Guoqing Liu

Prof. Guoqing Liu


Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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1 January 2012 in Journal of Theoretical Biology
Verified
Journal Article
Closed access
GLGuoqing Liu
Guoqing Liu
JLJia Liu
Jia Liu
XCXiangjun Cui
Xiangjun Cui
LCLu Cai
Lu Cai

28 September 2018 in Frontiers in Genetics
Verified
Journal Article
Open access
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GLGuojun Liu
Guojun Liu
ZCzihao chen
zihao chen
IDIrina G. Danilova
Irina G. Danilova
MBMikhail A. Bolkov
Mikhail A. Bolkov
ITIrina A. Tuzankina
Irina A. Tuzankina
GLGuoqing Liu
Guoqing Liu
Basal and luminal subtypes of muscle-invasive bladder cancer (MIBC) have distinct molecular profiles and heterogeneous clinical behaviors. The interactions between mRNAs and lncRNAs, which might be regulated by miRNAs, have crucial roles in many cancers. However, the miRNA-dependent crosstalk between lncRNA and mRNA in specific MIBC subtypes still remains unclear. In this study, we first classified MIBC into two conservative subtypes using miRNA, mRNA and lncRNA expression data derived from The Cancer Genome Atlas. Then we investigated subtype-related biological pathways and evaluated the subtype classification performance using Decision Trees, Random Forest and eXtreme Gradient Boosting (XGBoost). At last, we explored potential miRNA-mediated lncRNA-mRNA crosstalks based on co-expression analysis. Our results show that: (1) the luminal subtype is primarily characterized by upregulation of metabolism-related pathways while the basal subtype is predominantly characterized by upregulation of epithelial-mesenchymal transition, metastasis, and immune system process-related pathways; (2) the XGBoost prediction model is consistently robust for classification of the molecular subtypes of MIBC across four datasets (The area under the ROC curve > 0.9); (3) the expression levels of the molecules in the miR-200c and miR141-mediated lncRNA-mRNA crosstalks differ considerably between the two subtypes and have close relationships with the prognosis of MIBC. The miR-200c and miR-141-dependent mRNA-lncRNA crosstalks might be of great significance in tumorigenesis and tumor progression and may serve as the novel prognostic predictors and classification markers of MIBC subtypes.

23 August 2023 in Scientific Reports
Verified
Journal Article
Open access
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GLGuoqing Liu
Guoqing Liu
YYYan Yang
Yan Yang
XKXuejia Kang
Xuejia Kang
HXHao Xu
Hao Xu
JAJing Ai
Jing Ai
GLGuojun Liu
Guojun Liu
Metabolic reprogramming is a hallmark of cancers, but pan-cancer level roles of lipid metabolism in cancer development are remains poorly understood. We investigated the possible roles of lipid metabolic genes (LMGs) in 14 cancer types. The results indicate that: (1) there is strong evidence for increased lipid metabolism in THCA and KICH. (2) Although the overall levels of lipid metabolic processes are down-regulated in some cancer types, fatty acid synthase activity and fatty acid elongation are moderately up-regulated in more than half of the cancer types. Cholesterol synthesis is up-regulated in five cancers including KICH, BLCA, COAD, BRCA, UCEC, and THCA. (3) The catabolism of cholesterols, triglycerides and fatty acids is repressed in most cancers, but a specific form of lipid degradation, lipophagy, is activated in THCA and KICH. (4) Lipid storage is enhanced in in kidney cancers and thyroid cancer. (5) Similarly to primary tumors, metastatic tumors tend to up-regulate biosynthetic processes of diverse lipids, but down-regulate lipid catabolic processes, except lipophagy. (6) The frequently mutated lipid metabolic genes are not key LMGs. (7) We established a LMG-based model for predicting cancer prognosis. Our results are helpful in expanding our understanding of the role of lipid metabolism in cancer.

7 April 2016 in Scientific Reports
Verified
Journal Article
Open access
GLGuoqing Liu
Guoqing Liu
YXYongqiang Xing
Yongqiang Xing
HZHongyu Zhao
Hongyu Zhao
JWJianying Wang
Jianying Wang
YSYu Shang
Yu Shang
LCLu Cai
Lu Cai
Nucleosome plays an essential role in various cellular processes, such as DNA replication, recombination and transcription. Hence, it is important to decode the mechanism of nucleosome positioning and identify nucleosome positions in the genome. In this paper, we present a model for predicting nucleosome positioning based on DNA deformation, in which both bending and shearing of the nucleosomal DNA are considered. The model successfully predicted the dyad positions of nucleosomes assembledin vitroand thein vitromap of nucleosomes inSaccharomyces cerevisiae. Applying the model toCaenorhabditis elegansandDrosophila melanogaster, we achieved satisfactory results. Our data also show that shearing energy of nucleosomal DNA outperforms bending energy in nucleosome occupancy prediction and the ability to predict nucleosome dyad positions is attributed to bending energy that is associated with rotational positioning of nucleosomes.


1 October 2012 in Chromosome Research
Verified
Journal Article
Closed access
PDF file
JWJian-Ying Wang
Jian-Ying Wang
JWJingyan Wang
Jingyan Wang
GLGuoqing Liu
Guoqing Liu