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Updated: May 15, 2025

Isolating Human Peripheral Blood Mononuclear Cells and CD4+ T cells from Sézary Syndrome Patients for Transcriptomic Profiling

Isolating Human Peripheral Blood Mononuclear Cells and CD4+ T cells from Sézary Syndrome Patients for Transcriptomic Profiling

Published on: October 14, 2021

Unique and shared transcriptomic signatures underlying localized scleroderma pathogenesis identified using

Aaron Bi Rosen¹, Anwesha Sanyal², Theresa Hutchins²

¹Center for Systems Immunology, Departments of Immunology and Computational & Systems Biology.

|April 8, 2025

Summary

This summary is machine-generated.

This study reveals distinct molecular signatures in localized scleroderma (LS) between adults and children using single-cell RNA sequencing. Findings identify age- and severity-specific cellular factors and shared signaling pathways with systemic sclerosis.

Keywords:

Autoimmune diseases Autoimmunity Bioinformatics Immunology

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Area of Science:

Immunology
Genomics
Dermatology

Background:

Localized scleroderma (LS) is an inflammatory fibrotic skin condition with distinct adult and pediatric presentations.
Understanding the molecular drivers of LS pathogenesis is crucial for developing targeted therapies.

Purpose of the Study:

To investigate cell-intrinsic and cell-extrinsic molecular signatures in adult and pediatric localized scleroderma (LS).
To identify latent factors underlying LS pathophysiology using advanced machine learning.
To compare molecular profiles between pediatric and adult LS and with systemic sclerosis (SSc).

Main Methods:

Single-cell RNA sequencing (scRNA-Seq) was performed on LS patients (adult and pediatric) and healthy controls.
Analysis utilized the Significant Latent Factor Interaction Discovery and Exploration (SLIDE) machine learning framework.
SLIDE infers latent factors with statistical guarantees for identifiability and inference.

Main Results:

Distinct differences in molecular signatures were observed between adult and pediatric LS.
SLIDE identified cell type-specific determinants of LS related to age and disease severity.
Shared signaling mechanisms between LS and SSc were revealed, alongside pediatric-specific onset differences.

Conclusions:

Single-cell transcriptomics and SLIDE provide deep insights into LS pathophysiology.
Age and severity-specific cellular drivers and shared signaling pathways with SSc are identified.
These findings can stratify LS subtypes and inform therapeutic strategies.