Clinical-mediated discovery of pyroptosis in CD8+ T cell and NK cell reveals melanoma heterogeneity by single-cell and bulk sequence

Abstract

Histologically, melanoma tissues had fewer positive cells percentage of pyroptosis-related genes (PRGs), GZMA, GSDMB, NLRP1, IL18, and CHMP4A in epidermal than in normal skin. Pyroptosis, a new frontier in cancer, affects the tumor microenvironment and tumor immunotherapy. Nevertheless, the role of pyroptosis remains controversial, which reason is partly due to the heterogeneity of the cellular composition in melanoma. In this study, we present a comprehensive analysis of the single-cell transcriptome landscape of pyroptosis in melanoma specimens. Our findings reveal dysregulation in the expression of PRGs, particularly in immune cells, such as CD8⁺ cells (representing CD8⁺ T cells) and CD57⁺ cells (representing NK cells). Additionally, the immunohistochemical and multiplex immunofluorescence staining experiments results further confirmed GZMA⁺ cells and GSDMB⁺ cells were predominantly expressed in immune cells, especially in CD8 ⁺ T cells and NK cells. Melanoma specimens secreted a minimal presence of GZMA⁺ merged CD8⁺ T cells (0.11%) and GSDMB⁺ merged CD57⁺ cells (0.08%), compared to the control groups exhibiting proportions of 4.02% and 0.62%, respectively. The aforementioned findings indicate that a reduced presence of immune cells within tumors may play a role in diminishing the ability of pyroptosis, consequently posing a potential risk to the anti-melanoma properties. To quantify clinical relevance, we constructed a prognostic risk model and an individualized nomogram (C-index=0.58, P = 0.002), suggesting a potential role of PRGs in malignant melanoma prevention. In conclusion, our integrated single-cell and bulk RNA-seq analysis identified immune cell clusters and immune gene modules with experiment validation, contributing to our better understanding of pyroptosis in melanoma.

Fig. 1

An overview of the pathways involved in pyroptosis.

Fig. 2. Melanoma specimens reduce PRGs positive cells in epidermal clinically.

A Overall survival analysis based on K-M was calculated to identify the potential PRGs clinically. B PPI via MCODE and CytoNCA algorithm was established, in which PRGs were screened out as central protein functioning in melanoma deficiency. C GZMA, GSDMB, CHMP4A, NLRP1, and IL18 protein expression of melanoma and control patients detected by ELISA. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, n = 5, compared with the normal group. D Representative IHC stanning of GZMA⁺, GSMDB⁺, CHMP4A⁺, NLRP1⁺, and IL18⁺ in melanoma specimens from the clinic. Scale bar = 100 μm, n = 5 samples per group. E The quantification of PRGs protein in epidermal areas, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, compared with the control group.

Fig. 3. scRNA-seq profiling of the melanoma environments.

A T-distributed stochastic neighbor embedding (tSNE) plot of control samples, non-immune cells, and immune cells are shown separately. B tSNE plot of melanoma samples, showing the annotation and color code for cell types in the melanoma ecosystem and cell origins by color, non-immune cells, and immune cells are shown separately. C The cell classification basis of melanoma scRNA-seq analysis was displayed with the marker genes expression in the Feature plot. D Histogram indicating the proportion of cells in tumor tissue of each group. E The expression of kernel PRGs in melanoma indicates the origination of immune cells.

Fig. 4. scRNA-seq profiling of immune cell components in melanoma.

A. t-SNE plot showing the clusters of immune cells and cell origins by color, according to immune cell types. B The cell classification basis of immune cell scRNA-seq analysis was displayed with the marker genes expression in Feature plot. C Pseudotime-ordered analysis to construct the developmental trajectories of the isolated immune cell subgroups. D WGCNA in bulk sequence. Gene cluster dendrogram clustered by weighted gene co-expression network in different colors. E The heatmap of module-trait relationships. The number in and outside the bracket represents the P-value and Pearson coefficient, respectively. F Representative IHC stanning of CD8⁺ and CD57⁺ in immune cell from the clinic. Scale bar = 100 μm, n = 4 samples per group. G The quantification of PRGs protein in epidermal areas, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, compared with the control group.

Fig. 5. PRGs were primarily expressed in immune cells.

A Feature plots depicting the expression of key pyroptosis, violin plots were also displayed to determine the cell type. B Representative IHC stanning of GZMA⁺, GSMDB⁺, CHMP4A⁺, NLRP1⁺, and IL18⁺ in melanoma specimens, especially in lymphocyte areas. Scale bar = 100 μm, n = 4 samples per group. C The quantification of PRGs protein in dermal areas, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, compared with the control group.

Fig. 6. GZMA⁺ cells and GSDMB⁺ cells are secreted by CD8⁺ T cells.

A Representative multi-color staining of phenotypes of control and melanoma. 40,6-diamidino-2phenylindole (DAPI) (blue), CD8 (pink), GZMA (green), and GSDMB (red). Scale bars, 50 μm. B The scattergrams of different CD8⁺GZMA⁺and CD8⁺ GSDMB⁺ percent cells among the whole sample.

Fig. 7. GZMA⁺ cells and GSDMB⁺ cells are secreted by NK cells.

A Representative multi-color staining of phenotypes of control and melanoma. 40,6-diamidino-2phenylindole (DAPI) DAPI (blue), CD57 (pink), GZMA (green), and GSDMB (red). Scale bars, 50 μm. B The scattergrams of different CD57⁺GZMA⁺ and CD57⁺GSDMB⁺ percent cells among the whole sample.

Fig. 8. Clinical relevance and individualized prognostic nomogram.

A Forest plot of univariate Cox regression of the PRGs, including pyroptosis (GZMA and GSDMB) and clinical predicts (age, gender, pT/N/M-stage). B Forest plot of multivariate Cox regression of the PRGs, including pyroptosis (GZMA and GSDMB) and clinical predicts (age, gender, pT/N/M-stage). C K–M analysis showing the overall survival rate of high-risk patients (red) and low-risk patients (blue). The numbers of patients and the risk classification are indicated in the figure. D ROC curve was adopted to evolute the prediction performance of pyroptosis-related signature. E The individual prognostic nomogram of the 1-year, 2-year, and 3-year survival prediction of melanoma patients. F Calibration curve for the individual prognostic nomogram. A dashed diagonal line represents the ideal nomogram, and the blue line, red line, and orange line represent the 1-y, 2-y, and 3-y observed nomograms.