Project description:The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the "Substudies" box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. <ol> <li>Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80°C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors.</li> <li>Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors.</li> <li>Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80°C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80°C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors.</li> <li>Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors.</li> <li>Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors.</li> <li>Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80°C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors.</li> <li>mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors.</li> </ol> The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page <a href="study.cgi?study_id=phs001304">phs001304</a> Biospecimen PV cohort. <ul> <li><a href="study.cgi?study_id=phs001634">phs001634</a> CIT mRNA</li> <li><a href="study.cgi?study_id=phs001635">phs001635</a> CNV aCGH</li> <li><a href="study.cgi?study_id=phs001636">phs001636</a> Fixation Delay</li> <li><a href="study.cgi?study_id=phs001637">phs001637</a> Global Metabolite Profiling</li> <li><a href="study.cgi?study_id=phs001638">phs001638</a> mRNA TaqMan</li> <li><a href="study.cgi?study_id=phs001639">phs001639</a> NGS</li> <li><a href="study.cgi?study_id=phs001640">phs001640</a> Tumor Storage</li> </ul>

Project description:Purpose: RNA-sequencing (RNA-seq) was used to identify the changes in gene expression profile in horse skin fibroblast cell line expressing one of the BPV genes encoding transforming proteins (BPV-E4 and BPV-E4^E1). The whole transcriptome sequencing allows us to establish the influence of BPV gene transfection on host cells and indicates which virus genes can be responsible for the neoplastic process. It is the first study concerning a cell model of horse skin transfected with BPV genes. Such a model could contribute to a more accurate understanding of changes inside cells during viral infection. Methods: The equine fibroblast cell lines were transfected using the nucleofection method with BPV-E4 and BPV-E4^E1 constructs. RNA was isolated from cell lines directly from culture dishes with PureLink™ RNA mini kit. The quality and quantity of obtained libraries (the TruSeq RNA Kit v2 kit (Illumina, San Diego, CA, USA) ) were assessed using Qubit 2.0 (Qubit™ dsDNA BR AssayKit, Invitrogen, Waltham, MA, USA ) and TapeStation 2200 (D100 screencaps, Agilent). Next, the cDNA libraries were sequenced on NextSeq 500 Illumina platform (Illumina, San Diego, CA, USA) and NextSeq 500/550 High Output KIT v 2.5 (75 cycles) according to protocol. The qPCR validation was used to confirm RNA-seq data. Then, the quality of raw reads was checked with FastQC software followed by removal of adapters and reads of low quality (under phred quality of 20) and reads under length of 36 (Flexbar software). Next, the filtered reads were mapped to EquCab3 genome with STAR software and reads were counted to specific gene thresholds provided in Ensembl gtf file version 100 by htseq-count software. Differential expresion extimation was followed with the use of Deseq2 software. Results: The transcriptome profiling allowed us to perform a comparison of the whole expression profile between the control and both BPV-E4 and BPV-E4^E1 groups. According to the comparison of control and BPV-E4 groups, the 1640 DEGs were identified, of which 624 were up-regulated and 1016 down-regulated in the BPV-E4 group. The highest number of DEGs – 3328 were detected from the control and BPV-E4^E1 comparison. Among them, 1626 genes were up-regulated and 1602 down-regulated in the BPV-E4^E1 group compared to control samples. The most overrepresented Gene Ontology Term between control and BPV-E4 groups were negative regulation of cell proliferation – 34 DEGs (FDR<0.002); positive regulation of cell migration – 24 DEGs (FDR<0.0001); cell adhesion and cell migration; 21 DEGs in both GO terms (FDR<0.003 and 0.0005; respectively). The enrichment analysis performed for differentially expressed genes between control and BPV-E4^E1 samples showed the focal adhesion GO terms were overrepresented by 99 DEGs of which 65 were up-regulated and 34 down-regulated (FDR<0.0001). For cells transfected BPV-E4 and BPV-E4^E1 constructs, the most significant were pathways: of the cell cycle, cytoskeleton, and ECM-matrix remodelling; regulation of actin cytoskeleton; focal adhesion and ECM-receptor interaction. The Pathways in cancer were identified uniquely for cells transfected by BPV-E4 construct, while only for BPV-E4^E1 cells the FoxO, Rap1, and TNF-signaling path-ways and Proteoglycans in cancer. Conclusions: The results obtained showed that both transfection types significantly affected cells transcriptome towards cancer transformation. Nevertheless, cells transfected with BPV-E4^E1 genes seem to be closer to the molecular modification that occurred in vivo in equine sarcoids. The present study showed how equine fibroblast cells could be modified, at the molecular level, in the presence of BPV E4 gene. These findings broaden the knowledge about the possible interaction of BPV viruses on host cells.

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Biospecimen Pre-analytical Variables (BPV)

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