Oncotarget
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2016
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IF 5.008
Mei Peng,Qiongli Su,Qing Zeng,Le Li,Zhihong Liu,Lei Xue,Yan Cheng,Yanjun Huang,Ting Tao,Hongwei Lv,Xiaohui Li,Xiaojun Tao,Peng Guo,Alex F. Chen,Xiaoping Yang
Anticancer potential of metformin has been extensively studied. However, its anticancer clinical use remains yet to be approved since sufficient concentration on target organs could not be achieved via conventional administration. To overcome this drawback, we aim to examine the efficiency of novel intravesical treatment of metformin on syngeneic orthotopic preclinical model. Three human and one murine bladder cancer cell lines were tested in vitro for inhibitory sensitivity by MTT and cologenic assays. AMPK pathway including AKT, Erk and S6K was examined by western blot and further explored by regulating activated levels using specific inhibitors. In vivo efficacy was determined by Kaplan-Meier survival curves and measurements of body and bladder weights plus tumor biomarkers. Lactic acid and metformin levels of plasma were measured by standard procedures. The results demonstrated that metformin activated AMPK and decreased phosphorylation of Akt and Erk. Furthermore, combinations of metformin with either Akt or Erk inhibitors synergistically diminished cancer proliferation, suggesting the involvement of Akt- and Erk- related pathways. Intravesical metformin 26 and 104 mg/kg, twice per week demonstrated a rapid elimination of the implanted tumor without any evidence of toxicity. In contrast, oral treatment at a dose of 800mg/kg/d exhibited little efficacy whereas severe toxicity existed if the dosage is higher. Collectively, intravesical metformin displays potent inhibition on bladder cancer in vitro and this preclinical study reveals the profound therapeutic application of metformin with durable tolerance via intravesical administration route.
研究领域:
肿瘤学
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药理学
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分子生物学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Discover Oncology
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2024
·Vol. 15
·期 1
·1-18
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IF 2.8
Feng Rui,Li Haolin,Meng Tong,Fei Mingtian,Yang Cheng
Purpose This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database. Methods First, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan–Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and cuproptosis, and may promote ccRCC progression. Results We constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan–Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group. Conclusion Overall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.
研究领域:
生物信息学
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癌症生物学
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分子生物学
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基因组学
✓ 已验证
DOI
PubMed
高影响因子
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
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2021
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IF 3.935
Zhongjian Chen,Yun Gao,Xiancong Huang,Yao Yao,Keke Chen,Su Zeng,Weimin Mao
Prognosis for esophageal squamous cell carcinoma (ESCC) is poor, so it is essential to develop a more complete understanding of the disease. The purpose of this study was to explore metabolic biomarkers and potential therapeutic targets for ESCC. An ultra-high-performance liquid chromatography coupled with high resolution mass (UPLC/MS)-based metabolomic analysis was performed in 141 ESCC cancerous tissue samples and 70 non-cancerous counterparts. The results showed that 41 differential metabolites were annotated in the training set, and 37 were validated in the test set. Single-metabolite-based receiver operating characteristic (ROC) curves as well as metabolite-based machine learning models, including Partial Least Squares (PLS), Support Vector Machine (SVM), and Random Forest (RF), were investigated for cancerous and non-cancerous tissue classification. Six most prevalent diagnostic metabolites—adenylsuccinic acid, UDP-GalNAc, maleylacetoacetic acid, hydroxyphenylacetylglycine, galactose, and kynurenine—showed testing predictive accuracies of 0.89, 0.95, 0.97, 0.89, 0.84, and 0.84, respectively. Moreover, the metabolite-based models (PLS, SVM, and RF) had testing predictive accuracies of 0.95, 0.95, and 1.00, respectively. Kaplan–Meier survival analysis and Cox proportional hazards regression analysis demonstrated that 2-hydroxymyristoylcarnitine (HR: 0.55, 95 % CI: 0.32 to 0.92), 3-hydroxyhexadecanoylcarnitine (HR: 0.49, 95 % CI: 0.29 to 0.83), and 2,3-Dinor-TXB1 (HR: 0.56, 95 % CI: 0.33 to 0.95) to be significantly associated with OS. Based on the observation of accumulation in amino acids, immunohistochemistry (IHC) staining revealed that the amino acid transporters SLC7A5/LAT1, SLC1A5/ASCT2, and SLC16A10/MCT10 were up-regulated in ESCC cancerous tissues when compared to non-cancerous equivalents. Consistently, the same panel of amino acids were downregulated in cells with SLC1A5 knockdown. Herein, it is concluded that this study not only identified several metabolites with diagnostic and/or prognostic value, but also provided accurate metabolite-based prediction models for ESCC tissue classification. Furthermore, the three up-regulated amino acid transporters were identified as potential therapeutic targets for ESCC, especially SLC1A5.
研究领域:
肿瘤学
·
代谢组学
·
生物信息学
·
分子生物学
·
癌症研究
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）