Zhaoli Zhou

Dr. Zhaoli Zhou


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

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

Representative Publications

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10 October 2016 in Journal of Experimental Medicine
Verified
Journal Article
Open access
PDF file
SDSylvain Delaunay
Sylvain Delaunay
FRFrancesca Rapino
Francesca Rapino
LTLars Tharun
Lars Tharun
ZZZhaoli Zhou
Zhaoli Zhou
LHLukas C. Heukamp
Lukas C. Heukamp
PCPierre Close
Pierre Close
Quantitative and qualitative changes in mRNA translation occur in tumor cells and support cancer progression and metastasis. Posttranscriptional modifications of transfer RNAs (tRNAs) at the wobble uridine 34 (U34) base are highly conserved and contribute to translation fidelity. Here, we show that ELP3 and CTU1/2, partner enzymes in U34 mcm5s2-tRNA modification, are up-regulated in human breast cancers and sustain metastasis. Elp3 genetic ablation strongly impaired invasion and metastasis formation in the PyMT model of invasive breast cancer. Mechanistically, ELP3 and CTU1/2 support cellular invasion through the translation of the oncoprotein DEK. As a result, DEK promotes the IRES-dependent translation of the proinvasive transcription factor LEF1. Consistently, a DEK mutant, whose codon composition is independent of U34 mcm5s2-tRNA modification, escapes the ELP3- and CTU1-dependent regulation and restores the IRES-dependent LEF1 expression. Our results demonstrate that the key role of U34 tRNA modification is to support specific translation during breast cancer progression and highlight a functional link between tRNA modification– and IRES-dependent translation during tumor cell invasion and metastasis.

1 August 2018 in Medicine
Verified
Journal Article
Open access
PLPing Li
Ping Li
HRHe Ren
He Ren
YZYan Zhang
Yan Zhang
ZZZhaoli Zhou
Zhaoli Zhou
Clear-cell renal cell carcinoma (ccRCC) is the major renal cell carcinoma subtype, but its postsurgical prognosis varies among individual patients. We used gene expression, machine learning (random forest variable hunting), and Cox regression analysis to develop a risk score model based on 15 genes to predict survival of patients with ccRCC in the The Cancer Genome Atlas dataset (N = 533). We validated this model in another cohort, and analyzed correlations between risk score and other clinical indicators. Patients in the high-risk group had significantly worse overall survival (OS) than did those in the low-risk group (P = 5.6e-16); recurrence-free survival showed a similar pattern. This result was reproducible in another dataset, E-MTAB-1980 (N = 101, P = .00029). We evaluated correlations between risk score and other clinical indicators. Risk was independent of age and sex, but was significantly associated with hemoglobin level, primary tumor size, and grade. Radiation therapy also had no effect on the prognostic value of the risk score. Cox multivariate regression showed risk score to be an important indicator for ccRCC prognosis. We plotted a nomogram for 3-year OS to facilitate use of risk score and other indicators. The risk score model based on expression of the 15 selected genes can predict survival of patients with ccRCC.

1 October 2018 in The International Journal of Biochemistry & Cell Biology
Verified
Journal Article
Closed access
WXWei Xie
Wei Xie
YZYan Zhang
Yan Zhang
YHYuan He
Yuan He
KZKunchi Zhang
Kunchi Zhang
GWguoqing wan
guoqing wan
JWJin Wang
Jin Wang

1 January 2019
Verified
Journal Article
Closed access
WXWei Xie
Wei Xie
YZYan Zhang
Yan Zhang
SZShiwei Zhang
Shiwei Zhang
FWFengxian Wan
Fengxian Wan
KZKunchi Zhang
Kunchi Zhang
JWJin Wang
Jin Wang

29 May 2020 in Experimental and Therapeutic Medicine
Verified
Journal Article
Open access
PDF file
HYHao Yang
Hao Yang
YCYa Chen
Ya Chen
YJYuan Jiang
Yuan Jiang
DWDongliang Wang
Dongliang Wang
JYJun Yan
Jun Yan
ZZZhaoli Zhou
Zhaoli Zhou
Chemoresistance of colorectal cancer (CRC) leads to tumor recurrence and metastasis and new strategies are urgently needed to improve the outcomes of conventional chemotherapy. Sirtuin (SIRT) inhibitors prevent tumor cell growth by increasing the levels of acetylated histones and non‑histones, as well as disrupting survival‑related pathways. The aim of the present study was to determine the effect of SIRT inhibitors on CRC chemotherapy. The CompuSyn software program was used to evaluate the synergistic or antagonistic effects of various drugs, and the status of the protein deacetylation regulatory genes in microarray datasets were analyzed using bioinformatics. In HCT116 cells expressing wild‑type (wt) TP53, SIRT inhibitors were found to act antagonistically with multiple chemotherapeutic agents (cisplatin, 5‑fluorouracil, oxaliplatin, gefitinib, LY294002 and metformin), and decreased the anti‑tumor effects of these agents. By contrast, SIRT inhibitors sensitized TP53‑mutant (mut) SW620 cells to various chemotherapeutic drugs. Bioinformatics analysis indicated that SIRT1 and protein deacetylation related genes were highly expressed in TP53wt CRC cells when compared to TP53mut cells. Therefore, it was hypothesized that the likely mechanism underlying the antagonistic effect of SIRT inhibitors on TP53wt CRC cells was a reduction in the level of stable p53 protein. The present results indicated that divergent TP53 status may translate to a different chemosensitivity profile, and suggested that a combination therapy of SIRT inhibitors and first‑line chemotherapeutic drugs may be beneficial for the treatment of patients with TP53mut CRC.

1 April 2021 in International Journal of Pharmaceutics
Verified
Journal Article
Closed access
YLYue Li
Yue Li
shuncong wangshuncong wang
shuncong wang
XJXiao Jiang
Xiao Jiang
XWXiaoxiong Wang
Xiaoxiong Wang
XZXiang Zhou
Xiang Zhou
XHXiaoyan He
Xiaoyan He