Article Text

THU0005 Investigating the Plasma Cell Signature in Autoimmune Disease
  1. K. Streicher1,
  2. C. Morehouse1,
  3. C. Groves2,
  4. B. Rajan2,
  5. F. Pilataxi1,
  6. K. Lehmann1,
  7. P. Z. Brohawn1,
  8. B. W. Higgs1,
  9. K. McKeever1,
  10. S. A. Greenberg3,
  11. D. Fiorentino4,
  12. L. Richman1,
  13. B. Jallal2,
  14. R. Herbst2,
  15. Y. Yao1,
  16. K. Ranade1
  1. 1Translational Science
  2. 2MedImmune, Gaithersburg
  3. 3Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston
  4. 4Dermatology, Stanford University School of Medicine, Stanford, United States


Background Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases; thus, PC levels could be associated with efficacy of B-cell depleting therapies. Additionally, investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response.

Objectives Flow cytometry methods that are commonly used to enumerate and describe PC are difficult to implement routinely in the clinic and almost impossible in large clinical trials because of the fragility of PC. This difficulty has hampered thorough assessment of the effect of therapeutics on PC. For this reason, we first developed a highly sensitive and specific gene expression signature that can be easily implemented in the clinic, and then applied this signature to assess the impact of a novel therapeutic on PC and the prevalence of PC in different autoimmune diseases.

Methods Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, whose expression is highly significantly enriched in PC. We combined expression levels of these genes to create a signature score that estimates PC counts in blood and tissue. The sensitivity of this PC signature score was assessed through ex vivo experiments with sorted cells. The PC signature was used to monitor changes in PC levels following anti-CD19 therapy; evaluate the relationship between PC and other autoimmune disease-related genes; and estimate PC levels in affected blood and tissue from multiple autoimmune diseases.

Results Results indicated that the PC signature was highly sensitive and capable of detecting as few as 300 PCs. In scleroderma patients enrolled in a Phase I trial with MEDI-551, an anti-CD19 antibody with enhanced effector function, the PC signature was reduced over 90% following MEDI-551 treatment and this reduction was highly correlated (r=0.72, p=0.002) between blood and skin. Comparing the distribution of the PC signature in tissue and whole blood of patients with various autoimmune diseases revealed 30-35% of systemic lupus erythematosus, rheumatoid arthritis, and scleroderma patients with increased PC levels.

Conclusions Our results demonstrate the utility of this newly developed gene expression-based PC signature. In addition to providing a robust and straightforward way to accurately measure PC levels in the clinic, the signature may be especially useful to tailor the treatment of autoimmune diseases by identifying those patients who may most benefit from PC-targeted therapies.

Disclosure of Interest K. Streicher Shareholder of: MedImmune; AstraZeneca, C. Morehouse Shareholder of: MedImmune; AstraZeneca, C. Groves Shareholder of: MedImmune; AstraZeneca, B. Rajan Shareholder of: MedImmune; AstraZeneca, F. Pilataxi Shareholder of: MedImmune; AstraZeneca, K. Lehmann Shareholder of: MedImmune; AstraZeneca, P. Brohawn Shareholder of: MedImmune; AstraZeneca, B. Higgs Shareholder of: MedImmune; AstraZeneca, K. McKeever Shareholder of: MedImmune; AstraZeneca, S. Greenberg: None Declared, D. Fiorentino: None Declared, L. Richman: None Declared, B. Jallal Shareholder of: MedImmune; AstraZeneca, R. Herbst Shareholder of: MedImmune; AstraZeneca, Y. Yao Shareholder of: MedImmune; AstraZeneca, K. Ranade Shareholder of: MedImmune; AstraZeneca

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