S

Sara Wedrén

Karolinska University Hospital

ORCID: 0000-0002-2436-1519

Publishes on Rheumatoid Arthritis Research and Therapies, Estrogen and related hormone effects, BRCA gene mutations in cancer. 66 papers and 6.6k citations.

66Publications
6.6kTotal Citations

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Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts
Yudi Pawitan, Judith Bjöhle, Lukas C. Amler et al.|Breast Cancer Research|2005
Cited by 833Open Access

INTRODUCTION: Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction. METHODS: We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined. RESULTS: Among the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston-Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively. CONCLUSION: We have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.

Patients with early rheumatoid arthritis who smoke are less likely to respond to treatment with methotrexate and tumor necrosis factor inhibitors: Observations from the Epidemiological Investigation of Rheumatoid Arthritis and the Swedish Rheumatology Register cohorts
Saedís Saevarsdóttir, Sara Wedrén, Maria Seddighzadeh et al.|Arthritis & Rheumatism|2010
Cited by 254

OBJECTIVE: To determine whether cigarette smoking influences the response to treatment in patients with early rheumatoid arthritis (RA). METHODS: We retrieved clinical information about patients entering the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) early RA cohort from 1996 to 2006 (n=1,998) who were also in the Swedish Rheumatology Register (until 2007). Overall, 1,430 of the 1,621 registered patients were followed up from the time of inclusion in the EIRA cohort. Of these, 873 started methotrexate (MTX) monotherapy at inclusion, and 535 later started treatment with a tumor necrosis factor (TNF) inhibitor as the first biologic agent. The primary outcome was a good response according to the European League Against Rheumatism criteria at the 3-month visit. The influence of cigarette smoking (current or past) on the response to therapy was evaluated by logistic regression, with never smokers as the referent group. RESULTS: Compared with never smokers, current smokers were less likely to achieve a good response at 3 months following the start of MTX (27% versus 36%; P=0.05) and at 3 months following the start of TNF inhibitors (29% versus 43%; P=0.03). In multivariate analyses in which clinical, serologic, and genetic factors were considered, the inverse associations between current smoking and good response remained (adjusted odds ratio [OR] for MTX response 0.60 [95% CI 0.39-0.94]; adjusted OR for TNF inhibitor response 0.52 [95% CI 0.29-0.96]). The lower likelihood of a good response remained at later followup visits. Evaluating remission or joint counts yielded similar findings. Past smoking did not affect the chance of response to MTX or TNF inhibitors. Evaluating the overall cohort, which reflects all treatments used, current smoking was similarly associated with a lower chance of a good response (adjusted ORs for the 3-month, 6-month, 1-year, and 5-year visits 0.61, 0.65, 0.78, 0.66, and 0.61, respectively). CONCLUSION: Among patients with early RA, current cigarette smokers are less likely to respond to MTX and TNF inhibitors.

Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis
Jing Cui, Eli A. Stahl, Saedís Saevarsdóttir et al.|PLoS Genetics|2013
Cited by 163Open Access

Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8 × 10(-8)), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3' UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1 × 10(-11) in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.