Single‐cell transcriptome dissecting the microenvironment remodeled by PD1 blockade combined with photodynamic therapy in a mouse model of oral carcinogenesis

Abstract Oral squamous cell carcinoma (OSCC) stands as a predominant and perilous malignant neoplasm globally, with the majority of cases originating from oral potential malignant disorders (OPMDs). Despite this, effective strategies to impede the progression of OPMDs to OSCC remain elusive. In this study, we established mouse models of oral carcinogenesis via 4‐nitroquinoline 1‐oxide induction, mirroring the sequential transformation from normal oral mucosa to OPMDs, culminating in OSCC development. By intervening during the OPMDs stage, we observed that combining PD1 blockade with photodynamic therapy (PDT) significantly mitigated oral carcinogenesis progression. Single‐cell transcriptomic sequencing unveiled microenvironmental dysregulation occurring predominantly from OPMDs to OSCC stages, fostering a tumor‐promoting milieu characterized by increased Treg proportion, heightened S100A8 expression, and decreased Fib_Igfbp5 (a specific fibroblast subtype) proportion, among others. Notably, intervening with PD1 blockade and PDT during the OPMDs stage hindered the formation of the tumor‐promoting microenvironment, resulting in decreased Treg proportion, reduced S100A8 expression, and increased Fib_Igfbp5 proportion. Moreover, combination therapy elicited a more robust treatment‐associated immune response compared with monotherapy. In essence, our findings present a novel strategy for curtailing the progression of oral carcinogenesis.


SUPPLEMENTARY TABLES
Figure S1.Additional details of the mice model.(A) Images of tongue visible lesions.(B) Representative images of H&E staining for esophagus, heart, liver, spleen, lungs, and kidney tissues of OLK and OSCC mice.

Figure S2 .
Figure S2.Additional details of the whole-cell atlas.(A) Boxplot showing the number of unique molecular identifier (nCount_RNA) and genes (nFeature_RNA), and the frequency of mitochondrial ratio (percent.mt) in each sample.Each point in the graph represents an individual cell.(B) UMAP of scale normalized expression of selected marker genes.(C) Bar plot showing the number of immune cells and non-immune cells in each sample.(D) UMAP plot visualizing celltypes of human scRNA-seq datasets (including two normal oral mucosal samples, three OLK samples, and three OSCC samples).(E) Dotplot showing expression levels of marker genes for each celltype of human scRNA-seq datasets.

Figure S4 .
Figure S4.Endothelial subtypes and functional remodeling.(A) UMAP plot visualizing the identified five endothelial subtypes (total = 6,482 cells).(B) UMAP of scale normalized expression of selected marker genes.(C) Dotplot showing expression levels of top-expression genes for each endothelial subtype.(D) Stacked bar plot showing the proportion of per endothelial subtype in each sample.(E) Bar plot showing the proportion of Endo_Selp in each sample.(F) Volcano plot showing differentially expressed genes (DEGs) between Endo_Selp and other endothelial subtypes.(G) Bar plot showing the selected GO biological processes with the upregulated DEGs in Endo_Selp.Adjusted P-value by Benjamini-Hochberg.(H) Heatmap showing expression levels of inflammatory related genes across the six groups.

Figure S5 .
Figure S5.Myeloid cells are an important source which can inhibited the function of T cells.(A) UMAP of scale normalized expression of immune checkpoints and their ligands in total cells.(B) Scatter plot of the expression level of immune checkpoints and their ligands in each celltypes.(C) Scatter plot of the expression level of immune checkpoints and their ligands in each celltypes in human scRNA-seq datasets.(D) All the significant ligand-receptor pairs that contribute to the signaling sending from other celltypes to T cells.The dot color and size represent the calculated communication probability and P-values.P-values are computed from one-sided permutation test.(E) The inferred PD-L1 signaling network.The edge width represents the communication probability.

Figure S7 .
Figure S7.T cells subtypes and functional remodeling.(A) UMAP plot visualizing the identified nine T cells' subtypes (n=2,840).(B) Dotplot showing expression levels of top-expression genes for each T cells' subtype.(C) UMAP of scale normalized expression of selected marker genes.(D) Pie chart showing the proportion of each subset in total T cells.(E) Box plot showing the proportion of per T cells' subtype in each sample.(F) Heatmap showing expression levels of immune checkpoints and cytotoxicity related genes across the subtypes.(G) The correlation between the exhaustion and cytotoxicity score in T cells by Pearson.(H) The correlation between the expression level of immune checkpoints and

Figure
Figure S8.T cells subtypes and functional remodeling.(A) UMAP plot visualizing the expression of Cxcl9 in the whole-cell atlas.(B) UMAP plot visualizing the expression of Cxcl9 in the myeloid cells.(C) Scatter plot of Cxcl9 and Spp1expression in macrophages.(D) Pie chart showing the proportion of Cxcl9 + SPP1 -macrophages, Cxcl9 + SPP1 + macrophages, Cxcl9 -SPP1 -macrophages, and Cxcl9 -SPP1 + macrophages in total macrophages.(E) Violin plot showing the expression of Cxcl9 and Spp1 in macrophages for each sample.(F) mIHC staining of CXCL9, CD8, CK5 in mice tongue slides.