A biological question and a balanced (orthogonal) design: the ingredients to efficiently analyze two-color microarrays with Confirmatory Factor Analysis

Crijns, Anne; Gerbens, Frans; Plantinga, Auke; Meersma, Gert Jan; Jong, Steven de; Hofstra, Robert; Vries, Elisabeth G.E. de; Zee, Ate G.J. van der; Bock, Geertruida H. de; Meerman, Gerard J. te

doi:10.1186/1471-2164-7-232

Cited by 17 publications

(15 citation statements)

References 28 publications

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“…Briefly, median age was 60 years (range 21–84), 79.6% of patients had FIGO stage IIIC disease, and all patients were treated according to the Dutch guidelines and received cytoreductive surgery followed by platinum based chemotherapy. Tumour samples were microarray profiled on the Operon v3.0 probes two colour oligonucleotide microarrays [21] . The microarray data are accessible at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus ( http://www.ncbi.nlm.nih.gov/geo/ via series accession number GSE13876 ) and can also be downloaded from the Array express data set E-GEOD-13876 ( http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-13876/ ).…”

Section: Methodsmentioning

confidence: 99%

ATM, ATR and DNA-PKcs expressions correlate to adverse clinical outcomes in epithelial ovarian cancers

et al. 2014

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BackgroundAtaxia-telangiectasia mutated (ATM), ataxia-telangiectasia mutated and rad3 related (ATR) and DNA-dependent protein kinase catalytic sub-unit (DNA-PKcs) play critical roles in DNA damage response (DDR) by linking DNA damage sensing to DDR effectors that regulate cell cycle progression and DNA repair. Our objective was to evaluate if ATM, ATR and DNA-PKcs expressions could predict response to therapy and clinical outcome in epithelial ovarian cancers.MethodsWe investigated ATM, ATR, and DNA-PKcs expressions in ovarian epithelial cancers [protein expression (n = 194 patients), mRNA expression (n = 156 patients)] and correlated to clinicopathological outcomes as well as expression of X-ray repair cross-complementing protein 1 (XRCC1), cell division cycle-45 (CDC45), cyclin-dependent kinase 1(CDK1) and Ki-67 in tumours.ResultsHigh ATM protein expression was associated with serous cystadenocarcinomas (p = 0.021) and platinum resistance (p = 0.017). High DNA-PKcs protein expression was associated with serous cystadenocarcinomas (p = 0.006) and advanced stage tumours (p = 0.018). High ATM protein (p = 0.001), high ATM mRNA (p = 0.018), high DNA-PKcs protein (p = 0.002), high DNA-PKcs mRNA (p = 0.044) and high ATR protein (p = 0.001) expressions are correlated with poor ovarian cancer specific survival (OCSS). In multivariate Cox model, high DNA-PKcs (p = 0.006) and high ATR (p = 0.043) protein expressions remain independently associated with poor OCSS.ConclusionsATM, ATR and DNA-PKcs expressions may have prognostic and predictive significances in epithelial ovarian cancer.General significanceThe data presented here provides evidence that ATM, ATR and DNA-PKcs involved in DDR are not only promising biomarkers but are also rational targets for personalized therapy in ovarian cancer.

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Section: Methodsmentioning

confidence: 99%

ATM, ATR and DNA-PKcs expressions correlate to adverse clinical outcomes in epithelial ovarian cancers

et al. 2014

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“…After total RNA samples had been given DNAse treatment (Megascript T7 kit, Ambion, Huntingdon, UK), they were checked for residual DNA using a dinucleotide primer set (D11S875) specific for genomic DNA [ 12 ]. mRNA was linearly amplified by in vitro transcription using T7 RNA polymerase (Megascript T7 kit) [ 13 ]. Quality/integrity of total and amplified mRNA (cRNA) was checked by spectrophotometric analysis (criterion: UV 260/280 ratio > 1.8 for each sample), and/or agarose gel electrophoresis.…”

Section: Methodsmentioning

confidence: 99%

Survival-Related Profile, Pathways, and Transcription Factors in Ovarian Cancer

et al. 2009

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BackgroundOvarian cancer has a poor prognosis due to advanced stage at presentation and either intrinsic or acquired resistance to classic cytotoxic drugs such as platinum and taxoids. Recent large clinical trials with different combinations and sequences of classic cytotoxic drugs indicate that further significant improvement in prognosis by this type of drugs is not to be expected. Currently a large number of drugs, targeting dysregulated molecular pathways in cancer cells have been developed and are introduced in the clinic. A major challenge is to identify those patients who will benefit from drugs targeting these specific dysregulated pathways.The aims of our study were (1) to develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, (2) to assess the association of pathways and transcription factors with overall survival, and (3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers.Methods and FindingsAccording to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ∼35,000 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available dataset of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent dataset to assess the similarities with results from our own dataset. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 versus 41 mo, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that composed the overall survival profile were also able to discriminate between the two risk groups in the independent dataset. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival, of which 16 and 12, respectively, were confirmed in the independent dataset.ConclusionsOur study provides new clues to genes, pathways, and transcription factors that contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies.

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“…This constant pattern of expression is considered to be independent of the sample hybridized to the microarray and is not biological relevant for this study 3, 16. Samples with a factor loading with a first principal component of more than twice the standard deviation (SD) from the mean were excluded, as their hybridizations were considered to be of low quality 17. Intensities were standardized by subtracting the variance explained by the first principal component, as this is gene specific variation that does not contribute to differences between arrays.…”

Section: Methodsmentioning

confidence: 99%

Current smoking‐specific gene expression signature in normal bronchial epithelium is enhanced in squamous cell lung cancer

Boelens

Berg

Fehrmann

et al. 2009

The Journal of Pathology

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Cigarette smoking is the main risk factor for the development of squamous cell lung carcinoma (SCC). However, the smoking-related molecular changes in SCC have not been studied. Gene expression studies in both histologically normal bronchial epithelium and SCC epithelial samples identified genes differentially expressed between current and ex-smokers. Subsequently, expression levels of the smoking-related genes in normal bronchial epithelium were compared with those in SCC cells, since we hypothesized that the smoking-induced changes would be also deregulated in SCC. Gene expression profiles were generated using Agilent whole human genome microarrays on laser-microdissected normal bronchial epithelium and SCC samples. Expression levels of 246 genes, mainly related to oxidative stress response, were significantly different between normal bronchial epithelium of current and ex-smokers. Such a differential gene expression profile did not exist in SCC cells of smokers and ex-smokers. Interestingly, when comparing SCC and normal bronchial epithelium from ex-smokers, the vast majority of these 246 genes were also deregulated in SCC. When comparing SCC with normal epithelium from smokers, 22% of the up-regulated genes showed a similar high expression in SCC whereas 79% of the down-regulated genes were even further reduced in SCC as compared to current smokers. The down-regulated genes included several tumour suppressor genes, such as C9orf9, INHBB, LRIG1, SCGB3A1, SERPINI2, STEAP3 and ZMYND10. Thus, our study shows that the majority of genes up-regulated in normal bronchial epithelium of current smokers show similar high expression levels in SCC, while down-regulated genes are even further repressed in SCC. Our data indicate that smoking-related changes in normal bronchial epithelial cells persist in malignant transformed squamous cells.

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A biological question and a balanced (orthogonal) design: the ingredients to efficiently analyze two-color microarrays with Confirmatory Factor Analysis

Abstract: Background: Factor analysis (FA) has been widely applied in microarray studies as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis).

Cited by 17 publications

References 28 publications

ATM, ATR and DNA-PKcs expressions correlate to adverse clinical outcomes in epithelial ovarian cancers

ATM, ATR and DNA-PKcs expressions correlate to adverse clinical outcomes in epithelial ovarian cancers

Survival-Related Profile, Pathways, and Transcription Factors in Ovarian Cancer

Current smoking‐specific gene expression signature in normal bronchial epithelium is enhanced in squamous cell lung cancer

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