longxiang xie

Dr. longxiang xie


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

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

Representative Publications

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GWGuoying Wang
Guoying Wang
ZGZhao GUO
Zhao GUO
XCXiaoyu Chao
Xiaoyu Chao
LXlongxiang xie
longxiang xie
HWHongju Wang
Hongju Wang
Klebsiella pneumoniae is an important gram-negative opportunistic pathogen that causes a variety of infectious diseases, including urinary tract infections, bacteremia, pneumonia, and liver abscesses. With the emergence of multidrug-resistant (MDR) and hypervirulent K. pneumoniae (hvKP) strains, the rapid spread of these clinical strains in geography is particularly worrying. However, the detailed mechanisms of virulence and antibiotic resistance in K. pneumoniae are still not very clear. Therefore, studying and elucidating the pathogenic mechanisms and drug resistance mechanism of K. pneumoniae infection are important parts of current medical research. In this paper, we systematically summarized the virulence, biofilm, and antibiotic tolerance mechanisms of K. pneumoniae, and explored the application of whole genome sequencing and global proteomics, which will provide new clues for clinical treatment of K. pneumoniae.

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Journal Article
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YWYange Wang
Yange Wang
CLChenyang Li
Chenyang Li
XQXinlei Qi
Xinlei Qi
YYYafei Yao
Yafei Yao
LZLu Zhang
Lu Zhang
XGXiangqian Guo
Xiangqian Guo
Blood group antigen is a class of heritable antigenic substances present on the erythrocyte membrane. However, the role of blood group antigens in cancer prognosis is still largely unclear. In this study, we investigated the expression of 33 blood group antigen genes and their association with the prognosis of 30 types of cancers in 31,870 tumor tissue samples. Our results revealed that blood group antigens are abnormally expressed in a variety of cancers. The high expression of these antigen genes was mainly related to the activation of the epithelial-mesenchymal transition (EMT) pathway. High expression of seven antigen genes, i.e., FUT7, AQP1, P1, C4A, AQP3, KEL and DARC, were significantly associated with good OS (Overall Survival) in six types of cancers, while ten genes, i.e., AQP1, P1, C4A, AQP3, BSG, CD44, CD151, LU, FUT2, and SEMA7A, were associated with poor OS in three types of cancers. Kidney renal clear cell carcinoma (KIRC) is associated with the largest number (14 genes) of prognostic antigen genes, i.e., CD44, CD151, SEMA7A, FUT7, CR1, AQP1, GYPA, FUT3, FUT6, FUT1, SLC14A1, ERMAP, C4A, and B3GALT3. High expression of SEMA7A gene was significantly correlated with a poor prognosis of KIRC in this analysis but has not been reported previously. SEMA7A might be a putative biomarker for poor prognosis in KIRC. In conclusion, our analysis indicates that blood group antigens may play functional important roles in tumorigenesis, progression, and especially prognosis. These results provide data to support prognostic marker development and future clinical management.

24 December 2021 in Biology
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ZYZhongyi Yan
Zhongyi Yan
QWqiang wang
qiang wang
SZSusu Zhao
Susu Zhao
LXlongxiang xie
longxiang xie
LZLu Zhang
Lu Zhang
XGXiangqian Guo
Xiangqian Guo
Ovarian cancer is one of the most aggressive and highly lethal gynecological cancers. The purpose of our study is to build a free prognostic web server to help researchers discover potential prognostic biomarkers by integrating gene expression profiling data and clinical follow-up information of ovarian cancer. We construct a prognostic web server OSov (Online consensus Survival analysis for Ovarian cancer) based on RNA expression profiles. OSov is a user-friendly web server which could present a Kaplan–Meier plot, forest plot, nomogram and survival summary table of queried genes in each individual cohort to evaluate the prognostic potency of each queried gene. To assess the performance of OSov web server, 163 previously published prognostic biomarkers of ovarian cancer were tested and 72% of them had their prognostic values confirmed in OSov. It is a free and valuable prognostic web server to screen and assess survival-associated biomarkers for ovarian cancer.