Project description:Using array comparative genomic hybridization (aCGH), a large number of deleted genomic regions have been identified in human cancers. However, subsequent efforts to identify target genes selected for inactivation in these regions have often been challenging. We integrated here genome-wide copy number data with gene expression data and non-sense mediated mRNA decay rates in breast cancer cell lines to prioritize gene candidates that are likely to be tumour suppressor genes inactivated by bi-allelic genetic events. The candidates were sequenced to identify potential mutations. This integrated genomic approach led to the identification of RIC8A at 11p15 as a putative candidate target gene for the genomic deletion in the ZR-75-1 breast cancer cell line. We identified a truncating mutation in this cell line, leading to loss of expression and rapid decay of the transcript. We screened 127 breast cancers for RIC8A mutations, but did not find any pathogenic mutations. No promoter hypermethylation in these tumours was detected either. However, analysis of gene expression data from breast tumours identified a small group of aggressive tumours that displayed low levels of RIC8A transcripts. Real-time PCR analysis of 38 breast tumours showed a strong association between low RIC8A expression and the presence of TP53 mutations (P=0.006). We demonstrate a data integration strategy leading to the identification of RIC8A as a gene undergoing a classical double-hit genetic inactivation in a breast cancer cell line, as well as in vivo evidence of loss of RIC8A expression in a subgroup of aggressive TP53 mutant breast cancers. Gene expression data: Samples GSM388181-GSM388198. The experiment utilized six breast cancer cell lines: MDA-MB-468, MDA-MB-231, ZR-75-1, MCF7, BT-474 and T-47D, and three non-malignant cell lines: HMECs (non-malignant human mammary epithelial cells), IMR90 (normal lung fibroblasts) and WS1 (normal skin fibroblasts). All cell lines were obtained from American Type Culture Collection and grown in accordance with the distributor's instructions. Both malignant and non-malignant cell lines were treated with the translation inhibitor emetine dihydrochloride hydrate. For each cell line, parallel cell cultures were grown in 175 cm2 flasks until 70-80 % confluence. Half of the subconfluent cultures were treated with 100 Î¼g ml-1 of emetine dihydrochloride hydrate while the other half were left as untreated controls. Genome-wide copy number data: Samples GSM388211-GSM388216. The experiment utilized six breast cancer cell lines; MDA-MB-468, MDA-MB-231, ZR-75-1, MCF7, BT-474 and T-47D. All cell lines were obtained from American Type Culture Collection and grown in accordance with the distributor's instructions. All samples were hybridized once on 44k Agilent Human Genome CGH microarrays according to manufacturers instructions. Genomic DNA pooled from healthy female donors was used as a reference in all hybridizations. DNA from cell line samples were labeled with Cy5 and DNA from reference were labeled with Cy3.

Project description:Mutations in BRCA1 and BRCA2 genes confer an increased lifetime risk for breast and ovarian cancer. Ovarian cancer risk can be decreased by risk-reducing salpingo-oophorectomy (RRSO). Studies on RRSO material have altered the paradigm of serous ovarian cancer pathogenesis. The purpose of this study was to identify candidate genes possibly involved in pathogenesis of serous ovarian cancer by carrying out a microarray analysis of differentially expressed genes in BRCA1/2- mutation positive ovarian and fallopian tube epithelium derived from RRSO surgery. Freshly frozen ovarian and fallopian tube samples from nine BRCA1/2 mutation carriers scheduled for RRSO were prospectively collected in comparison with five mutation-negative control patients undergoing salpingo-oophorectomy for benign indications. Microarray analysis of genome-wide gene expression was performed on ovarian and fallopian tube samples from BRCA1/2 and control patients. The validation of microarray data was performed by quantitative real-time polymerase chain reaction (qRT-PCR) in selected cases of RRSO samples, and also high grade serous carcinoma samples collected from patients with BRCA phenotype. From 22,733 genes, 454 transcripts were identified that were differentially expressed in BRCA1/2 mutation carriers when statistically compared to controls pooling all ovarian and fallopian tube samples together. Of these, 299 genes were statistically significantly downregulated and 155 genes were upregulated. Differentially expressed genes in BRCA1/2 samples reported here might be involved in serous ovarian carcinogenesis and provide interesting targets for further studies. Both fallopian tube and ovarian samples were collected from each BRCA1/2 mutation carrier resulting in eighteen mutation positive adnexal samples. Both fallopian tube and ovarian control samples were collected from one control patient while either ovarian or fallopian tube sample was available from four control patients, respectively, resulting in 6 adnexal control samples. High quality RNA was available from nine BRCA1/2-mutation positive ovarian and eight BRCA1/2-mutation positive fallopian tube samples and from three control ovarian and three control fallopian tube samples.

Project description:Background: Castration-resistant prostate cancer (CRPC) represents a therapeutic challenge for current medications. Methods: In order to explore the molecular mechanisms involved in CRPC progression and to identify new therapeutic targets, we analyzed a unique sample set of 11 castration-resistant prostate cancers and 7 advanced tumors by array-CGH and gene expression microarrays. The genome-wide DNA and RNA data were integrated to identify genes whose overexpression was driven by their amplification. To assess the functional role of these genes, their expression was analyzed in a transcriptional dataset of 329 clinical prostate cancers and the corresponding gene products were silenced using RNA interference in prostate cancer cells. Results: Six recurrent genetic targets were identified in the CRPCs; ATP1B1, AR, FAM110B, LAS1L, MYC and YIPF6. In addition to AR and MYC, FAM110B emerged as a potential key gene involved in CRPC progression in a subset of the tumors. FAM110B was able to regulate AR signaling in prostate cancer cells and FAM110B itself was regulated by androgens. FAM110B siRNA inhibited the growth of prostate cancer cells in vitro, and this effect was substantially enhanced in androgen deficient conditions. Ectopic FAM110B expression in non-cancerous epithelial prostate cells induced aneuploidy and impaired antigen presentation. Conclusions: The DNA / RNA gene outlier detection combined with siRNA cell proliferation assay identified FAM110B as a potential growth promoting key gene for CRPC. FAM110B appears to have a key role in the androgen signaling and progression of CRPC impacting multiple cancer hallmarks and therefore highlighting a potential therapeutic target. [1] Gene expression levels from 13 samples were measured using Affymetrix GeneChip Human Genome U133 plus 2.0 arrays. Sample processing and labeling were done according to the protocol provided by Affymetrix. Three micrograms of total RNA from each sample was used for the initial one-cycle cDNA synthesis. Arrays were scanned immediately after staining using a GeneChip scanner (Affymetrix). [2] aCGH was performed from 18 prostate cancer samples using 44K arrays by Agilent Technologies. Male genomic DNA (catalog number G1471, Promega, Madison, WI) was used as reference in all hybridizations. [3] Gene expression changes following FAM110B silencing in LNCaP prostate cancer cells (48 h: pooled FAM110B siRNA vs. Scrambled siRNA; 72 h: FAM110B siRNAs 1 - 4 and pooled siRNA vs. Scrambled siRNA) and ectopic FAM110B over-expression in both RWPE-1 and LNCaP cells (FAM110B-pEGFP vs. pEGFP, 48 h) were analyzed. The raw data for these Samples are available in the 'GSE28403_LNCaP_RWPE-1_Raw_Data.txt' file, which is linked to this record as a supplementary file.

Project description:Effluents from sewage treatment plants contain a mixture of micropollutants with the potential of harming aquatic organisms. Thus, addition of advanced treatment techniques to complement existing conventional methods has been proposed. Some of the advanced techniques could, however, potentially produce additional compounds affecting exposed organisms by unknown modes of action. In the present study the aim was to improve our understanding of how exposure to different sewage effluents affects fish. This was achieved by explorative microarray and quantitative PCR analyses of hepatic gene expression, as well as relative organ sizes of rainbow trout exposed to different sewage effluents (conventionally treated, granular activated carbon, ozonation (5 or 15 mg/L), 5 mg/L ozone plus a moving bed biofilm reactor, or UV-light treatment in combination with hydrogen peroxide). Exposure to the conventionally treated effluent caused a significant increase in liver and heart somatic indexes, an effect removed by all other treatments. Genes connected to xenobiotic metabolism, including cytochrome p450 1A, were differentially expressed in the fish exposed to the conventionally treated effluents, though only effluent treatment with granular activated carbon or ozone at 15 mg/L completely removed this response. The mRNA expression of heat shock protein 70 kDa was induced in all three groups exposed to ozone-treated effluents, suggesting some form of added stress in these fish. The induction of estrogen-responsive genes in the fish exposed to the conventionally treated effluent was effectively reduced by all investigated advanced treatment technologies, although the moving bed biofilm reactor was least efficient. Taken together, granular activated carbon showed the highest potential of reducing responses in fish induced by exposure to sewage effluents. The fish exposure was carried out in March 3-17, 2008 at Henriksdal STP (Stockholm, Sweden) using a large scale pilot plant with parallel treatment lines under ethic permits approved by the local animal committee in Gothenburg (permission no. 36-2007). A thorough description of the different treatment steps (both conventional and advanced) and the experimental setup during the exposure (Fig. 1) has been previously described elsewhere (Samuelsson et al., 2011). In brief, the raw influent underwent conventional activated sludge treatment to generate a reference effluent (Conventional Activated Sludge; CAS). This includes mechanical treatment (removal of large objects using grids with 3 mm column width); primary sedimentation; biological treatment (activated sludge aged 20 days); secondary sedimentation; sand filter. The additional advanced treatment processes were granular activated carbon (GAC), ozonation at 5 mg/L (OZ5) or 15 mg/L (OZ15), ozonation 5 mg/L followed by a moving bed biofilm reactor (MBBR) and irradiation by ultraviolet radiation (0.75 Wh/L) plus hydrogen peroxide (10 mg/L; UH). Two aquaria were used for positive controls. As the tap water available is not as well accepted by the fish, and to better reflect the organic content and overall chemistry of surface water, the control aquaria (TW1 and TW2, together TW) contained carbon-filtered tap water supplemented by 2% of conventionally treated reference effluent. We consider evaluation of implementation and running costs to be outside the scope of this paper. Juvenile rainbow trout (Oncorhynchus mykiss; 113M-BM-123 g; mean bodyweight M-BM-1 standard deviation) of both sexes were obtained from Antens Laxodling AB (AlingsM-CM-%s, Sweden). Rainbow trout is a commonly used species for this type of studies and our lab have ample experience using this species. Furthermore, rainbow trout of sufficient size for metabolomic studies (Samuelsson et al., 2011) can easily be obtained. Finally, the use of trout provides the opportunity for comparisons with other studies (e.g. Gunnarsson et al., 2009 and Albertsson et al., 2010). During an acclimatization period of four days on site, the fish were kept in tanks containing carbon-filtered tap water + 2% reference effluent. On the onset of the experiment, the fish were randomly distributed among eight 100 L aquaria (n=25/aquarium), supplied with treated effluent from the different parallel treatment lines. Aquaria duplicates were used for the controls. During both the acclimatization period as well as the 14 day exposure, the aquaria were aerated and the fish were not fed to reduce variability due to differences in food intake. It should be stressed that trout easily cope with food deprivations for several weeks (Kullgren et al., 2010). Measurements of temperature (13.5M-BM-10.5M-BM-0C), oxygen saturation (97M-BM-13%), pH (7.4M-BM-10.3), conductivity and flow rate were monitored 5 d per week throughout the exposure. In addition, to evaluate differences in removal efficiency between the treatments, total organic carbon (TOC), 7-day biochemical oxygen demand (BOD7), suspended solids (SS), total nitrogen (Tot-N) and total phosphorus (Tot-P) were measured in all effluents (Samuelsson et al., 2011). The sampling took place during two consecutive days (day 14 and 15) due to the large number of fish. For each day, an equal number of fish from each treatment was sampled in random order and killed by a blow to the head. The fish were weighed, their fork length was measured and their sex was determined by macroscopical observation of their gonads. Liver samples were collected for several different studies (hence sample size limitations), frozen on dry ice and stored at -70M-BM-0C until analysis. Homogenization of the frozen liver tissue was carried out using Tissuelyser (Qiagen, Hilden, Germany) and hepatic total RNA was extracted and purified using QIAcube and RNeasyM-BM-. Plus Mini Kit (Qiagen). The RNA quantity and quality were assessed by spectrophotometric measurements with the Nanodrop 1000 (NanoDrop Technologies, Wilmington, DE). To ensure that no degradation had occurred, the isolated RNA was analyzed using Experion automated electrophoresis (Bio-Rad, Hercules, CA). A 15k rainbow trout gene expression microarray was designed for the RT analyzer platform (febit, Heidelberg, Germany) by using The Institute for Genomic Research (TIGR) Rainbow Trout Gene Index (RTGI) database version 7.0 (http://compbio.dfci.harvard.edu/tgi/). Details on the probe design strategy, but for eelpout (Zoarces viviparus), and transcript selection strategy are described elsewhere (Kristiansson et al., 2009; Cuklev et al., 2011). However, in the present study, singletons and non-annotated expressed sequence tags (ESTs) were replaced by newly well-annotated ESTs in rainbow trout. When available, transcripts at GenBank (http://www.ncbi.nlm.nih.gov/nucleotide) were used. In our lab, results from similar microarrays using the same platform have shown good correlation with quantitative polymerase chain reaction (qPCR) data (Gunnarsson et al., 2009b; Kristiansson et al., 2009; Cuklev et al., 2011; Lennquist et al., 2011). To reduce variation in estrogen-responsive genes, only males were used for the subsequent gene expression analyses. Biotinylated antisense RNA (aRNA) was synthesized using MessageAmpM-bM-^DM-" II-Biotin Enhanced Single Round aRNA Amplification Kit (AmbionM-BM-.). The aRNA samples (20 M-BM-5g) were vacuum dried in a vacuum centrifuge, dissolved in 10 M-BM-5l water and fragmented according to the manufacturerM-bM-^@M-^Ys protocol. The following steps described in this subchapter were all performed by febit. Oligonucleotide arrays were synthesized by photo-controlled in situ synthesis using the Geniom One system (febit). Each biochip consists of eight individually accessible micro channels, each of which is referred to as a microarray in this manuscript. Eight individual samples from each aquarium were included in the analysis. In total, 64 microarrays were analyzed. A customized protocol, described in detail elsewhere (Cuklev et al., 2011), was used for prehybridization and hybridization. All samples were randomly placed on the biochips, with one sample from each exposure on each biochip. Signals were detected using the internal CCD-camera system of the RT analyzer instrument (febit) and quantified using the Geniom Wizard software. Integration times were between 156 and 570 ms, determined automatically by the instrument software. All microarray data processing and statistical calculations were performed in R-2.12.2 (www.r-project.org; R Development Core Team, 2010). The quality of pre- and post normalized arrays was verified with box- and MA plots. The data analysis was performed in the R-package LIMMA (Smyth, 2005). Data were normalized using the M-bM-^@M-^XquantileM-bM-^@M-^Y method. Moderated t-statistics and adjusted p-values of differential expression were calculated using the empirical Bayes model.

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