Biology subjects

Wang, L. D.

Publications and source records attributed to Wang, L. D..

10 recordsLinked to original sources

bioRxiv2025

Sirtuin 1 is an endogenous NETosis inhibitor that becomes dysfunctional in diabetes

Neutrophils release their chromatin with toxic granular proteins as neutrophil extracellular traps (NETs) when activated. Diabetes exacerbates NET formation (NETosis), resulting in tissue damage and diabetic complications such as non-healing wounds. How diabetes predisposes neutrophils to NETosis remains unclear. Herein, we found that pharmacological inhibition or siRNA-knockdown of sirtuin 1 (SIRT1) increased NETosis in neutrophils of healthy humans and mice, unveiling SIRT1 as an endogenous suppressor of NETosis. In contrast, SIRT1 inhibition did not cause further increase in NETosis in neutrophils of diabetic patients and mice, indicative of SIRT1 dysfunction in disease state. Indeed, SIRT1 activity was significantly lower in neutrophils of diabetic individuals, accompanied by a concomitant increase in the activity of peptidylarginine deiminase 4 (PAD4), a key enzyme that mediates NETosis. PAD4 was co-detected with SIRT1 immunoprecipitated from HL-60-derived neutrophils cultured in basal glucose; such co- immunoprecipitation was absent in cells with high-glucose exposure, suggesting that hyperglycemia disrupts the SIRT1-PAD4 interaction. SIRT1 activators restored the SIRT1-PAD4 interaction and normalized the exacerbated NETosis and PAD4 activity in diabetes and hyperglycemia. This study reveals a novel regulatory role of SIRT1 on PAD4 activity. Revitalizing SIRT1 can be a new preventive or therapeutic strategy for combating NET-mediated inflammation in diabetes and beyond.

cell biology↗

bioRxiv2025

Tirzepatide reduces diet-induced senescence and NETosis-mediated liver fibrosis in mice

Lipofuscin, a protein-lipid complex that progressively accumulates in senescent cells, was commonly observed in the liver biopsies from patients with liver fibrosis or cirrhosis regardless of the etiological insults. However, whether and how lipofuscin contributes to the development of liver fibrosis remains unknown. Using a mouse model of liver fibrosis induced by choline-deficient L-amino acid-defined high-fat diet (HFD), we found that lipofuscin accumulation preceded the emergence of liver fibrosis. A significant, positive and strong correlation was observed between the hepatic lipofuscin levels and liver fibrosis severity. Neutrophils were recruited to the liver in mice fed HFD, and those that were in close proximity to lipofuscin-laden hepatocytes displayed higher susceptibility to produce neutrophil extracellular traps (NETs). We revealed that lipofuscin-laden hepatocytes generated CXCL5, which promoted NETosis. When mice defective in NETosis (Vav1-Cre Padi4fl/fl) were fed HFD, they had significantly less collagen deposition in the liver, indicating the critical role of NETs in the development of liver fibrosis associated with lipofuscin accumulation. Notably, we showed that tirzepatide, the latest glucagon-like peptide-1 receptor and glucose-dependent insulinotropic polypeptide receptor dual agonist recently approved for type 2 diabetes, attenuated NETosis-dependent liver fibrosis by preventing hepatic lipofuscin accumulation, and reduced other hepatic senescence signatures as well. In summary, our study unveiled the pathogenic, NETosis-enhancing effect of lipofuscin in liver fibrosis, and demonstrated the potential of repurposing tirzepatide for combating liver fibrosis associated with lipofuscin and for preventing organ senescence.

molecular biology↗

bioRxiv2022

The 3D chromatin landscape of rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric soft tissue cancer with a lack of precision therapy option for patients. We hypothesized that with a general paucity of known mutations in RMS, chromatin structural driving mechanisms are essential for tumor proliferation. Thus, we carried out high-depth in situ Hi-C in representative cell lines and patient-derived xenografts to understand chromatin architecture in each major RMS subtype. We report a comprehensive 3D chromatin structural analysis and characterization of fusion-positive (FP-RMS) and fusion-negative rhabdomyosarcoma (FN-RMS). We have generated spike-in in situ Hi-C chromatin interaction maps for the most common FP-RMS and FN-RMS cell lines, and compared our data with patient derived xenograft (PDX) models. In our studies we uncover common and distinct structural elements in large Mb-scale chromatin compartments, tumor-essential genes within variable topologically associating domains, and unique patterns of structural variation. Our comprehensive analysis provides high-depth chromatin interactivity maps for contextualizing gene regulation events identification of functionally critical chromatin domains in RMS. HIGHLIGHTSO_LIPAX3-FOXO1 and MYOD localize in both A- and B-compartments C_LIO_LIConserved mechanisms dictate CTCF orientation at TAD boundaries in RMS C_LIO_LIDifferential TADs in each RMS subtype encompass tumor-specific genes C_LIO_LINeo-TADs are formed from SV events in each subtype of RMS C_LIO_LIBoth major RMS subtypes have structural variation that is identifiable from Hi-C C_LIO_LIDistinct mechanisms can produce the major fusion alleles in rhabdomyosarcoma C_LIO_LIPAX3-FOXO1 and MYOD genomic binding is more enriched at regions with CNV C_LI

cancer biology↗

bioRxiv2022

Selective IL13Rα2-Targeted Functionality of IL13-Ligand CARs is Enhanced by Inclusion of 4-1BB Co-Stimulation

ABSTRACTChimeric antigen receptor (CAR) T cell immunotherapy is emerging as a powerful strategy for cancer therapy; however, an important safety consideration is the potential for off-tumor recognition of normal tissue. This is particularly important as ligand-based CARs are optimized for clinical translation. Our group has developed and clinically translated an IL13(E12Y) ligand- based CAR targeting the cancer antigen IL13R2 for treatment of glioblastoma (GBM). There remains limited understanding of how IL13-ligand CAR design impacts the activity and selectivity for the intended tumor-associated target IL13R2 versus the more ubiquitous unintended target IL13R1. In this study, we functionally compared IL13(E12Y)-CARs incorporating different intracellular signaling domains, including first-generation CD3{zeta}- containing CARs (IL13{zeta}), second-generation 4-1BB- (CD137) or CD28-containing CARs (IL13- BB{zeta} or IL13-28{zeta}), and third-generation CARs containing both 4-1BB and CD28 (IL13-28BB{zeta}). In vitro co-culture assays at high tumor burden establish that 2nd generation IL13-BB{zeta} or IL13- 28{zeta} outperform first-generation IL13{zeta} and 3rd generation IL13-28BB{zeta} CAR designs, with IL13- BB{zeta} providing superior CAR proliferation and in vivo anti-tumor potency in human xenograft mouse models. IL13-28{zeta} displayed a lower threshold for antigen recognition, resulting in higher off-target IL13R1 reactivity both in vitro and in vivo. Syngeneic mouse models of GBM also demonstrate safety and anti-tumor potency of murine IL13-BB{zeta} CAR T cells delivered systemically after lymphodepletion. These findings support the use of IL13-BB{zeta} CARs for greater selective recognition of IL13R2 over IL13R1, higher proliferative potential, and superior anti-tumor responsiveness. This study exemplifies the potential of modulating factors outside the antigen targeting domain of a CAR to improve selective tumor recognition..

immunology↗

bioRxiv2021

APIR: a universal FDR-control framework for boosting peptide identification power by aggregating multiple proteomics database search algorithms

Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and control on the false discovery rate (FDR). To fill in this gap, we propose a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard shows that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies show that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR.

bioinformatics↗

bioRxiv2021

Deep Proteome Profiling of Human Mammary Epithelia at Lineage and Age Resolution

Age is the major risk factor in most carcinomas, yet little is known about how proteomes change with age in any human epithelium. We present comprehensive proteomes comprised of >9,000 total proteins, and >15,000 phosphopeptides, from normal primary human mammary epithelia at lineage resolution from ten women ranging in age from 19 to 68. Data were quality controlled, and results were biologically validated with cell-based assays. Age-dependent protein signatures were identified using differential expression analyses and weighted protein co-expression network analyses. Up-regulation of basal markers in luminal cells, including KRT14 and AXL, were a prominent consequence of aging. PEAK1 was identified as an age-dependent signaling kinase in luminal cells, which revealed a potential age-dependent vulnerability for targeted ablation. Correlation analyses between transcriptome and proteome revealed age-associated loss of proteostasis regulation. Protein expression and phosphorylation changes in the aging breast epithelium identify potential therapeutic targets for reducing breast cancer susceptibility.

cell biology↗

bioRxiv2020

Deep immune profiling reveals targetable mechanisms of immune evasion in checkpoint blockade-refractory glioblastoma

BackgroundGlioblastoma (GBM) is refractory to checkpoint blockade immunotherapy (CPI). We sought to determine to what extent this immune evasion is due to intrinsic properties of the tumor cells versus the specialized immune context of the brain, and if it can be reversed. MethodsWe used CyTOF mass cytometry to compare the tumor immune microenvironments (TIME) of human tumors that are generally CPI-refractory (GBM and sarcoma) or CPI-responsive (renal cell carcinoma), as well as mouse models of GBM that are CPI-responsive (GL261) or CPI-refractory (SB28). We further compared SB28 tumors grown intracerebrally versus subcutaneously to determine how tumor site affects TIME and responsiveness to dual CTLA-4/PD-1 blockade. Informed by these data, we explored rational immunotherapeutic combinations. ResultsCPI-sensitivity in human and mouse tumors was associated with increased T cells and dendritic cells, and fewer myeloid cells, in particular PD-L1+ tumor associated macrophages. The SB28 mouse model of GBM responded to CPI when grown subcutaneously but not intracerebrally, providing a system to explore mechanisms underlying CPI resistance in GBM. The response to CPI in the subcutaneous SB28 model required CD4 T cells and NK cells, but not CD8 T cells. Recombinant FLT3L expanded dendritic cells, improved antigen-specific T cell priming, and prolonged survival of mice with intracerebral SB28 tumors, but at the cost of increased Tregs. Targeting PD-L1 also prolonged survival, especially when combined with stereotactic radiation. ConclusionsOur data suggest that a major obstacle for effective immunotherapy of GBM is the low antigenicity of the tumor cells coupled with poor antigen presentation in the brain, rather than intrinsic immunosuppressive properties of GBM tumor cells. Deep immune profiling identified dendritic cells and PD-L1+ tumor-associated macrophages as promising targetable cell populations, which was confirmed using therapeutic interventions in vivo. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/404939v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@bdd0e4org.highwire.dtl.DTLVardef@1dd335forg.highwire.dtl.DTLVardef@157bfa6org.highwire.dtl.DTLVardef@1e76151_HPS_FORMAT_FIGEXP M_FIG C_FIG In BriefIn mice and humans, tumors that were sensitive to checkpoint blockade had consistent immunological features. A mouse model of glioma that is refractory to checkpoint blockade was sensitized by increasing antigen presentation through a variety of approaches.

cancer biology↗

bioRxiv2020

Clipper: p-value-free FDR control on high-throughput data from two conditions

High-throughput biological data analysis commonly involves identifying features such as genes, genomic regions, and proteins, whose values differ between two conditions, from numerous features measured simultaneously. The most widely-used criterion to ensure the analysis reliability is the false discovery rate (FDR), which is primarily controlled based on p-values. However, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions. Clipper is a general statistical framework for FDR control without relying on p-values or specific data distributions. Clipper outperforms existing methods for a broad range of applications in high-throughput data analysis.

bioinformatics↗

bioRxiv2020

Arhgap25 deficiency leads to decreased numbers of peripheral blood B cells and defective germinal center reactions

Rho family GTPases are critical for normal B cell development and function and their activity is regulated by a large and complex network of guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs). However, the role of GAPs in B cell development is poorly understood. Here we show that the novel Rac-GAP ARHGAP25 is important for B cell development in mice in a CXCR4-dependent manner. We show that Arhgap25 deficiency leads to a significant decrease in peripheral blood B cell numbers, as well as defects in mature B cell differentiation. Arhgap25-/- B cells respond to antigen stimulation in vitro and in vivo but have impaired germinal center formation and decreased IgG1 class switching. Additionally, Arhgap25-/- B cells exhibit increased chemotaxis to CXCL12. Taken together, these studies demonstrate an important role for Arhgap25 in peripheral B cell development and antigen response.

immunology↗

bioRxiv2017

Transcriptome dynamics describe and predict state transition from health to leukemia

Temporal dynamics of gene expression are informative of changes associated with disease development and evolution. Given the complexity of high-dimensional temporal datasets, an analytical framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Herein, we use acute myeloid leukemia as a proof-of-principle to model gene expression dynamics in a transcriptome state-space constructed based on time-sequential RNA-sequencing data. We describe the construction of a state-transition model to identify state-transition critical points which accurately predicts leukemia development. We show an analytical approach based on state-transition critical points identified step-wise transcriptomic perturbations driving leukemia progression. Furthermore, the gene(s) trajectory and geometry of the transcriptome state-space provides biologically-relevant gene expression signals that are not synchronized in time, and allows quantification of gene(s) contribution to leukemia development. Therefore, our state-transition model can synthesize information, identify critical points to guide interpretation of transcriptome trajectories and predict disease development.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=193 HEIGHT=200 SRC=\"FIGDIR/small/238923v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (55K):\norg.highwire.dtl.DTLVardef@12eeaccorg.highwire.dtl.DTLVardef@1392af9org.highwire.dtl.DTLVardef@34786dorg.highwire.dtl.DTLVardef@ce78bb_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefThe theory of state-transition is applied to acute myeloid leukemia (AML) to model transcriptome dynamics and trajectories in a state-space, and is used to identify critical points corresponding to critical transcriptomic perturbations that predict leukemia development.\n\nHighlightsO_LILeukemia transcriptome dynamics are modeled as movement in transcriptome state-space\nC_LIO_LIState-transition model and critical points accurately predicts leukemia development\nC_LIO_LICritical point-based approach identifies step-wise transcriptome events in leukemia\nC_LIO_LIState-based geometric analysis provides quantification of leukemogenic contribution\nC_LI

cancer biology↗