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Your search keyword '"Deng, Wei‐Wei"' showing total 411 results
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411 results on '"Deng, Wei‐Wei"'

40. Identification of a Favorable Prognostic Subgroup in Oral Squamous Cell Carcinoma: Characterization of ITGB4/PD-L1 high with CD8/PD-1 high.

Author

Ma, Si-Rui, Liu, Jian-Feng, Jia, Rong, Deng, Wei-Wei, and Jia, Jun

Subjects
PROGRAMMED cell death 1 receptors, SQUAMOUS cell carcinoma, ORAL mucosa, EXTRACELLULAR matrix, T cells, CELL adhesion, CANCER cells
Abstract

Integrin β4 (ITGB4) is a member of the integrin family, which plays a crucial role in mediating cell adhesion to the extracellular matrix. Recent studies have demonstrated that ITGB4 is involved in tumorigenesis and metastasis during the development of cancer. However, the role of ITGB4 in oral squamous cell carcinoma (OSCC) remains unclear. A Multiplex immunohistochemistry (OPAL™, mIHC) assay was employed to stain ITGB4, ALDH1, PD-L1, cytokeratin (CK), CD8 and PD-1 in a human OSCC tissue microarray, containing 26 normal oral epithelium samples, 21 oral epithelium dysplasia samples and 76 OSCC samples. The expression pattern and clinicopathological characteristics of ITGB4 were analyzed and compared with those of PD-1, PD-L1, ALDH1 and CD8. The correlation between subgroups of tumor cells, including ITGB4+PD-L1+ and ITGB4+ALDH1+, and subgroups of T cells, including CD8+ and CD8+PD-1+, was evaluated using two-tailed Pearson's statistics. A Kaplan–Meier curve was built, and a log-rank test was performed to analyze the survival rate of different subgroups. The mIHC staining results show that ITGB4 was mostly expressed in the tumor cells, with a significant increase in the OSCC specimens compared with normal oral epithelium and oral epithelium dysplasia. The paired analysis, conducted between the OSCC tumor tissue and normal paracancer mucosa, confirmed the results. The study further revealed that ITGB4+PD-L1+ cancer cells, but not ITGB4+ALDH1+ cancer cells, were significantly associated with the infiltration of CD8+ T cells (positivity p = 0.005, positive number p = 0.03). Additionally, ITGB4+PD-L1+ tumor cells were positively correlated with CD8+PD-1+ T cells (positivity p = 0.02, positive number p = 0.03). Most intriguingly, the subgroup of ITGB4/PD-L1high with CD8/PD-1high displayed the best prognosis compared with the other considered subgroups. The results show that the expression of ITGB4 was increased in OSCC compared with normal oral mucosa. Furthermore, a specific subgroup with high levels of expression of ITGB4/PD-L1 and CD8/PD-1 was found to have a relatively better prognosis compared with the other subgroups. Ultimately, this study sheds light on the potential role of ITGB4 in OSCC and provides a basis for further investigation. [ABSTRACT FROM AUTHOR]

Published
2023
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47. An RGB-emitting molecular cocktail for the detection of bacterial fingerprints† †Electronic supplementary information (ESI) available. See DOI: 10.1039/d0sc01704c

Author

Hong, Sheng, Zheng, Di-Wei, Zhang, Qiu-Ling, Deng, Wei-Wei, Song, Wen-Fang, Cheng, Si-Xue, Sun, Zhi-Jun, and Zhang, Xian-Zheng

Subjects
Chemistry, sense organs, skin and connective tissue diseases
Abstract

A technique named the Microcolor system was developed to detect microbes and diagnose diseases based on changes in microbiota signatures., Accumulating evidence indicates that colonized microbes play a crucial role in regulating health and disease in the human body. Detecting microbes should be essential for understanding the relationship between microbes and diseases, as well as increasing our ability to detect diseases. Here, a combined metabolic labeling strategy was developed to identify different bacterial species and microbiota by the use of three different fluorescent metabolite derivatives emitting red, green, and blue (RGB) fluorescence. Upon co-incubation with microbes, these fluorescent metabolite derivatives are incorporated into bacteria, generating unique true-color fingerprints for different bacterial species and different microbiota. A portable spectrometer was also fabricated to automate the colorimetric analysis in combination with a smartphone to conveniently identify different bacterial species and microbiota. Herein, the effectiveness of this system was demonstrated by the identification of certain bacterial species and microbiota in mice with different diseases, such as skin infections and bacteremia. By analyzing the microbiota fingerprints of saliva samples from clinical patients and healthy people, this system was proved to precisely distinguish oral squamous cell carcinoma (OSCC, n = 29) samples from precancerous (n = 10) and healthy (n = 5) samples.

Published
2020

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