Ze-Yan Zhang

Prof. Dr. Ze-Yan Zhang


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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18 February 2019 in Cell Death & Differentiation
Verified
Journal Article
Closed access
PDF file
QZQi Zhang
Qi Zhang
ZZZe-Yan Zhang
Ze-Yan Zhang
HDHuan Du
Huan Du
SLShang-Ze Li
Shang-Ze Li
RTRongfu Tu
Rongfu Tu
Xiao-Dong ZhangXiao-Dong Zhang
Xiao-Dong Zhang

13 June 2014 in Cell Death & Differentiation
Verified
Journal Article
Closed access
HZH-H Zhang
H-H Zhang
SLS-Z Li
S-Z Li
ZZZe-Yan Zhang
Ze-Yan Zhang
XHX-M Hu
X-M Hu
PHP-N Hou
P-N Hou
Xiao-Dong ZhangXiao-Dong Zhang
Xiao-Dong Zhang

1 November 2017 in European Journal of Medicinal Chemistry
Verified
Journal Article
Closed access
ZZZe-Yan Zhang
Ze-Yan Zhang
XXXingpeng Xiao
Xingpeng Xiao
TSTong Su
Tong Su
JWJinyi Wu
Jinyi Wu
JRJianwei Ren
Jianwei Ren
RDRunlei Du
Runlei Du

29 July 2022 in Nature Communications
Verified
Journal Article
Open access
PDF file
JYJie Yang
Jie Yang
QWQianghu Wang
Qianghu Wang
ZZZe-Yan Zhang
Ze-Yan Zhang
LLLihong Long
Lihong Long
RERavesanker Ezhilarasan
Ravesanker Ezhilarasan
ESErik P. Sulman
Erik P. Sulman
Molecular classification has improved diagnosis and treatment for patients with malignant gliomas. However, classification has relied on individual assays that are both costly and slow, leading to frequent delays in treatment. Here, we propose the use of DNA methylation, as an emerging clinical diagnostic platform, to classify gliomas based on major genomic alterations and provide insight into subtype characteristics. We show that using machine learning models, DNA methylation signatures can accurately predict somatic alterations and show improvement over existing classifiers. The established Unified Diagnostic Pipeline (UniD) we develop is rapid and cost-effective for genomic alterations and gene expression subtypes diagnostic at early clinical phase and improves over individual assays currently in clinical use. The significant relationship between genetic alteration and epigenetic signature indicates broad applicability of our approach to other malignancies.

1 July 2013 in Biochemical and Biophysical Research Communications
Verified
Journal Article
Closed access
SLShang-Ze Li
Shang-Ze Li
HZHui-Hui Zhang
Hui-Hui Zhang
JZJia-Nong Zhang
Jia-Nong Zhang
ZZZe-Yan Zhang
Ze-Yan Zhang
XZXiao-Fei Zhang
Xiao-Fei Zhang
RDRun-Lei Du
Run-Lei Du

24 December 2024 in Journal of Clinical Investigation
Verified
Journal Article
Open access
PDF file
DLDezhi Li
Dezhi Li
KGKe Geng
Ke Geng
YHYuan Hao
Yuan Hao
JGJiajia Gu
Jiajia Gu
SKSaurav Kumar
Saurav Kumar
HZHua Zhang
Hua Zhang
Kirsten rat sarcoma viral oncogene homolog ( KRAS ) is the most frequently mutated oncogene in lung adenocarcinoma, with G12C and G12V being the most predominant forms. Recent breakthroughs in KRAS G12C inhibitors have transformed the clinical management of patients with the G12C mutation and advanced our understanding of the function of this mutation. However, little is known about the targeted disruption of KRAS G12V , partly due to a lack of specific inhibitors. Here, we leverage the degradation tag (dTAG) system to develop a KRAS G12V - transgenic mouse model. We explored the therapeutic potential of KRAS G12V degradation and characterized its effect on the tumor microenvironment (TME). Our study reveals that degradation of KRAS G12V abolished lung and pancreatic tumors in mice and caused a robust inhibition of KRAS-regulated cancer-intrinsic signaling. Importantly, targeted degradation of KRAS G12V reprogrammed the TME toward a stimulatory milieu and drove antitumor immunity, elicited mainly by effector and cytotoxic CD8 + T cells. Our work provides insights into the effect of KRAS G12V degradation on both tumor progression and the immune response, highlighting degraders as a powerful strategy for targeting KRAS -mutant cancers.