Additional file 3: Fig. S1. A, B PCA based on the six pyroptosis-related genes signature. C, D The relationship between the risk score and metastasis. E-G The nomogram calibration curves for predicting 1-, 3-, and 5-year survival in the GSE21257 cohort. H Kaplan–Meier analysis based on the pan-cancer data set and univariate Cox regression analysis of CHMP4C. I The expressions of CHMP4C in tumor and adjacent normal tissues.

Additional file 4: Figure S3. Volcano plot showing the log2 fold change of 517 significantly differentially expressed miRNAs in CRC patients from the TCGA database.

Additional file 5: Figure S4. Prediction of 6 miRNAs (miR-29b-3p, miR-4677-3p, miR-144-3p, miR-30b-5p, miR-30e-5p and miR-374b-5p) targeting LIFR-AS1 in CRC.

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary Figure 4

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary Figure 4

Additional file 1: Figure S1. The mRNA level of CBFA1 in qRT-PCR (a) and RNA-Seq (b). *P < 0.05.

Additional file 4: Figure S4. HE (scale bar = 50 μm) and Masson (scale bar = 50 μm) staining were performed to evaluate ectopic bone formation in nude mice (n=4).

TableS1. Clinical data of ovarian cancer patients from TCGA and ICGC.
TableS2.Identified DNA driver methylation (DNAme) in TCGA, ICGC and GSE146556.
TableS3. The correlation between DNAme and corresponding mRNA expression in TCGA, ICGC and GSE146556. TableS4.Analysis of pathway enrichment (KEGG) and Gene Ontology (GO) of DNAme-associated mRNA in TCGA.
TableS5. Univariate Cox regression analysis of DNAme-associated mRNA. (P < 0.05)
TableS6. Analysis of pathway enrichment (KEGG) and Gene Ontology (GO) of...

Additional file 3: Fig. S1. A, B PCA based on the six pyroptosis-related genes signature. C, D The relationship between the risk score and metastasis. E-G The nomogram calibration curves for predicting 1-, 3-, and 5-year survival in the GSE21257 cohort. H Kaplan–Meier analysis based on the pan-cancer data set and univariate Cox regression analysis of CHMP4C. I The expressions of CHMP4C in tumor and adjacent normal tissues.

Additional file 4: Fig. S2. The PPI network.

Additional file 3: Figure S3. HE (scale bar = 200 μm) and Masson (scale bar = 50 μm) staining in the rat calvarial defect model (n = 6).

Additional file 3: Figure S2. Correlation (P values derive from Spearman’s correlation) between DNA methylation and the expression of LIFR-AS1 in CRC samples.

Additional file 3: Figure S2. Correlation (P values derive from Spearman’s correlation) between DNA methylation and the expression of LIFR-AS1 in CRC samples.

Additional file 1: Fig. S1 The distributions of variant allele frequencies (VAFs) of ARID1A, ARID1B, ARID2, PBRM1, SMARCA4, and SMARCB1. The median VAFs of the above genes were 16.1%, 13.4%, 13.3%, 17.2%, 15.2%, and 16.7%, respectively. Red solid line, median; black dotted line, quartiles.

Additional file 3: Fig. S3 The signaling pathway enrichment of the variated genes in the SWI/SNF-mutant tumors by GO analysis. The GO analysis was performed on all the mutated genes in 1001 SWI/SNF-mutant samples.

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary Figure 3

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary Figure 3

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary figure

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary figure

Additional file 1: Fig. S1 The distributions of variant allele frequencies (VAFs) of ARID1A, ARID1B, ARID2, PBRM1, SMARCA4, and SMARCB1. The median VAFs of the above genes were 16.1%, 13.4%, 13.3%, 17.2%, 15.2%, and 16.7%, respectively. Red solid line, median; black dotted line, quartiles.

Additional file 1: Figure S1. Pie chart shows the number of differentially expressed lncRNAs in each category.

Additional file 4: Figure S3. Volcano plot showing the log2 fold change of 517 significantly differentially expressed miRNAs in CRC patients from the TCGA database.

Supplementary Material 2

Additional file 2: Figure S2. Results of western blot analysis showed that ETV2 overexpression induced the the activation of p-ERK and p-AKT at days 3, 7 and 14 of osteogenic differentiation. *P < 0.05, compared with the 0 day group.

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor Supplementary Figure 2