Nobiletin Inhibits Breast Cancer Stem Cell by Regulating the Cell Cycle: A Comprehensive Bioinformatics Analysis and In Vitro Experiments.

Inhibiting breast cancer stem cell (BCSC) signaling pathways is a strategic method for successfully treating breast cancer. Nobiletin (NOB) is a compound widely found in orange peel that exhibits a toxic effect on various types of cancer cells, and inhibits the signaling pathways that regulate the properties of BCSCs; however, the effects of NOB on BCSCs remain elusive. The purpose of this study was to determine the target genes of NOB for inhibiting BCSCs using in vitro three-dimensional breast cancer cell culture (mammospheres) and in silico approaches. We combined in vitro experiments to develop mammospheres and conducted cytotoxicity, next-generation sequencing, and bioinformatics analyses, such as gene ontology, the Reactome pathway enrichment, network topology, gene set enrichment analysis, hub genes selection, genetic alterations, prognostic value related to the mRNA expression, and mRNA and protein expression of potential NOB target genes that inhibit BCSCs. Here, we show that NOB inhibited BCSCs in mammospheres from MCF-7 cells. We also identified CDC6, CHEK1, BRCA1, UCHL5, TOP2A, MTMR4, and EXO1 as potential NOB targets inhibiting BCSCs. NOB decreased G0/G1, but increased the G2/M cell population. These findings showed that NOB is a potential therapeutic candidate for BCSCs treatment by regulating cell cycle.

Transcriptomics analysis reveals distinct mechanism of breast cancer stem cells regulation in mammospheres from MCF-7 and T47D cells.

Luminal A breast cancer, constituting 70 % of breast cancer cases, presents a challenge due to the development of resistance and recurrence caused by breast cancer stem cells (BCSC). Luminal breast tumors are characterized by TP53 expression, a tumor suppressor gene involved in maintaining stem cell attributes in cancer. Although a previous study successfully developed mammospheres (MS) from MCF-7 (with wild-type TP53) and T47D (with mutant TP53) luminal breast cancer cells for BCSC enrichment, their transcriptomic profiles remain unclear. We aimed to elucidate the transcriptomic disparities between MS of MCF-7 and T47D cells using bioinformatics analyses of differentially expressed genes (DEGs), including the KEGG pathway, Gene Ontology (GO), drug-gene association, disease-gene association, Gene Set Enrichment Analysis (GSEA), DNA methylation analysis, correlation analysis of DEGs with immune cell infiltration, and association analysis of genes and small-molecule compounds via the Connectivity Map (CMap). Upregulated DEGs were enriched in metabolism-related KEGG pathways, whereas downregulated DEGs were enriched in the MAPK signaling pathway. Drug-gene association analysis revealed that both upregulated and downregulated DEGs were associated with fostamatinib. The KEGG pathway GSEA results indicated that the DEGs were enriched for oxidative phosphorylation, whereas the downregulated DEGs were negatively enriched for the p53 signaling pathway. Examination of DNA methylation revealed a noticeable disparity in the expression patterns of the PKM2, ERO1L, SLC6A6, EPAS1, APLP2, RPL10L, and NEDD4 genes when comparing cohorts with low- and high-risk breast cancer. Furthermore, a significant positive correlation was identified between SLC6A6 expression and macrophage presence, as well as MSN, and AKR1B1 expression and neutrophil and dentritic cell infiltration. CMap analysis unveiled SA-83851 as a potential candidate to counteract the effects of DEGs, specifically in cells harbouring mutant TP53. Further research, including in vitro and in vivo validations, is warranted to develop drugs targeting BCSCs.

Identification of potential target genes of honokiol in overcoming breast cancer resistance to tamoxifen.

Background: Honokiol (HON) inhibits epidermal growth factor receptor (EGFR) signaling and increases the activity of erlotinib, an EGFR inhibitor, in human head and neck cancers. In this study, using a bioinformatics approach and in vitro experiments, we assessed the target genes of HON against breast cancer resistance to tamoxifen (TAM). Materials and methods: Microarray data were obtained from GSE67916 and GSE85871 datasets to identify differentially expressed genes (DEGs). DEGs common between HON-treated and TAM-resistant cells were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and protein-protein interaction (PPI) networks were constructed. Selected genes were analyzed for genetic alterations, expression, prognostic value, and receiver operating characteristics (ROC). TAM-resistant MCF-7 (MCF-7 TAM-R) cells were generated and characterized for their resistance toward TAM. A combination of HON and TAM was used for cytotoxicity and gene expression analyses. Molecular docking was performed using the Molecular Operating Environment software. Results: PPI network analysis revealed that FN1, FGFR2, and RET were the top three genes with the highest scores. A genetic alteration study of potential target genes revealed MMP16 and ERBB4 as the genes with the highest alterations among the breast cancer samples. Pathway enrichment analysis of FGFR2, RET, ERBB4, SOX2, FN1, and MMP16 showed that the genetic alterations herein were likely to impact the RTK-Ras pathway. The expression levels of RET, MMP16, and SOX2 were strongly correlated with prognostic power, with areas under the ROC curves (AUC) ​​of 1, 0.8, and 0.8, respectively. The HON and TAM combination increased TAM cytotoxicity in MCF-7 TAM-R cells by regulating the expression of potential target genes ret, ERBB4, SOX2, and FN1, as well as the TAM resistance regulatory genes including HES1, VIM, PCNA, TP53, and CASP7. Molecular docking results indicated that HON tended to bind RET, ErbB4, and the receptor protein Notch1 ankyrin domain more robustly than its native ligand. Conclusion: HON could overcome breast cancer resistance to TAM, potentially by targeting FGFR2, RET, ERBB4, MMP16, FN1, and SOX2. However, further studies are required to validate these results.