Xiaogang Wu

Peking University

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Jianhua Zhang

The University of Texas MD Anderson Cancer Center

P. Andrew Futreal

The University of Texas MD Anderson Cancer Center

Jennifer A. Wargo

The University of Texas MD Anderson Cancer Center

Nadim J. Ajami

Baylor College of Medicine

Tatiana V. Karpinets

The University of Texas MD Anderson Cancer Center

Lauren E. Colbert

The University of Texas MD Anderson Cancer Center

Ann H. Klopp

The University of Texas MD Anderson Cancer Center

Julie M. Simon

The University of Texas MD Anderson Cancer Center

Jake Y. Chen

Huashan Hospital

Carrie R. Daniel

The University of Texas MD Anderson Cancer Center

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The University of Texas MD Anderson Cancer Center

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The University of Texas Health Science Center at Houston

Chinese Academy of Sciences

Baylor College of Medicine

Harvard University

Peking University

Huazhong University of Science and Technology

University of Nevada, Las Vegas

Scripps MD Anderson Cancer Center

University of California, San Francisco

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Genome-wide Profiling of Urinary Extracellular Vesicle microRNAs Associated With Diabetic Nephropathy in Type 1 Diabetes

Kidney International Reports (2017)

Vikas Ghai Xiaogang Wu Anjalei Bheda-Malge Christos Argyropoulos José F. Bernardo

IntroductionDiabetic nephropathy (DN) is a form of progressive kidney disease that often leads to end-stage renal disease (ESRD). It is initiated by microvascular complications due to diabetes. Although microalbuminuria (MA) is the earliest clinical indication of DN among patients with type 1 diabetes (T1D), it lacks the sensitivity and specificity to detect the early onset of DN. Recently, microRNAs (miRNAs) have emerged as critical regulators in diabetes as well as various forms of kidney disease, including renal fibrosis, acute kidney injury, and progressive kidney disease. Additionally, circulating extracellular miRNAs, especially miRNAs packaged in extracellular vesicles (EVs), have garnered significant attention as potential noninvasive biomarkers for various diseases and health conditions.MethodsAs part of the University of Pittsburgh Epidemiology of Diabetes Complications (EDC) study, urine was collected from individuals with T1D with various grades of DN or MA (normal, overt, intermittent, and persistent) over a decade at prespecified intervals. We isolated EVs from urine and analyzed the small-RNA using NextGen sequencing.ResultsWe identified a set of miRNAs that are enriched in urinary EVs compared with EV-depleted samples, and identified a number of miRNAs showing concentration changes associated with DN occurrence, MA status, and other variables, such as hemoglobin A1c levels.ConclusionMany of the miRNAs associated with DN occurrence or MA status directly target pathways associated with renal fibrosis (including transforming growth factor-β and phosphatase and tensin homolog), which is one of the major contributors to the pathology of DN. These miRNAs are potential biomarkers for DN and MA.

Extracellular Vesicles

Extracellular vesicles

10.1016/j.ekir.2017.11.019

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Somatic Mutations in TP53 Identified in T-Cells of Patients with TP53-mutated AML

Blood (2022)

Ghayas C. Issa Aram Bidikian Edward Ayoub Feng Wang Vakul Mohanty

10.1182/blood-2022-165439

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A new approach to construct pathway connected networks and its application in dose responsive gene expression profiles of rat liver regulated by 2,4DNT

Publisher (2010)

Sudhir Chowbina Youping Deng Junmei Ai Xiaogang Wu Xin‐Yuan Guan

Military and industrial activities have lead to reported release of 2,4-dinitrotoluene (2,4DNT) into soil, groundwater or surface water. It has been reported that 2,4DNT can induce toxic effects on humans and other organisms. However the mechanism of 2,4DNT induced toxicity is still unclear. Although a series of methods for gene network construction have been developed, few instances of applying such technology to generate pathway connected networks have been reported. Microarray analyses were conducted using liver tissue of rats collected 24h after exposure to a single oral gavage with one of five concentrations of 2,4DNT. We observed a strong dose response of differentially expressed genes after 2,4DNT treatment. The most affected pathways included: long term depression, breast cancer regulation by stathmin1, WNT Signaling; and PI3K signaling pathways. In addition, we propose a new approach to construct pathway connected networks regulated by 2,4DNT. We also observed clear dose response pathway networks regulated by 2,4DNT. We developed a new method for constructing pathway connected networks. This new method was successfully applied to microarray data from liver tissue of 2,4DNT exposed animals and resulted in the identification of unique dose responsive biomarkers in regards to affected pathways.

Biological pathway

Liver toxicity

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Data from Obesity Is Associated with Altered Tumor Metabolism in Metastatic Melanoma

Andrew W. Hahn Ashley V. Menk Dayana B. Rivadeneira Ryan C. Augustin Mingchu Xu

<div>AbstractPurpose:Overweight/obese (OW/OB) patients with metastatic melanoma unexpectedly have improved outcomes with immune checkpoint inhibitors (ICI) and BRAF-targeted therapies. The mechanism(s) underlying this association remain unclear, thus we assessed the integrated molecular, metabolic, and immune profile of tumors, as well as gut microbiome features, for associations with patient body mass index (BMI).Experimental Design:Associations between BMI [normal (NL < 25) or OW/OB (BMI ≥ 25)] and tumor or microbiome characteristics were examined in specimens from 782 patients with metastatic melanoma across 7 cohorts. DNA associations were evaluated in The Cancer Genome Atlas cohort. RNA sequencing from 4 cohorts (n = 357) was batch corrected and gene set enrichment analysis (GSEA) by BMI category was performed. Metabolic profiling was conducted in a subset of patients (x = 36) by LC/MS, and in flow-sorted melanoma tumor cells (x = 37) and patient-derived melanoma cell lines (x = 17) using the Seahorse XF assay. Gut microbiome features were examined in an independent cohort (n = 371).Results:DNA mutations and copy number variations were not associated with BMI. GSEA demonstrated that tumors from OW/OB patients were metabolically quiescent, with downregulation of oxidative phosphorylation and multiple other metabolic pathways. Direct metabolite analysis and functional metabolic profiling confirmed decreased central carbon metabolism in OW/OB metastatic melanoma tumors and patient-derived cell lines. The overall structure, diversity, and taxonomy of the fecal microbiome did not differ by BMI.Conclusions:These findings suggest that the host metabolic phenotype influences melanoma metabolism and provide insight into the improved outcomes observed in OW/OB patients with metastatic melanoma treated with ICIs and targeted therapies.<a href="https://aacrjournals.org/clincancerres/article/doi/10.1158/1078-0432.CCR-22-3028" target="_blank">See related commentary by Smalley, p. 5</a></div>

10.1158/1078-0432.c.6532803.v1

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Supplementary Figure S7 from Obesity Is Associated with Altered Tumor Metabolism in Metastatic Melanoma

Andrew W. Hahn Ashley V. Menk Dayana B. Rivadeneira Ryan C. Augustin Mingchu Xu

Beta-diversity analysis stratified by sex based on Bray-Curtis dissimilarity represents microbiome samples with metastatic melanoma in terms of the two top principal components (explaining around 17% of variance) obtained from the principal coordinate analysis. Red dots are from overweight/obese (OW/OB) BMI patients, and blue dots are from normal (NL) BMI patients. Shading inside the dots indicates the female gender. This is a subgroup analysis of Figure 5B.

10.1158/1078-0432.22488750

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Supplementary Tables 1 and 6-8 from Obesity Is Associated with Altered Tumor Metabolism in Metastatic Melanoma

Andrew W. Hahn Ashley V. Menk Dayana B. Rivadeneira Ryan C. Augustin Mingchu Xu

Supplementary Table 1: Baseline characteristics for patients included in the integrated gene set enrichment analysis (Figure 2-3) by cohort; Supplementary Table 6: The most frequent somatic alterations (alts) in patients with regionally metastatic melanoma by body mass index from The Cancer Genome Atlas cohort; Supplemental Table 7: Integrated gene set enrichment analysis for pathways associated with fatty acid metabolism by body mass index; Supplemental Table 8: Gene expression of selected genes of interest involved in fatty acid metabolism.

Fatty Acid Metabolism

10.1158/1078-0432.22488729

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Effect of La Doping on Kinetic and Thermodynamic Performances of Ti_1.2CrMn Alloy upon De/Hydrogenation

ACS Omega (2022)

Hanbing Zhang Jichao� Ye Xiaogang Wu Xinwei Hu Huazhou Hu

Development of efficient hydrogen storage materials is one of the great challenges in the area of hydrogen energy and fuel cells. Herein, a La-doped Ti1.2CrMn alloy with high hydriding capacity (2.1 wt % H) and dehydriding capacity (1.8 wt % H) was successfully developed. The crystallographic characteristics, microstructural evolution, and hydrogen storage mechanisms of the alloy were investigated systematically. It was found that the introduction of La increased the cell volume of alloy and thus improved the hydrogenation kinetic, practical hydrogenation capacity, and cyclic property. The hydrogenation kinetic results of the La-doped alloy indicate that it exhibited a higher hydrogenation rate than that of the La-free alloy. It is ascribed to the formation of LaH3, which provides a fast diffusion channel for hydrogen atoms to enter the alloy matrix. The dehydrogenation enthalpy (ΔH) of the La-doped alloy was calculated by the van't Hoff equation and PCT curves to be ∼18.2 kJ/mol. The cycle test proves that the La-doped Ti1.2CrMn alloy, due to La addition, reduces the lattice expansion and lattice stress and exhibits excellent durability.

10.1021/acsomega.2c03367

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Additional file 2: Table S2. of Prior infection with Type A Francisella tularensis antagonizes the pulmonary transcriptional response to an aerosolized Toll-like receptor 4 agonist

Figshare (2015)

Kathie‐Anne Walters Rachael Olsufka Rolf Kuestner Xiaogang Wu Kai Wang

LPS-responsive genes partially suppressed by FT SchuS4. (XLSX 20Â kb)

Tularemia

Aerosolization

Table (database)

10.6084/m9.figshare.c.3640820_d3

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Reordering based integrative expression profiling for microarray classification

BMC Bioinformatics (2012)

Xiaogang Wu Hui Huang Madhankumar Sonachalam Sina Reinhard Jeffrey D. Shen

Current network-based microarray analysis uses the information of interactions among concerned genes/gene products, but still considers each gene expression individually. We propose an organized knowledge-supervised approach - Integrative eXpression Profiling (IXP), to improve microarray classification accuracy, and help discover groups of genes that have been too weak to detect individually by traditional ways. To implement IXP, ant colony optimization reordering (ACOR) algorithm is used to group functionally related genes in an ordered way.Using Alzheimer's disease (AD) as an example, we demonstrate how to apply ACOR-based IXP approach into microarray classifications. Using a microarray dataset - GSE1297 with 31 samples as training set, the result for the blinded classification on another microarray dataset - GSE5281 with 151 samples, shows that our approach can improve accuracy from 74.83% to 82.78%. A recently-published 1372-probe signature for AD can only achieve 61.59% accuracy in the same condition. The ACOR-based IXP approach also has better performance than the IXP approach based on classic network ranking, graph clustering, and random-ordering methods in an overall classification performance comparison.The ACOR-based IXP approach can serve as a knowledge-supervised feature transformation approach to increase classification accuracy dramatically, by transforming each gene expression profile to an integrated expression files as features inputting into standard classifiers. The IXP approach integrates both gene expression information and organized knowledge - disease gene/protein network topology information, which is represented as both network node weights (local topological properties) and network node orders (global topological characteristics).

Microarray databases

10.1186/1471-2105-13-s2-s1

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GigaAssay – An adaptable high-throughput saturation mutagenesis assay platform

Genomics (2022)

Ronald Benjamin Christopher J. Giacoletto Zachary T. FitzHugh Danielle Eames Lindsay Buczek

High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the “GigaAssay”, a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow-sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.

High-Throughput Screening

Saturated mutagenesis

10.1016/j.ygeno.2022.110439

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Citations (11)