Citations

Abstract We previously reported, on the basis of a genome-wide association study for aromatase inhibitor-induced musculoskeletal symptoms, that single-nucleotide polymorphisms (SNPs) near the T-cell leukemia/lymphoma 1A (TCL1A) gene were associated with aromatase inhibitor-induced musculoskeletal pain and with estradiol (E2)-induced TCL1A expression. Furthermore, variation in TCL1A expression influenced the downstream expression of proinflammatory cytokines and cytokine receptors. Specifically, the top hit genome-wide association study SNP, rs11849538, created a functional estrogen response element (ERE) that displayed estrogen receptor (ER) binding and increased E2 induction of TCL1A expression only for the variant SNP genotype. In the present study, we pursued mechanisms underlying the E2-SNP-dependent regulation of TCL1A expression and, in parallel, our subsequent observations that SNPs at a distance from EREs can regulate ERα binding and that ER antagonists can reverse phenotypes associated with those SNPs. Specifically, we performed a series of functional genomic studies using a large panel of lymphoblastoid cell lines with dense genomic data that demonstrated that TCL1A SNPs at a distance from EREs can modulate ERα binding and expression of TCL1A as well as the expression of downstream immune mediators. Furthermore, 4-hydroxytamoxifen or fulvestrant could reverse these SNP-genotype effects. Similar results were found for SNPs in the IL17A cytokine and CCR6 chemokine receptor genes. These observations greatly expand our previous results and support the existence of a novel molecular mechanism that contributes to the complex interplay between estrogens and immune systems. They also raise the possibility of the pharmacological manipulation of the expression of proinflammatory cytokines and chemokines in a SNP genotype-dependent fashion.

Abstract Background: The use of anti-estrogen (AE) therapies (selective estrogen receptor modulators [SERMs], aromatase inhibitors [AIs]) in breast cancer (BC) patients was recently associated with risk of developing rheumatoid arthritis (RA) (J Rheum 2015;42:55-9). We attempted to replicate and extend these results using electronic health record (EHR) enhanced cancer registry data that assessed specific AE therapies and also accounted for potential confounding by age, smoking status, and chemotherapy use. Methods: Using cancer registry and EHR data, we identified a cohort of BC patients who were newly diagnosed and treated at Mayo Clinic Rochester from 1998-2011 and had no previous diagnosis of RA. Smoking status at diagnosis, BC treatments and RA at diagnosis and during follow-up were identified using validated EHR-based algorithms. Hazard ratios (HRs) and 95% confidence intervals (CI) from a multivariate Cox model were used to estimate the association of AE use with risk of RA, controlling for age, smoking status at BC diagnosis, and BC chemotherapy use. Results: The analytic cohort of 9,244 newly diagnosed BC patients treated and followed at Mayo Clinic had a median age at diagnosis of 59 years (range 18-97); 32% were smokers; and 29% were treated with chemotherapy. During a median follow-up of 49 months (range 1-191), 19 patients developed RA. Compared to BC patients not receiving any AE therapy, those receiving AI monotherapy, but not SERM monotherapy or both SERMs and AIs, were at significantly increased risk of developing RA (Table). AE Therapy# of RA Cases / # patientsHR* (95% CI)P-valueNo AE therapy6/4,0711.00 (reference)SERMs only5/2,5371.20 (0.36 - 3.95)0.77AIs only5/7126.37 (1.77 - 22.92)0.005SERMs then AIs3/1,8750.90AI then SERMs0/490.91 (0.21 - 3.86)*Adjusted for age, smoking status and use of chemotherapy Conclusions: Our findings indicate that the use of AIs for BC therapy, but not SERMs or SERMs followed by AIs, is associated with increased risk for development of RA, when controlling for smoking status and use of chemotherapy. While needing replication, these findings suggest a specific role for AIs in RA development and suggest pathways that could be targeted to prevent this potential treatment complication. Citation Format: Matthew K. Breitenstein, Ming-Fen Ho, Richard M. Weinshilboum, James R. Cerhan, Jyotishman Pathak, Tim Bongartz, Liewei Wang, James N. Ingle. Association of anti-estrogen therapy in breast cancer patients and subsequent risk of rheumatoid arthritis: An electronic health record study. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-191. doi:10.1158/1538-7445.AM2015-LB-191