Transcriptional landscape of human cancers

Abstract

The homogeneity and heterogeneity in somatic mutations, copy number alterations and methylation across different cancer types have been extensively explored. However, the related exploration based on transcriptome data is lacking. In this study we explored gene expression profiles across 33 human cancer types using The Cancer Genome Atlas (TCGA) data. We identified consistently upregulated genes (such as E2F1, EZH2, FOXM1, MYBL2, PLK1, TTK, AURKA/B and BUB1) and consistently downregulated genes (such as SCARA5, MYOM1, NKAPL, PEG3, USP2, SLC5A7 and HMGCLL1) across various cancers. The dysregulation of these genes is likely to be associated with poor clinical outcomes in cancer. The dysregulated pathways commonly in cancers include cell cycle, DNA replication, repair, and recombination, Notch signaling, p53 signaling, Wnt signaling, TGFβ signaling, immune response etc. We also identified genes consistently upregulated or downregulated in highly-advanced cancers compared to lowly-advanced cancers. The highly (low) expressed genes in highly-advanced cancers are likely to have higher (lower) expression levels in cancers than in normal tissue, indicating that common gene expression perturbations drive cancer initiation and cancer progression. In addition, we identified a substantial number of genes exclusively dysregulated in a single cancer type or inconsistently dysregulated in different cancer types, demonstrating the intertumor heterogeneity. More importantly, we found a number of genes commonly dysregulated in various cancers such as PLP1, MYOM1, NKAPL and USP2 which were investigated in few cancer related studies, and thus represent our novel findings. Our study provides comprehensive portraits of transcriptional landscape of human cancers.