Additional file 2 of Single-cell RNA sequencing reveals pro-invasive cancer-associated fibroblasts in hypopharyngeal squamous cell carcinoma
Creators: name: Cai, Zhimou
name: Chen, Lin
name: Chen, Siyu
name: Fang, Ruihua
name: Chen, Xiaolin
name: Lei, Wenbin
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Space Science
subject: Medicine
subject: Cell Biology
subject: Molecular Biology
subject: Pharmacology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Plant Biology
subject: FOS: Biological sciences

description: Additional file 2: Fig. S1. Expression of marker genes for major cell types. Eleven major cell types were identified: epithelial cells (EPCAM+), endothelial cells (VWF+), fibroblasts (DCN+), T/NKT cells (CD3D+), B cells (MS4A1+), plasmocytes (JCHAIN), pDC cells (LILRA4), mast cells (TPSAB1+), myeloid cells (LYZ+), and neutrophils (FCGR3B+). Fig. S2. Copy number variations and characterization of malignant epithelial cells in HPSCC. a UMAP plot of epithelial cells (EpCs) colored by cluster (left) and patient (right). b Violin plots showing marker gene expression in EpCs subsets. c Copy number variations (CNVs) evaluated per cell using InferCNV. Immune and stromal cells were used as references. RNA velocities visualized with UMAP. EpCs (d) and fibroblasts (e) using Gaussian smoothing on a regular grid. f Scatter plots show expression of the top five highly expressed regulons in each malignant EpC subset, estimated using SCENIC. Kaplan–Meier curve of overall survival (OS) in the TCGA-HNSC cohort stratified by the optimal cut-off point for p-EMT marker gene (g), EMT marker gene (h), migratory proliferative marker gene (i), keratinocyte differentiation marker gene (j), and proliferative-related gene (k) expression levels. P-values were calculated using the two-sided log-rank test. Fig. S3. Heterogeneity and characterization of fibroblast in HPSCC. a UMAP plot of fibroblasts colored by cluster. b Bubble heatmap showing marker gene expression in pericytes. Dot size indicates the fraction of expressing cells, colored according to expression normalized by z-score. c Comparison of the absolute infiltration proportion of pericytes between paired normal (n = 43) and tumor tissues (n = 43) in the TCGA-HNSC cohort. Kaplan–Meier curve of the OS in the TCGA-HNSC cohort stratified by the optimal cut-off point for pericyte infiltration. P-values were calculated using the two-sided log-rank test. d Representative images showing multiplex immunohistochemistry (mIHC) staining of FAP in HPSCC tumor samples, in merged channels. Scale bar represents 50 μm. e Representative images showing mIHC staining of panCK and FAP in HPSCC tumor samples, in merged channels. Scale bar represents 20 μm. f Differences in the activities of hallmark pathways between different fibroblast subsets, scored using GSVA. g Representative plots of tumor-derived fibroblast (cancer-associated fibroblast, CAF) and normal tissue-derived fibroblast (normal fibroblast, NF). h Heatmap of t-values for the AUC scores of expression regulation based on transcription factor expression of fibroblast subsets, estimated using SCENIC. i UMAP plots of TF expression (up) and AUC scores (down). Fig. S4. Cell–cell interactions in HPSCC of fibroblast subsets and malignant epithelial cell subsets. Fig. S5. Expression of marker genes for myeloid and characteristics of SPP1+/C1QC+ TAM pathway. a Expression of marker genes for myeloid lineage cells. b GSEA shows top enriched pathways in SPP1+ TAM and C1QC+ TAM. NES denotes the normalized enrichment score. Fig. S6. Distribution of dendritic cell subsets and the relationship between DC and T cell subsets. a Bar graph showing abundance of dendritic cell (DC) subsets that differ between tumors (red) and adjacent normal tissues (blue) from scRNA-seq data. b Correlation between LAMP3+ DC signature and Treg, Tex and effector T cell signatures in the TCGA-HNSC cohort. Coefficients were calculated with Pearson’s correlation analysis. c Heatmap of t-values for the AUC scores of expression regulation based on transcription factor expression of DC subsets, estimated using SCENIC.