Nanbin Liu

Mr. Nanbin Liu

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

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

Representative Publications

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1 March 2022 in Journal of Trace Elements in Medicine and Biology
Verified
Journal Article
Open access
RQRan Qi
Ran Qi
YBYixuan Bai
Yixuan Bai
YWYuhua Wei
Yuhua Wei
NLNanbin Liu
Nanbin Liu
BSBaomin Shi
Baomin Shi
Ferroptosis is a newly recognized form of cell death that is distinct from apoptosis, necrosis, autophagy in morphology, biochemistry, and heredity. The basic process of ferroptosis involves disordered permeability of plasma membrane, which is caused by abnormal accumulation of lipids and reactive oxygen species (ROS). The regulatory mechanism of ferroptosis is important due to its involvement in tumor progression, neurotoxicity, neurodegenerative diseases, acute renal failure, and ischemia-reperfusion injury. Recent studies have shown that in ferroptosis metabolism, non-coding RNAs (ncRNAs) can interfere with multiple signaling pathways at both the pre-transcriptional and post-transcriptional levels. Despite great progress, current research on the mechanism of ncRNAs and ferroptosis remains insufficient. This review provides an overview of the main mechanisms and targets of ferroptosis and focuses on the mechanisms of non-coding RNA regulation. Analyzing the deficiencies in current research may provide ideas for future studies to investigate.

31 October 2023 in Cancers
Verified
Journal Article
Open access
PDF file
NLNanbin Liu
Nanbin Liu
HZHailong Zhang
Hailong Zhang
CZChunli Zhang
Chunli Zhang
ZLZeyu Li
Zeyu Li
LHLimin Huang
Limin Huang
HTHongwei Tian
Hongwei Tian
DHX37, a member of the DEAD/H-box RNA helicase family, has been implicated in various diseases, including tumors. However, the biological characteristics and prognostic significance of DHX37 in HCC remain unclear. In this study, we use R software 3.6.3 and multiple bioinformatics analysis tools, such as GDSC, HPA, STRING, TISCH, and TIMER2, to analyze the characterization and function of DHX37 in HCC. In addition, Western blot (WB) and immunohistochemistry (IHC) based on clinical samples validated some of the findings. DHX37 was more highly expressed in HCC samples compared to adjacent non-tumor tissues. Higher DHX37 expression is correlated with various clinicopathological characteristics in HCC, including AFP, adjacent hepatic tissue inflammation, histologic grade, T stage, and pathologic stage. Survival analysis revealed that the high DHX37 group had significantly shorter overall survival (OS), progress-free interval (PFI), and disease-specific survival (DSS) compared to the low DHX37 group. By analyzing the correlation between DHX37 and the IC50 of chemotherapeutic drugs, the results showed that DHX37 expression level was negatively correlated with the IC50 of 11 chemotherapeutic drugs. Further analysis indicated that DHX37 and its co-expressed genes may play important roles in activating the cell cycle, DNA repair, chemokine signaling pathways, and regulating the immune response, which leads to a poor prognosis in HCC. High expression of DHX37 is an independent risk factor for poor prognosis in HCC, and DHX37 is expected to be a potential target to inhibit tumor progression. Targeting DHX37 may enhance chemotherapeutic drug sensitivity and immunotherapeutic efficacy in HCC.

22 July 2026 in European Journal of Medical Research
Verified
Journal Article
Open access
PDF file
XLXiaona Liu
Xiaona Liu
YQYajie Qi
Yajie Qi
XDXinyi Dang
Xinyi Dang
PZPengpeng Zhu
Pengpeng Zhu
NLNanbin Liu
Nanbin Liu
QWQian Wang
Qian Wang
BUB3 is a core component of the spindle assembly checkpoint (SAC) that is indispensable for faithful chromosome segregation and mitotic progression. Althou

6 August 2026 in Molecular and Cellular Probes
Verified
Journal Article
Open access
CZChongyu Zhang
Chongyu Zhang
QWQiankun Wang
Qiankun Wang
MZMengchen Zhu
Mengchen Zhu
XLXiaowen Li
Xiaowen Li
JLJi Li
Ji Li
NLNanbin Liu
Nanbin Liu

14 May 2026 in Cancer Cell International
Verified
Journal Article
Open access
YQYajie Qi
Yajie Qi
KLKun Li
Kun Li
PLPincheng Li
Pincheng Li
JYJianyu Yan
Jianyu Yan
SFShuyue Feng
Shuyue Feng
NLNanbin Liu
Nanbin Liu
Liver hepatocellular carcinoma (LIHC) is a common malignancy, yet the core genes driving its progression and potential therapeutic targets remain insufficiently explored. Ribosome biogenesis (RB) is a critical biological process linked to various cancers; however, its systematic role in LIHC remains unclear. This study integrated LIHC single-cell RNA-Seq, bulk RNA-Seq, and spatial transcriptomic data with ribosome biogenesis-related gene sets to construct a single-cell atlas of LIHC. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to characterize myeloid cell subsets. Furthermore, an LIHC prognostic risk model based on RB-related genes was developed using 117 machine-learning algorithm combinations. Key findings were subsequently corroborated through experimental validation and clinical sample analysis. We identified a distinct macrophage subpopulation with high ribosome biogenesis activity, termed ribosome biogenesis-active macrophages (RAMs). These cells exhibited strong communication with inflammatory macrophages, potentially mediated by MIF-related receptor-ligand interactions. We further constructed an 8-gene prognostic model (PA2G4, GNL2, PWP1, DDX49, NOC4L, GDI2, CST7, and RCL1), which showed good predictive performance. Drug sensitivity analysis suggested that the high-risk group may be more responsive to several agents, including docetaxel. Among these genes, GNL2 was selected for further investigation. Elevated GNL2 expression was associated with increased stemness features in myeloid cells. Molecular docking analysis identified several candidate compounds with potential binding affinity to GNL2. Functionally, GNL2 knockdown in macrophages reduced TGF-β and TNF-α expression and was associated with decreased proliferation, migration, and invasion of LIHC cells. We identified a highly active ribosome biogenesis-macrophage subpopulation (RAM), and constructed a robust risk model to aid in the diagnosis, prognosis, and treatment of LIHC. GNL2 is associated with increased expression of TGF-β and TNF-α and may contribute to LIHC progression.