Biological network analysis with the Core&Peel method

Genes are organized in functional modules (or pathways), thus their action and their dysregulation in diseases may be better understood by the identification of the modules most affected by the disease (aka disease modules, or active subnetworks). We describe how an algorithm based on the Core&Peel method is used to detect disease modules in a co-expression network of genes. We first validate Core&Peel for the general task of functional module detection by comparison with 42 methods participating in the Disease Module Identification DREAM challenge. Next, we use four specific disease test cases (colorectal cancer, prostate cancer, asthma, and rheumatoid arthritis), four state-of-the-art algorithms (ModuleDiscoverer, Degas, KeyPathwayMiner, and ClustEx), and several pathway databases to validate the proposed algorithm. Core&Peel is the only method able to find significant associations of the predicted disease module with known validated relevant pathways for all four diseases. Finally, we apply Core&Peel and other methods to explore the transcriptional response of human cells to SARS-CoV-2 infection, finding supporting evidence for drug repositioning efforts at a pre-clinical level. Computational drug repositioning aims at ranking and selecting existing drugs for novel diseases or novel use in old diseases. In silico drug screening has the potential for speeding up considerably the shortlisting of promising candidates in response to outbreaks of diseases such as COVID-19 for which no satisfactory cure has yet been found. We describe DrugMerge as a methodology for preclinical computational drug repositioning based on merging multiple drug rankings obtained with an ensemble of disease active subnetworks. DrugMerge uses differential transcriptomic data on drugs and diseases in the context of a large gene co-expression network. Experiments with four benchmark diseases demonstrate that our method detects in first position drugs in clinical use for the specified disease, in all four cases. Application of DrugMerge to COVID-19 found rankings with many drugs currently in clinical trials for COVID-19 in top positions, thus showing that DrugMerge can mimic human expert judgment. Apoptosis and autophagy play essential roles in cellular homeostasis, and their deregulation can lead to cancer. These two pathways are interconnected by several molecular nodes of crosstalk, enabling their regulation. The finding of new molecules acting in the crosstalk is an important step for a more complete understanding of the regulation of autophagy and apoptosis, which is essential for the rational design of successful anticancer therapeutics. To predict new proteins acting in the crosstalk, we apply the Core&Peel method to a protein-protein interaction network to firstly predict complexes involved in apoptosis and autophagy. Core&Peel can predict complexes that have some proteins in common with each other, and this feature enables us to select proteins that are shared between the apoptosis-complexes and autophagy-complexes. These candidate proteins are presumably involved in both pathways since they belong to apoptosis-complex and autophagy-complex. In the end, we obtained 54 candidate proteins that include two short linear motifs that are crucial in mediating autophagic and apoptotic processes, and they are annotated in the main apoptosis and autophagy pathways.