These data suggest that the novel SLE autoantibody clusters may be of prognostic utility for predicting organ involvement in SLE patients and for stratifying SLE patients for specific therapies.
BackgroundMelanotic neuroectodermal tumor of infancy (MNTI) is exceptionally rare and occurs predominantly in the head and neck (92.8 % cases). The patient reported here is only the eighth case of MNTI presenting in an extremity, and the first reported in the fibula.Case presentationA 2-month-old female presented with a mass arising in the fibula. Exhaustive genomic, transcriptomic, epigenetic and pathological characterization was performed on the excised primary tumor and a derived cell line. Whole-exome analysis of genomic DNA from both the tumor and blood indicated no somatic, non-synonymous coding mutations within the tumor, but a heterozygous, unique germline, loss of function mutation in CDKN2A (p16INK4A, D74A). SNP-array CGH on DNA samples revealed the tumor to be euploid, with no detectable gene copy number variants. Multiple chromosomal translocations were identified by RNA-Seq, and fusion genes included RPLP1-C19MC, potentially deregulating the C19MC cluster, an imprinted locus containing microRNA genes reactivated by gene fusion in embryonal tumors with multilayered rosettes. Since the presumed cell of origin of MNTI is from the neural crest, we also compared gene expression with a dataset from human neural crest cells and identified 185 genes with significantly different expression. Consistent with the melanotic phenotype of the tumor, elevated expression of tyrosinase was observed. Other highly expressed genes encoded muscle proteins and modulators of the extracellular matrix. A derived MNTI cell line was sensitive to inhibitors of lysine demethylase, but not to compounds targeting other epigenetic regulators.ConclusionsIn the absence of somatic copy number variations or mutations, the fully transformed phenotype of the MNTI may have arisen in infancy because of the combined effects of a germline CDKN2A mutation, tumor promoting somatic fusion genes and epigenetic deregulation. Very little is known about the etiology of MNTI and this report advances knowledge of these rare tumors by providing the first comprehensive genomic, transcriptomic and epigenetic characterization of a case.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2669-3) contains supplementary material, which is available to authorized users.
BackgroundWhile the European Union is striving to become the ‘Innovation Union’, there remains a lack of quantifiable indicators to compare and benchmark regional innovation clusters. To address this issue, a HealthTIES (Healthcare, Technology and Innovation for Economic Success) consortium was funded by the European Union’s Regions of Knowledge initiative, research and innovation funding programme FP7. HealthTIES examined whether the health technology innovation cycle was functioning differently in five European regional innovation clusters and proposed regional and joint actions to improve their performance. The clusters included BioCat (Barcelona, Catalonia, Spain), Medical Delta (Leiden, Rotterdam and Delft, South Holland, Netherlands), Oxford and Thames Valley (United Kingdom), Life Science Zürich (Switzerland), and Innova Észak-Alföld (Debrecen, Hungary).MethodsAppreciation of the ‘triple helix’ of university–industry–government innovation provided the impetus for the development of two quantifiable innovation indexes and related indicators. The HealthTIES H-index is calculated for disease and technology platforms based on the h-index proposed by Hirsch. The HealthTIES Innovation Index is calculated for regions based on 32 relevant quantitative and discriminative indicators grouped into 12 categories and 3 innovation phases, namely ‘Input’ (n = 12), ‘Innovation System’ (n = 9) and ‘Output’ (n = 11).ResultsThe HealthTIES regions had developed relatively similar disease and technology platform profiles, yet with distinctive strengths and weaknesses. The regional profiles of the innovation cycle in each of the three phases were surprisingly divergent. Comparative assessments based on the indicators and indexes helped identify and share best practice and inform regional and joint action plans to strengthen the competitiveness of the HealthTIES regions.ConclusionThe HealthTIES indicators and indexes provide useful practical tools for the measurement and benchmarking of university–industry–government innovation in European medical and life science clusters. They are validated internally within the HealthTIES consortium and appear to have a degree of external prima facie validity. Potentially, the tools and accompanying analyses can be used beyond the HealthTIES consortium to inform other regional governments, researchers and, possibly, large companies searching for their next location, analyse and benchmark ‘triple helix’ dynamics within their own networks over time, and to develop integrated public–private and cross-regional research and innovation strategies in Europe and beyond.Electronic supplementary materialThe online version of this article (10.1186/s12961-019-0414-5) contains supplementary material, which is available to authorized users.
The issues surrounding the use of prostate-specific antigen (PSA) in the diagnosis of prostate cancer (PCa) are well documented and the need for a molecular diagnostic test with greater discriminatory power is clear. The development of autoantibodies associated with prostate cancer has also been described. In general, the appearance of such antibodies can precede disease symptoms by many years, making them attractive as potential biomarkers for early diagnosis. We have developed a unique “functional protein” array platform which utilises correctly folded proteins and has the ability to display native, discontinuous epitopes. The reproducibility of the platform is exceptionally good, making it possible to screen statistically meaningful numbers of samples. Following on from a successful pilot study, where panels of autoantibody biomarkers exhibiting a specificity and sensitivity for PCa superior to PSA were identified using the platform1, we have validated this approach in a large-scale analytical study. The current analytical study involving approximately 1800 samples was primarily designed to identify panels of biomarkers with the ability to distinguish between PCa (n=400) and control samples from patients with benign prostatic hypertrophy (BPH, n=406). BPH can present with similar symptoms to PCa and can also result in elevated PSA levels. Additional sample cohorts included prostatitis, other cancers of various origin and non-disease/healthy controls (n=400). All samples were age, ethnicity and gender matched. The products of 1296 unique genes (1330 proteins), chosen for their association with disease, signal transduction and cancer autoimmunity, are immobilized on each array. Serum samples (n=1781) were analysed using the arrays as described previously1. Data were split into test and training sets and analyzed with several classification algorithms to identify classifiers which would successfully distinguish case from control samples. Data were repeatedly split into test and training sets and analysis cycles repeated until a stable set of classifiers was identified. At the time of writing, data is still under analysis; however, early indications are encouraging and suggest that panels of biomarkers with a performance that significantly exceeds that of PSA may be identified. Full results of the study will be presented. 1 McAndrew et al Development of a panel of biomarkers for the diagnosis of prostate cancer (2010) Molecular Diagnostics in Cancer Therapeutic Development conference Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5071. doi:10.1158/1538-7445.AM2011-5071
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