Fig. 1
Sample filtering workflow used for integrative genomic analyses and differential expression results by comparing 11 PBRM1 mutated and 33 “pan-negative” ccRCC samples. a A sample filtering workflow was used for integrative genomic analyses. First, 548 ccRCC samples were split into PBRM1 mutated group (177 samples) and PBRM1 non-mutated group (371 samples). Five high-confidence ccRCC driver genes (VHL, BAP1, SETD2, PTEN and KDM5C) were excluded in both groups, resulting in 31 PBRM1 mutated samples and 109 “pan-negative” samples. After that, samples that have all DNA methylation, RNA-Seq, and miRNA-Seq data were extracted; resulting in 11 PBRM1 mutated samples and 33 “pan-negative” samples for further in-depth integrative analysis. b Cartoon representation of mutation types and locations in 11 PBRM1 truncation mutated samples. Five nonsense mutations (red diamond), three splice sites mutations (green round), and three frame shift deletions (purple square) were observed in 11 PBRM1 truncated mutation samples. c Volcano plot of significance of gene expression difference between PBRM1 mutated group and “pan-negative” group at gene expression levels. Each dot represents one gene. The x axis shows the gene expression difference by a log transformed fold change while the y axis shows significance by –log10 transformed p-value value obtained from edgeR. A gene is called significantly and differentially expressed if its |log(FC)| > 2 and p-value < 0.05. Red dashed line shows |log(FC)| =2 or p-value = 0.05. d Bar plot of log transfer of fold change in differentially expressed transcriptional factors. 23 transcriptional factors were found to be down-regulated in PBRM1 mutated group while three transcriptional factors were found up-regulated