma and the well-established ARA-C safety profile, clinical trials testing ARA-C are warranted.
We demonstrate that a gene expression–based approach to small-molecule library screening can identify, for rapid clinical testing, candidate drugs that modulate previously intractable targets. Furthermore, this is a generic approach that can, in principle, be applied to the identification of modulators of any tumor-associated oncoprotein in the rare pediatric malignancies, but also in the more common adult cancers.
Todd Golub and colleagues show that a gene expression-based screen of small-molecule libraries can identify candidate drugs that modulate cancer-associated oncoproteins.
Editors' Summary
Cancer occurs when cells accumulate genetic changes (mutations) that allow them to divide uncontrollably and to travel throughout the body (metastasize). Chemotherapy, a mainstay of cancer treatments, works by killing rapidly dividing cells. Because some normal tissues also contain dividing cells and are therefore sensitive to chemotherapy drugs, it is hard to treat cancer without causing serious side effects. In recent years, however, researchers have identified some of the mutations that drive the growth of cancer cells. This raises the possibility of designing drugs that kill only cancer cells by specifically targeting “oncoproteins” (the abnormal proteins generated by mutations that transform normal cells into cancer cells). Some “targeted” drugs have already reached the clinic, but unfortunately medicinal chemists do not know how to inhibit the function of many classes of oncoproteins with the small organic molecules that make the best medicines. One oncoprotein in this category is EWS/FLI. This contains part of a protein called EWS fused to part of a transcription factor (a protein that controls cell behavior by telling the cell which proteins to make) called FLI. About 80% of patients with Ewing sarcoma (the second commonest childhood cancer of bone and soft tissue) have the mutation responsible for EWS/FLI expression. Localized Ewing sarcoma can be treated with nontargeted chemotherapy (often in combination with surgery and radiotherapy), but treatment for recurrent or metastatic disease remains very poor.
Why Was This Study Done?
Researchers have known for years that EWS/FLI expression drives the development of Ewing sarcoma by activating the expression of target genes needed for tumor formation. However, EWS/FLI has never been exploited as a target for therapy of this cancer—mainly because traditional approaches used to screen libraries of small molecules do not identify compounds that modulate the activity of transcription factors. In this study, the researchers have used a new gene expression–based, high-throughput screening (GE-HTS) approach to identify compounds that modulate the activity of EWS/FLI.
What Did the Researchers Do and Find?
The researchers used a molecular biology technique called microarray expression profiling to define a 14-gene expression signature that differentiates between Ewing sarcoma cells in which the EWS/FLI fusion protein is active and those in which it is inactive. They then used this signature to screen a library of about 1,000 chemicals (many already approved for other clinical uses) in a “ligation-mediated amplification assay.” For this, the researchers grew Ewing sarcoma cells with the test chemicals, extracted RNA from the cells, and generated a DNA copy of the RNA. They then added two short pieces of DNA (probes) specific for each signature gene to the samples. In samples that expressed a given signature gene, both probes bound and were then ligated (joined together) and amplified. Because one of each probe pair also contained a unique “capture sequence,” the signature genes expressed in each sample were finally identified by adding colored fluorescent beads, each linked to DNA complementary to a different capture sequence. The most active modulator of EWS/FLI activity identified by this GE-HTS approach was cytosine arabinoside (ARA-C). At levels achievable in people, this compound reduced the abundance of EWS/FLI protein in and the viability and cancer-like behavior of Ewing sarcoma cells growing in test tubes. ARA-C treatment also slowed the growth of Ewing sarcoma cells transplanted into mice.
What Do These Findings Mean?
These findings identify ARA-C, which is already used to treat children with some forms of leukemia, as a potent modulator of EWS/FLI activity. More laboratory experiments are needed to discover how ARA-C changes the behavior of Ewing sarcoma cells. Nevertheless, given the poor outcomes currently seen in many patients with Ewing sarcoma and the historical reluctance to test new drugs in children, these findings strongly support the initiation of clinical trials of ARA-C in children with Ewing sarcoma. These results also show that the GE-HTS approach is a powerful way to identify candidate drugs able to modulate the activity of some of the oncoproteins (including transcription factors and other previously intractable targets) that drive cancer development.
Additional Information.
Please access these Web sites via the online version of this summary at
Cancerquest from Emory University, provides information on cancer biology (also includes information in Spanish, Chinese and Russian)
The MedlinePlus encyclopedia has pages on Ewing sarcoma
Information for patients and health professionals on Ewing sarcoma is available from the US National Cancer Institute
Cancerbackup offers information for patients and their parents on Ewing sarcoma
Wikipedia has pages on DNA microarrays and expression profiling (note that Wikipedia is a free online encyclopedia that anyone can edit)
PMCID: PMC1851624  PMID: 17425403
24.  Establishment of HLA-DR4 Transgenic Mice for the Identification of CD4+ T Cell Epitopes of Tumor-Associated Antigens 
PLoS ONE  2013;8(12):e84908.
Reports have shown that activation of tumor-specific CD4+ helper T (Th) cells is crucial for effective anti-tumor immunity and identification of Th-cell epitopes is critical for peptide vaccine-based cancer immunotherapy. Although computer algorithms are available to predict peptides with high binding affinity to a specific HLA class II molecule, the ability of those peptides to induce Th-cell responses must be evaluated. We have established HLA-DR4 (HLA-DRA*01:01/HLA-DRB1*04:05) transgenic mice (Tgm), since this HLA-DR allele is most frequent (13.6%) in Japanese population, to evaluate HLA-DR4-restricted Th-cell responses to tumor-associated antigen (TAA)-derived peptides predicted to bind to HLA-DR4. To avoid weak binding between mouse CD4 and HLA-DR4, Tgm were designed to express chimeric HLA-DR4/I-Ed, where I-Ed α1 and β1 domains were replaced with those from HLA-DR4. Th cells isolated from Tgm immunized with adjuvant and HLA-DR4-binding cytomegalovirus-derived peptide proliferated when stimulated with peptide-pulsed HLA-DR4-transduced mouse L cells, indicating chimeric HLA-DR4/I-Ed has equivalent antigen presenting capacity to HLA-DR4. Immunization with CDCA155-78 peptide, a computer algorithm-predicted HLA-DR4-binding peptide derived from TAA CDCA1, successfully induced Th-cell responses in Tgm, while immunization of HLA-DR4-binding Wilms' tumor 1 antigen-derived peptide with identical amino acid sequence to mouse ortholog failed. This was overcome by using peptide-pulsed syngeneic bone marrow-derived dendritic cells (BM-DC) followed by immunization with peptide/CFA booster. BM-DC-based immunization of KIF20A494-517 peptide from another TAA KIF20A, with an almost identical HLA-binding core amino acid sequence to mouse ortholog, successfully induced Th-cell responses in Tgm. Notably, both CDCA155-78 and KIF20A494-517 peptides induced human Th-cell responses in PBMCs from HLA-DR4-positive donors. Finally, an HLA-DR4 binding DEPDC1191-213 peptide from a new TAA DEPDC1 overexpressed in bladder cancer induced strong Th-cell responses both in Tgm and in PBMCs from an HLA-DR4-positive donor. Thus, the HLA-DR4 Tgm combined with computer algorithm was useful for preliminary screening of candidate peptides for vaccination.
PMCID: PMC3875545  PMID: 24386437
25.  Integrating peptides' sequence and energy of contact residues information improves prediction of peptide and HLA-I binding with unknown alleles 
BMC Bioinformatics  2013;14(Suppl 8):S1.
The HLA (human leukocyte antigen) class I is a kind of molecule encoded by a large family of genes and is characteristic of high polymorphism. Now the number of the registered HLA-I molecules has exceeded 3000. Slight differences in the amino acid sequences of HLAs would make them bind to different sets of peptides. In the past decades, although many methods have been proposed to predict the binding between peptides and HLA-I molecules and achieved good performance, most experimental data used by them is limited to the HLAs with a small number of alleles. Thus they are inclined to obtain high prediction accuracy only for data with similar alleles. Because the peptides and HLAs together determine the binding, it's necessary to consider their contribution meanwhile.
By taking into account the features of the peptides sequence and the energy of contact residues, in this paper a method based on the artificial neural network is proposed to predict the binding of peptides and HLA-I even when the HLAs' potential alleles are unknown. Two experiments in the allele-specific and super-type cases are performed respectively to validate our method. In the first case, we collect 14 HLA-A and 14 HLA-B molecules on Bjoern Peters dataset, and compare our method with the ARB, SMM, NetMHC and other 16 online methods. Our method gets the best average AUC (Area under the ROC) value as 0.909. In the second one, we use leave one out cross validation on MHC-peptide binding data that has different alleles but shares the common super-type. Compared to gold standard methods like NetMHC and NetMHCpan, our method again achieves the best average AUC value as 0.847.
Our method achieves satisfactory results. Whenever it's tested on the HLA-I with single definite gene or with super-type gene locus, it gets better classification accuracy. Especially, when the training set is small, our method still works better than the other methods in the comparison. Therefore, we could make a conclusion that by combining the peptides' information, HLAs amino acid residues' interaction information and contact energy, our method really could improve prediction of the peptide HLA-I binding even when there aren't the prior experimental dataset for HLAs with various alleles.
PMCID: PMC3654895  PMID: 23815611

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