Additional file 12: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Figure S8. Expression of HMAG1 isoforms in medulloblastoma tumors. a) Schematic representation of HMGA11 isoforms and Boxplots representing the mRNA expression levels for HMGA1 isoforms. b). Western blot of HMGA1 isoforms in the four medulloblastoma subgroups. Both HMAG1 isoforms are highly expressed in group 3 medulloblastoma. c) Kaplan–Meier survival curve shows that increased levels of HMGA1 are associated with poor survival in Group 3 Medulloblastoma. d) Expression level of HMGA1 is highly correlated with the expression of the oncogene MYC in Group 3 Medulloblastoma. (PDF 1.94 mb

Additional file 2: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Table S2. Correlation between mRNA and Protein abundance. Column names legend. Gene: Gene name symbol, TumorID_Prot: Protein quantification value, TumorID_RNA: mRNA quantification value, corr: spearman correlation coefficient, p-value: spearman correlation coefficient p-value. (XLSX 2 mb

Additional file 11: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Figure S7. Expression of CALD1 isoforms in medulloblastoma tumors. The protein expression level of CALD1 isoforms in medulloblastoma subgroups is confirmed at the epigenetic (H3K27Ac Chip-seq) and mRNA level. a) Schematic representation of CALD1 isoforms. b) H3K27Ac Chip-seq genome tracks in medulloblastoma tumors. Active transcription region marks (H3K27Ac) are observed in the alternative transcription start site for the isoforms HeLa l-CaD I and II correlating with higher expression of these protein isoforms. c) Boxplots representing the mRNA expression levels for CALD1 isoforms. (PDF 2.2 mb

Additional file 14: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Table S6. List of present and absent proteins. (XLSX 153 kb

Additional file 17: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Table S8. List of pathways representative for each medulloblastoma subgroup. (XLSX 72.6 kb

Additional file 13: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Table S5. List of Differentially expressed proteins. (XLSX 235 kb

Additional file 7: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Figure S4. Copy number effect on mRNA and protein abundance on chromosome arm 17q. a) GRB2, LASP1, KPNB1 and ARHGDIA showed significant CNA-protein correlations (p < 0.05). The colors depict the range from low (white) to high (green) of copy-number, protein and mRNA abundance. Samples were ranked by copy number at each gene locus. b) ARHGDIA protein was found to be significantly overexpressed in group 4 tumors which frequently harbor 17q gains but not at the mRNA transcript level. Differences among the four subgroups were evaluated based on the Kruskal-Wallisrank-sum test. (PDF 916 kb

Additional file 10: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Figure S6. Medulloblastoma subgroup specific isoforms. Schematic representation of MCM3, TPM4, SPTAN1 and EEF1D isoforms. Boxplots show the quantification of each protein isoforms group across all medulloblastoma subgroups. p-values for differences between subgroups were calculated based on the Kruskal-Wallis rank-sum test. A protein group is defined as the group of isoforms that are indistinguishable due to the position of identified peptides. (PDF 1.13 mb

Additional file 3: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Figure S1. Correlation between mRNA and protein abundance by subgroups. a) Frequency distribution plots of mRNA-protein spearman’s correlations for each medulloblastoma subgroup. Positive mRNA-protein correlations were found for 68–80% of mRNA-protein pairs with means between (0.30–0.16) depending on the subgroup. However, just a small proportion of them were significant (10–17%). Group 3 was the subgroup with the highest number of significant positive correlations and the highest mean; in contrast, group 4 had the lowest mean. b) Box-plots depicting the distribution of mRNA-protein Spearman’s correlations by subgroup. p-values for differences between the subgroups were calculated with the Kruskal-Wallis rank-sum test. p-values indicating the differences between group 4 and the others were calculated with a two-sided Wilcoxon rank sum test. (PDF 706 kb

Additional file 8: of Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Figure S5. Proteomic subgroup classification recapitulates genomic subgroups using different data elements. Comparison of non-negative matrix factorization consensus clustering between protein and mRNA expression data from 34 primary medulloblastoma and five normal cerebellar tissues. a) The Cophenetic and Silhouette coefficient values for rank k between 2 and 10 in mRNA and protein dataset. b) NMF clusters (k = 6) for the same genes coding for the proteins used in the proteomic classification at the mRNA or protein level. Clustering did not improve for other k values 2 through 10 (data not shown). (PDF 994 kb