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Biomedical subjects

Wenzhong Xiao

Publications and source records attributed to Wenzhong Xiao.

At least 19 recordsLinked to original sources

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

Circulating Tumor DNA↗

Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level.

Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification-based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non-small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non-small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.

Carcinoma, Non-Small-Cell Lung↗

KERIS: kaleidoscope of gene responses to inflammation between species.

A cornerstone of modern biomedical research is the use of animal models to study disease mechanisms and to develop new therapeutic approaches. In order to help the research community to better explore the similarities and differences of genomic response between human inflammatory diseases and murine models, we developed KERIS: kaleidoscope of gene responses to inflammation between species (available at http://www.igenomed.org/keris/). As of June 2016, KERIS includes comparisons of the genomic response of six human inflammatory diseases (burns, trauma, infection, sepsis, endotoxin and acute respiratory distress syndrome) and matched mouse models, using 2257 curated samples from the Inflammation and the Host Response to Injury Glue Grant studies and other representative studies in Gene Expression Omnibus. A researcher can browse, query, visualize and compare the response patterns of genes, pathways and functional modules across different diseases and corresponding murine models. The database is expected to help biologists choosing models when studying the mechanisms of particular genes and pathways in a disease and prioritizing the translation of findings from disease models into clinical studies.

Animals↗

The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.

Acute Kidney Injury↗

Cell-specific expression and pathway analyses reveal alterations in trauma-related human T cell and monocyte pathways.

Monitoring genome-wide, cell-specific responses to human disease, although challenging, holds great promise for the future of medicine. Patients with injuries severe enough to develop multiple organ dysfunction syndrome have multiple immune derangements, including T cell apoptosis and anergy combined with depressed monocyte antigen presentation. Genome-wide expression analysis of highly enriched circulating leukocyte subpopulations, combined with cell-specific pathway analyses, offers an opportunity to discover leukocyte regulatory networks in critically injured patients. Severe injury induced significant changes in T cell (5,693 genes), monocyte (2,801 genes), and total leukocyte (3,437 genes) transcriptomes, with only 911 of these genes common to all three cell populations (12%). T cell-specific pathway analyses identified increased gene expression of several inhibitory receptors (PD-1, CD152, NRP-1, and Lag3) and concomitant decreases in stimulatory receptors (CD28, CD4, and IL-2Ralpha). Functional analysis of T cells and monocytes confirmed reduced T cell proliferation and increased cell surface expression of negative signaling receptors paired with decreased monocyte costimulation ligands. Thus, genome-wide expression from highly enriched cell populations combined with knowledge-based pathway analyses leads to the identification of regulatory networks differentially expressed in injured patients. Importantly, application of cell separation, genome-wide expression, and cell-specific pathway analyses can be used to discover pathway alterations in human disease.

Gene Expression Profiling↗

High dynamic range characterization of the trauma patient plasma proteome.

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3,654 different proteins with 1,494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2,910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1,553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.

Blood Proteins↗

Commonality and differences in leukocyte gene expression patterns among three models of inflammation and injury.

The aim of this study was to compare gene expression profiles of leukocytes from blood (white blood cells; WBCs) and spleen harvested at an early time point after injury or sham injury in mice subjected to trauma/hemorrhage, burn injury, or lipopolysaccharide (LPS) infusion at three experimental sites. Groups of injured or LPS-infused animals and sham controls were killed at 2 h after injury and resuscitation, blood and spleen were harvested, and leukocyte populations were recovered after erythrocyte lysis. RNA was extracted from postlysis leukocyte populations. Complementary RNA was synthesized from each RNA sample and hybridized to microarrays. A large number (500-1,400) of genes were differentially expressed at the 2-h time point in injured or LPS-infused vs. sham animals. Thirteen of the differentially expressed genes in blood, and 46 in the spleen, were upregulated or downregulated in common among all three animal models and may represent a common, early transcriptional response to systemic inflammation from a variety of causes. The majority of these genes could be assigned to pathways involved in the immune response and cell death. The up- or downregulation of a cohort of 23 of these genes was validated by RT-PCR. This large-scale microarray analysis shows that, at the 2-h time point, there is marked alteration in leukocyte gene expression in three animal models of injury and inflammation. Although there is some commonality among the models, the majority of the differentially expressed genes appear to be uniquely associated with the type of injury and/or the inflammatory stimulus.

Animals↗

Significance analysis of time course microarray experiments.

Characterizing the genome-wide dynamic regulation of gene expression is important and will be of much interest in the future. However, there is currently no established method for identifying differentially expressed genes in a time course study. Here we propose a significance method for analyzing time course microarray studies that can be applied to the typical types of comparisons and sampling schemes. This method is applied to two studies on humans. In one study, genes are identified that show differential expression over time in response to in vivo endotoxin administration. By using our method, 7,409 genes are called significant at a 1% false-discovery rate level, whereas several existing approaches fail to identify any genes. In another study, 417 genes are identified at a 10% false-discovery rate level that show expression changing with age in the kidney cortex. Here it is also shown that as many as 47% of the genes change with age in a manner more complex than simple exponential growth or decay. The methodology proposed here has been implemented in the freely distributed and open-source edge software package.

Adult↗

A network-based analysis of systemic inflammation in humans.

Oligonucleotide and complementary DNA microarrays are being used to subclassify histologically similar tumours, monitor disease progress, and individualize treatment regimens. However, extracting new biological insight from high-throughput genomic studies of human diseases is a challenge, limited by difficulties in recognizing and evaluating relevant biological processes from huge quantities of experimental data. Here we present a structured network knowledge-base approach to analyse genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes. This approach was used to analyse changes in blood leukocyte gene expression patterns in human subjects receiving an inflammatory stimulus (bacterial endotoxin). We explore the known genome-wide interaction network to identify significant functional modules perturbed in response to this stimulus. Our analysis reveals that the human blood leukocyte response to acute systemic inflammation includes the transient dysregulation of leukocyte bioenergetics and modulation of translational machinery. These findings provide insight into the regulation of global leukocyte activities as they relate to innate immune system tolerance and increased susceptibility to infection in humans.

Acute Disease↗

Application of genome-wide expression analysis to human health and disease.

The application of genome-wide expression analysis to a large-scale, multicentered program in critically ill patients poses a number of theoretical and technical challenges. We describe here an analytical and organizational approach to a systematic evaluation of the variance associated with genome-wide expression analysis specifically tailored to study human disease. We analyzed sources of variance in genome-wide expression analyses performed with commercial oligonucleotide arrays. In addition, variance in gene expression in human blood leukocytes caused by repeated sampling in the same subject, among different healthy subjects, among different leukocyte subpopulations, and the effect of traumatic injury, were also explored. We report that analytical variance caused by sample processing was acceptably small. Blood leukocyte gene expression in the same individual over a 24-h period was remarkably constant. In contrast, genome-wide expression varied significantly among different subjects and leukocyte subpopulations. Expectedly, traumatic injury induced dramatic changes in apparent gene expression that were greater in magnitude than the analytical noise and interindividual variance. We demonstrate that the development of a nation-wide program for gene expression analysis with careful attention to analytical details can reduce the variance in the clinical setting to a level where patterns of gene expression are informative among different healthy human subjects, and can be studied with confidence in human disease.

Cluster Analysis↗

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach.

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.

Blood Proteins↗

Profiling early infection responses: Pseudomonas aeruginosa eludes host defenses by suppressing antimicrobial peptide gene expression.

Insights into the host factors and mechanisms mediating the primary host responses after pathogen presentation remain limited, due in part to the complexity and genetic intractability of host systems. Here, we employ the model Drosophila melanogaster to dissect and identify early host responses that function in the initiation and progression of Pseudomonas aeruginosa pathogenesis. First, we use immune potentiation and genetic studies to demonstrate that flies mount a heightened defense against the highly virulent P. aeruginosa strain PA14 when first inoculated with strain CF5, which is avirulent in flies; this effect is mediated via the Imd and Toll signaling pathways. Second, we use whole-genome expression profiling to assess and compare the Drosophila early defense responses triggered by the PA14 vs. CF5 strains to identify genes whose expression patterns are different in susceptible vs. resistant host-pathogen interactions, respectively. Our results identify pathogenesis- and defense-specific genes and uncover a previously undescribed mechanism used by P. aeruginosa in the initial stages of its host interaction: suppression of Drosophila defense responses by limiting antimicrobial peptide gene expression. These results provide insights into the genetic factors that mediate or restrict pathogenesis during the early stages of the bacterial-host interaction to advance our understanding of P. aeruginosa-human infections.

Animals↗

Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry.

There is significant interest in characterization of the human plasma proteome due to its potential for providing biomarkers applicable to clinical diagnosis and treatment and for gaining a better understanding of human diseases. We describe here a strategy for comparative proteome analyses of human plasma, which is applicable to biomarker identifications for various disease states. Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been applied to make comparative proteome analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Peptide peak areas and the number of peptide identifications for each protein were used to evaluate the reproducibility of LC-MS/MS and to compare relative changes in protein concentration between the samples following LPS treatment. A total of 804 distinct plasma proteins (not including immunoglobulins) were confidently identified with 32 proteins observed to be significantly increased in concentration following LPS administration, including several known inflammatory response or acute-phase mediators such as C-reactive protein, serum amyloid A and A2, LPS-binding protein, LPS-responsive and beige-like anchor protein, hepatocyte growth factor activator, and von Willebrand factor, and thus, constituting potential biomarkers for inflammatory response.

Blood Proteins↗

A transcriptional profile of aging in the human kidney.

In this study, we found 985 genes that change expression in the cortex and the medulla of the kidney with age. Some of the genes whose transcripts increase in abundance with age are known to be specifically expressed in immune cells, suggesting that immune surveillance or inflammation increases with age. The age-regulated genes show a similar aging profile in the cortex and the medulla, suggesting a common underlying mechanism for aging. Expression profiles of these age-regulated genes mark not only age, but also the relative health and physiology of the kidney in older individuals. Finally, the set of aging-regulated kidney genes suggests specific mechanisms and pathways that may play a role in kidney degeneration with age.

Adult↗

Whole blood and leukocyte RNA isolation for gene expression analyses.

The analysis of gene expression data in clinical medicine has been plagued by the lack of a critical evaluation of accepted methodologies for the collection, processing, and labeling of RNA. In the present report, the reliability of two commonly used techniques to isolate RNA from whole blood or its leukocyte compartment was compared by examining their reproducibility, variance, and signal-to-noise ratios. Whole blood was obtained from healthy subjects and was either untreated or stimulated ex vivo with Staphylococcus enterotoxin B (SEB). Blood samples were also obtained from trauma patients but were not stimulated with SEB ex vivo. Total RNA was isolated from whole blood with the PAXgene proprietary blood collection system or from isolated leukocytes. Biotin-labeled cRNA was hybridized to Affymetrix GeneChips. The Pearson correlation coefficient for gene expression measurements in replicates from healthy subjects with both techniques was excellent, exceeding 0.985. Unsupervised analyses, including hierarchical cluster analysis, however, revealed that the RNA isolation method resulted in greater differences in gene expression than stimulation with SEB or among different trauma patients. The intraclass correlation, a measure of signal-to-noise ratio, of the difference between SEB-stimulated and unstimulated blood from healthy subjects was significantly higher in leukocyte-derived samples than in whole blood: 0.75 vs. 0.46 (P = 0.002). At the P < 0.001 level of significance, twice as many probe sets discriminated between SEB-stimulated and unstimulated blood with leukocyte isolation than with PAXgene. The findings suggest that the method of RNA isolation from whole blood is a critical variable in the design of clinical studies using microarray analyses.

Adolescent↗

Integrative analysis of the mitochondrial proteome in yeast.

In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.

Chemical Fractionation↗

Genomic and proteomic determinants of outcome in patients undergoing thoracoabdominal aortic aneurysm repair.

Thoracoabdominal aortic aneurysm repair, with its requisite intraoperative mesenteric ischemia-reperfusion, often results in the development of systemic inflammatory response syndrome, multiorgan dysfunction syndrome (MODS), and death. In the present study, an adverse clinical outcome following thoracoabdominal aortic aneurysm repair was identified by blood leukocyte genomic and plasma proteomic responses. Time-dependent changes in the expression of 146 genes from blood leukocytes were observed (p < 0.001). Expression of 138 genes (p < 0.001) and the concentration of seven plasma proteins discriminated between patients who developed MODS and those who did not, and many of these differences were evident even before surgery. These findings suggest that changes in blood leukocyte gene expression and plasma protein concentrations can illuminate pathophysiological processes that are subsequently associated with the clinical sequelae of systemic inflammatory response syndrome and MODS. These changes in gene expression and plasma protein concentrations are often observed before surgery, consistent with either a genetic predisposition or pre-existing inflammatory state.

Aged↗