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Abstract Background Clinically useful treatment moderators of Major Depressive Disorder (MDD) have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. Methods/Design The International Study to Predict Optimized Treatment - in Depression (iSPOT-D) is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65) from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls). Study-eligible patients are antidepressant medication (ADM) naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary) and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary). Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. Discussion First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. Trial registration International Study to Predict Optimised Treatment - in Depression (iSPOT-D) ClinicalTrials.gov Identifier: NCT00693849 URL: http://clinicaltrials.gov/ct2/show/NCT00693849?term=International+Study+to+Predict+Optimized+Treatment+for+Depression&rank=1

Background: The identification of molecular predictors of type of recurrence (non-invasive vs invasive) after local therapy for ductal carcinoma in situ (DCIS) remains a challenge. We hypothesized that gene expression profiling using a panel of 32 breast cancer-related genes could identify a signature predictive of type of recurrence. Methods: From a prospectively maintained database of 1873 pts treated with conservative surgery +/- radiation for DCIS (1991-2006), we identified 190 (10%) patients who recurred. Original DCIS archival blocks were available for 108 (57%) of these cases. Freshly cut sections were obtained for microdissection of pure DCIS lesions, RNA was extraction and mRNA transcript quantification was performed with the Nanostring™ nCounter® system. Data were normalized using the nCounter® digital analyzer software for analysis. Results: Among the 108 studied cases, 66 (61%) recurred as DCIS and 42 (39%) recurred as invasive cancer. Median time to recurrence was 40 months (range 7-156 mo) and did not differ by type of recurrence. Similarly, patient age, grade of DCIS, ER status, use of radiation or tamoxifen therapy did not differ. Unsupervised hierarchical clustering using all 32 genes demonstrated two predominant groups, one enriched for recurrent-as-invasive (RI) tumors, and the other enriched for recurrent-as-DCIS (RD) tumors. Refined analysis by selection of 14 genes with significant differential expression between the RI and the RD tumors identified four main groups. The first cluster was dominated by ERBB2 over-expression and is equally composed of RI and RD tumors. The second cluster was composed almost exclusively of RI tumors and showed high level of COX2 and CCND1 and low level of CDKN2A (p16). The clusters 3 and 4 were enriched for RD tumors, with the fourth cluster completely devoid of RI cases. This RD-only group showed the lowest level of CCND1, but highest level of AKT3, EGFR, CDKN2A, and MKI67, thus displaying molecular traits typical of basal-like tumors. Conclusion: In this cohort of patients who recurred following conservative treatment for DCIS, HER2 expression was not predictive, however gene expression analysis demonstrated that high COX2 and CCND1 and low CDKN2a (p16) levels were strongly associated with invasive recurrences (RI), whereas increased AKT3 and MKI67 were associated with non-invasive recurrences (RD). Although the optimal combination of predictive markers requires validation, these data suggest that molecular alterations associated with RI differ from those associated with RD and warrant further investigation. [ABSTRACT FROM AUTHOR]