Integrative analysis reveals therapeutic potential of pyrvinium pamoate in Merkel cell carcinoma

Abstract

Merkel Cell Carcinoma (MCC) is an aggressive neuroendocrine cutaneous malignancy arising from either ultraviolet-induced mutagenesis or Merkel cell polyomavirus (MCPyV) integration. Despite extensive research, our understanding of the molecular mechanisms driving the transition from normal cells to MCC remains limited. To address this knowledge gap, we assessed the impact of inducible MCPyV T antigens on normal human fibroblasts by performing RNA-seq. Our data uncovered changes in expression and regulation of Wnt signaling pathway members. Building on this observation, we bioinformatically evaluated various Wnt pathway perturbagens for their ability to reverse the MCC gene expression signature and identified pyrvinium pamoate, an FDA-approved anthelminthic drug known for its antitumor activity in other cancers. Leveraging transcriptomic, network, and molecular analyses, we found that pyrvinium targets multiple MCC vulnerabilities. Pyrvinium not only reverses the neuroendocrine features of MCC by modulating canonical and noncanonical Wnt signaling but also inhibits cancer cell growth by activating p53-mediated apoptosis, disrupting mitochondrial function, and inducing endoplasmic reticulum stress. Finally, we demonstrated that pyrvinium reduces tumor growth in an MCC mouse xenograft model. These findings offer a deeper understanding of the role of Wnt signaling in MCC and highlight the utility of pyrvinium as a potential treatment for MCC.

Keywords: Bioinformatics; Dermatology; Drug therapy; Oncology; Skin cancer; Virology.

Figure 1. MCPyV-perturbed cell model reveals signaling pathways altered during MCC development.

IMR90 normal human fibroblasts expressing inducible MCPyV early region (ER) were subjected to bulk RNA-seq. (A) Principal component analysis (PCA) performed on all 13,870 expressed genes in the time series RNA-seq data. (B) The eigengenes of the 14 WGCNA modules were projected onto each time point and the modules were grouped by their dynamic patterns using hierarchical clustering. (C) Force-directed network of hub genes in the 14 WGCNA modules. The attraction forces between nodes were defined by the topological overlap matrix and were inversely proportional to the length of edges in the graph. (D) GO term enrichment analysis of each WGCNA gene module. The terms are ranked by adjusted P value, and the top-ranked terms are shown. Neuroendocrine related terms are highlighted in red, Wnt signaling related terms are highlighted in blue.

Figure 2. Identifying areas of active gene regulation in IMR90 cells expressing MCPyV T antigens.

(A) Graphic workflow of regulatory network analysis. RNA-seq data was integrated with TF motif binding prior and TF protein-protein interactions to infer sample-specific regulatory networks using PANDA and LIONESS. IMR90-ER networks were grouped into 5 time periods and compared with IMR90-GFP networks from the same time period using ALPACA, to identify differential modules. (B) Sankey plot shows the dynamics of differential network communities detected by the workflow shown in A. Each vertical bar represents a differential community, with the size of the bar proportional to the number of genes in the community. Ribbons between adjacent bars represent the number of overlapping genes. Word cloud in the same color as the gene module annotates the enriched biological functions of genes inside the module (font size reflects the P_adj value).

Figure 3. MCPyV-ER induces characteristic changes in Wnt expression resembling the Wnt profile in MCC tumors.

(A) Bubble plot showing GO term enrichment results for DEGs between MCC tumor samples and normal skin samples (P_adj ≤ 0.05 and |log₂ fold change| ≥ 1). The Wnt signaling pathway ranked as one of the most significantly enriched pathways. (B) Log₂ fold change of selected Wnt gene expression levels in IMR90-ER samples, relative to the IMR90-GFP samples at the corresponding time points. The genes were categorized into 2 sets based on their expression dynamics. (C) Heatmap of Wnt signaling pathway genes in MCC tumor samples and normal skin samples. Two distinct trends in Wnt gene expression were observed, with several genes, including FZD7, WNT16, TCF3, and TCF7, showing trends consistent with those observed in our IMR90 model.

Figure 4. Characterization of pyrvinium pamoate as an effective perturbagen against MCC.

(A) Simplified diagram of commercially available Wnt signaling perturbagens in LINCS L1000 dataset and their reported MOAs. (Created in BioRender. Yang, J. (2025) https://BioRender.com/v23e056) (B) Circos plot showing pairwise comparison between MCC signature genes (MCC1000) and top drug-perturbed genes (ranked by z-scored log₂[fold change]) under different drug treatments. Statistical significance was determined by Fisher’s exact test. (C and D) Cell proliferation assay in WaGa and MKL-1 cells, under treatment with pyrvinium, CHIR-99021, and DMSO control. Statistical significance was determined by unpaired 2-sample, 2-tailed t test (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05). (E) Representative immunofluorescence (IF) images of WaGa cells treated with 500 nM pyrvinium and DMSO, with Ki67 staining as a proliferation marker, GAPDH as internal control, and DAPI for nucleus. Scale bar: 100 μm. (F) Bar graph showing the quantification of the Ki67-positive cell count relative to the total nucleus count in IF images of WaGa cells treated with 500 nM pyrvinium or DMSO. Data are presented as mean ± SEM (n = 10, P = 0.00126). Statistical significance was determined by unpaired 2-sample, 2-tailed t test. (G) Flow cytometry analysis showing the levels of Annexin V-APC and SYTOX blue staining to assess apoptotic populations in WaGa cells treated with varying doses and durations. (H) Bar graphs showing the quantification of different populations in pyrvinium-treated WaGa cells at 24 hours and 48 hours separately.

Figure 5. Pyrvinium pamoate reverses neuroendocrine and Wnt signaling signature in MCC cells.

(A) Volcano plot of DEGs in WaGa cells treated with pyrvinium compared with DMSO for 24 hours. DEGs with P_adj ≤ 0.05 and |log₂ fold change|≥ 1 that show a reversed expression trend relative to MCC versus normal skin are highlighted in red (upregulated in MCC) or blue (downregulated in MCC). Known MCC marker genes are labeled in red text. (B) Scatter plot of predicted master regulator activity levels in pyrvinium-treated MCC versus DMSO-treated MCC cells. Blue (or red) indicates regulators with decreased (or increased) activity. (C) Relative mRNA levels of TCF7 and TCF3 in WaGa TopGFP cells treated with siRNA control, siTCF7, and siTCF3, as measured by RT-qPCR. Statistical significance determined by unpaired 2-sample t-test. (D) Protein levels of ATOH1, SOX2, and GFP, in untreated WaGa TopGFP cells and the cells treated with siRNA negative control, siTCF7, and siTCF3. (E) Protein levels of WNT5A/B following pyrvinium treatment for 24 hours in MCC cell lines. (F) Relative mRNA levels of AXIN2, ATOH1, and SOX2 in WaGa cells treated with recombinant hWNT5B protein for 6 hours, as measured by RT-qPCR. Statistical significance determined by unpaired 2-sample, 2-tailed t test. (G) Protein levels of total β-catenin, WNT5B, ATOH1, SOX2, and GFP following 6 hours of treatment with recombinant hWNT5B in WaGa TopGFP cells. (H) WNT5B, ATOH1, and SOX2 protein levels at 0, 12, 24, and 48 hours after 1 μg/mL doxycycline induction in WaGa WNT5B OE cells. (I and J) Cell viability in WaGa WNT5B OE cells and GFP control cells with or without 1 μg/mL doxycycline. Statistical significance between dox+ and dox– conditions on the same day was assessed by unpaired 2-sample, 2-tailed t test. (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05).

Figure 6. Pyrvinium targets multiple vulnerabilities of MCC.

(A) GO term enrichment for 1 μM pyrvinium-treated WaGa and MKL1 cells at 6 and 24 hours. Size of dot indicates number of genes annotated to the GO term, and color reflects the adjusted P value from the hypergeometric test. GO terms are primarily ranked by significance in the 24-hour MKL1 analysis. (B and C) Protein levels of p53, cleaved-PARP, and PUMA in TP53 WT cell lines (WaGa, MKL-1) and TP53^Mut/TP53^–/– cell lines (MS-1, MKL-2) 24 hours after treatment with 0.5 μM pyrvinium and 1 μM Nutlin-3a. (D) Representative data displayed as a line chart showing basal respiration level and maximal respiration capacity (after FCCP injection) at each time point (means ± SEM, n = 4). (E) Seahorse OCR analysis measuring uncoupled OCR in WaGa cells treated with different doses of pyrvinium for 24 hours compared with DMSO treated cells. Statistical significance determined by Kruskal-Wallis H Test followed by Dunnett’s post hoc test. (F) Quantification of OXPHOS protein levels from Western blot (Supplemental Figure 12B). All values are presented relative to mean GAPDH expression in vehicle control samples (means ± SEM, n = 4 replicate blots). Statistical significance determined by ANOVA followed by Dunnett’s multiple comparison test. (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05). (G) Protein levels of endoplasmic reticulum stress markers in MCC cells treated with pyrvinium for 6 and 24 hours. (H) A graphic model illustrating pyrvinium’s effect on the balance between endoplasmic reticulum stress and UPR signaling. (I) Proteins levels of Unfolded Protein Response (UPR) markers in WaGa cells after 24 hours of treatment with pyrvinium or other endoplasmic reticulum stress inducers.

Figure 7. Antitumor activity of pyrvinium in an MKL-1 xenograft tumor model.

(A) Experimental design of the in vivo study. (B) Tumor growth curve showing the mean tumor volume of vehicle control and pyrvinium-treated mice from day 0 to day 20 of treatment (mean ± SEM, n = 7). (C) H&E and IHC staining results on serial sectioning slides for each marker in the same lesion. Tumor tissues were collected 0.5 to 1 hour after the final 1 mg/kg dose of pyrvinium in in vivo Study number 2 (experimental design shown in Supplemental Figure 14C). (D) Percentage of MKL-1 xenograft tumor tissue expressing ATOH1 or Ki67 in vehicle control group and pyrvinium-treated group.