HuPEX®-Based Research Published in Nature Communications

Research conducted using HuPEX®, a comprehensive human proteome expression platform, has been published in Nature Communications, one of the world’s leading scientific journals.

Systemic sclerosis (SSc) is a rare autoimmune disease characterized by progressive fibrosis, causing hardening of the skin and internal organs. While B-cell depletion therapy with rituximab (RTX) has shown clinical benefit in some patients, there have been no reliable biomarkers to predict which patients will respond to treatment.

In this study, researchers utilized HuPEX® (Human Proteome Expression resource), which enables large-scale expression of human proteins. More than 13,000 human proteins were synthesized and incorporated into a HuPEX® proteome-wide protein array. Using this platform, the team comprehensively analyzed autoantibodies present in the sera of patients with systemic sclerosis who received RTX therapy.

This proteome-wide approach allowed researchers to move beyond conventional analyses limited to specific autoantibodies and instead capture the full autoantibody profile unique to each patient.

The study demonstrated that total autoantibody levels were significantly higher in patients with systemic sclerosis than in healthy individuals. Importantly, patients who showed a strong clinical response to RTX experienced a greater reduction in total autoantibody levels after treatment compared with low responders.

Further analysis identified autoantibodies targeting CCR8, a chemokine receptor involved in immune regulation, as a potential marker associated with treatment response and disease mechanisms. Experiments using CCR8-overexpressing cells and disease model mice suggested that these autoantibodies may influence immune cell function and contribute to fibrotic disease progression.

These findings provide new insights into the role of autoantibodies in systemic sclerosis and highlight the potential of HuPEX® as a powerful platform for biomarker discovery. The results may support future efforts to better understand disease pathology and to develop predictive indicators for therapeutic response.

For more information, please refer to the published article in Nature Communications.