Objective: We sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma).
Methods: Fifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in two clinical trials. Histologic/immunophenotypic assessments of global severity, alpha-smooth muscle actin (aSMA), CD34, collagen, inflammatory infiltrate, follicles and thickness were compared with gene expression and clinical data. Support vector machine learning was performed using scleroderma gene expression subset (normal-like, fibroproliferative, inflammatory) as classifiers and histology scores as inputs. Comparison of w-vector mean absolute weights was used to identify histologic features most predictive of gene expression subset. We then tested for differential gene expression according to histologic severity and compared those with clinical improvement (according to the Combined Response Index in Systemic Sclerosis).
Results: aSMA was highest and CD34 lowest in samples with highest local Modified Rodnan Skin Score. CD34 and aSMA changed significantly from baseline to 52 weeks in clinical improvers. CD34 and aSMA were the strongest predictors of gene expression subset, with highest CD34 staining in the normal-like subset (p<0.001) and highest aSMA staining in the inflammatory subset (p=0.016). Analysis of gene expression according to CD34 and aSMA binarised scores identified a 47-gene fibroblast polarisation signature that decreases over time only in improvers (vs non-improvers). Pathway analysis of these genes identified gene expression signatures of inflammatory fibroblasts.
Conclusion: CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc.
Kimberly Showalter 1, Robert Spiera 2, Cynthia Magro 3, Phaedra Agius 4, Viktor Martyanov 5 6, Jennifer M Franks 5 6, Roshan Sharma 4, Heather Geiger 4, Tammara A Wood 5 6, Yaxia Zhang 7, Caryn R Hale 8, Jackie Finik 9, Michael L Whitfield 5 6, Dana E Orange # 2 8, Jessica K Gordon # 2
Affiliations
1Department of Medicine, Division of Rheumatology, Hospital for Special Surgery, New York, New York, USA showalterk@hss.edu.
2Department of Medicine, Division of Rheumatology, Hospital for Special Surgery, New York, New York, USA.
3Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York, USA.
4New York Genome Center, New York, New York, USA.
5Molecular and Systems Biology, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA.
6Biomedical Data Science, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA.
7Department of Pathology, Hospital for Special Surgery, New York, New York, USA.
8Laboratory of Molecular Neuro-Oncology, The Rockefeller University, New York, New York, USA.
9Department of Medicine, Hospital for Special Surgery, New York, New York, USA.
#Contributed equally.
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