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Robust Gene Expression Signature from Formalin-Fixed Paraffin-Embedded Samples Predicts Prognosis of Non-Small-Cell Lung Cancer Patients

ABSTRACT: The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling using microarray technology. Keywords: Lung Cancer Prognosis, Gene Expression Signature, Formalin Fixed Paraffin Embedded Samples The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes. FFPE tumor specimens were collected, and total RNA was processed for analysis on the Affymetrix U133 plus 2.0 arrays according to Affymetrix protocols. The quality control procedure for microarray data analysis was based on the percentage of present calls calculated by the MAS5 package. We selected 55 arrays with at least 15% of probe sets present, and we selected 1400 probe sets that present on all 55 arrays for data analysis. After microarray analysis QC, we used the RMA background correction algorithm to remove non-specific background noise. A robust regression model was fitted to the probe level data, and the fitted expression values for the probes at the 3' end were used to summarize the probe set expression values. Quantile-quantile normalization was used to normalize all the arrays. The 55 samples and the derived gene expression values for 1400 genes based on the robust regression model were used to develop gene signatures and were uploaded as supplementary data (GSE29013_fitted_1400_probes.txt).

ORGANISM(S): Homo sapiens

PROVIDER: GSE29013 | GEO | 2011/09/01

SECONDARY ACCESSION(S): PRJNA140467

REPOSITORIES: GEO

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Project description:In order to determine BCL6 target genes an EBV negative Burkitt's lymphoma cell line, DG75, was stably transfected with a tetracycline transactivator and tight doxycycline responsive expression of GFP was established. The endogenous BCL6 genes of this cell line were disrupted by homologous recombination and a BCL6 cDNA downstream of tetracycline responsive elements (TRE) was inserted to produce Bcl6-/-:tetBCL6-HA cells. Westerns demonstrated doxycycline dependent BCL6 expression.Bcl6-/-:tet. BCL6-HA cells (clone AB7) were either grown without doxycycline (control) or with 1 ug/ml doxycycline for 16, 48 or 96 hours. Total RNA was extracted using RNeasy minipreps (Qiagen) and concentration and quality were checked on the NanoDrop® ND- 1000 spectrophotometer (NanoDrop Technologies, USA) and the RNA Nano 6000 kit (Agilent Technologies) on a 2100 Bioanalyzer (Agilent Technologies). One hundred ng of total RNA was processed with the GeneChip® Eukaryotic Whole Transcript Sense Target Labelling Assay kit (Affymetrix) according to the manufacturer's details. Hybridisation and scanning of GeneChips® was carried out at the CSC/IC Microarray Centre, MRC Clinical Sciences Centre Imperial College London and data analysis by Bioinformatics Support Service, Imperial College London. Briefly, pre- processing of data was performed using GeneSpring GX 10.0.2 software (Agilent Technologies) which applied the "Exon RMA16"¸ algorhithm to the data set. Exon RMA16 performs background correction, quantile normalisation, median polish summarisation and variance stabilisation of 16. In background correction, intensity values of each individual array are corrected for non-specific binding by subtracting the average signal intensity of the area between spots from each probe set. Normalisation is required so multiple chips can be compared to each other. Quantile normalisation adjusts the distribution of probe intensity of each array analysed and so that the distribution of probe intensities for each array in a set of arrays is the same. Probe summarisation refers to the conversion of probe level values (there are approximately 26 probes per gene on each GeneChip®) to a single probe set expression value. Variance stabilisation of 16 refers to the addition of the value 16 to the expression values. By increasing the expression value, the variance of the data set is reduced and the distribution (defined by its mean and its variance) is stabilised.

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Robust Gene Expression Signature from Formalin-Fixed Paraffin-Embedded Samples Predicts Prognosis of Non-Small-Cell Lung Cancer Patients

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