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Validation of a gene expression-based subclassification strategy for pediatric septic shock
Hector R Wong1, Natalie Z Cvijanovich, Geoffrey L Allen
1Department of Pediatrics, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA. hector.wong@cchmc.org
Insights
Researchers validated three septic shock subclasses in children using a 100-gene expression signature. These subclasses show distinct clinical differences, aiding patient management and clinical trials.
Area of Science:
- Pediatric critical care medicine
- Molecular biology
- Bioinformatics
Background:
- Septic shock exhibits significant heterogeneity, complicating clinical trials and patient care.
- Previous research identified three potential septic shock subclasses in children based on a 100-gene expression signature.
Purpose of the Study:
- To prospectively validate the previously identified gene expression-based subclasses of pediatric septic shock.
- To confirm the clinical relevance and distinct characteristics of these subclasses in a new cohort.
Main Methods:
- Prospective observational study utilizing microarray-based bioinformatics.
- Analysis of separate derivation (n=98) and validation (n=82) cohorts of children with septic shock.
- Classification of patients into subclasses A, B, or C using computer-based image analysis of gene expression mosaics.
Main Results:
- The 100-gene signature successfully classified 82 children in the validation cohort into three subclasses.
- Subclass A exhibited higher illness severity, greater organ failure, fewer intensive care unit-free days, and higher Pediatric Risk of Mortality scores.
- Subclass A patients showed repressed adaptive immunity and glucocorticoid receptor signaling genes. Clinician consensus showed modest agreement with the algorithm.
Conclusions:
- The existence of distinct subclasses in pediatric septic shock, defined by a 100-gene expression signature, has been prospectively validated.
- These gene expression-based subclasses possess clinically significant differences, offering potential for improved patient stratification and management.
Objective:
Septic shock heterogeneity has important implications for clinical trial implementation and patient management. We previously addressed this heterogeneity by identifying three putative subclasses of children with septic shock based exclusively on a 100-gene expression signature. Here we attempted to prospectively validate the existence of these gene expression-based subclasses in a validation cohort.
Design:
Prospective observational study involving microarray-based bioinformatics.
Setting:
Multiple pediatric intensive care units in the United States.
Patients:
Separate derivation (n = 98) and validation (n = 82) cohorts of children with septic shock.
Interventions:
None other than standard care.
Measurements And Main Results:
Gene expression mosaics of the 100 class-defining genes were generated for 82 individual patients in the validation cohort. Using computer-based image analysis, patients were classified into one of three subclasses ("A," "B," or "C") based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. After subclassification, the clinical database was mined for phenotyping. Subclass A patients had higher illness severity relative to subclasses B and C as measured by maximal organ failure, fewer intensive care unit-free days, and a higher Pediatric Risk of Mortality score. Patients in subclass A were characterized by repression of genes corresponding to adaptive immunity and glucocorticoid receptor signaling. Separate subclass assignments were conducted by 21 individual clinicians using visual inspection. The consensus classification of the clinicians had modest agreement with the computer algorithm.
Conclusions:
We have validated the existence of subclasses of children with septic shock based on a biologically relevant, 100-gene expression signature. The subclasses have relevant clinical differences.
