Abstract
Current methods of high-throughput molecular and genomic analyses enabled to reconstruct thousands of human molecular pathways. Knowledge of molecular pathways structure and architecture taken along with the gene expression data can help interrogating the pathway activation levels (PALs) using different bioinformatic algorithms. In turn, the pathway activation profiles can characterize molecular processes, which are differentially regulated and give numeric characteristics of the extent of their activation or inhibition. However, different pathway nodes may have different functions toward overall pathway regulation, and calculation of PAL requires knowledge of molecular function of every node in the pathway in terms of its activator or inhibitory role. Thus, high-throughput annotation of functional roles of pathway nodes is required for the comprehensive analysis of the pathway activation profiles. We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. The resulting knowledgebase can be applied for the direct calculation of the PALs and establishing large scale profiles of the signaling, metabolic, and DNA repair pathway regulation using high throughput gene expression data. We also provide a bioinformatic tool for PAL data calculations using the current pathway knowledgebase.
Highlights
Intracellular molecular pathways are specific networks of interacting molecules that are involved in certain molecular functions (Junaid et al, 2020; Ma and Liao, 2020; Zheng et al, 2020)
We proposed an algorithm that identifies functional roles of the pathway components based on the pathway topology and applied it here to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, Kyoto Encyclopedia of Genes and Genomes (KEGG), National Cancer Institute (NCI), and HumanCYC databases, collectively covering 9,022 gene products
We propose here the recursive algorithm for functional annotation of the molecular pathway nodes, and its application to annotation of 3,044 human molecular pathways, including signaling, metabolic, and DNA repair pathways extracted from six major pathway hubs (Table 1)
Summary
Intracellular molecular pathways are specific networks of interacting molecules that are involved in certain molecular functions (Junaid et al, 2020; Ma and Liao, 2020; Zheng et al, 2020). Several popular algorithms and software like gene ontology (GO) analysis tools (Huang et al, 2009a,b), Metacore (Ekins et al, 2007) and Pathway Studio (Thomas and Bonchev, 2010) can analyze gene expression data to identify pathways significantly enriched by differentially regulated genes (Dubovenko et al, 2017) Those techniques cannot identify the enhanced or inhibited status of a pathway regulation, because pathways may have numerous negative feedback loops or negative regulatory nodes (Khatri et al, 2012) and, the pathway nodes may involve both genes with its activating and genes with inhibitory functions (Borisov et al, 2020). Several techniques had been proposed, e.g., Oncofinder (Buzdin et al, 2014b), iPANDA (Ozerov et al, 2016), and Oncobox (Borisov et al, 2020) that utilize transcriptome-wide or even proteome-wide (Borisov et al, 2017) data to calculate pathway activation levels (PALs) Those are the numeric characteristics that can be used in all types of comparisons including biomarker investigations. The resulting knowledgebase can be applied for the direct calculation of the PALs and establishing large scale profiles of the signaling, metabolic, and DNA repair pathway regulation using high throughput gene expression data
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