In rare disease (RD) research there is a huge need to systematically collect biomaterials, phenotypic and genomic data in a standardized way and to make them Findable, Accessible, Interoperable and Reusable (FAIR). RD-Connect is a 6 years global infrastructure project initiated in November 2012 that links genomic data with patient registries, biobanks, and clinical bioinformatics tools to create a central research resource for RDs. Here we present RD-Connect Registry & Biobank Finder, a tool that helps RD researchers to find RD biobanks and registries and provide information on the availability and accessibility of content in each database. The Finder concentrates information that is currently sparse on different repositories (inventories, websites, scientific journals, technical reports, etc.), including aggregated data and metadata from participating databases. Aggregated data provided by the Finder, if appropriately checked, can be used by researchers who are trying to estimate the prevalence of a RD, to organize a clinical trial on a RD, or to estimate the volume of patients seen by different clinical centers. The Finder is also a portal to other RD-Connect tools, providing a link to the RD-Connect Sample Catalogue, a large inventory of RD biological samples available in participating biobanks for RD research. There are several kinds of users and potential uses for the RD-Connect Registry & Biobank Finder, including researchers collaborating with academia and the industry, dealing with the questions of basic, translational and/or clinical research. As of November 2017 the Finder is populated with aggregated data for 222 registries and 21 biobanks.

The aim of this study was to assess the prognostic and predictive value of an untargeted assessment of tumor fractions in the plasma of metastatic breast cancer patients and to compare circulating tumor DNA (ctDNA) with circulating tumor cells (CTC) and conventional tumor markers. In metastatic breast cancer patients (n = 29), tumor fractions in plasma were assessed using the untargeted mFAST-SeqS method from 127 serial blood samples. Resulting z-scores for the ctDNA were compared to tumor fractions established with the recently published ichorCNA algorithm and associated with the clinical outcome. We observed a close correlation between mFAST-SeqS z-scores and ichorCNA ctDNA quantifications. Patients with mFAST-SeqS z-scores above three (34.5%) showed significantly worse overall survival (p = 0.014) and progression-free survival (p = 0.018) compared to patients with lower values. Elevated z-score values were clearly associated with radiologically proven progression. The baseline CTC count, carcinoembryonic antigen (CEA), and cancer antigen (CA)15-5 had no prognostic impact on the outcome of patients in the analyzed cohort. This proof of principle study demonstrates the prognostic impact of ctDNA levels detected with mFAST-SeqS as a very fast and cost-effective means to assess the ctDNA fraction without prior knowledge of the genetic landscape of the tumor. Furthermore, mFAST-SeqS-based ctDNA levels provided an early means of measuring treatment response.

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Background: The prognostic performance of the residual cancer burden (RCB) score is a promising tool for breast cancer patients undergoing neoadjuvant therapy. We independently evaluated the prognostic value of RCB scores in an extended validation cohort. Additionally, we analyzed the association between chemotherapy dose reduction and RCB scores. Methods: In this extended validation study, 367 breast cancer patients with available RCB scores were followed up for recurrence-free survival (RFS), distant disease-free survival (DDFS), and overall survival (OS). We also computed standardized cumulative doses of anthracyclines and taxanes (A/Ts) to investigate a potential interaction between neoadjuvant chemotherapy dose reduction and RCB scores. Results: Higher RCB scores were consistently associated with adverse clinical outcomes across different molecular subtypes (HR for RFS = 1.60, 95% CI 1.33–1.93, p < 0.0001; HR for DDFS = 1.70, 95% CI 1.39–2.05, p < 0.0001; HR for OS = 1.67, 95% CI 1.34–2.08, p < 0.0001). The adverse impact prevailed throughout 5 years of follow-up, with a peak for relapse risk between 1–2 years after surgery. Clinical outcomes of patients with RCB class 1 did not differ substantially at 5 years compared to RCB class 0. A total of 180 patients (49.1%) underwent dose reduction of neoadjuvant A/T chemotherapy. We observed a statistically significant interaction between dose reduction and higher RCB scores (interaction p-value = 0.042). Conclusion: Our results confirm RCB score as a prognostic marker for RFS, DDFS, and OS independent of the molecular subtype. Importantly, we show that lower doses of cumulative neoadjuvant A/T were associated with higher RCB scores in patients who required a dose reduction.

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