Biomedical subjects

Yingdong Zhao

Publications and source records attributed to Yingdong Zhao.

17 recordsLinked to original sources

PubMed2006

Common cancer biomarkers.

There is an increasing interest in complementing conventional histopathologic evaluation with molecular tools that could increase the sensitivity and specificity of cancer staging for diagnostic and prognostic purposes. This study strove to identify cancer-specific markers for the molecular detection of a broad range of cancer types. We used 373 archival samples inclusive of normal tissues of various lineages and benign or malignant tumors (predominantly colon, melanoma, ovarian, and esophageal cancers). All samples were processed identically and cohybridized with an identical reference RNA source to a custom-made cDNA array platform. The database was split into training (n = 201) and comparable prediction (n = 172) sets. Leave-one-out cross-validation and gene pairing analysis identified putative cancer biomarkers overexpressed by malignant lesions independent of tissue of derivation. In particular, seven gene pairs were identified with high predictive power (87%) in segregating malignant from benign lesions. Receiver operator characteristic curves based on the same genes could segregate malignant from benign tissues with 94% accuracy. The relevance of this study rests on the identification of a restricted number of biomarkers ubiquitously expressed by cancers of distinct histology. This has not been done before. These biomarkers could be used broadly to increase the sensitivity and accuracy of cancer staging and early detection of locoregional or systemic recurrence. Their selective expression by cancerous compared with paired normal tissues suggests an association with the oncogenic process resulting in stable expression during disease progression when the presently used differentiation markers are unreliable.

Biomarkers, Tumor↗

PubMed2006

Redundancy in antigen-presenting function of the HLA-DR and -DQ molecules in the multiple sclerosis-associated HLA-DR2 haplotype.

The three HLA class II alleles of the DR2 haplotype, DRB1*1501, DRB5*0101, and DQB1*0602, are in strong linkage disequilibrium and confer most of the genetic risk to multiple sclerosis. Functional redundancy in Ag presentation by these class II molecules would allow recognition by a single TCR of identical peptides with the different restriction elements, facilitating T cell activation and providing one explanation how a disease-associated HLA haplotype could be linked to a CD4+ T cell-mediated autoimmune disease. Using combinatorial peptide libraries and B cell lines expressing single HLA-DR/DQ molecules, we show that two of five in vivo-expanded and likely disease-relevant, cross-reactive cerebrospinal fluid-infiltrating T cell clones use multiple disease-associated HLA class II molecules as restriction elements. One of these T cell clones recognizes >30 identical foreign and human peptides using all DR and DQ molecules of the multiple sclerosis-associated DR2 haplotype. A T cell signaling machinery tuned for efficient responses to weak ligands together with structural features of the TCR-HLA/peptide complex result in this promiscuous HLA class II restriction.

Amino Acid Sequence↗

PubMed2005

Recognition of conserved amino acid motifs of common viruses and its role in autoimmunity.

The triggers of autoimmune diseases such as multiple sclerosis (MS) remain elusive. Epidemiological studies suggest that common pathogens can exacerbate and also induce MS, but it has been difficult to pinpoint individual organisms. Here we demonstrate that in vivo clonally expanded CD4+ T cells isolated from the cerebrospinal fluid of a MS patient during disease exacerbation respond to a poly-arginine motif of the nonpathogenic and ubiquitous Torque Teno virus. These T cell clones also can be stimulated by arginine-enriched protein domains from other common viruses and recognize multiple autoantigens. Our data suggest that repeated infections with common pathogenic and even nonpathogenic viruses could expand T cells specific for conserved protein domains that are able to cross-react with tissue-derived and ubiquitous autoantigens.

Amino Acid Sequence↗

PubMed2005

HLAMatchmaker-driven analysis of responses to HLA-typed platelet transfusions in alloimmunized thrombocytopenic patients.

This study describes a novel application of HLAMatchmaker to determine platelet compatibility in 16 alloimmunized patients with aplastic anemia refractory to random donor platelet transfusions. HLAMatchmaker is a software algorithm that predicts HLA compatibility by identifying immunogenic epitopes represented by amino acid triplets in antibody-accessible regions of human leukocyte antigen (HLA) molecules and determines the number of triplet mismatches (TMMs) and highly immunogenic triplet mismatches (HIMMs). Corrected count increments (CCIs) and molecular HLA typing were available for 523 transfusions. Conventional compatibility assessment based on cross-reactive group (CREG) determination was not predictive of transfusion outcome. Low HIMMs and TMMs numbers were associated with a higher likelihood of satisfactory (CCIs > or = 8) compared with unsatisfactory (CCIs < 8) outcomes (median HIMMs = 4 vs 6, p2 value < .001; median TMMs = 11 vs 13, p2 value < .001). Although receiver operator characteristic curves revealed that HIMMs or TMMs number are not powerful predictors of individual transfusion outcome, a threshold of at least 3 HIMMs or at least 9 TMMs appeared to be associated with successful transfusions. Triplet-matched transfusions were successful, regardless of CREG matching. Our data validate HLAMatchmaker for platelet transfusions and demonstrate its potential to refine and expand donor selection for HLA-alloimmunized patients.

Cross Reactions↗

PubMed2005

High level of cross-reactivity in influenza virus hemagglutinin-specific CD4+ T-cell response: implications for the initiation of autoimmune response in multiple sclerosis.

Viral infections play a role in shaping and maintaining the peripheral T-cell repertoire, as well as in the initiation of autoimmune response via mechanisms of molecular mimicry. In this study, we addressed the flexibility of T-cell receptor (TCR) recognition and the degree of structural and sequence homology required for cross-reactive immune response in the induction of autoimmune response. We studied the extent of cross-reactivity of a CD4+T-cell clone (TCC) specific for the immunodominant influenza virus hemagglutinin (Flu-HA) peptide derived from a patient with multiple sclerosis (MS) using positional scanning synthetic peptide combinatorial libraries (PS-SCL). We documented cross-reactivity against 14 Flu-HA variants, 11 viral, 15 human, and 3 myelin-derived peptides. Moreover, we identified six naturally occurring peptides with higher stimulatory potency than the native ligand, implicating high potential for cross-reactivity even for a virus-specific memory TCC. Our study demonstrates that flexibility of TCR recognition is present even in a clone with a high degree of TCR specificity for an infectious agent. The results have implications for vaccine design and for antigen-specific treatment strategies for autoimmune diseases.

CD4-Positive T-Lymphocytes↗

PubMed2005

An adaptive method for cDNA microarray normalization.

BACKGROUND: Normalization is a critical step in analysis of gene expression profiles. For dual-labeled arrays, global normalization assumes that the majority of the genes on the array are non-differentially expressed between the two channels and that the number of over-expressed genes approximately equals the number of under-expressed genes. These assumptions can be inappropriate for custom arrays or arrays in which the reference RNA is very different from the experimental samples. RESULTS: We propose a mixture model based normalization method that adaptively identifies non-differentially expressed genes and thereby substantially improves normalization for dual-labeled arrays in settings where the assumptions of global normalization are problematic. The new method is evaluated using both simulated and real data. CONCLUSIONS: The new normalization method is effective for general microarray platforms when samples with very different expression profile are co-hybridized and for custom arrays where the majority of genes are likely to be differentially expressed.

Calibration↗

PubMed2004

Selection and validation of endogenous reference genes using a high throughput approach.

BACKGROUND: Endogenous reference genes are commonly used to normalize expression levels of other genes with the assumption that the expression of the former is constant in different tissues and in different physiopathological conditions. Whether this assumption is correct it is, however, still matter of debate. In this study, we searched for stably expressed genes in 384 cDNA array hybridization experiments encompassing different tissues and cell lines. RESULTS: Several genes were identified whose expression was highly stable across all samples studied. The usefulness of 8 genes among them was tested by normalizing the relative gene expression against test genes whose expression pattern was known. The range of accuracy of individual endogenous reference genes was wide whereas consistent information could be obtained when information pooled from different endogenous reference genes was used. CONCLUSIONS: This study suggests that even when the most stably expressed genes in array experiments are used as endogenous reference, significant variation in test gene expression estimates may occur and the best normalization is achieved when data from several endogenous reference genes are pooled together to minimize minimal but significant variation among samples. We are presently optimizing strategies for the preparation of endogenous reference gene mixtures that could yield information comparable to that of data pooled from individual endogenous reference gene normalizations.

Carcinoma↗

PubMed2003

Application of support vector machines for T-cell epitopes prediction.

MOTIVATION: The T-cell receptor, a major histocompatibility complex (MHC) molecule, and a bound antigenic peptide, play major roles in the process of antigen-specific T-cell activation. T-cell recognition was long considered exquisitely specific. Recent data also indicate that it is highly flexible, and one receptor may recognize thousands of different peptides. Deciphering the patterns of peptides that elicit a MHC restricted T-cell response is critical for vaccine development. RESULTS: For the first time we develop a support vector machine (SVM) for T-cell epitope prediction with an MHC type I restricted T-cell clone. Using cross-validation, we demonstrate that SVMs can be trained on relatively small data sets to provide prediction more accurate than those based on previously published methods or on MHC binding. SUPPLEMENTARY INFORMATION: Data for 203 synthesized peptides is available at http://linus.nci.nih.gov/Data/LAU203_Peptide.pdf

Algorithms↗

PubMed2003

A strategy for detection of known and unknown SNP using a minimum number of oligonucleotides applicable in the clinical settings.

Detection of unknown single nucleotide polymorphism (SNP) relies on large scale sequencing expeditions of genomic fragments or complex high-throughput chip technology. We describe a simplified strategy for fluorimetric detection of known and unknown SNP by proportional hybridization to oligonucleotide arrays based on optimization of the established principle of signal loss or gain that requires a drastically reduced number of matched or mismatched probes. The array consists of two sets of 18-mer oligonucleotide probes. One set includes overlapping oligos with 4-nucleotide tiling representing an arbitrarily selected "consensus" sequence (consensus-oligos), the other includes oligos specific for known SNP within the same genomic region (variant-oligos). Fluorescence-labeled DNA amplified from a homozygous source identical to the consensus represents the reference target and is co-hybridized with a differentially-labeled test sample. Lack of hybridization of the test sample to consensus- with simultaneous hybridization to variant-oligos designates a known allele. Lack of hybridization to consensus- and variant-oligos indicates a new allele. Detection of unknown variants in heterozygous samples depends upon fluorimetric analysis of signal intensity based on the principle that homozygous samples generate twice the amount of signal. This method can identify unknown SNP in heterozygous conditions with a sensitivity of 82% and specificity of 90%. This strategy should dramatically increase the efficiency of SNP detection throughout the human genome and will decrease the cost and complexity of applying genomic wide analysis in the context of clinical trials.

Journal Article↗

PubMed2003

Molecular differentiation of high- and moderate-grade human prostate cancer by cDNA microarray analysis.

The prognosis of men with moderate-grade prostate cancer is uncertain. At present, there are few if any reliable molecular markers that can distinguish moderate-grade tumors from those that behave more aggressively. To better understand the molecular basis of human prostate cancer and potentially provide information toward more accurate prognosis, we measured and analyzed gene expression profiles of 13 high- and moderate-grade human prostate tumors using cDNA microarrays. The expression of 136 genes was observed to differ significantly (P < 0.001) between normal prostate and tumors using one-sample t testing and Wilcoxon ranking. Hierarchical clustering of genes demonstrated a relatively similar pattern of differential expression across the tumors. However, importantly, permutation t tests (two-tailed P < 0.001) revealed 21 genes whose expression profiles segregated moderate- and high-grade tumors from each other, which was significantly (P < 0.03) greater than what was expected by chance. These results were compared in silico with prostate cancer profiling efforts performed by other groups, including a meta-analysis of four data sets, which validated many of the dysregulated genes. We suggest that these data provide insight into the molecular nature of clinically aggressive prostate cancer.

Adenocarcinoma↗

PubMed2002

Positional scanning-synthetic peptide library-based analysis of self- and pathogen-derived peptide cross-reactivity with tumor-reactive Melan-A-specific CTL.

Synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) have recently emerged as a useful tool for the analysis of T cell recognition. This includes identification of potentially cross-reactive sequences of self or pathogen origin that could be relevant for the understanding of TCR repertoire selection and maintenance, as well as of the cross-reactive potential of Ag-specific immune responses. In this study, we have analyzed the recognition of sequences retrieved by using a biometric analysis of the data generated by screening a PS-SCL with a tumor-reactive CTL clone specific for an immunodominant peptide from the melanocyte differentiation and tumor-associated Ag Melan-A. We found that 39% of the retrieved peptides were recognized by the CTL clone used for PS-SCL screening. The proportion of peptides recognized was higher among those with both high predicted affinity for the HLA-A2 molecule and high predicted stimulatory score. Interestingly, up to 94% of the retrieved peptides were cross-recognized by other Melan-A-specific CTL. Cross-recognition was at least partially focused, as some peptides were cross-recognized by the majority of CTL. Importantly, stimulation of PBMC from melanoma patients with the most frequently recognized peptides elicited the expansion of heterogeneous CD8(+) T cell populations, one fraction of which cross-recognized Melan-A. Together, these results underline the high predictive value of PS-SCL for the identification of sequences cross-recognized by Ag-specific T cells.

Antigens, Bacterial↗

PubMed2002

Crystal structure of calcineurin-cyclophilin-cyclosporin shows common but distinct recognition of immunophilin-drug complexes.

Calcineurin, a Ca2+/calmodulin-dependent protein phosphatase, is the common target for two immunophilin-immunosuppressant complexes, cyclophilin A-cyclosporin A (CyPA-CsA) and FKBP-FK506. How the two structurally distinct immunophilin-drug complexes bind the same target has remained unknown. We report the crystal structure of calcineurin (CN) in complex with CyPA-CsA at 2.8-A resolution. The CyPA-CsA complex binds to a composite surface formed by the catalytic and regulatory subunits of CN, where the complex of FK506 and its binding protein FKBP also binds. While the majority of the CN residues involved in the binding are common for both immunophilin-immunosuppressant complexes, a significant number of the residues are distinct. Unlike FKBP-FK506, CyPA-CsA interacts with Arg-122 at the active site of CN, implying direct involvement of CyPA-CsA in the regulation of CN catalysis. The simultaneous interaction of CyPA with both the composite surface and the active site of CN suggests that the composite surface may serve as a substrate recognition site responsible for the narrow substrate specificity of CN. The comparison of CyPA-CsA-CN with FKBP-FK506-CN significantly contributes to understanding the molecular basis of regulation of CN activity by the immunophilin-immunosuppressant.

Calcineurin↗

PubMed2002

Findings on T cell specificity revealed by synthetic combinatorial libraries.

Combinatorial libraries and in particular positional scanning synthetic combinatorial libraries (PS-SCL) allow the study of T cell specificity. This is a systematic and unbiased approach that does not require any previous knowledge about the clones to be studied, neither their specificity nor they major histocompatibility complex (MHC) restriction. Two different types of T cell clone ligands can be identified: (1) peptides that do not necessarily correspond to proteins described in the databases, and (2) peptides that are fragments of natural proteins. In this paper, relevant examples of the application of PS-SCL and the deconvolution strategies followed to identify T cell epitopes for clones of known and unknown specificity will be reviewed. Also, important issues like the immunogenicity of such T cell ligands will be discussed.

Animals↗

PubMed2002

Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness.

We amplified RNAs from 63 fine needle aspiration (FNA) samples from 37 s.c. melanoma metastases from 25 patients undergoing immunotherapy for hybridization to a 6108-gene human cDNA chip. By prospectively following the history of the lesions, we could correlate transcript patterns with clinical outcome. Cluster analysis revealed a tight relationship among autologous synchronously sampled tumors compared with unrelated lesions (average Pearson's r = 0.83 and 0.7, respectively, P < 0.0003). As reported previously, two subgroups of metastatic melanoma lesions were identified that, however, had no predictive correlation with clinical outcome. Ranking of gene expression data from pretreatment samples identified approximately 30 genes predictive of clinical response (P < 0.001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition.

Adult↗

PubMed2002

Toward synthetic combinatorial peptide libraries in positional scanning format (PS-SCL)-based identification of CD8+ Tumor-reactive T-Cell Ligands: a comparative analysis of PS-SCL recognition by a single tumor-reactive CD8+ cytolytic T-lymphocyte clone.

The use of synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) has emerged recently as an alternative approach for the identification of peptides recognized by T lymphocytes. The choice of both the PS-SCL used for screening experiments and the method used for data analysis are crucial for implementing this approach. With this aim, we tested the recognition of different PS-SCL by a tyrosinase 368-376-specific CTL clone and analyzed the data obtained with a recently developed biometric data analysis based on a model of independent and additive contribution of individual amino acids to peptide antigen recognition. Mixtures defined with amino acids present at the corresponding positions in the native sequence were among the most active for all of the libraries. Somewhat surprisingly, a higher number of native amino acids were identifiable by using amidated COOH-terminal rather than free COOH-terminal PS-SCL. Also, our data clearly indicate that when using PS-SCL longer than optimal, frame shifts occur frequently and should be taken into account. Biometric analysis of the data obtained with the amidated COOH-terminal nonapeptide library allowed the identification of the native ligand as the sequence with the highest score in a public human protein database. However, the adequacy of the PS-SCL data for the identification for the peptide ligand varied depending on the PS-SCL used. Altogether these results provide insight into the potential of PS-SCL for the identification of CTL-defined tumor-derived antigenic sequences and may significantly implement our ability to interpret the results of these analyses.

Biometry↗

PubMed2002

T-cell epitope prediction with combinatorial peptide libraries.

T cell receptors (TCR) recognize antigenic peptides in complex with the major histocompatibility complex (MHC) molecules and this trimolecular interaction initiates antigen-specific signaling pathways in the responding T lymphocytes. For the study of autoimmune diseases and vaccine development, it is important to identify peptides (epitopes) that can stimulate a given TCR. The use of combinatorial peptide libraries has recently been introduced as a powerful tool for this purpose. A combinatorial library of n-mer peptides is a set of complex mixtures each characterized by one position fixed to be a specified amino acid and all other positions randomized. A given TCR can be fingerprinted by screening a variety of combinatorial libraries using a proliferation assay. Here, we present statistical models for elucidating the recognition profile of a TCR using combinatorial library proliferation assay data and known MHC binding data.

Combinatorial Chemistry Techniques↗

PubMed2002

The feasibility of using fine needle aspiration from primary breast cancers for cDNA microarray analyses.

PURPOSE: Our aims in this pilot study were to determine whether fine needle aspirates (FNAs) provide a sufficient quantity of mRNA for cDNA microarray analysis, produce a set of quality control criteria to accept individual arrays, and determine whether gene expression profiles obtained from FNAs were representative of the source tumor. EXPERIMENTAL DESIGN: Twenty-seven women with breast cancer for treatment with primary surgery had a FNA before and at the time of surgery, and a portion of excised tumor was taken for array analysis. Control experiments were performed using two Ewing's sarcoma xenograft models. mRNA was extracted from the samples and hybridized with the reference (MCF7 cell line) on cDNA microarrays. Statistical methods were applied to identify acceptability criteria for the arrays. RESULTS: Statistical analyses demonstrated that an adequate array could be identified by calculating the SD of the log of fluorescence intensities from the arrays. Using this criterion, only 4 of the 27 patients (15%) had FNA samples suitable for array analysis. Gene expression profiles from the FNAs closely resembled that of the corresponding source tumors and were clearly distinguished from FNAs derived from the xenografts. CONCLUSIONS: SD is a useful quality index for the clinical application of cDNA microarrays. This "proof of principle" study demonstrates that FNAs from primary breast cancers can be used for microarray analysis, although without amplification, it is feasible in only a small proportion of patients. For this to be clinically useful, validated amplification techniques for FNA samples are probably required.

Adult↗