METHODS: By utilizing a panel of breast cancer cells and mammospheres culture as cell-based screening platforms, we performed high-throughput chemical library screens to identify agents that are effective against breast CSCs and non-CSCs. The hit molecules were paired with conventional chemotherapy to evaluate the combinatorial treatment effects on breast CSCs and non-CSCs.
RESULTS: We identified a total of 193 inhibitors that effectively targeting both breast CSCs and non-CSCs. We observed that histone deacetylase inhibitors (HDACi) synergized conventional chemotherapeutic agents (i.e., doxorubicin and cisplatin) in targeting breast CSCs and non-CSCs simultaneously. Further analyses revealed that quisinostat, a potent inhibitor for class I and II HDACs, potentiated doxorubicin-induced cytotoxicity in both breast CSCs and non-CSCs derived from the basal-like (MDA-MB-468 and HCC38), mesenchymal-like (MDA-MB-231), and luminal-like breast cancer (MCF-7). It was also observed that the basal-like breast CSCs and non-CSCs were more sensitive to the co-treatment of quisinostat with doxorubicin compared to that of the luminal-like breast cancer subtype.
CONCLUSION: In conclusion, this study demonstrates the potential of HDACi as therapeutic options, either as monotherapy or in combination with chemotherapeutics against refractory breast cancer.
METHODS: We investigated the anti-proliferative efficacy of polar leaf extracts (LP), non-polar leaf extracts (LN), polar stem extract (SP) and non-polar stem extracts (SN) in human breast, colorectal, lung, endometrial, nasopharyngeal, and pancreatic cancer cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, MTT assay. The most potent extracts was tested along with gemcitabine using our established drug combination analysis. The effect of the combinatory treatment in apoptosis were quantified using enzyme-linked immunosorbent assay (ELISA), Annexin V assay, antibody array and immunoblotting. Statistical significance was analysed using one-way analysis of variance (ANOVA) and post hoc Dunnett's test. A p-value of less than 0.05 (p
METHODS: mRNA was extracted from 44 fibroadenomas and 36 giant fibroadenomas, and transcriptomic profiling was performed to identify up- and down-regulated genes in the giant fibroadenomas as compared to the fibroadenomas.
RESULTS: A total of 40 genes were significantly up-regulated and 18 genes were significantly down-regulated in the giant fibroadenomas as compared to the fibroadenomas of the breast. The top 5 up-regulated genes were FN1, IL3, CDC6, FGF8 and BMP8A. The top 5 down-regulated genes were TNR, CDKN2A, COL5A1, THBS4 and BMPR1B. The differentially expressed genes (DEGs) were found to be associated with 5 major canonical pathways involved in cell growth (PI3K-AKT, cell cycle regulation, WNT, and RAS signalling) and immune response (JAK-STAT signalling). Further analyses using 3 supervised learning algorithms identified an 8-gene signature (FN1, CDC6, IL23A, CCNA1, MCM4, FLT1, FGF22 and COL5A1) that could distinguish giant fibroadenomas from fibroadenomas with high predictive accuracy.
CONCLUSION: Our findings demonstrated that the giant fibroadenomas are biologically distinct to fibroadenomas of the breast with overexpression of genes involved in the regulation of cell growth and immune response.