A comprehensive overview of oncogenic pathways in human cancer

Abstract

Alterations of biological pathways can lead to oncogenesis. An overview of these oncogenic pathways would be highly valuable for researchers to reveal the pathogenic mechanism and develop novel therapeutic approaches for cancers. Here, we reviewed approximately 8500 literatures and documented experimentally validated cancer-pathway associations as benchmarking data set. This data resource includes 4709 manually curated relationships between 1557 paths and 49 cancers with 2427 upstream regulators in 7 species. Based on this resource, we first summarized the cancer-pathway associations and revealed some commonly deregulated pathways across tumor types. Then, we systematically analyzed these oncogenic pathways by integrating TCGA pan-cancer data sets. Multi-omics analysis showed oncogenic pathways may play different roles across tumor types under different omics contexts. We also charted the survival relevance landscape of oncogenic pathways in 26 tumor types, identified dominant omics features and found survival relevance for oncogenic pathways varied in tumor types and omics levels. Moreover, we predicted upstream regulators and constructed a hierarchical network model to understand the pathogenic mechanism of human cancers underlying oncogenic pathway context. Finally, we developed `CPAD’ (freely available at http://bio-bigdata.hrbmu.edu.cn/CPAD/), an online resource for exploring oncogenic pathways in human cancers, that integrated manually curated cancer-pathway associations, TCGA pan-cancer multi-omics data sets, drug–target data, drug sensitivity and multi-omics data for cancer cell lines. In summary, our study provides a comprehensive characterization of oncogenic pathways and also presents a valuable resource for investigating the pathogenesis of human cancer.

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis

“…More complex annotation records express a combination of multiple attributes. For example, each of the annotations from the Cancer Pathway Association Database20 (CPAD) contain seven attributes to describe a relationship between a protein or miRNA, a pathway and their effect on a specific cancer type (SupplementaryFigure S4). The pathway and gene sets are also part of the annotation database, as these are useful for functional characterization of omics data and enrichment analysis.Overall, the annotations database included 5,475,532 records about 20,365 proteins, virtually the whole protein-coding genome, 19,566 complexes and 182 miRNAs.…”

Integrated intra‐ and intercellular signaling knowledge for multicellular omics analysis

“…More complex annotation records express a combination of multiple attributes. For example, each of the annotations from the Cancer Pathway Association Database (CPAD) (Li et al, 2020) contain seven attributes to describe a relationship between a protein or miRNA, a pathway, and their effect on a specific cancer type (Fig EV3). The pathway and gene sets are also part of the annotation database, as these are useful for functional characterization of omics data and enrichment analysis.…”

Identifying subpathway signatures for individualized anticancer drug response by integrating multi-omics data

“…7). Furthermore, we focused on the roles of pathways related to more than 25% anticancer drug responses in tumorigenesis and found that some of them were experimentally validated to be associated with many cancer types according to a reliable database CPAD [53]. Especially, some notable oncogenic pathways are consistently implicated in most cancers, for example, AMPK signaling pathway, p53 signaling pathway, Jak-STAT signaling pathway and MAPK signaling pathway.…”