CD44s and CD44v6 Expression in Head and Neck Epithelia

Background: CD44 splice variants are long-known as being associated with cell transformation. Recently, the standard form of CD44 (CD44s) was shown to be part of the signature of cancer stem cells (CSCs) in colon, breast, and in head and neck squamous cell carcinomas (HNSCC). This is somewhat in contradiction to previous reports on the expression of CD44s in HNSCC. The aim of the present study was to clarify the actual pattern of CD44 expression in head and neck epithelia. Methods: Expression of CD44s and CD44v6 was analysed by immunohistochemistry with specific antibodies in primary head and neck tissues. Scoring of all specimens followed a two-parameters system, which implemented percentages of positive cells and staining intensities from − to +++ (score = %×intensity; resulting max. score 300). In addition, cell surface expression of CD44s and CD44v6 was assessed in lymphocytes and HNSCC. Results: In normal epithelia CD44s and CD44v6 were expressed in 60–95% and 50–80% of cells and yielded mean scores with a standard error of a mean (SEM) of 249.5±14.5 and 198±11.13, respectively. In oral leukoplakia and in moderately differentiated carcinomas CD44s and CD44v6 levels were slightly increased (278.9±7.16 and 242±11.7; 291.8±5.88 and 287.3±6.88). Carcinomas in situ displayed unchanged levels of both proteins whereas poorly differentiated carcinomas consistently expressed diminished CD44s and CD44v6 levels. Lymphocytes and HNSCC lines strongly expressed CD44s but not CD44v6. Conclusion: CD44s and CD44v6 expression does not distinguish normal from benign or malignant epithelia of the head and neck. CD44s and CD44v6 were abundantly present in the great majority of cells in head and neck tissues, including carcinomas. Hence, the value of CD44s as a marker for the definition of a small subset of cells (i.e. less than 10%) representing head and neck cancer stem cells may need revision

CD44 Expression in Oro-Pharyngeal Carcinoma Tissues and Cell Lines

Expression of CD44, a transmembrane hyaluronan-binding glycoprotein, is variably considered to have prognostic significance for different cancers, including oral squamous cell carcinoma. Although unclear at present, tissue-specific expression of particular isoforms of CD44 might underlie the different outcomes in currently available studies. We mined public transcriptomics databases for gene expression data on CD44, and analyzed normal, immortalized and tumour-derived human cell lines for splice variants of CD44 at both the transcript and protein levels. Bioinformatics readouts, from a total of more than 15,000 analyses, implied an increased CD44 expression in head and neck cancer, including increased expression levels relative to many normal and tumor tissue types. Also, meta-analysis of over 260 cell lines and over 4,000 tissue specimens of diverse origins indicated lower CD44 expression levels in cell lines compared to tissue. With minor exceptions, reverse transcribed polymerase chain reaction identified expression of the four main isoforms of CD44 in normal oral keratinocytes, transformed lines termed DT and HaCaT, and a series of paired primary and metastasis-derived cell lines from oral or pharyngeal carcinomas termed HN4/HN12, HN22/HN8 and HN30/HN31. Immunocytochemistry, Western blotting and flow cytometric assessments all confirmed the isoform expression pattern at the protein level. Overall, bioinformatic processing of large numbers of global gene expression analyses demonstrated elevated CD44 expression in head and neck cancer relative to other cancer types, and that the application of standard cell culture protocols might decrease CD44 expression. Additionally, the results show that the many variant CD44 exons are not fundamentally deregulated in a diverse range of cultured normal and transformed keratinocyte lines

Use of RNA sequencing to evaluate rheumatic disease patients

Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale in a particular cell, tissue or organ. Microarray analysis has led to gene signatures that differentiate rheumatic diseases, and stages of a disease, as well as response to treatments. Nowadays, however, with the advent of next-generation sequencing methods, massive parallel sequencing of RNA tends to be the technology of choice for gene expression profiling, due to several advantages over microarrays, as well as for the detection of non-coding transcripts and alternative splicing events. In this review, we describe how RNA sequencing enables unbiased interrogation of the abundance and complexity of the transcriptome, and present a typical experimental workflow and bioinformatics tools that are often used for RNA sequencing analysis. We also discuss different uses of this next-generation sequencing technology to evaluate rheumatic disease patients and investigate the pathogenesis of rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, juvenile idiopathic arthritis and Sjögren\u27s syndrome

Measurement of the tt̄W and tt̄Z production cross sections in pp collisions at √s = 8 TeV with the ATLAS detector

The production cross sections of top-quark pairs in association with massive vector bosons have been measured using data from pp collisions at s√ = 8 TeV. The dataset corresponds to an integrated luminosity of 20.3 fb−¹ collected by the ATLAS detector in 2012 at the LHC. Final states with two, three or four leptons are considered. A fit to the data considering the tt̄W and tt̄Z processes simultaneously yields a significance of 5.0σ (4.2σ) over the background-only hypothesis for tt¯Wtt¯W (tt̄Z) production. The measured cross sections are σtt̄W = 369 + 100−91 fb and σtt̄Z = 176 + 58−52 fb. The background-only hypothesis with neither tt̄W nor tt̄Z production is excluded at 7.1σ. All measurements are consistent with next-to-leading-order calculations for the tt̄W and tt̄Z processes