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. 2025 Aug 4;15(15):2274.
doi: 10.3390/ani15152274.

A Small-Molecule Compound Targeting Canine Mammary Cancer Regulates CXCL10 and MECOM Transcripts via Histone Modifications in CMT-N7

Affiliations

A Small-Molecule Compound Targeting Canine Mammary Cancer Regulates CXCL10 and MECOM Transcripts via Histone Modifications in CMT-N7

Rongrong Wang et al. Animals (Basel). .

Abstract

Nuclear receptors are involved in multiple biological processes, among which RORγ can regulate the expression of inflammation-related genes and is thus frequently used as a therapeutic target for cancer. Canine mammary cancer is one of the most common tumor diseases in dogs, with a relative incidence rate of 46.71% for CMT in China over the past five years, severely threatening the life and health of dogs. Therefore, the search for novel drugs targeting canine mammary cancer is of great significance. This study aims to investigate how the RORγ inhibitors W6134 and XY018 affect the expression of inflammatory genes through histone modifications in CMT-N7 cells. These results show that W6134 and XY018 can upregulate signaling pathways related to inflammation and apoptosis and influence the expression of associated genes. The close link between RORγ and inflammation-related genes further confirms that RORγ may serve as a therapeutic target for canine cancer. Additionally, ChIP-qPCR was used to detect the enrichment of histone markers such as P300, H3K27ac, H3K4me1, H3K9la, and H3K9bhb at the target loci of CXCL10 and MECOM genes. Collectively, our findings provide molecular evidence for the protective role of RORγ in canine mammary cancer, potentially by regulating inflammatory pathways via histone modifications, offering new insights for improving the cure rate and survival of affected dogs.

Keywords: RORγ; canine mammary cancer; histone modifications; inflammation.

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Conflict of interest statement

Ms. Rongrong Wang’s work in this study was entirely based on scientific principles, and there are no conflicts of interest that could inappropriately influence the representation or interpretation of the research results. The remaining authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
W6134 (5μM) and XY018 (5μM) induce cell death. (A) Calcein staining of cells treated with W6134 or XY018 for 48 h (scale bar = 100 μm); (B) cell counting after 48 h treatment with W6134 or XY018; (C) CCK8 cell viability assays at 24 h and 48 h post-treatment with W6134 or XY018; (D) GO analysis showing upregulated pathways enriched in apoptosis and downregulated pathways enriched in cell proliferation and cycle in W6134 cells; (E,F) KEGG analysis demonstrating upregulated pathways enriched in apoptosis and downregulated pathways enriched in cell cycle in W6134 cells; (G) GO analysis showing upregulated pathways enriched in apoptosis and downregulated pathways enriched in cell proliferation and cycle in XY018 cells; (H,I) KEGG analysis demonstrating upregulated pathways enriched in apoptosis and downregulated pathways enriched in cell cycle in XY018 cells. Figure (B) was statistically analyzed using the two-way ANOVA, and figure (C) was statistically analyzed using the one-way ANOVA. Data are presented as the means ± SEM, n = 3. Statistical significance is indicated as follows: ** p < 0.01.
Figure 2
Figure 2
W6134 (5μM) and XY018 (5μM) alter expression of cell death-related genes. (A) GSEA plots of cell proliferation, cell cycle, and apoptosis pathways in W6134-treated cells; (B) GSEA plots of cell proliferation, cell cycle, and apoptosis pathways in XY018-treated cells; (C) heatmap of mRNA expression changes (RNA-seq, log2-transformed) in genes related to cell proliferation, cell cycle, and apoptosis pathways after W6134 and XY018 treatments.
Figure 3
Figure 3
GSEA, KEGG, and GO enrichment analyses of DEGs, showing GSEA enrichment plots, enrichment bubble plots, pathway diagrams, and GO enrichment maps. (A) GSEA analysis outlining pathways pertinent to differentially expressed genes in W6134-treated canine cancer cells relative to the control group. (B) KEGG enrichment analysis of upregulated DEGs. X-axis: enrichment ratio; Y-axis: KEGG pathways. Count: bubble size indicates the number of genes annotated to KEGG pathways. P: color gradient represents enrichment significance. Left panel: gene names corresponding to each pathway. (C) TNF signaling pathway diagram. (D) GO enrichment analysis results. (E) KEGG enrichment analysis of downregulated DEGs. X-axis: enrichment ratio; Y-axis: KEGG pathways. Count: bubble size reflects gene number annotated to pathways. p-value: color indicates enrichment significance. Left panel: gene names for each pathway. (F) p53 signaling pathway diagram.
Figure 4
Figure 4
GSEA, KEGG, and GO enrichment analyses of DEGs, showing GSEA enrichment plots, enrichment bubble plots, pathway diagrams, and GO enrichment maps. (A) GSEA analysis outlining pathways pertinent to differentially expressed genes in XY018-treated canine cancer cells relative to the control group. (B) KEGG enrichment analysis of upregulated DEGs. X-axis: enrichment ratio; Y-axis: KEGG pathways. Count: Bubble size indicates the number of genes annotated to KEGG pathways. p-value: Color gradient represents enrichment significance. Left panel: Gene names corresponding to each pathway. (C) IL-17 signaling pathway diagram. (D) GO enrichment analysis results. (E) KEGG enrichment analysis of downregulated DEGs. X-axis: enrichment ratio; Y-axis: KEGG pathways. Count: Bubble size reflects the number of genes annotated to pathways. p-value: Color indicates enrichment significance. Left panel: Gene names for each pathway. (F) FoxO signaling pathway diagram.
Figure 5
Figure 5
Histone modifications on CXCL10 and MECOM genes. (A) STRING-ELIXIR analysis predicted interactions between key differentially expressed genes involved in RORγ transcriptional regulation within the inflammatory response, TNF signaling pathway, and IL-17 signaling pathway. Enrichment p-value: <1.0 × 10−16. The network view summarizes the network of predicted associations for a particular group of proteins. The network nodes are proteins. The edges represent the predicted functional associations. Red line indicates the presence of fusion evidence. Green line indicates neighborhood evidence. Blue line indicates cooccurrence evidence. Purple line indicates experimental evidence. Yellow line indicates textmining evidence. Light blue line indicates database evidence and Black line indicates coexpression evidence. (B,C) Heatmaps of differentially expressed genes in TNF/MAPK pathways after W6134 and XY018 treatments. (D) Expression levels of core genes in TNF/MAPK pathways after W6134 and XY018 treatments. (E) Histone marker measurements by ChIP-qPCR in cells treated with W6134 and XY018. Figures (D,E) were statistically analyzed using one-way ANOVA. Data are presented as means ± SEM, n = 3. Statistical significance is indicated as follows: * p < 0.05, *** p < 0.001.

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