Search

Your search keyword '"He, Qiaojun"' showing total 689 results
Start Over Author "He, Qiaojun" Language english
689 results on '"He, Qiaojun"'

19. Fingolimod exerts in vitro anticancer activity against hepatocellular carcinoma cell lines via YAP/TAZ suppression

Author

Du Jiamin, Qian Meijia, Yuan Tao, Zhang Bo, Chen Xueqin, An Ning, He Qiaojun, Yang Bo, Ye Song, and Zhu Hong

Subjects
fingolimod, hepatocellular carcinoma, hippo signalling, yap/taz, Pharmaceutical industry, HD9665-9675
Abstract

Hepatocellular carcinoma (HCC) remains a notably global health challenge with high mortality rates and poor prognosis. The deregulation of the Hippo signalling pathway, especially the overexpression and activation of downstream effector Yes-associated protein (YAP), has been demonstrated to result in the rapid malignant evolution of HCC. In this context, multiple efforts have been dedicated to targeting YAP for HCC therapy, but effective YAP inhibitors are still lacking. In this study, through a YAP-TEAD (8×GTIIC) luciferase reporter assay, we identified fingolimod, an immunomodulatory drug approved for the treatment of multiple sclerosis, as a novel YAP inhibitor. Fingolimod suppressed the proliferation of HCC cell lines by downregulating the protein levels as well as the trans-activating function of YAP. Overall, our current study not only identifies fingolimod as a novel YAP-targeting in hibitor, but also indicates that this clinically-approved drug could be utilized as a potential and feasible therapeutic drug for HCC.

Published
2022
Full Text
View/download PDF

36. Canagliflozin primes antitumor immunity by triggering PD-L1 degradation in endocytic recycling

Author

Ding, Ling, Chen, Xi, Zhang, Wenxin, Dai, Xiaoyang, Guo, Hongjie, Pan, Xiaohui, Xu, Yanjun, Feng, Jianguo, Yuan, Meng, Gao, Xiaomeng, Wang, Jian, Xu, Xiaqing, Li, Sicheng, Wu, Honghai, Cao, Ji, He, Qiaojun, and Yang, Bo

Subjects
Oncology, Experimental, Proteolysis -- Research, Immune response -- Research, Endocytosis -- Research, Membrane proteins -- Health aspects, Lung cancer, Non-small cell -- Drug therapy, Cancer -- Research, Health care industry
Abstract

Understanding the regulatory mechanisms of PD-L1 expression in tumors provides key clues for improving immune checkpoint blockade efficacy or developing novel oncoimmunotherapy. Here, we showed that the FDA-approved sodium- glucose cotransporter-2 (SGLT2) inhibitor canagliflozin dramatically suppressed PD-L1 expression and enhanced T cell-mediated cytotoxicity. Mechanistic study revealed that SGLT2 colocalized with PD-L1 at the plasma membrane and recycling endosomes and thereby prevented PD-L1 from proteasome-mediated degradation. Canagliflozin disturbed the physical interaction between SGLT2 and PD-L1 and subsequently allowed the recognition of PD-L1 by Cullin3SPOP E3 ligase, which triggered the ubiquitination and proteasome-mediated degradation of PD-L1. In mouse models and humanized immune- transformation models, either canagliflozin treatment or SGLT2 silencing significantly reduced PD-L1 expression and limited tumor progression--to a level equal to the PD-1 mAb--which was correlated with an increase in the activity of antitumor cytotoxic T cells. Notably, prolonged progression-free survival and overall survival curves were observed in the group of PD-1 mAb-treated patients with non-small cell lung cancer with high expression of SGLT2. Therefore, our study identifies a regulator of cell surface PD-L1, provides a ready-to-use small-molecule drug for PD-L1 degradation, and highlights a potential therapeutic target to overcome immune evasion by tumor cells., Introduction The remarkable clinical responses of PD-L1/PD-1 blockade confirm the crucial role of the PD-L1/PD-1 axis in tumor immune escape and led to the approval of PD-L1/PD-1 inhibitors by the [...]

Published
2023
Full Text
View/download PDF

43. CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses.

Author

Zhang, Xue, Wu, JingCheng, Luo, Yuanyuan, Wang, Yilin, Wu, Yujie, Xu, Xiaobin, Zhang, Yufang, Kong, Ruiying, Chi, Ying, Sun, Yisheng, Chen, Shuqing, He, Qiaojun, Zhu, Feng, and Zhou, Zhan

Subjects
DATABASES, EPITOPES, CORONAVIRUSES, MONOCLONAL antibodies, IMMUNOGLOBULINS, SARS-CoV-2
Abstract

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

44. SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction.

Author

Guo, Yue, Hu, Haitao, Chen, Wenbo, Yin, Hao, Wu, Jian, Hsieh, Chang-Yu, He, Qiaojun, and Cao, Ji

Subjects
DRUG synergism, BIOLOGICAL networks, DRUG interactions, ANTINEOPLASTIC agents, LUNG cancer, MEDICAL screening
Abstract

Discovering effective anti-tumor drug combinations is crucial for advancing cancer therapy. Taking full account of intricate biological interactions is highly important in accurately predicting drug synergy. However, the extremely limited prior knowledge poses great challenges in developing current computational methods. To address this, we introduce SynergyX, a multi-modality mutual attention network to improve anti-tumor drug synergy prediction. It dynamically captures cross-modal interactions, allowing for the modeling of complex biological networks and drug interactions. A convolution-augmented attention structure is adopted to integrate multi-omic data in this framework effectively. Compared with other state-of-the-art models, SynergyX demonstrates superior predictive accuracy in both the General Test and Blind Test and cross-dataset validation. By exhaustively screening combinations of approved drugs, SynergyX reveals its ability to identify promising drug combination candidates for potential lung cancer treatment. Another notable advantage lies in its multidimensional interpretability. Taking Sorafenib and Vorinostat as an example, SynergyX serves as a powerful tool for uncovering drug-gene interactions and deciphering cell selectivity mechanisms. In summary, SynergyX provides an illuminating and interpretable framework, poised to catalyze the expedition of drug synergy discovery and deepen our comprehension of rational combination therapy. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results