Quality control in microarray assessment of gene expression in human airway epithelium

<p>Abstract</p> <p>Background</p> <p>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 and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥ 7.0; (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.</p> <p>Results</p> <p>Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3%) passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6%) passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04) were significantly lower (p < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria.</p> <p>Conclusion</p> <p>Based on the aberrant maintenance 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.</p

Segmental chromosomal alterations have prognostic impact in neuroblastoma: a report from the INRG project

Background: In the INRG dataset, the hypothesis that any segmental chromosomal alteration might be of prognostic impact in neuroblastoma without MYCN amplification (MNA) was tested. Methods: The presence of any segmental chromosomal alteration (chromosome 1p deletion, 11q deletion and/or chromosome 17q gain) defined a segmental genomic profile. Only tumours with a confirmed unaltered status for all three chromosome arms were considered as having no segmental chromosomal alterations. Results: Among the 8800 patients in the INRG database, a genomic type could be attributed for 505 patients without MNA: 397 cases had a segmental genomic type, whereas 108 cases had an absence of any segmental alteration. A segmental genomic type was more frequent in patients >18 months and in stage 4 disease (P<0.0001). In univariate analysis, 11q deletion, 17q gain and a segmental genomic type were associated with a poorer event-free survival (EFS) (P<0.0001, P=0.0002 and P<0.0001, respectively). In multivariate analysis modelling EFS, the parameters age, stage and a segmental genomic type were retained in the model, whereas the individual genetic markers were not (P<0.0001 and RR=2.56; P=0.0002 and RR=1.8; P=0.01 and RR=1.7, respectively). Conclusion: A segmental genomic profile, rather than the single genetic markers, adds prognostic information to the clinical markers age and stage in neuroblastoma patients without MNA, underlining the importance of pangenomic studies

How to minimise the effect of tumour cell content in detection of aberrant genetic markers in neuroblastoma

Background:Clinical heterogeneity reflects the complexity of genetic events associated with neuroblastoma (NB). To identify the status of all described genetic loci with possible prognostic interest, high-throughput approaches have been used, but only with tumour cell content >60%. In some tumours, necrotic, haemorrhagic and/or calcification areas influence the low amount of neuroblasts. We evaluated the effect of tumour cell content in the detection of relevant aberrant genetic markers (AGM) diagnosed by fluorescence in situ hybridisation (FISH) on tissue microarrays (TMA) in NB.Methods:Two hundred and thirty-three MYCN non-amplified primary NB included in 12 TMAs were analysed.Results:Presence of AGM reduced event-free survival (EFS) (P=0.004) as well as overall survival (OS) (P=0.004) of patients in the whole cohort. There were no differences in prognostic impact of presence of AGM according to tumour cell content.Conclusion:We propose the use of FISH to diagnose AGM of all NB samples having the above-mentioned areas to determine patient risk

An integrated Bayesian analysis of LOH and copy number data

Background: Cancer and other disorders are due to genomic lesions. SNP-microarrays are able to measure simultaneously both genotype and copy number (CN) at several Single Nucleotide Polymorphisms (SNPs) along the genome. CN is defined as the number of DNA copies, and the normal is two, since we have two copies of each chromosome. The genotype of a SNP is the status given by the nucleotides (alleles) which are present on the two copies of DNA. It is defined homozygous or heterozygous if the two alleles are the same or if they differ, respectively. Loss of heterozygosity (LOH) is the loss of the heterozygous status due to genomic events. Combining CN and LOH data, it is possible to better identify different types of genomic aberrations. For example, a long sequence of homozygous SNPs might be caused by either the physical loss of one copy or a uniparental disomy event (UPD), i.e. each SNP has two identical nucleotides both derived from only one parent. In this situation, the knowledge of the CN can help in distinguishing between these two events. Results: To better identify genomic aberrations, we propose a method (called gBPCR) which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the homozygosity status of the SNPs, resulting from an altered CN level. Namely, we model the distributions of the detected genotype, given a specific genomic alteration and we estimate the parameters involved on public referenc

TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays

<p>Abstract</p> <p>Background</p> <p>High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, including total copy number and loss of heterozygosity (LOH) analyses. Even after state of the art preprocessing methods, allelic signal estimates from genotyping arrays still suffer from systematic effects that make them difficult to use effectively for such downstream analyses.</p> <p>Results</p> <p>We propose a method, TumorBoost, for normalizing allelic estimates of one tumor sample based on estimates from a single matched normal. The method applies to any paired tumor-normal estimates from any microarray-based technology, combined with any preprocessing method. We demonstrate that it increases the signal-to-noise ratio of allelic signals, making it significantly easier to detect allelic imbalances.</p> <p>Conclusions</p> <p>TumorBoost increases the power to detect somatic copy-number events (including copy-neutral LOH) in the tumor from allelic signals of Affymetrix or Illumina origin. We also conclude that high-precision allelic estimates can be obtained from a single pair of tumor-normal hybridizations, if TumorBoost is combined with single-array preprocessing methods such as (allele-specific) CRMA v2 for Affymetrix or BeadStudio's (proprietary) XY-normalization method for Illumina. A bounded-memory implementation is available in the open-source and cross-platform R package <it>aroma.cn</it>, which is part of the Aroma Project (<url>http://www.aroma-project.org/</url>).</p

Age-dependency of the prognostic impact of tumor genomics in localized resectable MYCN non-amplified neuroblastomas Report from the SIOPEN Biology Group on the LNESG Trials

BACKGROUND: Biology based treatment reduction, i.e. surgery alone also in case of not totally resected tumors, was advised in neuroblastoma patients with localized resectable disease without MYCN amplification. However, whether the genomic background of these tumors may influence outcome was unknown and therefore scrutinized in a meta-analysis comprising two prospective therapy studies and a ‘validation’ cohort. PATIENTS AND METHODS: Diagnostic samples were derived from 406 INSS stages 1/2A/2B tumors from three cohorts: LNESGI/II and COG. Genomic data were analyzed in two age groups (cut-off: 18 months) and quality controlled by the SIOPEN Biology Group. RESULTS: In both patient age groups stage 2 tumors led to similarly reduced event-free survival (5y-EFS: 83+3% versus 80+4%), but overall survival was only decreased in patients >18m (5y-OS: 97+1% versus 87+4%; p=0.001). In the latter age subgroup, only tumors with SCA led to relapses, with 11q loss as the strongest marker (5y-EFS: 40+15% versus 89+5%; p18m but not <18m. CONCLUSION: The tumor genomic make-up of resectable non-MYCN amplified stage 2 neuroblastomas has a distinct age-dependent prognostic impact in neuroblastoma patients. While in the younger age group tumors with unfavourable (SCA) and favorable genetics showed relapses, both without worsening OS, in the older age group only tumors with unfavorable genetics led to relapses and decreased OS.N/

A Constitutional Translocation t(1;17)(p36.2;q11.2) in a Neuroblastoma Patient Disrupts the Human NBPF1 and ACCN1 Genes

The human 1p36 region is deleted in many different types of tumors, and so it probably harbors one or more tumor suppressor genes. In a Belgian neuroblastoma patient, a constitutional balanced translocation t(1;17)(p36.2;q11.2) may have led to the development of the tumor by disrupting or activating a gene. Here, we report the cloning of both translocation breakpoints and the identification of a novel gene that is disrupted by this translocation. This gene, named NBPF1 for Neuroblastoma BreakPoint Family member 1, belongs to a recently described gene family encoding highly similar proteins, the functions of which are unknown. The translocation truncates NBPF1 and gives rise to two chimeric transcripts of NBPF1 sequences fused to sequences derived from chromosome 17. On chromosome 17, the translocation disrupts one of the isoforms of ACCN1, a potential glioma tumor suppressor gene. Expression of the NBPF family in neuroblastoma cell lines is highly variable, but it is decreased in cell lines that have a deletion of chromosome 1p. More importantly, expression profiling of the NBPF1 gene showed that its expression is significantly lower in cell lines with heterozygous NBPF1 loss than in cell lines with a normal 1p chromosome. Meta-analysis of the expression of NBPF and ACCN1 in neuroblastoma tumors indicates a role for the NBPF genes and for ACCN1 in tumor aggressiveness. Additionally, DLD1 cells with inducible NBPF1 expression showed a marked decrease of clonal growth in a soft agar assay. The disruption of both NBPF1 and ACCN1 genes in this neuroblastoma patient indicates that these genes might suppress development of neuroblastoma and possibly other tumor types

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies