Background: Accurate determination of the predictive markers human epidermal growth factor receptor 2 (HER2/ERBB2), estrogen receptor (ER/ESR1), progesterone receptor (PgR/PGR), and marker of proliferation Ki67 (MKI67) is indispensable for therapeutic decision making in early breast cancer. In this multicenter prospective study, we addressed the issue of inter- and intrasite reproducibility using the recently developed reverse transcription-quantitative real-time polymerase chain reaction-based MammaTyper (R) test. Methods: Ten international pathology institutions participated in this study and determined messenger RNA expression levels of ERBB2, ESR1, PGR, and MKI67 in both centrally and locally extracted RNA from formalin-fixed, paraffin-embedded breast cancer specimens with the MammaTyper (R) test. Samples were measured repeatedly on different days within the local laboratories, and reproducibility was assessed by means of variance component analysis, Fleiss' kappa statistics, and interclass correlation coefficients (ICCs). Results: Total variations in measurements of centrally and locally prepared RNA extracts were comparable; therefore, statistical analyses were performed on the complete dataset. Intersite reproducibility showed total SDs between 0.21 and 0.44 for the quantitative single-marker assessments, resulting in ICC values of 0.980-0.998, demonstrating excellent agreement of quantitative measurements. Also, the reproducibility of binary single-marker results (positive/negative), as well as the molecular subtype agreement, was almost perfect with kappa values ranging from 0.90 to 1.00. Conclusions: On the basis of these data, the MammaTyper (R) has the potential to substantially improve the current standards of breast cancer diagnostics by providing a highly precise and reproducible quantitative assessment of the established breast cancer biomarkers and molecular subtypes in a decentralized workup.

The lack of reproducibility of published studies is one of the major issues facing the scientific community, and the field of biofilm microbiology has been no exception. One effective strategy against this multifaceted problem is the use of minimum information guidelines. This strategy provides a guide for authors and reviewers on the necessary information that a manuscript should include for the experiments in a study to be clearly interpreted and independently reproduced. As a result of several discussions between international groups working in the area of biofilms, we present a guideline for the spectrophotometric and fluorometric assessment of biofilm formation in microplates. This guideline has been divided into 5 main sections, each presenting a comprehensive set of recommendations. The intention of the minimum information guideline is to improve the quality of scientific communication that will augment interlaboratory reproducibility in biofilm microplate assays.

Reproducibility of two different methods for quantifying fiber tracts by using a diffusion tensor imaging (DTI) sequence suitable for clinical magnetic resonance imaging (MRI) protocols was evaluated. DTI of 15 subjects was used to analyze intra-rater and inter-rater reproducibility. Another 10 subjects underwent MRI twice for assessment of between-scan reliability. Ten long association tracts were defined by fiber tracking using inclusion and exclusion regions of interest (ROIs). Whole-tract analysis and tractography-based core analysis were performed, and the effect of fractional anisotropy (FA 0.15/0.30) and turning angle threshold (27A degrees/60A degrees) on reproducibility was evaluated. Additionally, ROI measurements were performed in the core of the tracts. For the tract-based methods, intra-rater and inter-rater reliabilities of FA and mean diffusivity (MD) measurements were excellent. Between-scan reproducibility was good or excellent in 127 of 130 of the measurements. There was no systematic difference in the reproducibility of the FA, MD, and volume measurements depending on the FA or turning angle threshold. For the cross-sectional ROI measurements, reliability showed large variation from poor to excellent depending on the tract. Compared with the commonly used cross-sectional core ROI method, the tract-based analyses seem to be a more robust way to identify and measure white matter tracts of interest, and provide a novel reproducible tool to perform core analysis.

BackgroundThe Dachshund is a chondrodystrophic breed of dog predisposed to premature degeneration and calcification, and subsequent herniation, of intervertebral discs (IVDs). This condition is heritable in Dachshunds and breeding candidates are screened for radiographically detectable intervertebral disc calcification (RDIDC), a feature of advanced disc degeneration and a prognostic factor for clinical disease. RDIDC scoring has been previously shown to be consistent within scorers; however, strong scorer effect (subjectivity) was also reported. The aim of this study was to estimate the within- and between-scorer agreement (repeatability and reproducibility, respectively) of computed tomography (CT) scanning and magnetic resonance imaging (MRI) for scoring IVD calcification, and to compare these modalities with radiographic scoring.ResultsTwenty-one Dachshund dogs were screened for IVD calcification using the three imaging modalities. Three scorers scored each case twice, independently. Repeatability was highest for radiography (95.4%), and significantly higher than for CT (90.4%) but not MRI (93.8%). Reproducibility was also highest for radiography (92.9%), but not significantly higher than for CT or MRI (89.4% and 86.4%, respectively). Overall, CT scored IVDs differently than radiography and MRI (64.8% and 62.7% agreement, respectively), while radiography and MRI scored more similarly (85.7% agreement).ConclusionsDespite high precision for radiography, previous evidence of scorer subjectivity was confirmed, which was not generally observed with CT and MRI. The increased consistency of radiography may be related to prior scorer experience with the modality and RDIDC scoring. This study does not support replacing radiography with CT or MRI to screen for heritable IVD calcification in breeding Dachshunds; however, evaluation of dog-level precision and the accuracy of each modality is recommended.

Abstract Background Genome-wide loss-of-function profiling is widely used for systematic identification of genetic dependencies in cancer cells; however, the poor reproducibility of RNA interference (RNAi) screens has been a major concern due to frequent off-target effects. Currently, a detailed understanding of the key factors contributing to the sub-optimal consistency is still a lacking, especially on how to improve the reliability of future RNAi screens by controlling for factors that determine their off-target propensity. Methods We performed a systematic, quantitative analysis of the consistency between two genome-wide shRNA screens conducted on a compendium of cancer cell lines, and also compared several gene summarization methods for inferring gene essentiality from shRNA level data. We then devised novel concepts of seed essentiality and shRNA family, based on seed region sequences of shRNAs, to study in-depth the contribution of seed-mediated off-target effects to the consistency of the two screens. We further investigated two seed-sequence properties, seed pairing stability, and target abundance in terms of their capability to minimize the off-target effects in post-screening data analysis. Finally, we applied this novel methodology to identify genetic interactions and synthetic lethal partners of cancer drivers, and confirmed differential essentiality phenotypes by detailed CRISPR/Cas9 experiments. Results Using the novel concepts of seed essentiality and shRNA family, we demonstrate how genome-wide loss-of-function profiling of a common set of cancer cell lines can be actually made fairly reproducible when considering seed-mediated off-target effects. Importantly, by excluding shRNAs having higher propensity for off-target effects, based on their seed-sequence properties, one can remove noise from the genome-wide shRNA datasets. As a translational application case, we demonstrate enhanced reproducibility of genetic interaction partners of common cancer drivers, as well as identify novel synthetic lethal partners of a major oncogenic driver, PIK3CA, supported by a complementary CRISPR/Cas9 experiment. Conclusions We provide practical guidelines for improved design and analysis of genome-wide loss-of-function profiling and demonstrate how this novel strategy can be applied towards improved mapping of genetic dependencies of cancer cells to aid development of targeted anticancer treatments.

This commentary article conveys the views of the board of the Nanomedicine and Nanoscale Delivery Focus Group of the Controlled Release Society regarding the decision of the United States National Cancer Institute (NCI) in halting funding for the Centers of Cancer Nanotechnology Excellence (CCNEs), and the subsequent editorial articles that broadened this discussion.

A dataset, small or big, is often changed to correct errors, apply new algorithms, or add new data (e.g., as part of a time series), etc. In addition, datasets might be bundled into collections, distributed in different encodings or mirrored onto different platforms. All these differences between versions of datasets need to be understood by researchers who want to cite the exact version of the dataset that was used to underpin their research. Failing to do so reduces the reproducibility of research results. Ambiguous identification of datasets also impacts researchers and data centres who are unable to gain recognition and credit for their contributions to the collection, creation, curation and publication of individual datasets. Although the means to identify datasets using persistent identifiers have been in place for more than a decade, systematic data versioning practices are currently not available. In this work, we analysed 39 use cases and current practices of data versioning across 33 organisations. We noticed that the term ‘version’ was used in a very general sense, extending beyond the more common understanding of ‘version’ to refer primarily to revisions and replacements. Using concepts developed in software versioning and the Functional Requirements for Bibliographic Records (FRBR) as a conceptual framework, we developed six foundational principles for versioning of datasets: Revision, Release, Granularity, Manifestation, Provenance and Citation. These six principles provide a high-level framework for guiding the consistent practice of data versioning and can also serve as guidance for data centres or data providers when setting up their own data revision and version protocols and procedures.