PurposeBaicalein, a widely used Chinese herbal medicine, has shown anticancer effects on many types of human cancer cell lines. However, little is known about the underlying mechanism in human breast cancer cells. In this study, we examined the apoptotic and autophagic pathways activated following baicalein treatment in human breast cancer cells in vitro and in vivo.Materials and methodsIn in vitro study, we used MTT and clone formation assay to confirm the inhibitory role of baicalein on proliferation of MCF-7 and MDA-MB-231 breast cancer cells. Apoptosis was detected employing Hoechst 33258 staining, JC-1 staining, and flow cytometry. Autophagy was monitored by acridine orange staining and transmission electron microscopy observation. Quantitative real-time PCR and Western blot analysis were employed to study the effects of baicalein on PI3K/AKT signaling components of MCF-7 and MDA-MB-231 breast cancer cells. In in vivo study, the effect of baicalein was tested with a breast cancer cells transplantation tumor model.ResultsOur study showed that baicalein has the potential to suppress cell proliferation, induce apoptosis and autophagy of breast cancer cells in vitro and in vivo. Furthermore, baicalein significantly downregulated the expression of p-AKT, p-mTOR, NF-κB, and p-IκB while enhancing the expression of IκB in MCF-7 and MDA-MB-231 cells. It also decreased the p-AKT/AKT and p-mTOR/mTOR ratios.ConclusionOur study demonstrated that baicalein induces apoptosis and autophagy of breast cancer cells via inhibiting the PI3K/AKT signaling pathway in vivo and vitro. Our study revealed that baicalein may be a potential therapeutic agent for breast cancer.
Backgroundc-Met has been shown to promote organ development and cancer progression in many cancers. However, clinicopathological and prognostic value of c-Met in breast cancer remains elusive.MethodsPubMed and EMBASE databases were searched for eligible studies. Correlation of c-Met overexpression with survival data and clinicopathological features was analyzed by using hazard ratio (HR) or odds ratio (OR) and fixed-effect or random-effect model according to heterogeneity. All statistical tests were two-sided.Results32 studies with 8281 patients were analyzed in total. The c-Met overexpression was related to poor OS (overall survival) (HR=1.65 (1.328, 2.051)) of 18 studies with 4751 patients and poor RFS/DFS (relapse/disease free survival) (HR=1.53 (1.20, 1.95)) of 12 studies with 3598 patients. Subgroup analysis according to data source/methods/ethnicity showed c-Met overexpression was related to worse OS and RFS/DFS in Given by author group, all methods group and non-Asian group respectively. Besides, c-Met overexpression was associated with large tumor size, high histologic grade and metastasis.ConclusionsOur results showed that c-Met overexpression was connected with poor survival rates and malignant activities of cancer, including proliferation, migration and invasion, which highlighted the potential of c-Met as significant candidate biomarker to identify patients with breast cancer at high risk of tumor death.
Objective Watson for Oncology (WFO), an artificial intelligence from IBM Corporation, can provide a treatment plan by analyzing patient’s disease characteristics. The present study was performed to examine the concordance between treatment recommendations proposed by WFO and the multidisciplinary tumor board at our center. The aim was to explore the feasibility of using WFO for breast cancer cases in China and to ascertain the ways to make WFO more suitable for Chinese patients with breast cancer. Methods Data from 302 breast cancer patients treated at the Second Affiliated Hospital of Xi’an Jiaotong University between October 2016 and February 2018 was retrieved and retrospectively analyzed by WFO. The recommendations were divided into ‘recommended’, ‘considered’ and ‘not recommended’ groups. Results were considered concordant when oncologists’ recommendations were categorized as ‘recommended’ or ‘for consideration’ by WFO. Results The concordance rate of 200 subjects with postoperative adjuvant therapy was 77%. However, the rate was 27.5% in the remaining 102 cases with metastatic disease receiving either first-line or no treatment. Further analysis demonstrated that inconsistencies were mainly due to different choices of chemotherapy regimens. Subgroup study indicates that tumor stage, receptor status and age also had influences at the concordance rate. Conclusion The results of this study suggest that WFO is a promising artificial intelligence system for the treatment of breast cancer. These findings can also serve as a reference framework for the inclusion of artificial intelligence in the ongoing medical reform in China.
BACKGROUND:Inhibition of lymphocytes infiltration and activity may impair antitumor immune response and limit treatment responsiveness. Wnt/β-catenin pathway has been suggested to contribute to immune evasion in tumor by suppressing the function of immune cells and excluding T cell infiltration. However, the effects of Wnt/β-catenin on TILs recruitment remain controversial.OBJECTIVE:We aimed to investigate whether intratumoral Wnt/β-catenin signaling could affect the lymphocyte infiltration in breast cancer.METHODS: The distribution of stromal TILs, CD8+ and FOXP3+ TIL subsets, and the expression of β-catenin were separately assessed on consecutive sections of 96 breast cancer specimens.RESULTS: Both stromal infiltrated TILs and β-catenin expression were upregulated in hormone receptor negative HER2-enriched and TNBC subtypes. Furthermore, high levels of stromal TILs as well as CD8+ or FOXP3+ TIL subsets were associated with β-catenin overexpression by breast cancer, respectively.CONCLUSIONS: For the first time, we demonstrated that rather than excluding lymphocytes infiltration as reported in mela-noma, high levels of TILs were associated with β-catenin overexpression in BC. Wnt/β-catenin signaling may play a critical role in BC immunity, particularly in HER2-enriched and triple negative BC, and may serve as a potential target for regulating immune infiltrates in breast cancer.
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