Determination of test performance of two contemporary screening tests for Lynch syndrome in endometrial cancer: A clinical trial.

BACKGROUND/PURPOSE: Published data on the performance of the immunohistochemistry (IHC) test for mismatch repair (MMR) protein expression to detect Lynch syndrome (LS) index cases suggests it is highly variable; its performance in our system was unknown. Moreover, a brief family history questionnaire (bFHQ) developed by Eiriksson and colleagues in Canada demonstrated 100% sensitivity for LS case identification thus was of interest to us, but its performance outside of its original setting was unknown. Determination of the performance of these tests requires complete LS case identification in the testing population. METHODS: Two hundred women were recruited during routine care for endometrial cancer (EC) to administer the bFHQ and perform genetic testing for the LS genes. Independently, the IHC test was performed to screen for presumptive LS cases. We determined the sensitivity, specificity, and positive and negative predictive values of the bFHQ and IHC test as well as simulating outcomes of the complete protocols. RESULTS: Genetic testing all participants identified 8 cases of LS out of 200 (4% prevalence), the bFHQ identified 5 of 8 of these cases (62.5%, CI: 31.5%-87.6%), and the IHC test identified 6 or 7 of 8 cases (mean of 75% or 87.5%) depending on interpretation of test results. The specificities of the bFHQ and IHC test were 56.8% (CI: 49.8%-63.7%) and 79.8% (CI: 73.6%-85.1%), respectively. CONCLUSIONS: This study is the first, to our knowledge, to test the effectiveness of the bFHQ in an EC population since its original reporting; our results are consistent with many reports of the challenges of collecting family health history. The performance of the IHC test as a screen falls within ranges reported in the literature but do not provide the confidence to drive a decision for or against continued use of this test as a LS screen.

Automated Real-Time Collection of Pathogen-Specific Diagnostic Data: Syndromic Infectious Disease Epidemiology.

BACKGROUND: Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. OBJECTIVE: The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. METHODS: We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. RESULTS: The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. CONCLUSIONS: Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks.

Diffuse large B-cell lymphoma with coexpression of CD3 in a pediatric patient: a case report, review of the literature, and tissue microarray study.

The aberrant expression of T-cell antigens on B-cell-derived non-Hodgkin lymphomas has been described. However, the expression of the lineage-specific T-cell antigen, CD3, in hematologic malignancies is exceedingly rare and to the best of our knowledge has not been reported in pediatric patients. Here we describe the first case of a CD3+ diffuse large B-cell lymphoma in a 9-year-old male patient that is well documented by immunohistochemistry. In addition, results of a tissue microarray study composed of B-cell-derived non-Hodgkin lymphomas (n=77) and reactive lymphoid hyperplasia (n=13) dual stained for PAX5/CD3 are also reported.

Comprehensive identification of proteins in Hodgkin lymphoma-derived Reed-Sternberg cells by LC-MS/MS.

Mass spectrometry-based proteomics in conjunction with liquid chromatography and bioinformatics analysis provides a highly sensitive and high-throughput approach for the identification of proteins. Hodgkin lymphoma is a form of malignant lymphoma characterized by the proliferation of Reed-Sternberg cells and background reactive lymphocytes. Comprehensive analysis of proteins expressed and released by Reed-Sternberg cells would assist in the discovery of potential biomarkers and improve our understanding of its pathogenesis. The subcellular proteome of the three cellular compartments from L428 and KMH2 Hodgkin lymphoma-derived cell lines were fractionated, and analyzed by reverse-phase liquid chromatography coupled with electrospray ionization tandem mass spectrometry. Additionally, proteins released by Hodgkin lymphoma-derived L428 cells were extracted from serum-free culture media and analyzed. Peptide spectra were analyzed using TurboSEQUEST against the UniProt protein database (5.26.05; 188 712 entries). A subset of the identified proteins was validated by Western blot analysis, immunofluorescence microscopy and immunohistochemistry. A total of 1945 proteins were identified with 785 from the cytosolic fraction, 305 from the membrane fraction, 441 from the nuclear fraction and 414 released proteins using a minimum of two peptide identifications per protein and an error rate of <5.0%. Identification of proteins from diverse functional groups reflected the functional complexity of the Reed-Sternberg proteome. Proteins with previously reported oncogenic function in other cancers and from signaling pathways implicated in Hodgkin lymphoma were identified. Selected proteins without previously demonstrated expression in Hodgkin lymphoma were validated by Western blot analysis (B-RAF, Erb-B3), immunofluorescence microscopy (Axin1, Tenascin-X, Mucin-2) and immunohistochemistry using a tissue microarray (BRAF, PIM1). This study represents the first comprehensive inventory of proteins expressed by Reed-Sternberg cells of Hodgkin lymphoma and demonstrates the utility of combining cellular subfractionation, protein precipitation, tandem mass spectrometry and bioinformatics analysis for comprehensive identification of proteins that may represent potential biomarkers of the disease.