Xiaozhou He

Xiaozhou He


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
Open access
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XTXuesong Tian
Xuesong Tian
FHFei Hua
Fei Hua
HSHarleen K. K. Sandhu
Harleen K. K. Sandhu
DCDongman Chao
Dongman Chao
GBGianfranco Balboni
Gianfranco Balboni
YXYing Xia
Ying Xia
We investigated whether δ-opioid receptor (DOR)-induced neuroprotection involves the brain-derived neurotrophic factor (BDNF) pathway. We studied the effect of DOR activation on the expression of BDNF and other proteins in the cortex of C57BL/6 mice exposed to hypoxia (10% of oxygen) for 1–10 days. The results showed that: (1) 1-day hypoxia had no appreciable effect on BDNF expression, while 3- and 10-day hypoxia progressively decreased BDNF expression, resulting in 37.3% reduction (p < 0.05) after 10-day exposure; (2) DOR activation with UFP-512 (1 mg/kg, i.p., daily) partially reversed the hypoxia-induced reduction of BDNF expression in the 3- or 10-day exposed cortex; (3) DOR activation partially reversed the hypoxia-induced reduction in functional TrkB (140-kDa) and attenuated hypoxia-induced increase in truncated TrkB (90-kDa) in the 3- or 10-day hypoxic cortex; and (4) prolonged hypoxia (10 days) significantly increased TNF-α level and decreased CD11b expression in the cortex, which was completely reversed following DOR activation; and (5) there was no significant change in pCREB and pATF-1 levels in the hypoxic cortex. We conclude that prolonged hypoxia down-regulates BDNF-TrkB signaling leading to an increase in TNF-α in the cortex, while DOR activation up-regulates BDNF-TrkB signaling thereby decreasing TNF-α levels in the hypoxic cortex.

1 July 2018 in OncoTargets and Therapy
Verified
Journal Article
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XHXu Han
Xu Han
LPLianhua Piao
Lianhua Piao
QZQianfeng Zhuang
Qianfeng Zhuang
XYXiaofeng Yuan
Xiaofeng Yuan
ZLZhiwei Liu
Zhiwei Liu
XHXiaozhou He
Xiaozhou He
The growing number of findings demonstrate that nuclear receptor suppressor of variegation, enhancer of zeste, and trithorax domain-containing 3 (NSD3) is amplified and overexpressed in multiple cancer types. Nevertheless, the biological roles of NSD3 in carcinogenesis have not been well understood. In this review, we summarize the current knowledge on the mechanisms underlying NSD3 regulation in different cancers. In addition, NSD3 may serve as a potential druggable target for selective cancer therapy in the future.

23 February 2025 in Cell Death & Disease
Verified
Journal Article
Open access
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YPYihui Pan
Yihui Pan
SLShuang Liu
Shuang Liu
GSGuannan Shu
Guannan Shu
MCMinyu Chen
Minyu Chen
LFLiangmin Fu
Liangmin Fu
XHXiaozhou He
Xiaozhou He
Axitinib resistance remains a serious challenge in the treatment of advanced renal cell carcinoma (RCC), and the underlying mechanisms are not fully understood. Here, we constructed an in vivo axitinib-resistant RCC model and identified the long non-coding RNA STX17-DT as a driver of therapy resistance in RCC. The expression of STX17-DT was significantly elevated in axitinib-resistant RCC cells and correlated with poorer prognosis in RCC patients. Elevated levels of STX17-DT contributed to the development of resistance to axitinib both in vitro and in vivo. Mechanistically, STX17-DT modulated the stability of IFI6 mRNA by recruiting and binding to hnRNPA1, leading to decreased accumulation of mitochondrial reactive oxygen species (ROS) and attenuated ferroptosis. Meanwhile, STX17-DT was packaged into extracellular vesicles through hnRNPA1, thus transmitting axitinib resistance to other cells. Compared with axitinib monotherapy, combined treatment of axitinib and STX17-DT-targeted in vivo siRNA demonstrated enhanced therapeutic efficacy. These findings indicate a novel molecular mechanism of axitinib resistance in RCC and suggest that STX17-DT may serve as a prognostic indicator and potential therapeutic target to overcome resistance to targeted therapy.

23 July 2024 in Scientific Reports
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Journal Article
Open access
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ZXZhaoyu Xing
Zhaoyu Xing
LCLi Cui
Li Cui
YFYuehua Feng
Yuehua Feng
YYYang Yang
Yang Yang
XHXiaozhou He
Xiaozhou He
This study investigated the impact of novel copper ionophores on the prognosis of clear cell renal cell carcinoma (ccRCC) and the tumor microenvironment (TME). The differential expression of 10 cuproptosis and 40 TME-pathway-related genes were measured in 531 tumor samples and 71 adjacent kidney samples in The Cancer Genome Atlas database. A risk score model was constructed with LASSO cox to predict the prognosis of ccRCC patients. Forest plot and function enrichment were used to study the biological function of the key genes in depth. The study found that the risk score model accurately predicted the prognosis of ccRCC patients. Patients with high scores had higher immune responses with a higher proportion of anti-tumor lymphocytes and a lower proportion of immunosuppressive M2-like macrophages. However, the high-score group also exhibited a higher proportion of T follicular helper cells and regulatory T cells. These results suggest that cuproptosis-based therapy may be worth further investigation for the treatment of ccRCC and TME. Subsequently, by using RNAi, we established the stable depletion models of FDX1 and PDHB in ccRCC cell lines 786-O and ACHN. Through CCK8, colony formation, and Transwell assays, we observed that the knockdown of FDX1 and PDHB could significantly reduce the capabilities of proliferation and migration in ccRCC cells. In conclusion, this study illuminates the potential effectiveness of copper ionophores in the treatment of ccRCC, with higher risk scores correlating with better TME immune responses. It sets the stage for future cuproptosis-based therapy research in ccRCC and other cancers, focusing on copper’s role in TME.

1 January 2014 in Transplantation Proceedings
Verified
Journal Article
Closed access
DXD. Xue
D. Xue
XHXiaozhou He
Xiaozhou He
CZC. Zhou
C. Zhou

20 June 2014 in Chinese Medical Journal
Verified
Journal Article
Closed access
XLXuegan Lian
Xuegan Lian
HHHongwei Huang
Hongwei Huang
JWJian Wu
Jian Wu
NWNing Wei
Ning Wei
JZJianzhong Zhou
Jianzhong Zhou
XHXiaozhou He
Xiaozhou He