CyFi-MAP: an interactive pathway-based resource for cystic fibrosis

From CFTR to a CF signalling network: a systems biology approach to study Cystic Fibrosis

BACKGROUND

Cystic Fibrosis (CF) is a monogenic disease caused by mutations in the gene coding the Cystic Fibrosis Transmembrane Regulator (CFTR) protein, but its overall physio-pathology cannot be solely explained by the loss of the CFTR chloride channel function. Indeed, CFTR belongs to a yet not fully deciphered network of proteins participating in various signalling pathways.

METHODS

We propose a systems biology approach to study how the absence of the CFTR protein at the membrane leads to perturbation of these pathways, resulting in a panel of deleterious CF cellular phenotypes.

RESULTS

Based on publicly available transcriptomic datasets, we built and analyzed a CF network that recapitulates signalling dysregulations. The CF network topology and its resulting phenotypes were found to be consistent with CF pathology.

CONCLUSION

Analysis of the network topology highlighted a few proteins that may initiate the propagation of dysregulations, those that trigger CF cellular phenotypes, and suggested several candidate therapeutic targets. Although our research is focused on CF, the global approach proposed in the present paper could also be followed to study other rare monogenic diseases.

Recent advances in proteomic-based diagnostics of cystic fibrosis

INTRODUCTION

Cystic fibrosis (CF) is a genetic disease characterized by thick and sticky mucus accumulation, which may harm numerous internal organs. Various variables such as gene modifiers, environmental factors, age of diagnosis, and CF transmembrane conductance regulator (CFTR) gene mutations influence phenotypic disease diversity. Biomarkers that are based on genomic information may not accurately represent the underlying mechanism of the disease as well as its lethal complications. Therefore, recent advancements in mass spectrometry (MS)-based proteomics may provide deep insights into CF mechanisms and cellular functions by examining alterations in the protein expression patterns from various samples of individuals with CF.

AREAS COVERED

We present current developments in MS-based proteomics, its application, and findings in CF. In addition, the future roles of proteomics in finding diagnostic and prognostic novel biomarkers.

EXPERT OPINION

Despite significant advances in MS-based proteomics, extensive research in a large cohort for identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers for CF disease is highly needed.

A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance

As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.

Using the genome to correct the ion transport defect in cystic fibrosis

KEY POINTS

Human genome information can help finding drugs for human diseases. 'Omics' allow unbiased identification of novel drug targets. High-throughput (HT) approaches provide a global view on disease mechanisms. As a monogenic disease CF has led the way in multiple 'Omic' studies. 'Multi-omics' integration will generate maximal biological significance.

ABSTRACT

Today Biomedicine faces one of its greatest challenges, i.e. treating diseases through their causative dysfunctional processes and not just their symptoms. However, we still miss a global view of mechanisms and pathways involved in pathophysiology of most diseases. In fact, disease mechanisms and pathways can be achieved by holistic studies provided by 'Omic' approaches. Cystic Fibrosis (CF), caused by mutations in the CF transmembrane conductance regulator (CFTR) gene which encodes an anion channel, is paradigmatic for monogenic disorders, namely channelopathies. A high number of 'omics studies' have focussed on CF, namely several cell-based high-throughput (HT) approaches were developed and applied towards a global mechanistic characterization of CF pathophysiology and the identification of novel and 'unbiased' drug targets. Notwithstanding, it is likely that, through the integration of all these 'layers' of large datasets into comprehensive disease maps that biological significance can be extracted so that the enormous potential of these approaches to identifying dysfunctional mechanisms and novel drugs may become a reality. Abstract figure legend Schematic overview of the 3 main approaches to discovery of new drugs/drug targets. This article is protected by copyright. All rights reserved.