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Perspective to precision medicine in scleroderma.

Authors :
Kazuhiro Komura
Koichi Yanaba
Bouaziz, Jean-David
Ayumi Yoshizaki
Minoru Hasegawa
Varga, John
Kazuhiko Takehara
Takashi Matsushita
Source :
Frontiers in Immunology; 2024, p1-9, 9p
Publication Year :
2024

Abstract

Systemic sclerosis (SSc) is a rare and heterogeneous disease with no relevant environmental trigger or significant responsible gene. It has been and will continue to be difficult to identify large enough patients to conduct classic population-based epidemiologic exposure/non-exposure studies with adequate power to ascertain environmental and genetic risk factors for these entities. The complexity of pathogenesis and heterogeneity are likely to require personalized/precision medicine for SSc. Since several potential drugs are currently available for specific patients if not whole SSc, classification of SSc seems to form the foundation for a better therapeutic strategy. To date, SSc has been classified based on the extent/severity of the affected area as well as some disease markers, including the autoantibody profile. However, such an analysis should also lead to improvements in the design of appropriately stratified clinical trials to determine the effects and prediction of targeted therapies. An approach based on drug response preclinically conducted using patients' own fibroblasts in vitro, can provide a precise disease marker/therapeutic selection for clinical practice. Because scleroderma dermal fibroblasts have a persistent hyper-productive phenotype occurring not only in person, but also in cell culture conditions. Thus, an accumulating approach based on disease markers ensures progression and de-escalation to re-establish a better life with a personally optimized drug environment after the onset of SSc. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16643224
Database :
Complementary Index
Journal :
Frontiers in Immunology
Publication Type :
Academic Journal
Accession number :
175314089
Full Text :
https://doi.org/10.3389/fimmu.2023.1298665