Stem cell marker (Nanog) and Stat-3 signaling promote MicroRNA-21 expression and chemoresistance in hyaluronan/CD44-activated head and neck squamous cell carcinoma cells.

MicroRNAs are often associated with the pathogenesis of many cancers, including head and neck squamous cell carcinoma (HNSCC). In particular, microRNA-21 (miR-21) appears to have a critical role in tumor cell survival, chemoresistance and HNSCC progression. In this study, we investigated matrix hyaluronan (HA)-induced CD44 (a primary HA receptor) interaction with the stem cell markers, Nanog and Stat-3, in HNSCC cells (HSC-3 cells). Our results indicate that HA binding to CD44 promotes Nanog-Stat-3 (also tyrosine phosphorylated Stat-3) complex formation, nuclear translocation and transcriptional activation. Further analyses reveal that miR-21 is controlled by an upstream promoter containing Stat-3 binding site(s), while chromatin immunoprecipitation assays demonstrate that stimulation of miR-21 expression by HA/CD44 signaling is Nanog/Stat-3-dependent in HNSCC cells. This process results in a decrease of a tumor suppressor protein (PDCD4), and an upregulation of i nhibitors of the apoptosis family of proteins (IAPs) as well as chemoresistance in HSC-3 cells. Treatment of HSC-3 cells with Nanog- and/or Stat-3-specific small interfering RNAs effectively blocks HA-mediated Nanog-Stat-3 signaling events, abrogates miR-21 production and increases PDCD4 expression. Subsequently, this Nanog-Stat-3 signaling inhibition causes downregulation of survival protein (IAP) expression and enhancement of chemosensitivity. To further evaluate the role of miR-21 in tumor cell-specific functions, HSC-3 cells were also transfected with a specific anti-miR-21 inhibitor in order to silence miR-21 expression and block its target functions. Our results demonstrate that anti-miR-21 inhibitor not only upregulates PDCD4 expression but also decreases IAP expression and enhances chemosensitivity in HA-treated HNSCC cells. Together, these findings indicate that the HA-induced CD44 interaction with Nanog and Stat-3 has a pivotal role in miR-21 production leading to PDCD4 reduction, IAP upregulation and chemoresistance in HNSCC cells. This novel Nanog/Stat-3 signaling pathway-specific mechanism involved in miR-21 production is significant for the formation of future intervention strategies in the treatment of HA/CD44-activated HNSCC

On the pollutant removal, dispersion, and entrainment over two-dimensional idealized street canyons

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Neuropsychiatric manifestations in southern Chinese patients with systemic lupus erythematosus (SLE) according to the 1999 ACR nomenclature and their clinical associations

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Personalized Pancreatic Tumor Growth Prediction via Group Learning

Tumor growth prediction, a highly challenging task, has long been viewed as a mathematical modeling problem, where the tumor growth pattern is personalized based on imaging and clinical data of a target patient. Though mathematical models yield promising results, their prediction accuracy may be limited by the absence of population trend data and personalized clinical characteristics. In this paper, we propose a statistical group learning approach to predict the tumor growth pattern that incorporates both the population trend and personalized data, in order to discover high-level features from multimodal imaging data. A deep convolutional neural network approach is developed to model the voxel-wise spatio-temporal tumor progression. The deep features are combined with the time intervals and the clinical factors to feed a process of feature selection. Our predictive model is pretrained on a group data set and personalized on the target patient data to estimate the future spatio-temporal progression of the patient's tumor. Multimodal imaging data at multiple time points are used in the learning, personalization and inference stages. Our method achieves a Dice coefficient of 86.8% +- 3.6% and RVD of 7.9% +- 5.4% on a pancreatic tumor data set, outperforming the DSC of 84.4% +- 4.0% and RVD 13.9% +- 9.8% obtained by a previous state-of-the-art model-based method

Late-onset systemic lupus erythematosus (SLE) in southern Chinese

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Generalized camera calibration model for trapezoidal patterns on the road

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Real-Time Estimation of Lane-to-Lane Turning Flows at Isolated Signalized Junctions

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ACR/SLICC damage scores in an inception cohort of patients with systemic lupus erythematosus (SLE) and their relationship with disease flares and various clinical variables

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Late-onset systemic lupus erythematosus (SLE) in southern Chinese

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Cumulative disease damage in southern Chinese patients with systemic lupus erythematosus (SLE)

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