Background/Purpose:

Imatinib is a potent inhibitor of TGF-β signaling. Furthermore, a subgroup of SSc patients shows a prominent TGF-β gene expression signature in skin biopsy samples. We examined whether baseline TGF-β skin gene expression signature or other previously described signatures differentiate responders from non-responders to imatinib treatment.

Methods:

Patients with SSc were enrolled in a 1-year open-label pilot study of imatinib (Khanna D, A&R 2011).  All patients had active interstitial lung disease defined as forced vital capacity (FVC) < 85% predicted, dyspnea on exertion, and presence of a ground glass opacity on HRCT. Percent changes in the modified Rodnan Skin Score (mRSS) and % predicted FVC were calculated based on the baseline and last measurement in the study.  Baseline skin biopsies were available in five patients (3 diffuse and 2 limited cutaneous involvement) who completed a 12 month course of treatment. Additional 3 patients had 3 month data available who stopped due to adverse events. Percent change in mRSS ranged from 53% worsening to 33% improvement while percent change in FVC ranged from 9% worsening to 5% improvement.   Global gene expression profiling was performed on Illumina HumanHT-12 arrays in the baseline patient samples and 36 unaffected controls. All patient and control samples were processed according to the same procedures and the microarrays were performed in one batch. Previously described TGF- β, IL-13, and diffuse proliferative gene signatures (Milano et al. PLoS ONE 2008) were examined.  We also developed an IFN-α gene signature using control fibroblasts treated with IFNa. Unsupervised hierarchical clustering was performed after selecting genes that were present in the above gene signatures in separate analyses. The goal of our analysis was to examine whether clustering based on these gene lists separate responders from non-responders.

Results:

As shown in Figure 1, these five patients clustered separately from the majority of control samples when the transcript list was filtered based on TGF-β responsive genes. However, there was no clear separation between responders and non-responders in regard to skin (Figure 1) or lung disease. Similarly, patients clustered separately from the majority of control samples when the transcript list was selected based on IL-13, diffuse proliferative, or IFN-α gene signatures.  However, there was again no clear separation between responders and non-responders to treatment with imatinib. The findings were similar when additional 3 patients with 3 month data were included in the analysis.

Conclusion:

This pilot study confirms presence of distinct gene signatures in skin biopsy samples of patients with SSc. However, neither the TGF-β signature nor the other investigated transcript signatures were able to predict response to imatinib.