Kezhen Li

Prof. Dr. Kezhen Li

Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

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

Representative Publications

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10 May 2022 in Nature Communications
Verified
Journal Article
Open access
PDF file
LZLiyuan Zhou
Liyuan Zhou
QQQiongzi Qiu
Qiongzi Qiu
QZQing Zhou
Qing Zhou
JLJianwei Li
Jianwei Li
MYMengqian Yu
Mengqian Yu
YLYan Lu
Yan Lu
Integration of human papillomavirus (HPV) DNA into the human genome is considered as a key event in cervical carcinogenesis. Here, we perform comprehensive characterization of large-range virus-human integration events in 16 HPV16-positive cervical tumors using the Nanopore long-read sequencing technology. Four distinct integration types characterized by the integrated HPV DNA segments are identified with Type B being particularly notable as lacking E6/E7 genes. We further demonstrate that multiple clonal integration events are involved in the use of shared breakpoints, the induction of inter-chromosomal translocations and the formation of extrachromosomal circular virus-human hybrid structures. Combined with the corresponding RNA-seq data, we highlight LINC00290, LINC02500 and LENG9 as potential driver genes in cervical cancer. Finally, we reveal the spatial relationship of HPV integration and its various structural variations as well as their functional consequences in cervical cancer. These findings provide insight into HPV integration and its oncogenic progression in cervical cancer.

27 July 2021 in Nature Communications
Verified
Journal Article
Open access
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PWPeng Wu
Peng Wu
DCDongsheng Chen
Dongsheng Chen
WDWencheng Ding
Wencheng Ding
PWPing Wu
Ping Wu
HHHongyan Hou
Hongyan Hou
GCGang Chen
Gang Chen
The outbreak of coronavirus disease 2019 (COVID-19) is a global health emergency. Various omics results have been reported for COVID-19, but the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here we collect blood samples from 231 COVID-19 patients, prefiltered to exclude those with selected comorbidities, yet with symptoms ranging from asymptomatic to critically ill. Using integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles, we report a trans-omics landscape for COVID-19. Our analyses find neutrophils heterogeneity between asymptomatic and critically ill patients. Meanwhile, neutrophils over-activation, arginine depletion and tryptophan metabolites accumulation correlate with T cell dysfunction in critical patients. Our multi-omics data and characterization of peripheral blood from COVID-19 patients may thus help provide clues regarding pathophysiology of and potential therapeutic strategies for COVID-19.

20 November 2023 in Nature Genetics
Verified
Journal Article
Closed access
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JFJunpeng Fan
Junpeng Fan
FLFunian Lu
Funian Lu
TQTianyu Qin
Tianyu Qin
WPWenju Peng
Wenju Peng
XZXucui Zhuang
Xucui Zhuang
CSChaoyang Sun
Chaoyang Sun

26 March 2021 in Communications Biology
Verified
Journal Article
Open access
PDF file
QLQiuyue Liao
Qiuyue Liao
QZQi Zhang
Qi Zhang
XFXue Feng
Xue Feng
HHHaibo Huang
Haibo Huang
HXHaohao Xu
Haohao Xu
KLKezhen Li
Kezhen Li
Approaches to reliably predict the developmental potential of embryos and select suitable embryos for blastocyst culture are needed. The development of time-lapse monitoring (TLM) and artificial intelligence (AI) may help solve this problem. Here, we report deep learning models that can accurately predict blastocyst formation and usable blastocysts using TLM videos of the embryo’s first three days. The DenseNet201 network, focal loss, long short-term memory (LSTM) network and gradient boosting classifier were mainly employed, and video preparation algorithms, spatial stream and temporal stream models were developed into ensemble prediction models called STEM and STEM+. STEM exhibited 78.2% accuracy and 0.82 AUC in predicting blastocyst formation, and STEM+ achieved 71.9% accuracy and 0.79 AUC in predicting usable blastocysts. We believe the models are beneficial for blastocyst formation prediction and embryo selection in clinical practice, and our modeling methods will provide valuable information for analyzing medical videos with continuous appearance variation.

19 August 2022 in Frontiers in Endocrinology
Verified
Journal Article
Open access
JWJiachen Wu
Jiachen Wu
YLYang Liu
Yang Liu
YSYinhua Song
Yinhua Song
LWLingjuan Wang
Lingjuan Wang
HAhui ji Ai
hui ji Ai
KLKezhen Li
Kezhen Li
Progressive loss of physiological integrity and accumulation of degenerative changes leading to functional impairment and increased susceptibility to diseases are the main features of aging. The ovary, the key organ that maintains female reproductive and endocrine function, enters aging earlier and faster than other organs and has attracted extensive attention from society. Ovarian aging is mainly characterized by the progressive decline in the number and quality of oocytes, the regulatory mechanisms of which have yet to be systematically elucidated. This review discusses the hallmarks of aging to further highlight the main characteristics of ovarian aging and attempt to explore its clinical symptoms and underlying mechanisms. Finally, the intervention strategies related to aging are elaborated, especially the potential role of stem cells and cryopreservation of embryos, oocytes, or ovarian tissue in the delay of ovarian aging.

21 September 2011 in BMC Cancer
Verified
Journal Article
Open access
PDF file
Xia XiXia Xi
Xia Xi
QMQuanfu Ma
Quanfu Ma
XLXiao Li
Xiao Li
TJTeng Ji
Teng Ji
PCPingbo Chen
Pingbo Chen
DMDing Ma
Ding Ma
Background: P21(WAF1/Cip1) binds to cyclin-dependent kinase complexes and inhibits their activities. It was originally described as an inhibitor of cancer cell proliferation. However, many recent studies have shown that p21 promotes tumor progression when accumulated in the cell cytoplasm. So far, little is known about the correlation between cytoplasmic p21 and drug resistance. This study was aimed to investigate the role of p21 in the cisplatin resistance of ovarian cancer. Methods: RT-PCR, western blot and immunofluorescence were used to detect p21 expression and location in cisplatin-resistant ovarian cancer cell line C13* and its parental line OV2008. Regulation of cytoplasmic p21 was performed through transfection of p21 siRNA, Akt2 shRNA and Akt2 constitutively active vector in the two cell lines; their effects on cisplatin-induced apoptosis were evaluated by flow cytometry. Tumor tissue sections of clinical samples were analyzed by immunohistochemistry. Results: p21 predominantly localizes to the cytoplasm in C13* compared to OV2008. Persistent exposure to low dose cisplatin in OV2008 leads to p21 translocation from nuclear to cytoplasm, while it had not impact on p21 localization in C13*. Knockdown of cytoplasmic p21 by p21 siRNA transfection in C13* notably increased cisplatin-induced apoptosis through activation of caspase 3. Inhibition of p21 translocation into the cytoplasm by transfection of Akt2 shRNA into C13* cells significantly increased cisplatin-induced apoptosis, while induction of p21 translocation into the cytoplasm by transfection of constitutively active Akt2 in OV2008 enhanced the resistance to cisplatin. Immunohistochemical analysis of clinical ovarian tumor tissues demonstrated that cytoplasmic p21 was negatively correlated with the response to cisplatin based treatment. Conclusions: Cytoplasmic p21 is a novel biomarker of cisplatin resistance and it may represent a potential therapeutic target for ovarian tumors that are refractory to conventional treatment.