Publications by authors named "Ji Gang Zhang"

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models ( between 0.

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Myocarditis has emerged as an immune-related adverse event of immune checkpoint inhibitor (ICI) cancer therapy associated with significant mortality. To ensure patients continue to safely benefit from life-saving cancer therapy, an understanding of fundamental immunological phenomena underlying ICI myocarditis is essential. We recently developed the NOD-cMHCI/II-/-.

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Patients with hepatocellular carcinoma (HCC) are vulnerable to drug resistance. Although drug resistance has been taken much attention to HCC therapy, little is known of regorafenib and regorafenib resistance (RR). This study aimed to determine the drug resistance pattern and the role of RhoA in RR.

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Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we perform discovery-based proteomics in 10 tissues from 20 C57BL/6J mice, representing both sexes at adult and late midlife ages (8 and 18 months).

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Recently, N6-methyl-adenosine (m6A) ribonucleic acid (RNA) modification, a critical and common internal RNA modification in higher eukaryotes, has generated considerable research interests. Extensive studies have revealed that non-coding RNA m6A modifications (e.g.

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Background: Vasculogenic mimicry (VM) is a newly described tumor vascular phenomenon that is independent of traditional angiogenesis and provides an adequate blood supply for tumor growth. VM has been consistently observed in different cancer types. Hence, inhibition of VM may be considered a new anticancer therapeutic strategy.

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Cancer stem cells (CSCs) show a self-renewal capacity and differentiation potential that contribute to tumor progression and therapy resistance. However, the underlying processes are still unclear. Elucidation of the key hallmarks and resistance mechanisms of CSCs may help improve patient outcomes and reduce relapse by altering therapeutic regimens.

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Developing strategies to maintain cognitive health is critical to quality of life during aging. The basis of healthy cognitive aging is poorly understood; thus, it is difficult to predict who will have normal cognition later in life. Individuals may have higher baseline functioning (cognitive reserve) and others may maintain or even improve with age (cognitive resilience).

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Background: Vasculogenic mimicry (VM), defined as a capability of aggressive tumor Cells to mimic embryonic vasculogenic networks, caused poor prognosis in hepatocellular carcinoma (HCC). Rho kinases (ROCK), p21-activated kinase (PAK), hypoxia or epithelial-mesenchymal transition (EMT) contributed to the VM potential. However, the details underlying these biological behaviors have not been completely elucidated.

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MicroRNA-425-5p (miR-425-5p) has been reported to be involved in the tumorigenesis of several tumors, but its function in breast cancer is still unknown. In this study, miR-425-5p was found significantly upregulated in breast cancer cells, and predicted a poor prognosis for breast cancer patients. Overexpression of miR-425-5p could significantly promote breast cancer cell growth.

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Differential network analysis investigates how the network of connected genes changes from one condition to another and has become a prevalent tool to provide a deeper and more comprehensive understanding of the molecular etiology of complex diseases. Based on the asymptotically normal estimation of large Gaussian graphical model (GGM) in the high-dimensional setting, we developed a computationally efficient test for differential network analysis through testing the equality of two precision matrices, which summarize the conditional dependence network structures of the genes. Additionally, we applied a multiple testing procedure to infer the differential network structure with false discovery rate (FDR) control.

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Background: Our previous study described the crucial role of Rho-associated coiled-coil containing-kinases (ROCK) in hepatocellular carcinoma (HCC). However, the potential significance of long noncoding RNA downstream of ROCK is largely unknown. Here, a comprehensive comparative bioinformatics analysis of a microarray of an MHCC-97H cell line overexpressing ROCK1 or ROCK2 was performed.

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Article Synopsis
  • The study aimed to determine if genetic risk factors (GRFs) for fractures and bone mineral density (BMD) identified in Europeans could improve fracture risk and BMD prediction in elderly Chinese populations.
  • Using data from 700 and 1,620 Chinese Han subjects for fracture and BMD predictions respectively, researchers created logistic and linear regression models incorporating both genetic and clinical risk factors.
  • Results indicated that adding GRFs did not significantly enhance predictive capabilities for fractures or BMD compared to models using only clinical risk factors, suggesting limited applicability of European-derived genetic factors in the Chinese context.
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Across the population, individuals exhibit a wide variation of susceptibility or resilience to developing Alzheimer's disease (AD). Identifying specific factors that promote resilience would provide insight into disease mechanisms and nominate potential targets for therapeutic intervention. Here, we use transcriptome profiling to identify gene networks present in the pre-symptomatic AD mouse brain relating to neuroinflammation, brain vasculature, extracellular matrix organization, and synaptic signaling that predict cognitive performance at an advanced age.

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Vasculogenic mimicry (VM) results in the formation of an alternative circulatory system that can improve the blood supply to multiple malignant tumors, including hepatocellular carcinoma (HCC). However, the potential mechanisms of RhoC/ROCK in VM have not yet been investigated in HCC. Here, RhoC expression was upregulated in HCC tissues, especially the VM-positive (VM+) group, compared to noncancerous tissues (P < 0.

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Gene transcription is regulated with distinct sets of regulatory factors at multiple levels. Transcriptional and post-transcriptional regulation constitute two major regulation modes of gene expression to either activate or repress the initiation of transcription and thereby control the number of proteins synthesized during translation. Disruptions of the proper regulation patterns at transcriptional and post-transcriptional levels are increasingly recognized as causes of human diseases.

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The liver is the central metabolic organ and plays a pivotal role in regulating homeostasis of glucose and lipid metabolism. Aberrant liver metabolism promotes insulin resistance, which is reported to be a common characteristic of metabolic diseases such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). There is a complex and bidirectional relationship between NAFLD and T2DM.

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Background: Individuals' peak bone mineral density (BMD) achieved and maintained at ages 20-40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women.

Methods: A total of 136 women aged 20-40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled.

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Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power.

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Following a myocardial infarction (MI), the immune system helps to repair ischaemic damage and restore tissue integrity, but excessive inflammation has been implicated in adverse cardiac remodelling and development towards heart failure (HF). Pre-clinical studies suggest that timely resolution of inflammation may help prevent HF development and progression. Therapeutic attempts to prevent excessive post-MI inflammation in patients have included pharmacological interventions ranging from broad immunosuppression to immunomodulatory approaches targeting specific cell types or factors with the aim to maintain beneficial aspects of the early post-MI immune response.

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DNA methylation plays an important role in the development of various cancers mainly through the regulation on gene expression. Hence, the study on the relation between DNA methylation and gene expression is of particular interest to understand cancers. Recently, an increasing number of datasets are available from multiple cancers, which makes it possible to study both the similarity and difference of genomic alterations across multiple tumor types.

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Integrating diverse genomics data can provide a global view of the complex biological processes related to the human complex diseases. Although substantial efforts have been made to integrate different omics data, there are at least three challenges for multi-omics integration methods: (i) How to simultaneously consider the effects of various genomic factors, since these factors jointly influence the phenotypes; (ii) How to effectively incorporate the information from publicly accessible databases and omics datasets to fully capture the interactions among (epi)genomic factors from diverse omics data; and (iii) Until present, the combination of more than two omics datasets has been poorly explored. Current integration approaches are not sufficient to address all of these challenges together.

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Human monocyte is an important cell type which is involved in various complex human diseases. To better understand the biology of human monocytes and facilitate further studies, we developed the first comprehensive proteome knowledge base specifically for human monocytes by integrating both in vivo and in vitro datasets. The top 2000 expressed genes from in vitro datasets and 779 genes from in vivo experiments were integrated into this study.

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Next-generation sequencing-based genetic association study (GAS) is a powerful tool to identify candidate disease variants and genomic regions. Although low-coverage sequencing offers low cost but inadequacy in calling rare variants, high coverage is able to detect essentially every variant but at a high cost. Two-stage sequencing may be an economical way to conduct GAS without losing power.

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