8 research outputs found

    Structure and content of the EU-IVDR: current status and implications for pathology

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    Background Regulation (EU) 2017/746 on in vitro diagnostic medical devices (IVDR) was passed by the European Parliament and the Council of the European Union on 5 April 2017 and came into force on 26 May 2017. A new amending regulation, which introduces a phased implementation of the IVDR with new transitional provisions for certain in vitro diagnostic medical devices (IVDs) and a later date of application of some requirements for in-house devices for healthcare facilities, was adopted on 15 December 2021. The combined use of CE-certified IVDs (CE-IVDs), in-house IVDs (IH-IVDs), and research use only (RUO) devices are a cornerstone of diagnostics in pathology departments and crucial for optimal patient care. The IVDR not only regulates the manufacture and placement on the market of industrially manufactured IVDs, but also imposes conditions on the manufacture and use of IH-IVDs for internal use by healthcare facilities. Objectives Our work provides an overview of the background and structure of the IVDR and identifies core areas that need to be interpreted and fleshed out in the context of the legal framework as well as expert knowledge. Conclusions The gaps and ambiguities in the IVDR crucially require the expertise of professional societies, alliances, and individual stakeholders to successfully facilitate the implementation and use of the IVDR in pathology departments and to avoid aberrant developments

    Claudin-3 and Claudin-5 Protein Folding and Assembly into the Tight Junction Are Controlled by Non-conserved Residues in the Transmembrane 3 (TM3) and Extracellular Loop 2 (ECL2) Segments

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    The mechanism of tight junction (TJ) assembly and the structure of claudins (Cldn) that form the TJ strands are unclear. This limits the molecular understanding of paracellular barriers and strategies for drug delivery across tissue barriers. Cldn3 and Cldn5 are both common in the blood-brain barrier but form TJ strands with different ultrastructures. To identify the molecular determinants of folding and assembly of these classic claudins, Cldn3/Cldn5 chimeric mutants were generated and analyzed by cellular reconstitution of TJ strands, live cell confocal imaging, and freeze-fracture electron microscopy. A comprehensive screening was performed on the basis of the rescue of mutants deficient for strand formation. Cldn3/Cldn5 residues in transmembrane segment 3, TM3 (Ala-127/Cys-128, Ser-136/Cys-137, Ser-138/Phe-139), and the transition of TM3 to extracellular loop 2, ECL2 (Thr-141/Ile-142) and ECL2 (Asn-148/Asp-149, Leu-150/Thr-151, Arg-157/Tyr-158), were identified to be involved in claudin folding and/or assembly. Blue native PAGE and FRET assays revealed 1% n-dodecyl β-D-maltoside-resistant cis-dimerization for Cldn5 but not for Cldn3. This homophilic interaction was found to be stabilized by residues in TM3. The resulting subtype-specific cis-dimer is suggested to be a subunit of polymeric TJ strands and contributes to the specific ultrastructure of the TJ detected by freeze-fracture electron microscopy. In particular, the Cldn5-like exoplasmic face-associated and particle-type strands were found to be related to cis-dimerization. These results provide new insight into the mechanisms of paracellular barrier formation by demonstrating that defined non-conserved residues in TM3 and ECL2 of classic claudins contribute to the formation of TJ strands with differing ultrastructures

    STAT1 and STAT3 Exhibit a Crosstalk and Are Associated with Increased Inflammation in Hepatocellular Carcinoma

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    Liver cancers, which are mostly hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are very aggressive tumors with poor prognosis. Therapeutic options with curative intent are largely limited to surgery and available systemic therapies show limited benefit. Signal transducer and activator of transcription 1 (STAT1) and 3 (STAT3) are key transcription factors activated by pro-inflammatory cytokines such as interferon-γ (IFN-γ) and interleukin-6 (IL-6). In this study, we combined in vitro cell culture experiments and immunohistochemical analyses of human HCC (N = 124) and CCA (N = 138) specimens. We observed that in the absence of STAT3, IL-6 induced the activation of STAT1 and its target genes suggesting that IL-6 derived from the tumor microenvironment may activate both STAT1 and STAT3 target genes in HCC tumor cells. In addition, STAT1 and STAT3 were highly activated in a subset of HCC, which exhibited a high degree of infiltrating CD8- and FOXP3-positive immune cells and PD-L1 expression. Our results demonstrate that STAT1 and STAT3 are expressed and activated in HCC and tumor infiltrating immune cells. In addition, HCC cases with high STAT1 and STAT3 expression also exhibited a high degree of immune cell infiltration, suggesting increased immunological tolerance

    Trailblazing precision medicine in Europe : A joint view by Genomic Medicine Sweden and the Centers for Personalized Medicine, ZPM, in Germany

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    Over the last decades, rapid technological and scientific advances have led to a merge of molecular sciences and clinical medicine, resulting in a better understanding of disease mechanisms and the development of novel therapies that exploit specific molecular lesions or profiles driving disease. Precision oncology is here used as an example, illustrating the potential of precision/personalized medicine that also holds great promise in other medical fields. Real-world implementation can only be achieved by dedicated healthcare connected centers which amass and build up interdisciplinary expertise reflecting the complexity of precision medicine. Networks of such centers are ideally suited for a nation-wide outreach offering access to precision medicine to patients independent of their place of residence. Two of these multicentric initiatives, Genomic Medicine Sweden (GMS) and the Centers for Personalized Medicine (ZPM) initiative in Germany have teamed up to present and share their views on core concepts, potentials, challenges, and future developments in precision medicine. Together with other initiatives worldwide, GMS and ZPM aim at providing a robust and sustainable framework, covering all components from technology development to clinical trials, ethical and legal aspects as well as involvement of all relevant stakeholders, including patients and policymakers in the field

    NTRK testing: First results of the QuiP-EQA scheme and a comprehensive map of NTRK fusion variants and their diagnostic coverage by targeted RNA-based NGS assays

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    Gene fusions involving the three neurotrophic tyrosine receptor kinase genes NTRK1, NTRK2, or NTRK3 were identified as oncogenic drivers in many cancer types. Two small molecule inhibitors have been tested in clinical trials recently and require the detection of a NTRK fusion gene prior to therapeutic application. Fluorescence in situ hybridization (FISH) and targeted next-generation sequencing (tNGS) assays are commonly used for diagnostic profiling of gene fusions. In the presented study we applied an external quality assessment (EQA) scheme in order to investigate the suitability of FISH and RNA-/DNA-based tNGS for detection of NTRK fusions in a multinational and multicentric ring trial. In total 27 participants registered for this study. Nine institutions took part in the FISH-based and 18 in the NGS-based round robin test, the latter additionally subdivided into low-input and high-input NGS methods (regarding nucleic acid input). Regardless of the testing method applied, all participants received tumor sections of 10 formalin-fixed and paraffin-embedded (FFPE) tissue blocks for in situ hybridization or RNA/DNA extraction, and the results were submitted via an online questionnaire. For FISH testing, eight of nine (88.8%) participants, and for NGS-based testing 15 of 18 (83.3%) participants accomplished the round robin test successfully. The overall high success rate demonstrates that FISH- and tNGS-based NTRK testing can be well established in a routine diagnostic setting. Complementing this dataset, we provide an updated in silico analysis on the coverage of more than 150 NTRK fusion variants by several commercially available RNA-based tNGS panels

    Spatial and Temporal Heterogeneity of Panel-Based Tumor Mutational Burden in Pulmonary Adenocarcinoma: Separating Biology From Technical Artifacts.

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    Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB. TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients. On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound. Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample-based TMB estimations in a clinical context
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