Additional file 6 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 6: Figure S6. Comparison between the subsets of PIS1 and PIS3. A. Enrichment score of immune cells between PIS1A and PIS1B. B. Enrichment score of immune cells between PIS3A and PIS3B, respectively

Additional file 8 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 8: Figure S8. Identification of hub gene-based risk model of PRAD. A. The prognostic value of the co-expression modules. B–D. Biological function and signaling pathways that the three prognostic co-expression modules (pink, magenta, and purple) were involved. E. Risk score of each PRAD individual. F. Differential expression of ESPL1, CDC20, and MAPK8IP3 between the high-risk and low-risk groups. G. Survival probability of the high-risk and low-risk groups. H. Accuracy of the risk model presented with receiver operating curve

Additional file 3 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 3: Figure S3. Correlation of PRAD immune subtypes with existing biomarkers and homologous recombination deficiency score. Differential expression of HOXC6 (A), PDK4 (B), and STAT3 (C) across the PRAD immune subtypes. D. Copy number variation (CNV) counts across the PRAD immune subtypes. E. Mutation frequency of the top 20 mostly mutated genes in each PRAD immune subtype. F-H. Telomeric allelic imbalance score, large scale transition score, and loss of heterozygosity score for each PRAD immune subtype. * P < 0.01, ** P < 0.001, and *** P < 0.0001

Additional file 10 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 10: Figure S10. Association between PRAD immune subtypes and risk model. A. Risk model survival curve. B. Risk model receiver operating curve. C. Risk score of each PRAD immune subtype. D. Distribution of risk groups across the PRAD immune subtypes

Additional file 7 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 7: Figure S7. Immune status of the PRAD immune subtypes. Tumor mutation burden (A) and mutation counts (B) across PIS1, PIS2, and PIS3. C. Mutation frequency of the top 20 mostly mutated genes in each PRAD immune subtype. Copy number variation (CNV) across chromosomes (D) and CNV count (E) in the PRAD immune subtypes

Additional file 4 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 4: Figure S4. Correlation between the PRAD immune subtypes and the infiltration of immune cells. The comparison of the stromal score, immune score, tumor purity, and immune cells infiltration across PIS1 to PIS3 in the CGA-PRAD cohort (A-C) and validation cohort (D–F). * P < 0.01 and *** P < 0.0001

Additional file 5 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 5: Figure S5. Immune status of the PRAD immune subtypes. A. Association of anticancer immune activity and PRAD immune subtypes. Immune-checkpoint genes and immunogenic cell death genes are differentially expressed across the PRAD immune subtypes in the training (B–C) and validation (D–E) cohorts. * P < 0.01, ** P < 0.001, and *** P < 0.0001

Additional file 2 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 2: Figure S2. Clustering of PRAD samples and the clinical features of PRAD immune subtypes. Cumulative curve (A) and delta area (B) of clustering. C. Principal component analysis of the distribution of each individual in three clusters in the training cohort. D. The differential expression of 23 prognostic immunogenic genes across the three clusters. The distribution of PIS1, PIS2, and PIS3 in the groups diagnosed with different pathologic T stages (E) or N stages (F) or treated with radiation therapy (G)

Additional file 11 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 11

Additional file 9 of Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Additional file 9: Figure S9. Construction of differentially expressed genes (DEGs)-based risk model. A. Intersection of DEGs between PIS1, PIS2, and PIS3. B. Differential expression of DEGs in PIS1, PIS2, and PIS3, and their association with clinical features. C. Prognostic value of 21 DEGs that were selected to construct the risk model. D. Part of the survival curves of the 21 DEGs. E–F. Partial likelihood deviance and coefficients response status of constructing the risk model. G. Coefficients of each DEG in the Lasso regression. H. Risk classification of each PRAD individual