Liyun Xu

Dr. Liyun Xu


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

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

Representative Publications

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5 February 2020 in Cell Proliferation
Verified
Journal Article
Open access
PDF file
WLWen Liu
Wen Liu
HWHongxing Wang
Hongxing Wang
FBFuxiang Bai
Fuxiang Bai
LDLu Ding
Lu Ding
YHYanyan Huang
Yanyan Huang
LGLi-fen Gao
Li-fen Gao
Objectives: Interleukin‐6 (IL‐6) is critical for the development of non‐small‐cell lung cancer (NSCLC). Recently, we identified T‐cell immunoglobulin domain and mucin domain 4 (TIM‐4) as a new pro‐growth player in NSCLC progression. However, the role of TIM‐4 in IL‐6‐promoted NSCLC migration, invasion and epithelial‐to‐mesenchymal transition (EMT) remains unclear.Materials and Methods: Expressions of TIM‐4 and IL‐6 were both evaluated by immunohistochemical staining in NSCLC tissues. Real‐time quantitative PCR (qPCR), Western blot, flow cytometry and RT‐PCR were performed to detect TIM‐4 expression in NSCLC cells with IL‐6 stimulation. The roles of TIM‐4 in IL‐6 promoting migration and invasion of NSCLC were detected by transwell assay. EMT‐related markers were analysed by qPCR and Western blot in vitro, and metastasis was evaluated in BALB/c nude mice using lung cancer metastasis mouse model in vivo.Results: High IL‐6 expression was identified as an independent predictive factor for TIM‐4 expression in NSCLC tissues. NSCLC patients with TIM‐4 and IL‐6 double high expression showed the worst prognosis. IL‐6 promoted TIM‐4 expression in NSCLC cells depending on NF‐κB signal pathway. Both TIM‐4 and IL‐6 promoted migration, invasion and EMT of NSCLC cells. Interestingly, TIM‐4 knockdown reversed the role of IL‐6 in NSCLC and IL‐6 promoted metastasis of NSCLC by up‐regulating TIM‐4 via NF‐κB.Conclusions: TIM‐4 involves in IL‐6 promoted migration, invasion and EMT of NSCLC.

1 February 2015 in Immunology Letters
Verified
Journal Article
Closed access
YHYanyan Huang
Yanyan Huang
DCDongdong Chen
Dongdong Chen
JHJianying He
Jianying He
JCJun Cai
Jun Cai
KSKai Shen
Kai Shen
LXLiyun Xu
Liyun Xu

31 October 2014 in Inflammation
Verified
Journal Article
Closed access
PDF file
DCDongdong Chen
Dongdong Chen
JHJianying He
Jianying He
CLChangchang Lu
Changchang Lu
JZJihang Zhou
Jihang Zhou
KFKexin Fang
Kexin Fang
LXLiyun Xu
Liyun Xu

1 January 2015
Verified
Journal Article
Closed access
LXLiyun Xu
Liyun Xu
NCNgdong Chen
Ngdong Chen
CLChangchang Lu
Changchang Lu
XLXiaoguang Liu
Xiaoguang Liu
GWGuoqing Wu
Guoqing Wu
YZYongkui Zhang
Yongkui Zhang

1 January 2025 in American Journal of Cancer Research
Verified
Journal Article
Closed access
XZXinyue Zhang
Xinyue Zhang
SCSitong Chen
Sitong Chen
MSMiao Shi
Miao Shi
JLJinjin Lou
Jinjin Lou
QHQichen Huang
Qichen Huang
LXLiyun Xu
Liyun Xu
Monocytes, a crucial element of the innate immune system, act as the primary cells in the body’s immune response. Approved by the International Federation for Immunology in 2010, monocytes are categorized into three subsets based on the degree of cell surface molecule expression: classical monocytes, intermediate monocytes, and non-classical monocytes. Generally, different monocyte subsets have diverse responsibilities and can mutually transform to maintain the stability of the internal environment. Distinctions in functional characteristics and associations with diseases have been identified among the various monocyte subsets. This review aims to describe the expression and functions of monocytes in detail and discuss their roles in cancer immunity, which offers a novel approach for the diagnosis, treatment, and prognosis of tumors by exploring and summarizing the distribution of monocyte subsets in tumors. By delving into the distribution and functional characteristics of different monocyte subsets in tumors, it holds the promise of guiding individualized therapies and more precise tumor management.

31 August 2025 in Cancer Control
Verified
Journal Article
Open access
YHYanyan Huang
Yanyan Huang
FHFei Huang
Fei Huang
XZXinyue Zhang
Xinyue Zhang
CLChunyan Li
Chunyan Li
JLJinjin Lou
Jinjin Lou
LXLiyun Xu
Liyun Xu
Introduction: Tertiary lymphoid structures (TLSs) have been associated with the prognosis of various solid tumors. However, the association between TLSs and the prognosis of invasive lung adenocarcinoma (IAC) remains unclear in terms of location, density, and maturity. Methods: We retrospectively reviewed the clinicopathological characteristics of 750 patients with IAC. The density of TLSs in various tumor regions, as well as their maturation status, was examined by pathologists. The X-tile software was employed to determine the optimal cut-off values for the intratumoral and peritumoral TLS density based on overall survival. A threshold of 1.33 TLSs/cm 2 was used to distinguish between low- and high-density intratumoral TLSs, while a threshold of 1.39 TLSs/cm 2 was applied for peritumoral TLSs. Tissue slides exhibiting no or early TLSs demonstrated low maturation levels, while those with at least one lymphoid follicle indicated high maturation. We analyzed the correlation between TLS characteristics and clinicopathological parameters and assessed the impact of multiple clinicopathological factors on patient prognosis using Cox regression and Kaplan–Meier analyses. A multivariate logistic regression analysis model was used to explore predictive factors for the density of intratumoral TLSs and TLS maturity in patients with IAC. Results: Lower intratumoral TLS density, increased TLS maturation, lymph node metastasis, and the presence of solid (≥30%) and micropapillary (≥5%) pathological subtypes were identified as poor independent prognostic factors for overall survival in patients with IAC. Solid (≥30%) and micropapillary (≥5%) pathological subtypes were predictive factors for lower intratumoral TLS density (hazard ratio [HR] = 0.434, 95% confidence interval [CI] = 0.267-0.706, P = 0.001), while higher TLSs maturity was associated with a smoking history or pleural invasion (HR = 1.655, 95% CI = 1.048-2.613, P = 0.031; HR = 1.933, 95% CI = 1.054-3.546, P = 0.033). Conclusions: Both intratumoral TLS density and TLS maturation are independent prognostic factors for IAC. Additionally, higher TLS density predicted better prognosis, whereas greater TLS maturity predicted worse prognosis.