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Phytomedicine ; : 153786, 2021 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-34785104


BACKGROUND: Lung cancer has become the principal cause of cancer-related deaths. Emodin is a Chinese herb-derived compound extracted from the roots of Rheum officinale that exhibits numerous pharmacological characteristics. Secretory phospholipase A2-IIa (sPLA2-IIa) is overexpressed in cancers and plays an important role in cancer development. PURPOSE: This study aims to investigate the anti-tumor mechanism of emodin in non-small-cell lung cancer (NSCLC). METHODS: MTT assay was applied to detect the sensitivity of emodin to NSCLC cell line. Flow cytometry was used to examine the effect of emodin on cell cycle distribution and evaluate ROS level and apoptosis. Western blot analysis was utilised to examine the expression levels of sPLA2-IIa, PKM2, and AMPK and its downstream pathways induced by emodin. Enzyme inhibition assay was applied to investigate the inhibitory effect of emodin on sPLA2-IIa. The anticancer effect of emodin was also detected using an in vivo model. RESULTS: Emodin significantly inhibited NSCLC proliferation in vivo and in vitro and was relatively less cytotoxic to normal lung cell lines. Most importantly, emodin inhibited the proliferation of KRAS mutant cell lines by decreasing the expression of sPLA2-IIa and NF-κB pathways. Emodin also inhibited mTOR and AKT and activated the AMPK pathway. Furthermore, emodin induced apoptosis, increased the reactive oxygen species (ROS) level, and arrested the cell cycle. CONCLUSION: Emodin exhibited a novel anti-tumor mechanism of inhibiting the proliferation of KRAS mutant cell lines by decreasing the expression levels of sPLA2-IIa and NF-κB pathways. Hence, emodin can potentially serve as a therapeutic target in NSCLC.

BMC Cancer ; 21(1): 531, 2021 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-33971846


BACKGROUND: Cervical cancer continues to be one of the leading causes of cancer deaths among females in low and middle-income countries. In this study, we aimed to assess the independent prognostic value of clinical and potential prognostic factors in progression-free survival (PFS) in cervical cancer. METHODS: We conducted a retrospective study on 92 cervical cancer patients treated from 2017 to 2019 at the Zhuhai Hospital of Traditional Chinese and Western Medicine. Tumor characteristics, treatment options, progression-free survival and follow-up information were collected. Kaplan-Meier method was used to assess the PFS. RESULTS: Results showed that the number of retrieved lymph nodes had a statistically significant effect on PFS of cervical cancer patients (P = 0.002). Kaplan-Meier survival curve analysis showed that cervical cancer patients with initial symptoms age 25-39 had worse survival prognoses (P = 0.020). And the using of uterine manipulator in laparoscopic treatment showed a better prognosis (P < 0.001). A novel discovery of our study was to verify the prognostic values of retrieved lymph nodes count combining with FIGO staging system, which had never been investigated in cervical cancer before. According to the Kaplan-Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis, significant improvements were found after the combination of retrieved lymph nodes count and FIGO stage in predicting PFS for cervical cancer patients (P < 0.001, AUC = 0.826, 95% CI: 0.689-0.962). CONCLUSION: Number of retrieved lymph nodes, initial symptoms age, uterine manipulator, and retrieved lymph nodes count combining with FIGO staging system could be potential prognostic factors for cervical cancer patients.

Neoplasias do Colo do Útero/mortalidade , Adulto , Idoso , Feminino , Humanos , Excisão de Linfonodo , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Prognóstico , Estudos Retrospectivos , Neoplasias do Colo do Útero/patologia
Transl Oncol ; 14(1): 100907, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33217646


Early diagnosis has been proved to improve survival rate of lung cancer patients. The availability of blood-based screening could increase early lung cancer patient uptake. Our present study attempted to discover Chinese patients' plasma metabolites as diagnostic biomarkers for lung cancer. In this work, we use a pioneering interdisciplinary mechanism, which is firstly applied to lung cancer, to detect early lung cancer diagnostic biomarkers by combining metabolomics and machine learning methods. We collected total 110 lung cancer patients and 43 healthy individuals in our study. Levels of 61 plasma metabolites were from targeted metabolomic study using LC-MS/MS. A specific combination of six metabolic biomarkers note-worthily enabling the discrimination between stage I lung cancer patients and healthy individuals (AUC = 0.989, Sensitivity = 98.1%, Specificity = 100.0%). And the top 5 relative importance metabolic biomarkers developed by FCBF algorithm also could be potential screening biomarkers for early detection of lung cancer. Naïve Bayes is recommended as an exploitable tool for early lung tumor prediction. This research will provide strong support for the feasibility of blood-based screening, and bring a more accurate, quick and integrated application tool for early lung cancer diagnostic. The proposed interdisciplinary method could be adapted to other cancer beyond lung cancer.