IU Indianapolis ScholarWorks :: Browsing by Author "Zhang, Siyuan"

Browsing by Author "Zhang, Siyuan"

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Death effector domain-containing protein induces vulnerability to cell cycle inhibition in triple-negative breast cancer
(Springer Nature, 2019-06-28) Ni, Yingjia; Schmidt, Keon R.; Werner, Barnes A.; Koenig, Jenna K.; Guldner, Ian H.; Schnepp, Patricia M.; Tan, Xuejuan; Jiang, Lan; Host, Misha; Sun, Longhua; Howe, Erin N.; Wu, Junmin; Littlepage, Laurie E.; Nakshatri, Harikrishna; Zhang, Siyuan; Surgery, IU School of Medicine
Lacking targetable molecular drivers, triple-negative breast cancer (TNBC) is the most clinically challenging subtype of breast cancer. In this study, we reveal that Death Effector Domain-containing DNA-binding protein (DEDD), which is overexpressed in > 60% of TNBCs, drives a mitogen-independent G1/S cell cycle transition through cytoplasm localization. The gain of cytosolic DEDD enhances cyclin D1 expression by interacting with heat shock 71 kDa protein 8 (HSC70). Concurrently, DEDD interacts with Rb family proteins and promotes their proteasome-mediated degradation. DEDD overexpression renders TNBCs vulnerable to cell cycle inhibition. Patients with TNBC have been excluded from CDK 4/6 inhibitor clinical trials due to the perceived high frequency of Rb-loss in TNBCs. Interestingly, our study demonstrated that, irrespective of Rb status, TNBCs with DEDD overexpression exhibit a DEDD-dependent vulnerability to combinatorial treatment with CDK4/6 inhibitor and EGFR inhibitor in vitro and in vivo. Thus, our study provided a rationale for the clinical application of CDK4/6 inhibitor combinatorial regimens for patients with TNBC.
GAD1 Upregulation Programs Aggressive Features of Cancer Cell Metabolism in the Brain Metastatic Microenvironment
(American Association for Cancer Research, 2017-06-01) Schnepp, Patricia M.; Lee, Dennis D.; Guldner, Ian H.; O'Tighearnaigh, Treasa K.; Howe, Erin N.; Palakurthi, Bhavana; Eckert, Kaitlyn E.; Toni, Tiffany A.; Ashfeld, Brandon L.; Zhang, Siyuan; Medicine, School of Medicine
The impact of altered amino acid metabolism on cancer progression is not fully understood. We hypothesized that a metabolic transcriptome shift during metastatic evolution is crucial for brain metastasis. Here, we report a powerful impact in this setting caused by epigenetic upregulation of glutamate decarboxylase 1 (GAD1), a regulator of the GABA neurotransmitter metabolic pathway. In cell-based culture and brain metastasis models, we found that downregulation of the DNA methyltransferase DNMT1 induced by the brain microenvironment-derived clusterin resulted in decreased GAD1 promoter methylation and subsequent upregulation of GAD1 expression in brain metastatic tumor cells. In a system to dynamically visualize cellular metabolic responses mediated by GAD1, we monitored the cytosolic NADH:NAD+ equilibrium in tumor cells. Reducing GAD1 in metastatic cells by primary glia cell coculture abolished the capacity of metastatic cells to utilize extracellular glutamine, leading to cytosolic accumulation of NADH and increased oxidative status. Similarly, genetic or pharmacologic disruption of the GABA metabolic pathway decreased the incidence of brain metastasis in vivo Taken together, our results show how epigenetic changes in GAD1 expression alter local glutamate metabolism in the brain metastatic microenvironment, contributing to a metabolic adaption that facilitates metastasis outgrowth in that setting.
Generating intravital super-resolution movies with conventional microscopy reveals actin dynamics that construct pioneer axons
(The Company of Biologists, 2019-03-08) Zhang, Yide; Nichols, Evan L.; Zellmer, Abigail M.; Guldner, Ian H.; Kankel, Cody; Zhang, Siyuan; Howard, Scott S.; Smith, Cody J.; Medicine, School of Medicine
Super-resolution microscopy is broadening our in-depth understanding of cellular structure. However, super-resolution approaches are limited, for numerous reasons, from utilization in longer-term intravital imaging. We devised a combinatorial imaging technique that combines deconvolution with stepwise optical saturation microscopy (DeSOS) to circumvent this issue and image cells in their native physiological environment. Other than a traditional confocal or two-photon microscope, this approach requires no additional hardware. Here, we provide an open-access application to obtain DeSOS images from conventional microscope images obtained at low excitation powers. We show that DeSOS can be used in time-lapse imaging to generate super-resolution movies in zebrafish. DeSOS was also validated in live mice. These movies uncover that actin structures dynamically remodel to produce a single pioneer axon in a 'top-down' scaffolding event. Further, we identify an F-actin population - stable base clusters - that orchestrate that scaffolding event. We then identify that activation of Rac1 in pioneer axons destabilizes stable base clusters and disrupts pioneer axon formation. The ease of acquisition and processing with this approach provides a universal technique for biologists to answer questions in living animals.
The glutathione peroxidase Gpx4 prevents lipid peroxidation and ferroptosis to sustain Treg cell activation and suppression of antitumor immunity
(Elsevier, 2021-06) Xu, Chengxian; Sun, Shaogang; Johnson, Travis; Qi, Rong; Zhang, Siyuan; Zhang, Jie; Yang, Kai; Pediatrics, School of Medicine
T regulatory (Treg) cells are crucial to maintain immune tolerance and repress antitumor immunity, but the mechanisms governing their cellular redox homeostasis remain elusive. We report that glutathione peroxidase 4 (Gpx4) prevents Treg cells from lipid peroxidation and ferroptosis in regulating immune homeostasis and antitumor immunity. Treg-specific deletion of Gpx4 impairs immune homeostasis without substantially affecting survival of Treg cells at steady state. Loss of Gpx4 results in excessive accumulation of lipid peroxides and ferroptosis of Treg cells upon T cell receptor (TCR)/CD28 co-stimulation. Neutralization of lipid peroxides and blockade of iron availability rescue ferroptosis of Gpx4-deficient Treg cells. Moreover, Gpx4-deficient Treg cells elevate generation of mitochondrial superoxide and production of interleukin-1β (IL-1β) that facilitates T helper 17 (TH17) responses. Furthermore, Treg-specific ablation of Gpx4 represses tumor growth and concomitantly potentiates antitumor immunity. Our studies establish a crucial role for Gpx4 in protecting activated Treg cells from lipid peroxidation and ferroptosis and offer a potential therapeutic strategy to improve cancer treatment.
Integration of molecular features with clinical information for predicting outcomes for neuroblastoma patients
(BioMed Central, 2019-08-23) Han, Yatong; Ye, Xiufen; Wang, Chao; Liu, Yusong; Zhang, Siyuan; Feng, Weixing; Huang, Kun; Zhang, Jie; Medicine, School of Medicine
BACKGROUND: Neuroblastoma is one of the most common types of pediatric cancer. In current neuroblastoma prognosis, patients can be stratified into high- and low-risk groups. Generally, more than 90% of the patients in the low-risk group will survive, while less than 50% for those with the high-risk disease will survive. Since the so-called "high-risk" patients still contain patients with mixed good and poor outcomes, more refined stratification needs to be established so that for the patients with poor outcome, they can receive prompt and individualized treatment to improve their long-term survival rate, while the patients with good outcome can avoid unnecessary over treatment. METHODS: We first mined co-expressed gene modules from microarray and RNA-seq data of neuroblastoma samples using the weighted network mining algorithm lmQCM, and summarize the resulted modules into eigengenes. Then patient similarity weight matrix was constructed with module eigengenes using two different approaches. At the last step, a consensus clustering method called Molecular Regularized Consensus Patient Stratification (MRCPS) was applied to aggregate both clinical information (clinical stage and clinical risk level) and multiple eigengene data for refined patient stratification. RESULTS: The integrative method MRCPS demonstrated superior performance to clinical staging or transcriptomic features alone for the NB cohort stratification. It successfully identified the worst prognosis group from the clinical high-risk group, with less than 40% survived in the first 50 months of diagnosis. It also identified highly differentially expressed genes between best prognosis group and worst prognosis group, which can be potential gene biomarkers for clinical testing. CONCLUSIONS: To address the need for better prognosis and facilitate personalized treatment on neuroblastoma, we modified the recently developed bioinformatics workflow MRCPS for refined patient prognosis. It integrates clinical information and molecular features such as gene co-expression for prognosis. This clustering workflow is flexible, allowing the integration of both categorical and numerical data. The results demonstrate the power of survival prognosis with this integrative analysis workflow, with superior prognostic performance to only using transcriptomic data or clinical staging/risk information alone.
Integrative analysis based on survival associated co-expression gene modules for predicting Neuroblastoma patients' survival time
(Biomed Central, 2019-02-13) Han, Yatong; Ye, Xiufen; Cheng, Jun; Zhang, Siyuan; Feng, Weixing; Han, Zhi; Zhang, Jie; Huang, Kun; Medicine, School of Medicine
BACKGROUND: More than 90% of neuroblastoma patients are cured in the low-risk group while only less than 50% for those with high-risk disease can be cured. Since the high-risk patients still have poor outcomes, we need more accurate stratification to establish an individualized precise treatment plan for the patients to improve the long-term survival rate. RESULTS: We focus on extracting features and providing a workflow to improve survival prediction for neuroblastoma patients. With a workflow for gene co-expression network (GCN) mining in microarray and RNA-Seq datasets, we extracted molecular features from each co-expressed module and summarized them into eigengenes. Then we adopted the lasso-regularized Cox proportional hazards model to select the most informative eigengene features regarding association to the risk of metastasis. Nine eigengenes were selected which show strong association with patient survival prognosis. All of the nine corresponding gene modules also have highly enriched biological functions or cytoband locations. Three of them are unique modules to RNA-Seq data, which complement the modules from microarray data in terms of survival prognosis. We then merged all eigengenes from these unique modules and used an integrative method called Similarity Network Fusion to test the prognostic power of these eigengenes for prognosis. The prognostic accuracies are significantly improved as compared to using all eigengenes, and a subgroup of patients with very poor survival rate was identified. CONCLUSIONS: We first compared GCNs mined from microarray and RNA-seq data. We discovered that each data modality yields unique GCNs, which are enriched with clear biological functions. Then we do module unique analysis and use lasso-cox model to select survival-associated eigengenes. Integration of unique and survival-associated eigengenes from both data types provides complementary information that leads to more accurate survival prognosis.
Isolation of mouse brain-infiltrating leukocytes for single cell profiling of epitopes and transcriptomes
(Elsevier, 2021-05-13) Guldner, Ian H.; Golomb, Samantha M.; Wang, Qingfei; Wang, Emilia; Zhang, Siyuan; Medicine, School of Medicine
High dimensional compositional and transcriptional profiling of heterogeneous brain-infiltrating leukocytes can lead to novel biological and therapeutic discoveries. High-quality single-cell leukocyte preparations are a prerequisite for optimal single cell profiling. Here, we describe a protocol for epitope and RNA-preserving dissociation of adult mouse brains and subsequent leukocyte purification and staining, which is adaptable to homeostatic and pathogenic brains. Leukocyte preparation following this protocol permits exquisite single-cell surface protein and RNA profiling in applications including CyTOF and CITE-seq. For complete details on the use and execution of this protocol, please refer to Guldner et al. (2020) and Golomb et al. (2020).
Multi-modal Single-Cell Analysis Reveals Brain Immune Landscape Plasticity during Aging and Gut Microbiota Dysbiosis
(Elsevier, 2020-12-01) Golomb, Samantha M.; Guldner, Ian H.; Zhao, Anqi; Wang, Qingfei; Palakurthi, Bhavana; Aleksandrovic, Emilija A.; Lopez, Jacqueline A.; Lee, Shaun W.; Yang, Kai; Zhang, Siyuan; Medicine, School of Medicine
Phenotypic and functional plasticity of brain immune cells contribute to brain tissue homeostasis and disease. Immune cell plasticity is profoundly influenced by tissue microenvironment cues and systemic factors. Aging and gut microbiota dysbiosis that reshape brain immune cell plasticity and homeostasis has not been fully delineated. Using Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), we analyze compositional and transcriptional changes of the brain immune landscape in response to aging and gut dysbiosis. Discordance between canonical surface-marker-defined immune cell types and their transcriptomes suggest transcriptional plasticity among immune cells. Ly6C+ monocytes predominate a pro-inflammatory signature in the aged brain, while innate lymphoid cells (ILCs) shift toward an ILC2-like profile. Aging increases ILC-like cells expressing a T memory stemness (Tscm) signature, which is reduced through antibiotics-induced gut dysbiosis. Systemic changes due to aging and gut dysbiosis increase propensity for neuroinflammation, providing insights into gut dysbiosis in age-related neurological diseases.
Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor-resistant HER2-positive breast cancer
(Springer Nature, 2019-08-23) Wang, Qingfei; Guldner, Ian H.; Golomb, Samantha M.; Sun, Longhua; Harris, Jack A.; Lu, Xin; Zhang, Siyuan; Medicine, School of Medicine
Acquired resistance to targeted cancer therapy is a significant clinical challenge. In parallel with clinical trials combining CDK4/6 inhibitors to treat HER2+ breast cancer, we sought to prospectively model tumor evolution in response to this regimen in vivo and identify a clinically actionable strategy to combat drug resistance. Despite a promising initial response, acquired resistance emerges rapidly to the combination of anti-HER2/neu antibody and CDK4/6 inhibitor Palbociclib. Using high-throughput single-cell profiling over the course of treatments, we reveal a distinct immunosuppressive immature myeloid cell (IMC) population to infiltrate the resistant tumors. Guided by single-cell transcriptome analysis, we demonstrate that combination of IMC-targeting tyrosine kinase inhibitor cabozantinib and immune checkpoint blockade enhances anti-tumor immunity, and overcomes the resistance. Furthermore, sequential combinatorial immunotherapy enables a sustained control of the fast-evolving CDK4/6 inhibitor-resistant tumors. Our study demonstrates a translational framework for treating rapidly evolving tumors through preclinical modeling and single-cell analyses.

Browsing by Author "Zhang, Siyuan"

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