Additional file 1: Figure S1. Forest plot for failure to achieve clinical remission at 4 weeks subgroup by previous TNF-α exposure in ADA and control groups.

Additional file 15: Figure S8. Workflow of this study. Single-cell transcriptomes and bulk RNA-seq data were integrated to fully analyze the complicated relationship between colorectal epithelium and surrounding environment. C4 cells were featured with high invasive potential and related with TAMs and CAFs, and further validated in vitro using IHC and mIHC.

Additional file 13: Figure S6. Characterization of stromal cells in the SMC cohort. A. UMAP plot of stromal cells colored by cell cluster and sample origin. B. Heat map of marker genes identified through Seurat. For each cell cluster, cells were down-sampled to 100. C. Differentiation trajectories inferred by Monocle2. Dots represent stromal cells and are colored by identified cell cluster. D. Heat map of the top 5 ranked regulons in S5 and S6. E....

Additional file 8: Figure S1. Cellular landscape of CRC in the KUL3 cohort. A. UMAP plot of 26,268 cells colored by cell cluster, CMS and sample origin. Each dot represents a cell and cellular cluster is annotated with text. B. Proportions of the identified cell clusters distributed across tumor, border and adjacent normal tissues with the relative cell type proportions and total cell numbers. Upper: all cell clusters; lower: immune and stromal cell clusters. C....

Additional file 9: Figure S2. Functional heterogeneity of CRC epithelial cells in the SMC cohort. A. UMAP feature plot of the top 10 upregulated genes in the SMC cohort. B. Correlation heat map of 123 programs identified by cNMF. The Pearson correlation coefficient is indicated by the color. C. Heatmap of the relative mean signature score of cancer cell functional signatures across C1-C7. The signature score was calculated using the “AUCell” package. D. Heatmap of...

Additional file 2: Figure S2. Validation of the pyroptosis-related prognostic model in test set. (A) The patients were divided into two groups according to the threshold of median risk score. Green represents the low-risk group. Red represents the high-risk group. (B) Kaplan Meier curves showing the overall survival of patients in the high-risk and low-risk groups. (C) Survival status of patients with PAAD in high and low risk groups. Green represents survival. Red represents death....

Additional file 2: Figure S2. Validation of the pyroptosis-related prognostic model in test set. (A) The patients were divided into two groups according to the threshold of median risk score. Green represents the low-risk group. Red represents the high-risk group. (B) Kaplan Meier curves showing the overall survival of patients in the high-risk and low-risk groups. (C) Survival status of patients with PAAD in high and low risk groups. Green represents survival. Red represents death....

Additional file 3: Figure S3. Risk model independent prognostic analysis. (A) Univariate independent prognosis Cox regression analysis of risk score and indicated clinical characteristics. (B) Multivariate independent prognosis Cox regression analysis of risk score and indicated clinical characteristics.

Additional file 4: Figure S4. The correlation of pyroptosis-related prognostic genes and clinical features in the training set. (A, B, C) The correlation of NLRP1 with grade, N stage, T stage. (D) The correlation of NLRP2 with grade. (E) The correlation of GSDMC with stage. (F) The correlation of CASP4 with grade. (G) The correlation of risk score with grade.

Additional file 6: Figure S6. The correlation of immune infiltrating cells with risk scores was determined in the training set. (A) Boxplots represent the level of different types of immune infiltrating cells in high- and low- risk group. (B-F) the correlation between the risk score and immune infiltrating cells was further examined by Spearman correlation analysis. *p < 0.05, ***p < 0.001.

Additional file 7: Figure S7. Kaplan-Meier curves of the prognostic pyroptosis-related genes in the training set. The survival curves of NLRP1 (A), NLRP2 (B), GSDMC (C), IL18 (D), CASP4 (E).

Additional file 8: Figure S8. Restoration of GSDMC rescued the inhibition of cell proliferation, migration and invasion induced by GSDMC silencing. (A) PANC-1 (left panel) and CFPAC-1 (right panel) cells were subjected to immunoblotting as indicated. (B, C) Cell growth of PANC-1 cells (B) and CFPAC-1 cells (C) were measured by CCK-8 assay. *P < 0.05, **P < 0.01 by two-way ANOVA. (D, F) Clone formation of PANC-1 cells (D) and CFPAC-1 cells (F) were...

Additional file 15: Figure S6. circPVT1 promotes the migration and invasion of NPC cells by regulating cell adhesion andcytoskeleton remodeling. The 231 differentially expressed proteins regulated by c-Myc from LC-MS/MS data using the Ingenuity Pathway Analysis (IPA) software.

Additional file 1: Figure S1. Heatmap plot showing RNA expression changes of genes in HeLa cells 0.5 h A and 2 h B after irradiation compared to unirradiated cells

Additional file 2: Figure S2. A Scatter plot showing RNA expression changes of genes in HeLa cells 0.5 h after irradiation compared to unirradiated cells. KEGG B and GO C analyses of differentially expressed genes in HeLa cells 0.5 h after irradiation compared to unirradiated cells

Additional file 3: Figure S3. Significantly regulated PI3K pathway genes in HeLa cells 2 h after 4 Gy irradiation compared to unirradiated cells

Supplemental figures 1-6 and the correspondent figure legends.

Additional file 8: Figure S4. The overexpression of MYOCD indicated better overall survival in (A) breast cancer, (B) ovarian cancer and (C) lung cancer. Contracting survival outcomes can be observed in (D) gastric cancer. Data from KM-plotter.

Additional file 2: Fig. S2. Statistical power of differential expression of miR-222-3p in different groups was estimated using Gpower software.

Additional file 4: Figure S4. Enrichment of differentially expressed genes in Serpine1-overexpressing MLE-12 cells. A, B GO and KEGG enrichment of the upregulated genes. C, D GO and KEGG enrichment of the downregulated genes. Q-value ≤ 0.05 and fold-change ≥ 2 were used as the thresholds for screening the differentially expressed genes.

Additional file 6: Figure S6. HDAC2 inhibition promoted the expression of Serpine1. A SDS-PAGE identification of the proteins pulled-down by DNA fragment of Serpine1 promoter. The gel was stained with Coomassie blue. The indicated differential bands were excised with a scalpel and identified by LC-MS. B Total ion chromatogram of proteins. C–E Serpine1 expression analysed using RT-qPCR and western blot in trichostatin A (TSA)-treated MLE-12 cells. Data show mean ± SEM; Data was analysed using...

Additional file 6: Figure S6. HDAC2 inhibition promoted the expression of Serpine1. A SDS-PAGE identification of the proteins pulled-down by DNA fragment of Serpine1 promoter. The gel was stained with Coomassie blue. The indicated differential bands were excised with a scalpel and identified by LC-MS. B Total ion chromatogram of proteins. C–E Serpine1 expression analysed using RT-qPCR and western blot in trichostatin A (TSA)-treated MLE-12 cells. Data show mean ± SEM; Data was analysed using...

Additional file 3.

Supplemental material, sj-tif-1-npx-10.1177_1934578X221130874 for Cryptotanshinone From Salvia miltiorrhiza Inhibits the Growth of Tumors and Enhances the Efficacy of Chemotherapy in a Gastric Cancer Mouse Model by Wenkai Wu, Yezhi Cao, Ling Cheng, Linghu Wang, Qingsheng Yu, Hui Peng, Fuhai Zhou, Haiwei Liu and Qi Zhang in Natural Product Communications

Supplemental material, sj-tif-2-npx-10.1177_1934578X221130874 for Cryptotanshinone From Salvia miltiorrhiza Inhibits the Growth of Tumors and Enhances the Efficacy of Chemotherapy in a Gastric Cancer Mouse Model by Wenkai Wu, Yezhi Cao, Ling Cheng, Linghu Wang, Qingsheng Yu, Hui Peng, Fuhai Zhou, Haiwei Liu and Qi Zhang in Natural Product Communications