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Published on: May 27, 2021
A Synthetic Lethality-Informed Multi-Omic Framework for Identifying a Five-Gene Diagnostic Signature in Chronic
Yue Yang1, Zengrui Wang1, Xiaorong Su1
1The First School of Clinical Medicine, Kunming Medical University, Kunming 650500, China.
Current Issues in Molecular Biology
|May 27, 2026
Summary
Researchers identified a five-gene signature for diagnosing chronic obstructive pulmonary disease (COPD) using synthetic lethality gene prioritization. This molecular tool aids in early COPD diagnosis and risk stratification beyond traditional methods.
Area of Science:
- Genomics and Bioinformatics
- Molecular Biology
- Pulmonary Medicine
Background:
- Chronic obstructive pulmonary disease (COPD) diagnosis relies heavily on spirometry, lacking precise molecular biomarkers for early detection and risk stratification.
- Synthetic lethality (SL) gene prioritization offers a novel, biologically informed approach to identify potential disease-associated biomarkers.
- Integrating transcriptomic data with SL gene sets and machine learning can uncover novel diagnostic signatures for complex diseases like COPD.
Purpose of the Study:
- To identify a robust molecular diagnostic signature for COPD using synthetic lethality-related genes.
- To validate the diagnostic performance of the identified gene signature in an independent cohort.
- To explore the biological relevance and potential clinical utility of the identified COPD biomarkers.
Main Methods:
- Integrated public transcriptomic datasets (GSE47460, GSE57148) with SL-related gene sets.
- Employed machine learning algorithms (LASSO regression, random forest) for feature selection and signature development.
- Validated the diagnostic signature using an independent cohort and assessed performance via AUC.
Main Results:
- Identified 74 SL-related differentially expressed genes associated with inflammation and extracellular matrix organization in COPD.
- Developed a five-gene diagnostic signature (CYP1B1, VEGFA, RET, FGG, S100A9) with significant diagnostic performance (AUC=0.8311) in the validation cohort.
- Preliminary analyses including single-cell RNA sequencing and in vitro experiments supported the biological relevance of the identified genes.
Conclusions:
- Synthetic lethality-related gene prioritization combined with multi-omic integration is a viable strategy for COPD biomarker discovery.
- The identified five-gene signature demonstrates potential as an adjunctive molecular tool for COPD diagnosis and risk assessment.
- The study generates testable hypotheses regarding COPD-associated vulnerability pathways.
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