Gene expression profiling of FFPE breast cancer samples
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE38554 | GEO | 2014/02/01
SECONDARY ACCESSION(S): PRJNA169618
REPOSITORIES: GEO
Similar Datasets
Project description:We implemented an optimized processing, using alternative Chip Description Files (CDFs) and fRMA normalization, which improve the quality of downstream analysis. We profiled 44 FFPE primary breast cancer samples using Affymetrix HG-U133 Plus 2.0 microarray platform after RNA amplification with the Nugen WT-Ovation FFPE System
2014-02-01 | E-GEOD-38554 | biostudies-arrayexpress
Project description:JRS4 is our wild-type M6 serotype GAS and JRS519 is our Mga- M6 serotype GAS. SF370 is our wild-type M1 serotype GAS and KSM165L is our Mga- M1 serotype GAS. Table 1: Genomic Normalization Description: Step by Step instructions for the removal of outlier background data and any ORF data that did not meet threshold of 2SD above background average, using original data from gpr file provided in each of the sample files. Table 2: M1 Mga+ vs Mga- Description: Step by Step instructions for the removal of outlier data as compared across all possible data points for each ORF. Data points after genomic normalization are used with resultant averages and standard deviations for each ORF computed. Table 3: M6 Mga+ vs Mga- Description: Step by Step instructions for the removal of outlier data as compared across all possible data points for each ORF. Data points after genomic normalization are used with resultant averages and standard deviations for each ORF computed. Keywords: repeat sample
2005-04-06 | GSE1895 | GEO
Project description:ATAC-Seq was performed for 35 AML primary specimens from primary AML cells, followed by a detailed ATAC-Seq pipeline for data processing. We provide both raw files as well as various processed files such as individual and consensus peaks.
2022-02-06 | GSE150868 | GEO
Project description:Total RNA from each sample was quantified by the NanoDrop ND-1000 and RNA integrity was assessed by standard denaturing agarose gel electrophoresis. Total RNA of each sample was used for labeling and array hybridization as the following steps: 1) Reverse transcription with by Invitrogen Superscript ds-cDNA synthesis kit; 2) ds-cDNA labeling with NimbleGen one-color DNA labeling kit; 3) Array hybridization using the NimbleGen Hybridization System and followed by washing with the NimbleGen wash buffer kit; 4) Array scanning using the Axon GenePix 4000B microarray scanner (Molecular Devices Corporation). Scanned images (TIFF format) were then imported into NimbleScan software (version 2.5) for grid alignment and expression data analysis. Expression data were normalized through quantile normalization and the Robust Multichip Average (RMA) algorithm included in the NimbleScan software. The Probe level (*_norm_RMA.pair) files and Gene level (*_RMA.calls) files were generated after normalization. The 2 gene level files were imported into Agilent GeneSpring GX software (version 11.5.1). Genes that have values greater than or equal to lower cut-off: 100.0 in that at least 1 out of 2 samples (“All Targets Value”) were chosen for data analysis.
2022-07-20 | GSE208583 | GEO
Project description:Genome-wide assessment of protein-DNA interactions binding by ChIP-seq is a key technology to study transcription factor (TF) localization and regulation of gene-expression. In ChIP-seq, signal-to-noise-ratio as well as signal specificity depend on many variables including antibody quality, and efforts to improve ChIP-seq data thus far focused mostly on generating better reagents. Here we introduce KOIN (KO implemented normalization) as a novel strategy to increase signal specificity and reduce noise by using TF knockout-mice as a critical control for ChIP-seq. We tested our new peak calling strategy (KO implemented normalization = KOIN) on different ChIP-seq datasets to increase signal specificity and reduce noise.
2014-07-17 | E-GEOD-55317 | biostudies-arrayexpress
Project description:Nasopharyngeal carcinoma (NPC) is a challenging cancer that is rare in the United States but shows exceptionally high incidence in Southern China, Indonesia, and Malaysia. While the hallmark of NPC is striking geographic variation, early detection and clinical management are also critical characteristics of this cancer. The etiology of NPC is complex, involving the interplay of multiple factors, including Epstein Barr Virus (EBV), which appears to play an oncogenic role. While multimodality therapy is the mainstay of treatment for NPC, the impact of this treatment is greatly influenced by the presenting tumor stage, tumor size, nodal involvement, and the histologic subtype classification. Up to 40% percent of NPC cases present at an advanced stage, likely due to its deep location in the lymphatic-rich nasopharynx and its propensity for early lymphatic spread. Recent modifications in the TNM staging schema have attempted to improve prognostic accuracy, but variations in clinical outcome are still reported in patients with the same stage and similar treatment regimens. The various molecular markers developed to monitor disease progression have also proven unreliable. Hence, there is a significant need for a new kind of prognostic biomarker for NPC. Herein different approaches were applied to a set of samples to detect NPC-related miRNAs, potential circulating biomarkers. We have optimized the extraction of total RNA from NPC Formalin-fixed, paraffin-embedded (FFPE) samples and sera from four patients and matched controls and analyzed the miRNA expression profile by microarray, qPCR and RNAseq. The microarray analysis showed that 46 miRNAs were found to be differentially and significantly expressed in carcinogenic tissue compared to healthy tissue. Twenty-three (23) microRNAs were significantly upregulated (21 human microRNAs and 2 EBV miRNAs), whereas 13 were down-regulated.
2014-01-13 | GSE46172 | GEO
Project description:Nasopharyngeal carcinoma (NPC) is a challenging cancer that is rare in the United States but shows exceptionally high incidence in Southern China, Indonesia, and Malaysia. While the hallmark of NPC is striking geographic variation, early detection and clinical management are also critical characteristics of this cancer. The etiology of NPC is complex, involving the interplay of multiple factors, including Epstein Barr Virus (EBV), which appears to play an oncogenic role. While multimodality therapy is the mainstay of treatment for NPC, the impact of this treatment is greatly influenced by the presenting tumor stage, tumor size, nodal involvement, and the histologic subtype classification. Up to 40% percent of NPC cases present at an advanced stage, likely due to its deep location in the lymphatic-rich nasopharynx and its propensity for early lymphatic spread. Recent modifications in the TNM staging schema have attempted to improve prognostic accuracy, but variations in clinical outcome are still reported in patients with the same stage and similar treatment regimens. The various molecular markers developed to monitor disease progression have also proven unreliable. Hence, there is a significant need for a new kind of prognostic biomarker for NPC. Herein different approaches were applied to a set of samples to detect NPC-related miRNAs, potential circulating biomarkers. We have optimized the extraction of total RNA from NPC Formalin-fixed, paraffin-embedded (FFPE) samples and sera from four patients and matched controls and analyzed the miRNA expression profile by microarray, qPCR and RNAseq. The microarray analysis showed that 46 miRNAs were found to be differentially and significantly expressed in carcinogenic tissue compared to healthy tissue. Twenty-three (23) microRNAs were significantly upregulated (21 human microRNAs and 2 EBV miRNAs), whereas 13 were down-regulated. A total of 8 unique samples were analyzed on Agilent human miRNA microarray (miRBase Release 16.0). Of the 8 samples, 4 are from Non-keratinizing NPC tissue. Non-NPC (normal) tissue were taken from 4 individuals that were diagnosed with NPC (2 of which were matched/paired from the NPC case).
2014-01-13 | E-GEOD-46172 | biostudies-arrayexpress
Project description:The gene expression analysis of formalin-fixed paraffin-embedded (FFPE) tissues is often hampered by poor RNA quality, which results from the oxidation, cross-linking and other chemical modifications induced by the inclusion in paraffin. Yet, FFPE samples are a valuable source for molecular studies and can provide great insights into disease progression and prognosis. With the advancement of genomic technologies, new methods have been established that offer reliable and accurate gene expression workflows on samples of poor quality. NanoString is a probe-based technology that allows the direct counting of the mRNA transcripts and can be applied to degraded samples. Here, we have tested 2 RNA extraction methods for FFPE samples, and we have performed a titration experiment to evaluate the impact of RNA degradation and RNA input on the gene expression profiles assessed using the NanoString IO360 panel. We have selected FFPE samples of different DV200 values and assessed them on the nCounter platform with 2 different amounts of input RNA. This study concludes that the nCounter is a robust and reliable platform to assess the gene expression of RNA samples with DV200 > 30%; its robustness and ease of use could be of particular benefit to clinical settings.
| S-EPMC9706083 | biostudies-literature
Project description:The fetal hemoglobin (HbF) levels were 95.4 ± 1.5% and 4.4 ± 0.2% in fetal liver-derived and adult blood derived-cultured erythrocytes (n=5), respectively. Following RNA isolation from the CD71 high/GPA positive erythroblasts, gene expression analyses were performed using Affymetrix Human Gene 2.0 ST Array. The Affymetrix raw data files of microarray were preprocessed using robust multi-array average method for background correction, log-transformation, and quantile normalization. Differential gene expression between fetal liver derived- and adult peripheral blood derived-erythroblasts was determined using moderated t-statistics implemented in the Limma package. We found the 1366 genes were upregulated by more than 1.5-fold change with adjusted p-value less than 0.05 in fetal liver derived-erythroblasts.
2018-08-13 | GSE109186 | GEO
Project description:Artifact chimeric reads are enriched in next-generation sequencing data generated from formalin-fixed paraffin-embedded (FFPE) samples. Previous work indicated that these reads are characterized by erroneous split-read support that is interpreted as evidence of structural variants. Thus, a large number of false-positive structural variants are detected. To our knowledge, no tool is currently available to specifically call or filter structural variants in FFPE samples. To overcome this gap, we developed 2 R packages: SimFFPE and FilterFFPE. SimFFPE is a read simulator, specifically designed for next-generation sequencing data from FFPE samples. A mixture of characteristic artifact chimeric reads, as well as normal reads, is generated. FilterFFPE is a filtration algorithm, removing artifact chimeric reads from sequencing data while keeping real chimeric reads. To evaluate the performance of FilterFFPE, we performed structural variant calling with 3 common tools (Delly, Lumpy, and Manta) with and without prior filtration with FilterFFPE. After applying FilterFFPE, the mean positive predictive value improved from 0.27 to 0.48 in simulated samples and from 0.11 to 0.27 in real samples, while sensitivity remained basically unchanged or even slightly increased. FilterFFPE improves the performance of SV calling in FFPE samples. It was validated by analysis of simulated and real data.
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