Topical transdermal administration of lenalidomide nanosuspensions-based hydrogels against melanoma: In vitro and in vivo studies

Abstract

Percutaneous neoadjuvant therapy has proven effective in diminishing tumor size and the surgical intervention area, which couldeffectively mitigate the risk of tumor recurrence and enhance immunotherapy efficacy. Lenalidomide, an approved medication orally used to treat myeloma, was loaded into nanosuspensions-based hydrogels (Len-NBHs) for transdermal administration as a percutaneous neoadjuvant therapy. This study was designed to investigate the inhibitory effect and mechanism of Len-NBHs on melanoma. Network pharmacology and transcriptomic analyses identified key targets and signaling pathways. The effects of lenalidomide on melanoma were further verified through Western blotting, immunohistochemistry, immunofluorescence, and quantitative real-time polymerase chain reaction，using both in vitro cell experiments and in vivo melanoma mouse models. Lenalidomide could induce melanoma cells apoptosis, disrupt cell cycle progression, impede cell migration and invasion, and modify tumor microenvironment (TME). Mechanistically, lenalidomide reversed the abnormal activation of the PI3K-AKT signaling pathway and the overexpression of CD93, while also recruiting CD8+ T cells, CD4+ T cells, and dendritic cells to infiltrate the tumor site. Transdermal administration of Len-NBHs represents a promising adjuvant therapy for the treatment of malignant melanoma. Preoperative administration of Len-NBHs can inhibit the outward spread of melanoma, reduce tumor size, thereby decreasing the surgical excision area and improving patient survival rates and prognosis.

Keywords: Immunoregulation; Lenalidomide nanosuspensions-based hydrogels; Melanoma Transcriptomic; Transdermal administration.

Graphical abstract

Fig. 1

Lenalidomide nanosuspensions-based hydrogels. (A) Morphology of lenalidomide by SEM. (B) Morphology of the Len-Na freeze-dried powder by SEM. (C) Cumulative lenalidomide permeation rate within 24 h. (D) Cumulative lenalidomide permeation within 24 h. (E) Lenalidomide deposition within 24 h.

Fig. 2

In vitro inhibitory effect against B16-F10 cells of lenalidomide. (A) The viability of B16-F10 cells incubated with lenalidomide at concentrations ranging from 0 to 30 μM for 24 h. (B) Colony formation of B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM). (C) AO/EB dual staining images of B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM), scale bar = 50 μm. (D) cell viability of B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM), Part 1: Dead cells. Part 2: Low activity cells. Part 3: High activity cells. (E) Cell cycles of B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM).

Fig. 3

Inhibition of B16-F10 cell migration and invasion by lenalidomide. (A) Scratch test of B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM). (B) Transwell assay of B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM). (C) Western blot assay of MMP-2 and MMP-9 expressed by B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM). (D) Quantitative analysis of MMP-2 and MMP-9 expression. (E) RT-qPCR analysis of the relative mRNA expression of MMP-2 and MMP-9 in B16-F10 cells incubated with lenalidomide at different concentrations (1.25, 2.5, 5 μM). *p < 0.05, ***p < 0.001 vs the control group.

Fig. 4

In vivo anti-melanoma activity of trans-dermally administrated Len-NBHs. (A) Evolution of tumor volume during the experiment. (B) Pictures of excised tumor in different groups. (C) IL-4 levels in serum. (D) IL-6 levels in serum. (E) IL-2 levels in serum. (F) IFN-γ levels in serum. (G) HE staining images of tumor tissue, scale bar = 200 μm/50 μm. *p < 0.05, **p < 0.01, ***p < 0.001, vs the model group; ^#p < 0.05, ^###p < 0.001, vs the H-Len group.

Fig. 5

Immune response in the tumor microenvironment. (A) The IHC images of CD4, CD8, CD80, CD86, and CD11c in different groups, scale bar = 40 μm. (B-F) Quantitative analysis of expression of CD4, CD8, CD80, CD86, and CD11c, respectively. *p < 0.05, **p < 0.01, ***p < 0.001, vs the model group.

Fig. 6

Protein expression related to tumor invasion and angiogenesis. (A) The IHC images of MMP-2, MMP-9, EGFR, VEGFA and the merged IF images of DAPI and CD93, scale bar = 40 μm. (B-F) Quantitative analysis of expression of MMP-2, MMP-9, EGFR, VEGFA, and CD93, respectively. *p < 0.05, **p < 0.01, ***p < 0.001, vs the model group.

Fig. 7

Network pharmacology analysis. (A) The targets of lenalidomide and PPI network of melanoma-related targets of lenalidomide. (B) The top 35 targets involved in GO biological processes, molecular functions, and cell components. (C) KEGG analysis of the top 35 protein targets. (D) Molecular docking models of the four targets and lenalidomide.

Fig. 8

Transcriptome analysis of melanoma mouse model. (A) Volcano plot of the differentially expressed genes. Blue indicates the down-regulated gene, and red indicates the up-regulated gene. (B) Cluster Analysis of the differentially expressed genes. Blue indicates low gene expression, red indicates high gene expression, and the connection represents the clustering result. (C) GO enrichment analysis, including BP, CC, and MF. (D) The top 20 KEGG analyses for signaling pathway. (E) PI3K/AKT signaling pathway. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 9

Validation of predicted targets and assessment of the PI3K/AKT signaling pathway in melanoma. (A) The merged IF images of DAPI and TNF-α in tumor tissues (scale bar = 40 μm). (B) Quantitative analysis of expression of TNF-α in tumor tissues. (C) Western blotting of AKT1, PI3K, p-AKT1, and p-PI3K in B16-F10 cells. (D) Quantitative analysis of p-PI3K/PI3K, p-AKT1/AKT1 ratio in B16-F10 cells. (E) Western blotting of AKT1, PI3K, p-AKT1, and p-PI3K in tumor tissues. (F) Quantitative analysis of p-PI3K/PI3K, p-AKT1/AKT1 ratio in tumor tissues. (G, H) RT-qPCR was used to detect the relative mRNA expression of AKT1 and PI3K in each group of tumor tissues. **p < 0.01, ***p < 0.001, vs the control group or model group.