Browsing by Author "Wang, Michael"

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    PRMT5 is upregulated by B-cell receptor signaling and forms a positive-feedback loop with PI3K/AKT in lymphoma cells
    (Springer, 2019-05-23) Zhu, Fen; Guo, Hui; Bates, Paul D.; Zhang, Shanxiang; Zhang, Hui; Nomie, Krystle J.; Li, Yangguang; Lu, Li; Seibold, Kaitlyn R.; Wang, Fangyu; Rumball, Ian; Cameron, Hunter; Hoang, Nguyet M.; Yang, David T.; Xu, Wei; Zhang, Liang; Wang, Michael; Capitini, Christian M.; Rui, Lixin; Pathology and Laboratory Medicine, School of Medicine
    PRMT5, which regulates gene expression by symmetric dimethylation of histones and non-histone target proteins, is overexpressed and plays a pathogenic role in many cancers. In diffuse large B cell lymphoma (DLBCL), the mechanisms of PRMT5 dysregulation and its role in lymphomagenesis remain largely unknown. Here we demonstrate that B cell receptor (BCR) signaling regulates PRMT5 expression in DLBCL cells. Immunohistochemical analysis reveals elevated levels of PRMT5 expression in DLBCL cases and in germinal center (GC) B cells when compared to naive B cells. PRMT5 can be induced in naive B cells by BCR stimulation. We discovered that BTK-NF-κB signaling induces PRMT5 transcription in activated B cell-like (ABC) DLBCL cells while BCR downstream PI3K-AKT-MYC signaling upregulates PRMT5 expression in both ABC and GCB DLBCL cells. PRMT5 inhibition inhibits the growth of DLBCL cells in vitro and patient derived xenografts. Genomic and biochemical analysis demonstrate that PRMT5 promotes cell cycle progression and activates PI3K-AKT signaling, suggesting a feedback regulatory mechanism to enhance cell survival and proliferation. Co-targeting PRMT5 and AKT by their specific inhibitors is lethal to DLBCL cell lines and primary cancer cells. Therefore, this study provides a mechanistic rationale for clinical trials to evaluate PRMT5 and AKT inhibitors for DLBCL.
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    Tangent functional connectomes uncover more unique phenotypic traits
    (Elsevier, 2023-08-12) Abbas, Kausar; Liu, Mintao; Wang, Michael; Duong-Tran, Duy; Tipnis, Uttara; Amico, Enrico; Kaplan, Alan D.; Dzemidzic, Mario; Kareken, David; Ances, Beau M.; Harezlak, Jaroslaw; Goñi, Joaquín; Neurology, School of Medicine
    Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projections, resulting into tangent-FCs. Tangent-FCs have led to more accurate models predicting brain conditions or aging. Motivated by the fact that tangent-FCs seem to be better biomarkers than FCs, we hypothesized that tangent-FCs have also a higher fingerprint. We explored the effects of six factors: fMRI condition, scan length, parcellation granularity, reference matrix, main-diagonal regularization, and distance metric. Our results showed that identification rates are systematically higher when using tangent-FCs across the “fingerprint gradient” (here including test-retest, monozygotic and dizygotic twins). Highest identification rates were achieved when minimally (0.01) regularizing FCs while performing tangent space projection using Riemann reference matrix and using correlation distance to compare the resulting tangent-FCs. Such configuration was validated in a second dataset (resting-state).