Unknown,Transcriptomics,Genomics,Proteomics

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A nested case-control study to investigate drivers for metastatic disease in breast cancer (QC substudy)

ABSTRACT: This is a quality control (QC) substudy of GSE48091. The QC substudy comprises gene-expression profiling of re-extracted tumor RNA for a subset of the tumours in the full study. As background, a population-based cohort study of metastatic breast cancer patients was first designed. Thereafter, a case-control study nested in the corresponding population-based cohort of primary breast cancer patients was designed by selecting distant metastasis-free controls to each case. Tumor RNA was extracted in the same order. All RNA was profiled on microarrays in randomized order. For quality control, RNA was also re-extracted (new tumor piece) in a randomized order for randomly selected cases-controls sets and profiled with the rest. Keywords: Expression profiling by array The nested case-control study included 768 study subjects corresponding to 623 primary tumor samples. This QC substudy comprises 97 of the study subjects (all different primary tumor samples). Details concerning case-control status are given in the samples section. This Series includes a re-analysis of 97 samples from GSE48091. The file "full_data_matrix.txt" includes the re-normalized values for the 97 samples from GSE48091 and the normalized values for the 97 new samples from the same patients that were analyzed together.

ORGANISM(S): Homo sapiens

SUBMITTER: John LÃ¶vrot

PROVIDER: E-GEOD-81954 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n=223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals (42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD) were processed and hybridized to Affymetrix HG-U133 2.0 Plus microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥7.0 using Agilent 2100 Bioanalyzer software; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤3.0; and (3) the multi-chip normalization scaling factor ≤10.0 Of the 223 samples, 213 (95.5%) passed the QC criteria. In a data set of 34 arrays (10 samples failing QC criteria, 24 randomly chosen samples passing QC criteria), correlation coefficients for pairwise comparisons of expression levels for 100 housekeeping genes in which at least one array failed the QC criteria were significantly lower (average Pearson r = 0.90 ± 0.04) and more broadly dispersed than correlation coefficients for pairwise comparisons between any two arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). By using the QC cutoff criteria, the inter-array variability, as assessed by the coefficient of variation in the expression levels for 100 housekeeping genes, was reduced from 35.7% to 21.7%. Based on the aberrant housekeeping gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.

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A nested case-control study to investigate drivers for metastatic disease in breast cancer (QC substudy)

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