48 research outputs found

    Leveraging Biospecimen Resources for Discovery or Validation of Markers for Early Cancer Detection

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    Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts

    Mammalian tumour necrosis factor-α (TNF) and granulocyte/macrophage colony-stimulating factor (GM-CSF) AU-rich elements (AREs)

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    <p><b>Copyright information:</b></p><p>Taken from "The tandem CCCH zinc finger protein tristetraprolin and its relevance to cytokine mRNA turnover and arthritis"</p><p>Arthritis Research & Therapy 2004;6(6):248-264.</p><p>Published online 8 Oct 2004</p><p>PMCID:PMC1064869.</p><p>Copyright © 2004 BioMed Central Ltd</p> The central ARE region of the TNF mRNA 3' untranslated region from all mammalian species for which this region of the mRNA has been deposited in GenBank. In most cases these were derived from EST sequences; note that the horse sequence has not been completed at the 3' end. The overlines indicate the nine-base tristetraprolin (TTP)-binding site 5'-UUAUUUAUU-3'. Sequences from the various mammals are divided into groups based on the pattern of these nonamers, with the top group of 10 mammals being the most common group. A similar approach was used to align the central ARE from the GM-CSF transcript, after alignment using the program ClustalW. The asterisks below the alignment represent base identity at that position; note that gaps were used to optimize the alignment. The overlines again represent the nonamer TTP-binding site. These data are modified from [37]

    Robustness of RNA sequencing on older formalin-fixed paraffin-embedded tissue from high-grade ovarian serous adenocarcinomas.

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    Formalin-fixed paraffin-embedded (FFPE) tissues are among the most widely available clinical specimens. Their potential utility as a source of RNA for transcriptome studies would greatly enhance population-based cancer studies. Although preliminary studies suggest FFPE tissue may be used for RNA sequencing, the effect of storage time on these specimens needs to be determined. We conducted this study to determine whether RNA in archived FFPE high-grade ovarian serous adenocarcinomas from Surveillance, Epidemiology and End Results (SEER) registries was present in sufficient quantity and quality for RNA-Seq analysis. FFPE tissues, stored from 7 to 32 years, were obtained from three SEER sites. RNA was extracted, quantified, quality assessed, and subjected to RNA-Seq (a whole transcriptome sequencing technology). FFPE specimens stored for longer periods of time had poorer RNA sample quality as indicated by negative correlations between specimen storage time and fragment distribution values (DV). In addition, sample contamination was a common issue among the RNA, with 41 of 67 samples having 5% to 48% bacterial contamination. However, regardless of specimen storage time and bacterial contamination, 60% of the samples yielded data that enabled gene expression quantification, identifying more than 10,000 genes, with the correlations among most biological replicates above 0.7. This study demonstrates that FFPE high-grade ovarian serous adenocarcinomas specimens stored in repositories for up to 32 years and under varying storage conditions are a promising source of RNA for RNA-Seq. We also describe certain caveats to be considered when designing RNA-Seq studies using archived FFPE tissues

    Immunogenetic risk and protective factors for juvenile dermatomyositis in Caucasians

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    Objective. To define the relative importance (RI) of class II major histocompatibility complex (MHC) alleles and peptide binding motifs as risk or protective factors for juvenile dermatomyositis (DM), and to compare these with HLA associations in adult DM. Methods. DRB1 and DQA1 typing was performed in 142 Caucasian patients with juvenile DM, and the results were compared with HLA typing data from 193 patients with adult DM and 797 race-matched controls. Random Forests classification and multiple logistic regression were used to assess the RI of the HLA associations. Results. The HLA-DRB1*0301 allele was a primary risk factor (odds ratio [OR] 3.9), while DQA1*0301 (OR 2.8), DQA1*0501 (OR 2.1), and homozygosity for DQA1*0501 (OR 3.2) were additional risk factors for juvenile DM. These risk factors were not present in patients with adult DM without defined autoantibodies. DQA1 alleles *0201 (OR 0.37), *0101 (OR 0.38), and *0102 (OR 0.51) were identified as novel protective factors for juvenile DM, the latter 2 also being protective factors in adult DM. The peptide binding motif DRB1 9EYSTS 13 was a risk factor, and DQA1 motifs F25, S26, and 45(V/A)W(R/K)47 were protective. Random Forests classification analysis revealed that among the identified risk factors for juvenile DM, DRB1*0301 had a higher RI (100%) than DQA1*0301 (RI 57%), DQA1*0501 (RI 42%), or the peptide binding motifs. In a logistic regression model, DRB1*0301 and DQA1*0201 were the strongest risk and protective factors, respectively, for juvenile DM. Conclusion. DRB1*0301 is ranked higher in RI than DQA1*0501 as a risk factor for juvenile DM. DQA1*0301 is a newly identified HLA risk factor for juvenile DM, while 3 of the DQA1 alleles studied are newly identified protective factors for juvenile DM. © 2006, American College of Rheumatology
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