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THU0242 Biological pathway analysis in primary sjÖgren's syndrome associated lymphoma
  1. S Al-Ali1,2,
  2. A Skelton3,
  3. S Cockell3,
  4. J Tarn1,
  5. K James4,
  6. S Bowman5,
  7. B Griffiths6,
  8. D Young1,
  9. U Registry1,
  10. W-F Ng1
  1. 1Institute of Cellular Medicine, Newcastle University, Newcastle Upon Tyne, United Kingdom
  2. 2Department of Biology, College of Science/University of Basrah, Basrah, Iraq
  3. 3Bioinformatics Support Unit
  4. 4School of Computing Science, Newcastle University, Newcastle Upon Tyne
  5. 5University Hospital Birmingham, Birmingham
  6. 6Freeman Hospital, Newcastle Upon Tyne, United Kingdom


Background Lymphoma development is a serious complication of Primary Sjögren's syndrome (pSS). To date, the biological processes that may be involved in pSS-associated lymphoma are not fully understood.

Objectives The aim of our study is to use microarray gene expression data from a well-defined cohort of pSS patients to identify biological processes that may be relevant to pSS-associated lymphoma.

Methods pSS patients and healthy controls from the UK primary Sjögren's syndrome registry (UKPSSR) were used in this study. All patients fulfilled the AECG criteria. Whole genome gene expression data from whole blood RNA samples (n=144) stratified into five clinical subsets (pSS=61, pSS with lymphoma=16, pSS with other cancers=21, pSS with paraproteinemia=23 and healthy controls=23) were used for the pathway analysis. A list of 68 differentially expressed genes in pSS-associated lymphoma compared with pSS (non lymphoma) were uploaded into the Ingenuity Pathway Analysis (IPA) analytic tool. Similar approach was also used for comparison between the lymphoma and other pSS subject groups. Finally, we also examined the regulators and pathways involved in the genes from the gene expression signature in pSS-associated lymphoma we have previously described (BMS1, NUDT14 and MGST3) [1].

Results In pSS-associated lymphoma the top canonical pathway was “Aryl Hydrocarbon Receptor (AHR) signaling,” which includes MGST3. Several other canonical pathways also included the genes of the 3-gene biosignature of pSS-associated lymphoma. The downstream effects and gene-gene interactions were explored through molecular networks analysis. Furthermore, important upstream regulators of the 3 biosignature genes include NFE2L2, PPARA and TOCF1 were identified.

The pathway analyses of the other pSS subgroups showed 67 common canonical pathways showed among all the pSS subgroups. Focusing on pSS-associated lymphoma versus healthy controls, 94.9% of the canonical pathways in this comparison were in common with the canonical pathways identified when comparing pSS-associated lymphoma with pSS. The “Interferon Signaling pathway” was the top pathway for all pSS subgroups comparing with healthy controls. In addition, all the non-lymphoma pSS subgroups showed similar patterns in the downstream analysis which differ from the pSS-associated lymphoma group.

Conclusions The pathway analysis revealed different possible pathways that might be involved in lymphoma development in pSS and indicates a unique gene expression signature exist in pSS-associated lymphoma. These results might provide a deeper understanding and a direction for future studies to investigate lymphoma development in pSS patients.


  1. Al-Ali S, et al. Whole blood transcriptomic signature of primary Sjögren's syndrome associated lymphoma. Biomarkers and Targeted Therapeutics in Sjögren's (BATTS) Conference, 2016.


Disclosure of Interest None declared

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