Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation
Fig 5
Correlation between transcriptomics and proteomics analysis.
(A) Volcano plot distribution of the proteomics data. Fold change (Tumor/mucosa) is represented. Dots are labelled according to the transcriptomic fold change. (B) Scatter plot of significantly altered canonical proteins. Pearson’s coefficient is shown. (C) Histogram distribution of protein expression levels (ranked bins) and (D) Cellular Component analysis of proteins or genes significantly altered between normal mucosa and tumor in proteomics and/or transcriptomics. More relevant categories were selected. (E) Correlation of hazard ratios obtained using proteomics data and RNA-seq data from CPTAC. (F) Correlation of hazard ratios obtained using proteomics data (CPTAC) and RNA-seq data (TCGA). Only significantly prognosis-associated proteins are shown. Pearson correlation coefficient (r) is indicated. (G) Portion of the canonical proteins significantly associated with survival according to proteomics (CPTAC) and/or transcriptomics (TCGA) data. Significance was calculated by Cox regression analysis. Chart pie of all the significant associated mRNA (TCGA) and proteins (CPTAC).