Recent advances in proteomic-based diagnostics of cystic fibrosis

ABSTRACT

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.

KEYWORDS:

• Cystic fibrosis
• proteomics
• CFTR
• mass spectrometry
• diagnostic biomarker

Article highlights

• Cystic fibrosis (CF) is a complex, multiorgan disease with over 2,100 known cystic fibrosis transmembrane conductance regulator (CFTR) gene variations, making it challenging to correlate genotypes with phenotypes.

• This review focuses on current developments in mass spectrometry (MS)-based proteomics and its application in CF research, providing a deeper understanding of the disease and potential novel biomarkers.

• While genomic biomarkers may not fully represent CF’s underlying mechanisms and complications, recent advances in MS-based proteomics have revealed valuable insights into CF mechanisms, including dysregulated inflammatory pathways and misfolded CFTR protein accumulation.

• Integrating proteomics with other omics technologies, such as genomics, epigenomics, transcriptomics, lipidomics, and metabolomics, will provide a more comprehensive understanding of CF pathogenesis and identify novel biomarkers.

• Continued improvement in MS analysis, proteomics workflow, and sample preparation methods will contribute to translating omics-based research findings into the clinical setting for early CF diagnosis and improved disease management.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.