Tengfei Chao

Dr. Tengfei Chao


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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7 December 2023 in BMC Cancer
Verified
Journal Article
Open access
PDF file
JGJing Gao
Jing Gao
JLJianqiang Lan
Jianqiang Lan
HLHaiyan Liao
Haiyan Liao
FYFang Yang
Fang Yang
PQPei Qiu
Pei Qiu
YZYu Zhu
Yu Zhu
Gastrointestinal (GI) cancers (gastric cancer, oesophageal cancer, liver cancer, colorectal cancer, etc.) are the most common cancers with the highest morbidity and mortality in the world. The therapy for most GI cancers is difficult and is associated with a poor prognosis. In China, upper GI cancers, mainly gastric cancer (GC) and oesophageal cancer (EC), are very common due to Chinese people’s characteristics, and more than half of patients are diagnosed with distant metastatic or locally advanced disease. Compared to other solid cancers, such as lung cancer and breast cancer, personalized therapies, especially targeted therapy and immunotherapy, in GC and EC are relatively lacking, leading to poor prognosis. For a long time, most studies were carried out by using in vitro cancer cell lines or in vivo cell line-derived xenograft models, which are unable to reproduce the characteristics of tumours derived from patients, leading to the possible misguidance of subsequent clinical validation. The patient-derived models represented by patient-derived organoid (PDO) and xenograft (PDX) models, known for their high preservation of patient tumour features, have emerged as a very popular platform that has been widely used in numerous studies, especially in the research and development of antitumour drugs and personalized medicine. Herein, based on some of the available published literature, we review the research and application status of PDO and PDX models in GC and EC, as well as detail their future challenges and prospects, to promote their use in basic and translational studies or personalized therapy.

1 September 2016 in Biochemical and Biophysical Research Communications
Verified
Journal Article
Closed access
JZJiaxuan Zhang
Jiaxuan Zhang
BSBeibei Su
Beibei Su
CGChen Gong
Chen Gong
QXQingsongg Xi
Qingsongg Xi
TCTengfei Chao
Tengfei Chao

17 May 2024 in Pharmaceuticals
Verified
Journal Article
Open access
PDF file
YJYizhi Jiang
Yizhi Jiang
HZHaiting Zhou
Haiting Zhou
JLJunxia Liu
Junxia Liu
WHWentao Ha
Wentao Ha
XXXiaohui Xia
Xiaohui Xia
HXHuihua Xiong
Huihua Xiong
Precise targeting has become the main direction of anti-cancer drug development. Trophoblast cell surface antigen 2 (Trop-2) is highly expressed in different solid tumors but rarely in normal tissues, rendering it an attractive target. Trop-2-targeted antibody-drug conjugates (ADCs) have displayed promising efficacy in treating diverse solid tumors, especially breast cancer and urothelial carcinoma. However, their clinical application is still limited by insufficient efficacy, excessive toxicity, and the lack of biological markers related to effectiveness. This review summarizes the clinical trials and combination therapy strategies for Trop-2-targeted ADCs, discusses the current challenges, and provides new insights for future advancements.

19 May 2025 in BMC Cancer
Verified
Journal Article
Open access
PDF file
LXLei Xu
Lei Xu
TXTing Xiao
Ting Xiao
TCTengfei Chao
Tengfei Chao
HXHuihua Xiong
Huihua Xiong
WYWei Yao
Wei Yao
Hepatocellular Carcinoma (HCC) is related to dysregulated lipid metabolism and immunosuppressive microenvironment. This study developed a genetic risk model using lipid metabolism-related genes to predict survival and immune patterns in HCC patients. Differentially expressed genes (DEGs) related to lipid metabolism were identified in HCC via the TCGA-LIHC dataset. A risk model for survival prediction was constructed via DEGs related to survival. The immune signature associated with the risk model was also evaluated by the CIBERSORT algorithm, tumor immune dysfunction and exclusion algorithm, and single sample gene set enrichment analysis. This study identified six lipid metabolism-related genes, ADH4, LCAT, CYP2C9, CYP17A1, LPCAT1, and ACACA, to construct a lipid metabolism-related gene risk model that can divide HCC patients into low- and high-risk groups. Internal and external validation verified that the risk model could be a signature that could effectively predict HCC patient prognosis. High-risk patients showed disrupted immune cell profiles, reduced tumor-killing capacity, and increased expression of immune checkpoint genes. However, they responded more favorably to immune checkpoint inhibitor (ICB) therapy. The top ten hub genes related to the risk model were associated with tumor progression and deteriorating prognosis. In vitro experiments verified that the downregulation of the top 1 hub gene CDK1 was correlated to the HCC cell proliferation. The risk model constructed using lipid metabolism-related genes could effectively predict prognosis and was related to the immunosuppressive microenvironment and ICB immunotherapy. The hub genes related to the risk model were potential therapeutic targets.

10 June 2023 in Pharmaceutics
Verified
Journal Article
Open access
PDF file
JLJunxia Liu
Junxia Liu
TCTengfei Chao
Tengfei Chao
YLYingying Liu
Yingying Liu
CGChen Gong
Chen Gong
YZYinan Zhang
Yinan Zhang
HXHuihua Xiong
Huihua Xiong
Cancer is a top global public health concern. At present, molecular targeted therapy has emerged as one of the main therapies for cancer, with high efficacy and safety. The medical world continues to struggle with the development of efficient, extremely selective, and low-toxicity anticancer medications. Heterocyclic scaffolds based on the molecular structure of tumor therapeutic targets are widely used in anticancer drug design. In addition, a revolution in medicine has been brought on by the quick advancement of nanotechnology. Many nanomedicines have taken targeted cancer therapy to a new level. In this review, we highlight heterocyclic molecular-targeted drugs as well as heterocyclic-associated nanomedicines in cancer.

6 November 2023 in Cancer Biology & Medicine
Verified
Journal Article
Open access
PDF file
QLQingxu Liu
Qingxu Liu
LLLong Li
Long Li
WQWan Qin
Wan Qin
TCTengfei Chao
Tengfei Chao
Cancer remains a significant global health challenge with limited treatment options beyond systemic therapies, such as chemotherapy, radiotherapy, and molecular targeted therapy. Immunotherapy has emerged as a promising therapeutic modality but the efficacy has plateaued, which therefore provides limited benefits to patients with cancer. Identification of more effective approaches to improve patient outcomes and extend survival are urgently needed. Drug repurposing has emerged as an attractive strategy for drug development and has recently garnered considerable interest. This review comprehensively analyses the efficacy of various repurposed drugs, such as transforming growth factor-beta (TGF-β) inhibitors, metformin, receptor activator of nuclear factor-κB ligand (RANKL) inhibitors, granulocyte macrophage colony-stimulating factor (GM-CSF), thymosin α1 (Tα1), aspirin, and bisphosphonate, in tumorigenesis with a specific focus on their impact on tumor immunology and immunotherapy. Additionally, we present a concise overview of the current preclinical and clinical studies investigating the potential therapeutic synergies achieved by combining these agents with immune checkpoint inhibitors.