Abstract Small cell lung cancer (SCLC), is a highly aggressive and metastatic disease with a 5 year survival of 5%. SCLC represents 15-20% of all lung cancers and causes >160,000 deaths a year. The majority of patients present with metastatic disease and consequently resections are rare, while biopsies are small and only for diagnostic purposes thus hampering the study of SCLC. However, circulating tumour cells (CTCs) are highly prevalent in SCLC patients and may represent an avenue for the better understanding this disease. Our aim was to determine whether CTCs isolated from SCLC patients were able to form tumours in immunocompromised mice. This was accomplished by erythrocyte and leukocyte depletion and implantation of the remaining cells. Of the 6 initial patients whose CTCs were implanted, 4 gave rise to tumours in less than 5 months. Immuno-histochemical analysis of the tumours revealed them to be human in nature and express markers consistent with SCLC. Whole exome sequencing demonstrated that the tumours had mutations (e.g. TP53 and RB1) and CNV (e.g. loss of 3p and 13q) commonly observed in SCLC samples. Furthermore, single cell analysis of CTCs isolated from the corresponding patient revealed that genetic abnormalities detected in the tumour were also present in the patients CTCs. This confirmed that the tumours (termed CDX for CTC derived explant), were indeed derived from CTCs. In all 4 successful cases, analysis of parallel blood samples by CellSearch demonstrated that the patients had more than 400 CTCs/7.5 ml blood. Two of these patients were initially sensitive to platinum/etoposide therapy, while 2 were refractory. The doubling times of CDX derived from refractory and sensitive patients were 7.2 and 5.0 days compared to 14.2 and 13.4 days, consistent with refractory SCLC being more aggressive than sensitive SCLC. We have been able to successfully passage, freeze and resurrect all the CDX models and aim to report whether the patient response to therapy is mirrored in their CDX. These data demonstrate that SCLC CTCs are tumorigenic and we are investigating whether the CTC derived tumours represent a faithful model of the clinical disease. Citation Format: Christopher J. Morrow, Cassandra L. Hodgkinson, Yaoyong Li, Robert Metcalf, Dominic Rothwell, Francesca Trapani, Radoslaw Polanski, Debbie Burt, Kathryn Simpson, Karen Morris, Stuart Pepper, Daisuke Nonaka, Alastair Greystole, Paul Kelly, Matthew Krebs, Jenny Antonello, Mahmood Ayub, Suzanne Faulkner, Lynsey Priest, Louise Carter, Catriona Tate, Crispin J. Miller, Fiona Blackhall, Ged Brady, Caroline Dive. Circulating tumor cells from small cell lung cancer patients are tumorigenic. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3060. doi:10.1158/1538-7445.AM2014-3060

Although profiling of RNA in single cells has broadened our understanding of development, cancer biology and mechanisms of disease dissemination, it requires the development of reliable and flexible methods. Here we demonstrate that the EpiStem RNA-Amp™ methodology reproducibly generates microgram amounts of cDNA suitable for RNA-Seq, RT-qPCR arrays and Microarray analysis.

Circulating tumor cells from patients with small-cell lung cancer can form tumors in mice, and their derived explants recapitulate the patients' response to chemotherapy.

A hypoxia-associated gene signature (metagene) was previously derived via in vivo data-mining. In this study, we aimed to investigate whether this approach could identify novel hypoxia regulated genes. From an initial list of nine genes, three were selected for further study (BCAR1, IGF2BP2 and SLCO1B3). Ten cell lines were exposed to hypoxia and interrogated for the expression of the three genes. All three genes were hypoxia inducible in at least one of the 10 cell lines with SLCO1B3 induced in seven. SLCO1B3 was studied further using chromatin immunoprecipitation and luciferase assays to investigate hypoxia inducible factor (HIF) dependent transcription. Two functional HIF response elements were identified within intron 1 of the gene. The functional importance of SLCO1B3 was studied by gene knockdown experiments followed by cell growth assays, flow cytometry and Western blotting. SLCO1B3 knockdown reduced cell size and 3-dimensional spheroid volume, which was associated with decreased activation of the mammalian target of rapamycin (mTOR) pathway. Finally, Oncomine analysis revealed that head and neck and colorectal tumours had higher levels of SLCO1B3 compared to normal tissue. Thus, the knowledge based approach for deriving gene signatures can identify novel biologically relevant genes.

Refractory/relapsed diffuse large B-cell lymphoma (DLBCL) has a poor prognosis. Novel drugs targeting the constitutively activated NF-κB pathway characteristic of ABC-DLBCL are promising, but evaluation depends on accurate activated B cell-like (ABC)/germinal center B cell-like (GCB) molecular classification. This is traditionally performed on gene microarray expression profiles of fresh biopsies, which are not routinely collected, or by immunohistochemistry on formalin-fixed, paraffin-embedded (FFPE) tissue, which lacks reproducibility and classification accuracy. We explored the possibility of using routine archival FFPE tissue for gene microarray applications. We examined Affymetrix HG U133 Plus 2.0 gene expression profiles from paired archival FFPE and fresh-frozen tissues of 40 ABC/GCB-classified DLBCL cases to compare classification accuracy and test the potential for this approach to aid the discovery of therapeutic targets and disease classifiers in DLBCL. Unsupervised hierarchical clustering of unselected present probe sets distinguished ABC/GCB in FFPE with remarkable accuracy, and a Bayesian classifier correctly assigned 32 of 36 cases with >90% probability. Enrichment for NF-κB genes was appropriately seen in ABC-DLBCL FFPE tissues. The top discriminatory genes expressed in FFPE separated cases with high statistical significance and contained novel biology with potential therapeutic insights, warranting further investigation. These results support a growing understanding that archival FFPE tissues can be used in microarray experiments aimed at molecular classification, prognostic biomarker discovery, and molecular exploration of rare diseases.

Strand-specific RNA sequencing of S. pombe revealed a highly structured programme of ncRNA expression at over 600 loci. Waves of antisense transcription accompanied sexual differentiation. A substantial proportion of ncRNA arose from mechanisms previously considered to be largely artefactual, including improper 3' termination and bidirectional transcription. Constitutive induction of the entire spk1+, spo4+, dis1+ and spo6+ antisense transcripts from an integrated, ectopic, locus disrupted their respective meiotic functions. This ability of antisense transcripts to disrupt gene function when expressed in trans suggests that cis production at native loci during sexual differentiation may also control gene function. Consistently, insertion of a marker gene adjacent to the dis1+ antisense start site mimicked ectopic antisense expression in reducing the levels of this microtubule regulator and abolishing the microtubule-dependent 'horsetail' stage of meiosis. Antisense production had no impact at any of these loci when the RNA interference (RNAi) machinery was removed. Thus, far from being simply 'genome chatter', this extensive ncRNA landscape constitutes a fundamental component in the controls that drive the complex programme of sexual differentiation in S. pombe.

infant's lymphoma using 2 independent methods: FISH and microsatellite analysis.Procedures were carried out according to the Declaration of Helsinki and with the informed consent of the family.As a result, the infant's tumor cells were found to be of maternal origin (Figure 1A-B).Although HLA loss in the tumor tissue is one of the escape mechanisms for evading the immune surveillance system, tumor cells losing HLA-C antigens are recognized and removed by NK cells.Recently, Villalobos et al demonstrated that the uniparental disomy of the HLA-C locus as well as the loss of mismatched HLA-A and -B alleles were associated with leukemic relapse after HLA-haploidentical transplantation. 7 We could not precisely determine whether the tumor tissue lost noninherited maternal HLA alleles in the present study (supplemental Table 1).However, it was crucial that the maternal leukemic cells transmigrated into the paratesticular area, a sanctuary from the immuno-surveillance system, where they were engrafted and proliferated.

Background: RNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.0ST arrays. The use of Exon arrays makes it possible to assess the performance of RNA-Seq in two key areas: detection of expression at the granularity of individual exons, and discovery of transcription outside annotated loci.Results: We found a high degree of correspondence between the two platforms in terms of exon-level fold changes and detection. For example, over 80% of exons detected as expressed in RNA-Seq were also detected on the Exon array, and 91% of exons flagged as changing from Absent to Present on at least one platform had fold-changes in the same direction. The greatest detection correspondence was seen when the read count threshold at which to flag exons Absent in the SOLiD data was set to t < 1 suggesting that the background error rate is extremely low in RNA-Seq. We also found RNA-Seq more sensitive to detecting differentially expressed exons than the Exon array, reflecting the wider dynamic range achievable on the SOLiD platform. In addition, we find significant evidence of novel protein coding regions outside known exons, 93% of which map to Exon array probesets, and are able to infer the presence of thousands of novel transcripts through the detection of previously unreported exon-exon junctions.Conclusions: By focusing on exon-level expression, we present the most fine-grained comparison between RNA-Seq and microarrays to date. Overall, our study demonstrates that data from a SOLiD RNA-Seq experiment are sufficient to generate results comparable to those produced from Affymetrix Exon arrays, even using only a single replicate from each platform, and when presented with a large genome.

You have accessJournal of Urology1 Apr 2009GENETIC PROFILING OF THE STEM CELL ENRICHED PROSTATE SIDE POPULATION Benjamin R Grey, Jeremy E Oates, Claire A Hart, Yvonne Hey, Gill Newton, Sian Dibben, Stuart D Pepper, Michael D Brown, and Noel W Clarke Benjamin R GreyBenjamin R Grey More articles by this author , Jeremy E OatesJeremy E Oates More articles by this author , Claire A HartClaire A Hart More articles by this author , Yvonne HeyYvonne Hey More articles by this author , Gill NewtonGill Newton More articles by this author , Sian DibbenSian Dibben More articles by this author , Stuart D PepperStuart D Pepper More articles by this author , Michael D BrownMichael D Brown More articles by this author , and Noel W ClarkeNoel W Clarke More articles by this author View All Author Informationhttps://doi.org/10.1016/S0022-5347(09)60132-4AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "GENETIC PROFILING OF THE STEM CELL ENRICHED PROSTATE SIDE POPULATION." The Journal of Urology, 181(4S), pp. 42–43 © 2009 by American Urological AssociationFiguresReferencesRelatedDetails Volume 181 Issue 4S April 2009 Page: 42-43 Advertisement Copyright & Permissions© 2009 by American Urological AssociationMetrics Author Information Benjamin R Grey More articles by this author Jeremy E Oates More articles by this author Claire A Hart More articles by this author Yvonne Hey More articles by this author Gill Newton More articles by this author Sian Dibben More articles by this author Stuart D Pepper More articles by this author Michael D Brown More articles by this author Noel W Clarke More articles by this author Expand All Advertisement PDF downloadLoading ...

The last 10 years have seen microarrays go from being a nascent technology available only in a limited range of research facilities to becoming a ubiquitous approach to expression profiling. Developments in microarray technology have allowed the content of arrays to increase to the point that complete transcriptomes can be assayed on a single array, whilst developments in RNA labelling technology have reduced the amount of RNA needed down to the point where single cell profiling is technically possible. Recently it has also become possible to generate expression data from formalin-fixed paraffin-embedded archival samples. With the range of samples that can now be successfully profiled by microarray analysis this should be a good time to be running a microarray core facility. However, the arrival of Next Generation Sequencers means that for the first time there is an alternate platform that can potentially give a more complete picture of cellular expression than a microarray. Next Generation Sequencers are still in their infancy as a platform for expression profiling. Currently there are simply not enough Next Generation Sequencers in operation to meet the level of demand for expression profiling that microarray facilities service, but more systems are constantly becoming available. Looking ahead it seems certain that some proportion of expression profiling work will move from microarrays to Next Generation Sequencers, so now is a good time to consider some of the factors that might affect how significant that switch will be.

Microarray gene expression profiling of formalin-fixed paraffin-embedded (FFPE) tissues is a new and evolving technique. This report compares transcript detection rates on Affymetrix U133 Plus 2.0 and Human Exon 1.0 ST GeneChips across several RNA extraction and target labeling protocols, using routinely collected archival FFPE samples. All RNA extraction protocols tested (Ambion-Optimum, Ambion-RecoverAll, and Qiagen-RNeasy FFPE) provided extracts suitable for microarray hybridization. Compared with Affymetrix One-Cycle labeled extracts, NuGEN system protocols utilizing oligo(dT) and random hexamer primers, and cDNA target preparations instead of cRNA, achieved percent present rates up to 55% on Plus 2.0 arrays. Based on two paired-sample analyses, at 90% specificity this equalled an average 30 percentage-point increase (from 50% to 80%) in FFPE transcript sensitivity relative to fresh frozen tissues, which we have assumed to have 100% sensitivity and specificity. The high content of Exon arrays, with multiple probe sets per exon, improved FFPE sensitivity to 92% at 96% specificity, corresponding to an absolute increase of ~600 genes over Plus 2.0 arrays. While larger series are needed to confirm high correspondence between fresh-frozen and FFPE expression patterns, these data suggest that both Plus 2.0 and Exon arrays are suitable platforms for FFPE microarray expression analyses.

Exon arrays have demonstrated high concordance with standard gene expression arrays.1,2 We demonstrate that quantification of gene expression changes as measured by exon array analysis correlate closely with measurements of gene expression using Quantitative Real-Time PCR (qPCR) assays, for a panel of 39 genes (correlation coefficient 0.97). In a kinome siRNA screen for regulators of multi-drug sensitivity we have previously shown that CERT silencing promotes sensitivity to paclitaxel, doxorubicin, cisplatin and 5-FU.3,4 In order to detect genes or alternative splicing events that might influence drug sensitivity in a CERTspecific manner, we used the Affymetrix GeneChip Exon Array to detect gene expression changes following siRNA mediated CERT silencing. We compared data from the exon array platform with TaqMan Low Density Array (TLDA) qPCR data acquired from the HCT-116 cell line transfected with control or CERT siRNA treated with vehicle control, Paclitaxel, Ceramide or Tunicamycin. Graphical methods (P-P Plots and Q-Q Plots) were performed to assess the distribution of gene expression across the whole experiment (expressed as log2 fold ratios) as measured by exon array and TLDA. The distribution of the plots suggested a normal distribution for both groups of measurements (data not shown). Based on this distribution, we analysed the correlation between the gene expression assessed by the Affymetrix GeneChip Exon Array platform and gene expression measured by TLDA using the parametric Pearson’s Product Moment Correlation analysis. Relative gene expression data across the whole experiment measured by the exon array and TLDA platforms correlated well with a Pearson correlation coefficient of 0.96 (revised to 0.97 after exclusion of data for a gene with annotation error). Significance testing of the regression was performed with an ANOVA test, yielding a p value of less than 0.001. Linear regression was performed and a graph of gene expression levels across all conditions in the whole experiment as quantified by exon array compared to that quantified by TLDA was constructed (Fig. 1). The gradient was 0.76 and the intercept was 0.19. Our results indicate an excellent correlation between the two platforms, with some compression in measurement of the gene expression levels, as shown by the gradient, on the exon array platform as compared to the TLDA analysis. Gene expression changes <1.5 fold as determined by microarray profiling correlate poorly with qPCR assessments of gene expression.5,6 We initially obtained a correlation coefficient of 0.78 for fold changes <1.5. There appeared to be an outlier gene, MARVELD2. In our original analysis using the Affymetrix Netaffx software, transcript cluster ID3753372 was annotated as MARVELD2. To question this aberrant result in more detail, we determined that the ID375372 target sequence localises to an alternative locus, RFFL, confirmed on the most recent release of Netaffx v25. These data indicate that this outlier gene results from a gene annotation error and is not attributable to a splicing event or inaccuracy related to the exon array platform. Re-analysis of the exon array expression and TLDA data for fold changes <1.5 following omission of MARVELD2 revealed a correlation coefficient of 0.84. Reanalysing the data for all fold changes without MARVELD2 revealed a correlation coefficient of 0.97 with the gradient and intercept unchanged. In summary, gene expression levels as measured by the Affymetrix Exon Array platform demonstrate excellent concordance with results obtained by the TLDA qPCR system. We obtained a correlation coefficient of 0.97 for all points and a correlation coefficient of 0.84 for fold changes less than 1.5. Our results show a higher correlation coefficient of exon array gene expression datasets with qPCR TLDA quantification of gene expression even at lower fold changes compared to historical data from cell lines acquired from previous microarray platforms.5-8 We also asked whether the concordance of gene expression quantification could be improved by altering the quantification algorithm used in the analysis of the exon array data to provide gene level estimates. We used three approaches to provide gene level signal estimates, RMA, PLIER and iterPLIER. We found that whilst each of the three approaches all provided similar estimates of expressed genes equivalent to TLDA analysis, iterPLIER analysis appeared to provide estimates of gene expression levels with less compression or expansion effects, as determined by the gradient, (gradient closest to 1) when compared to TLDA analysis (Suppl. Fig. 1A–D). Reasons for the improved estimates of gene expression using the Affymetrix exon array analysis include the use of multiple probes per exon allowing data to be collected from the whole gene and not just the 3' end and the use of labelled cDNA in contrast to other microarray platforms which use labelled cRNA. Labelled cDNA produce less cross hybridisation compared to labelled cRNA and may account for the high performance of the exon array platforms.9 Our data indicates that whole genome exon array profiling platforms provide a quantitative genome wide assessment of gene expression changes that should be considered where samples are limited for qPCR validation purposes.

Correction to: British Journal of Cancer (2008) 98, 1403–1414. doi:10.1038/sj.bjc.6604316 During correction of this article, the affiliations of the authors were changed, therefore causing an error in the footnote attributing credit for the work involved in the paper. The correct affiliations are shown above and the corrected footnote should read ‘This work is attributed to institutions 1–3 and 5 above’.

Background: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses.Results: A series of validation datasets comparing breast cancer and normal breast cell lines (MCF7 and MCF10A) were generated to examine the variability between datasets generated using different amounts of starting RNA, alternative protocols, different generations of Affymetrix GeneChip or scanning hardware. We demonstrate that systematic, multiplicative biases are introduced at the RNA, hybridization and image-capture stages of a microarray experiment. Simple batch mean-centering was found to significantly reduce the level of inter-experimental variation, allowing raw transcript levels to be compared across datasets with confidence. By accounting for dataset-specific bias, we were able to assemble the largest gene expression dataset of primary breast tumours to-date (1107), from six previously published studies. Using this meta-dataset, we demonstrate that combining greater numbers of datasets or tumours leads to a greater overlap in differentially expressed genes and more accurate prognostic predictions. However, this is highly dependent upon the composition of the datasets and patient characteristics.Conclusion: Multiplicative, systematic biases are introduced at many stages of microarray experiments. When these are reconciled, raw data can be directly integrated from different gene expression datasets leading to new biological findings with increased statistical power.

Fanconi anemia (FA) is an inherited disease with congenital abnormalities and an extreme risk of acute myeloid leukemia (AML). Genetic events occurring during malignant transformation in FA and the biology of FA‐associated AML are poorly understood, but are often preceded by the development of chromosomal aberrations involving 3q26‐29 in bone marrow of FA patients. We report here the molecular cytogenetic characterization of FA‐derived AML cell lines SB1685CB and SB1690CB by conventional and array comparative genomic hybridization, fluorescence in situ hybridization, and SKY. We identified gains of a 3.7 MB chromosomal region on 3q26.2‐26.31, which preceded transformation to overt leukemia. This region harbors the oncogenic transcription factor EVI1. A third FA‐derived cell line, FA‐AML1, carried a translocation with ectopic localization of 3q26 including EVI1 . Rearrangements of 3q, which are rare in childhood AML, commonly result in overexpression of EVI1, which determines specific gene expression patterns and confers poor prognosis. We detected overexpression of EVI1 in all three FA‐derived AML. Our results suggest a link between the FA defect, chromosomal aberrations involving 3q and overexpression of EVI1 . We hypothesize that constitutional or acquired FA defects might be a common factor for the development of 3q abnormalities in AML. In addition, cryptic imbalances as detected here might account for overexpression of EVI1 in AML without overt 3q26 rearrangements. © 2007 Wiley‐Liss, Inc.

Fanconi anemia (FA) is an inherited disease with congenital abnormalities and an extreme risk of acute myeloid leukemia (AML). Genetic events occurring during malignant transformation in FA and the biology of FA-associated AML are poorly understood, but are often preceded by the development of chromosomal aberrations involving 3q26-29 in bone marrow of FA patients. We report here the molecular cytogenetic characterization of FA-derived AML cell lines SB1685CB and SB1690CB by conventional and array comparative genomic hybridization, fluorescence in situ hybridization, and SKY. We identified gains of a 3.7 MB chromosomal region on 3q26.2-26.31, which preceded transformation to overt leukemia. This region harbors the oncogenic transcription factor EVII. A third FA-derived cell line, EA-AMLI, carried a translocation with ectopic localization of 3q26 including EVII. Rearrangements of 3q, which are rare in childhood AML, commonly result in overexpression of EVII, which determines specific gene expression patterns and confers poor prognosis. We detected overexpression of EVII in all three FA-derived AML. Our results suggest a link between the FA defect, chromosomal aberrations involving 3q and overexpression of EVII. We hypothesize that constitutional or acquired FA defects might be a common factor for the development of 3q abnormalities in AML. In addition, cryptic imbalances as detected here might account for overexpression of EVII in AML without overt 3q26 rearrangements. (c) 2007 Wiley-Liss, Inc.