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Abstract Number: 3000

Intrinsic Gene Expression Subset Predicts Improvement in Systemic Sclerosis Patients during Dasatinib (SprycelTM) Therapy

Viktor Martyanov1, Jonathan Goldin2, Kim Hyun3, Oumar Sy4, Wendy Hayes4, Shuyan Du4, Michael Whitfield1 and John Varga5, 1Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH, 2David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 3Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 4Bristol-Myers Squibb, Princeton, NJ, 5Division of Rheumatology, Northwestern University, Feinberg School of Medicine, Chicago, IL

Meeting: 2015 ACR/ARHP Annual Meeting

Date of first publication: September 29, 2015

Keywords: fibrosis, Gene Expression, Safety, systemic sclerosis and tyrosine kinase inhibition

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Session Information

Date: Tuesday, November 10, 2015

Title: Systemic Sclerosis, Fibrosing Syndromes and Raynaud's - Pathogenesis, Animal Models and Genetics Poster II

Session Type: ACR Poster Session C

Session Time: 9:00AM-11:00AM

Background/Purpose:

Intrinsic gene expression subsets are molecular pathway-driven subtypes of systemic sclerosis (SSc) that have been reproduced across multiple cohorts of SSc patients. The goal of this study was to determine if intrinsic subset assignment could identify SSc patients who improved with treatment in an open-label clinical trial of dasatanib, the broad spectrum tyrosine kinase inhibitor.

Methods:

Biopsies of lesional forearm skin were performed on days 1 and 169 of the study. RNA was isolated and used for intrinsic subset assignment, differential gene expression and pathway enrichment analyses. Clinical response was determined by modified Rodnan Skin Score (mRSS) and pulmonary function was assessed at baseline and day 169. Improvement was defined by a decrease in mRSS of >5 or >20% from baseline. Quantitative image analysis of high-resolution computed tomography (HRCT) scans of the chest was performed and quantitative lung fibrosis (QLF) and ground class (QGG) scores were obtained at baseline and 6-month follow-up. Categorical variables were analyzed via Fisher’s exact test and continuous variables via Mann-Whitney and Wilcoxon signed-rank test.

Results:

Among twelve subjects with baseline and post-treatment skin biopsies, three were classified as improvers and nine as non-improvers. Intrinsic gene analysis identified 3207 probes (2532 unique genes) at False Discovery Rate (FDR)<1.1% which organized study samples into fibroproliferative, inflammatory and normal-like groups. Based on the intrinsic subset assignment, improvers were normal-like or fibroproliferative while 7/9 non-improvers were inflammatory at baseline (p=0.0455). Consistent with these results, improvers were enriched in cell cycle genes (e.g. EGFR, TOP1 and TOP3A) and growth-related pathways (e.g. intracellular signal transduction and kinase cascade). Non-improvers were enriched in immune response genes (IL6, TLR2 and CCR2) and inflammatory pathways (e.g. defense response and leukocyte migration). Improvers showed stable pulmonary function (as measured by forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO)) and stable QLF score post-treatment (as measured on HRCT). In contrast, non-improvers showed a trend towards decrease in FVC, a decrease in DLCO (p=0.1289 and p=0.0156, respectively) and progression in QLF (p=0.0313). Moreover, non-improvers at baseline had a higher QGG score (p=0.0364) and tended to have a higher interstitial lung disease (ILD) score than improvers (p=0.1212).

Conclusion:

Our results indicate that the intrinsic gene expression subset of SSc may be associated with those patients most likely to respond to therapy. In this trial of dasatinib, patients classified as inflammatory at baseline displayed worse clinical outcomes in terms of skin score, pulmonary function and lung fibrosis than patients from other intrinsic subsets. To our knowledge, this is the first report showing that SSc patients from the inflammatory subset show a distinct lack of response to a drug treatment. Molecular subset information may improve clinical trial design and guide the development of personalized therapies for rare and difficult to treat diseases, such as SSc.


Disclosure: V. Martyanov, None; J. Goldin, MedQIA LLC, 4; K. Hyun, MedQIA LLC, 5; O. Sy, Bristol-Myers Squibb, 1,Bristol-Myers Squibb, 3; W. Hayes, Bristol-Myers Squibb, 1,Bristol-Myers Squibb, 3; S. Du, Bristol-Myers Squibb, 1,Bristol-Myers Squibb, 3; M. Whitfield, Bristol-Myers Squibb, 2,Bristol-Myers Squibb, 5,Celdara Medical LLC, 4; J. Varga, Bristol-Myers Squibb, 2.

To cite this abstract in AMA style:

Martyanov V, Goldin J, Hyun K, Sy O, Hayes W, Du S, Whitfield M, Varga J. Intrinsic Gene Expression Subset Predicts Improvement in Systemic Sclerosis Patients during Dasatinib (SprycelTM) Therapy [abstract]. Arthritis Rheumatol. 2015; 67 (suppl 10). https://acrabstracts.org/abstract/intrinsic-gene-expression-subset-predicts-improvement-in-systemic-sclerosis-patients-during-dasatinib-spryceltm-therapy/. Accessed .
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