Recent Progress in Understanding the Action of Natural Compounds at Novel Therapeutic Drug Targets for the Treatment of Liver Cancer

Yao, Zheng; Zhang, Wenhui; Xu, Lin; Zhou, Hua; Yuan, Man; Xu, Hong‐Xi

doi:10.3389/fonc.2021.795548

Cited by 23 publications

(10 citation statements)

References 173 publications

(225 reference statements)

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“…With the promotion of the unique theory of traditional Chinese medicine and the highlight of clinical curative effect, more and more traditional Chinese medicines and their monomers are used in clinical and scientific research practice and show good synergistic and attenuated effects on malignant tumors. [ 3–5 ] Matrine is one of the main components of Sophora flavescens and a quinoline alkaloid compound with the chemical formula C 15 H 24 N 2 O. Matrine has been reported to have anti‐inflammatory, antiviral, antifibrosis, antiarrhythmic, and immunosuppressive pharmacology features, which could be used to treat viral hepatitis, cirrhosis, arrhythmia, skin inflammation, and other diseases. [ 6 ] Furthermore, matrine could inhibit the proliferation, differentiation, metastasis, angiogenesis, and Warburg effect in a variety of malignant cancer cells.…”

Section: Introductionmentioning

confidence: 99%

Matrine suppresses liver cancer progression and the Warburg effect by regulating the circROBO1/miR‐130a‐5p/ROBO1 axis

Huang

et al. 2023

J Biochem & Molecular Tox

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Matrine, an effective component extracted from the traditional Chinese herb, Sophora flavescens, has been indicated to exert antitumor activity in different types of cancer. However, the role and precise mechanism of matrine in the progression of liver cancer remains largely unclear. Cell viability, cell proliferation, cell apoptosis, and Warburg effect were estimated by cell counting kit‐8 assay, colony formation assay, flow cytometry assay, and glucose uptake and lactate production assay, respectively. The candidate Circular RNAs (circRNAs) were screened by integrating the Gene Expression Omnibus database (GSE155949) analysis with the online program GEO2R. A quantitative real‐time polymerase chain reaction was employed to test the expression of circRNA circROBO1, microRNA miR‐130a‐5p, and roundabout homolog 1 (ROBO1). The interaction of circROBO1/miR‐130a‐5p/ROBO1 axis was predicted and confirmed by bioinformatics analysis, a dual‐luciferase reporter assay, and an RNA pull‐down assay. A xenograft mouse model was employed to reveal the role of matrine in vivo. Matrine repressed liver cancer cell viability, proliferation, and Warburg effect, but increased cell apoptosis in vitro. CircROBO1 and ROBO1 were upregulated, but miR‐130a‐5p was downregulated in liver cancer tissues. Additionally, matrine could reduce the expression of circROBO1 and ROBO1, and increase the expression of miR‐130a‐5p. Mechanically, overexpression of circROBO1 partly recovered the effect of matrine on liver cancer cell viability, proliferation, apoptosis, and Warburg effect by regulating the miR‐130a‐5p/ROBO1 axis. Matrine impeded liver cancer development by mediating the circROBO1/miR‐130a‐5p/ROBO1 axis, which provided a theoretical basis for the application of matrine as an effective anticancer drug for liver cancer.

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Section: Introductionmentioning

confidence: 99%

Matrine suppresses liver cancer progression and the Warburg effect by regulating the circROBO1/miR‐130a‐5p/ROBO1 axis

Huang

et al. 2023

J Biochem & Molecular Tox

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“…Considerable experimental evidence has shown their anticancer potential in numerous cancer cell lines [ 15 , 18 ]. Anticancer effects of flavonoids can be evaluated by cell cycle arrests, apoptosis, autophagy, reactive oxygen species (ROS) modulation, suppression of cell invasion, and proliferation [ 19 , 20 ]. Almost all clinically used antitumor drugs have toxic side effects.…”

Section: Introductionmentioning

confidence: 99%

Apigetrin Promotes TNFα-Induced Apoptosis, Necroptosis, G2/M Phase Cell Cycle Arrest, and ROS Generation through Inhibition of NF-κB Pathway in Hep3B Liver Cancer Cells

Bhosale

Abusaliya

Kim

et al. 2022

Cells

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Apigetrin (7-(β-D-glucopyranosyloxy)-4′,5-dihydroxyflavone), a glycoside bioactive dietary flavonoid derived from Taraxacum officinale and Teucrium gnaphalodes, is known to possess anticancer, antioxidant, and anti-inflammatory effects on numerous cancers. In the present study, we examined the effect of apigetrin in Hep3B hepatocellular cancer cell line (HCC). Apigetrin inhibited cell growth and proliferation of Hep3B cells, as confirmed by MTT and colony formation assay. We used apigetrin at concentrations of 0, 50, and 100 µM for later experiments. Of these concentrations, 100 µM of apigetrin showed a significant effect on cell inhibition. In apigetrin-treated Hep3B cells, cell cycle arrest occurred at the G2/M phase. Apoptosis and necroptosis of Hep3B cells treated with apigetrin were confirmed by Annexin V/propidium iodide (PI) staining and flow cytometry results. Morphological observation through 4′,6-diamidino-2-phenylindole (DAPI) staining showed intense blue fluorescence representing chromatin condensation. Hematoxylin staining showed necroptotic features such as formation of vacuoles and swelling of organelles. Apigetrin increased reactive oxygen species (ROS) levels in cells, based on fluorescence imaging. Furthermore, the underlying mechanism involved in the apoptosis and necroptosis was elucidated through western blotting. Apigetrin up-regulated TNFα, but down-regulated phosphorylation of p-p65, and IκB. Apigetrin inhibited the expression of Bcl-xl but increased Bax levels. Up-regulation of cleaved PARP and cleaved caspase 3 confirmed the induction of apoptosis in apigetrin-treated Hep3B cells. Additionally, necroptosis markers RIP3, p-RIP3, and p-MLKL were significantly elevated by apigetrin dose-dependently, suggesting necroptotic cell death. Taken together, our findings strongly imply that apigetrin can induce apoptosis and necroptosis of Hep3B hepatocellular cancer cells. Thus, apigetrin as a natural compound might have potential for treating liver cancer.

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“…The mortality rate of HCC is as high as 93%, ranking third among all malignant tumors. In 2012, more than 782,500 new liver cancer cases were diagnosed, and more than 745,000 liver cancer-related deaths were recorded globally; of these, half of the total numbers of cases and deaths occurred in China [ 1 – 8 ]. In recent years, the global morbidity and mortality of liver cancer have continued to increase, and liver cancer has seriously threatened human life and health.…”

Section: Introductionmentioning

confidence: 99%

Classification of multi-differentiated liver cancer pathological images based on deep learning attention mechanism

Chen

et al. 2022

BMC Med Inform Decis Mak

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Purpose Liver cancer is one of the most common malignant tumors in the world, ranking fifth in malignant tumors. The degree of differentiation can reflect the degree of malignancy. The degree of malignancy of liver cancer can be divided into three types: poorly differentiated, moderately differentiated, and well differentiated. Diagnosis and treatment of different levels of differentiation are crucial to the survival rate and survival time of patients. As the gold standard for liver cancer diagnosis, histopathological images can accurately distinguish liver cancers of different levels of differentiation. Therefore, the study of intelligent classification of histopathological images is of great significance to patients with liver cancer. At present, the classification of histopathological images of liver cancer with different degrees of differentiation has disadvantages such as time-consuming, labor-intensive, and large manual investment. In this context, the importance of intelligent classification of histopathological images is obvious. Methods Based on the development of a complete data acquisition scheme, this paper applies the SENet deep learning model to the intelligent classification of all types of differentiated liver cancer histopathological images for the first time, and compares it with the four deep learning models of VGG16, ResNet50, ResNet_CBAM, and SKNet. The evaluation indexes adopted in this paper include confusion matrix, Precision, recall, F1 Score, etc. These evaluation indexes can be used to evaluate the model in a very comprehensive and accurate way. Results Five different deep learning classification models are applied to collect the data set and evaluate model. The experimental results show that the SENet model has achieved the best classification effect with an accuracy of 95.27%. The model also has good reliability and generalization ability. The experiment proves that the SENet deep learning model has a good application prospect in the intelligent classification of histopathological images. Conclusions This study also proves that deep learning has great application value in solving the time-consuming and laborious problems existing in traditional manual film reading, and it has certain practical significance for the intelligent classification research of other cancer histopathological images.

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Recent Progress in Understanding the Action of Natural Compounds at Novel Therapeutic Drug Targets for the Treatment of Liver Cancer

Cited by 23 publications

References 173 publications

Matrine suppresses liver cancer progression and the Warburg effect by regulating the circROBO1/miR‐130a‐5p/ROBO1 axis

Matrine suppresses liver cancer progression and the Warburg effect by regulating the circROBO1/miR‐130a‐5p/ROBO1 axis

Apigetrin Promotes TNFα-Induced Apoptosis, Necroptosis, G2/M Phase Cell Cycle Arrest, and ROS Generation through Inhibition of NF-κB Pathway in Hep3B Liver Cancer Cells

Classification of multi-differentiated liver cancer pathological images based on deep learning attention mechanism

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