Skin Gene Expression Profiles in Systemic Sclerosis: From Clinical Stratification to Precision Medicine

Area of Science:

• Computational biology
• Genomics
• Dermatology

Background:

• Systemic sclerosis (SSc), or scleroderma, exhibits significant heterogeneity in clinical presentation, disease progression, and treatment response.
• This heterogeneity poses challenges for designing effective clinical trials to identify therapeutic interventions.
• Recent advances in molecular profiling and stratification techniques offer potential for personalized treatment strategies.

Purpose of the Study:

• To review the current state of skin gene expression analysis in SSc using computational biology.
• To highlight the advantages of stratifying SSc patients based on their skin gene signatures.

Main Methods:

• Narrative review of existing literature.
• Focus on computational biology approaches for skin gene expression analysis.
• Exploration of patient stratification techniques based on molecular profiles.

Main Results:

• Skin gene expression analysis, coupled with computational biology, allows for the identification of distinct patient subgroups within SSc.
• Stratification based on skin gene signatures can reveal patient subgroups amenable to specific therapeutic interventions.
• This approach supports the development of personalized treatment strategies for SSc.

Conclusions:

• Skin gene expression profiling and computational analysis are crucial for understanding SSc heterogeneity.
• Patient stratification by gene signatures facilitates a precision medicine approach to SSc management.
• This strategy holds promise for improving treatment efficacy and clinical trial design in SSc.