Unknown,Transcriptomics,Genomics,Proteomics

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IGR_BLADDER_GE_STUDY_JA

ABSTRACT: Background: Although histology is the corner stone for decision analysis in bladder cancer, it still needs refinement and new tools to better identify tumours with the highest risk of progression or recurrence. Objective: We designed a prospective study to evaluate whether microarray analysis could find a molecular signature for pathologic staging and/or grading. Design, setting and participants: Prospective multicentric study conducted from September 2007 to May 2008 (108 bladder tumours (45 pTa, 35 pT1 and 28> pT1)). Microarray analysis was performed with Agilent Technologies Human Whole Genome 4 x 44K oligonucleotide microarrays and used a method of dual color type versus a reference consists of a pool of tumours. From the lists of genes provided by the BrB Class Comparison analyses, we validated the microarray results of 38 selected differentially expressed genes by RT-QPCR in another bladder tumour cohort (n = 95). Results: The cluster M-^Ssuperficial vs invasive stageM-^T properly classified 92.9% of invasive stages and 66.3% of superficial stages. Among the superficial tumours, the cluster analysis showed that pT1b tumours were closer to invasive stages than pT1a tumours. We also found molecular differences between low and high-grade superficial tumours. However these differences were less caricatural than the one observed for staging.Conclusions: We confirm that the histopathological classification into subgroups pTa, pT1a and pT1b may have a translation in a M-^Smolecular signatureM-^T with a continuous progression of deregulation (overexpression or repression of these genes) from superficial (pTa) to more invasive (pT1a then b stage).

ORGANISM(S): Homo sapiens

DISEASE(S): Bladder tumour

SUBMITTER: Philippe DESSEN

PROVIDER: E-MTAB-993 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Microarray gene expression profiling and analysis of bladder cancer supports the sub-classification of T1 tumours into T1a and T1b stages.

Descotes Françoise F Dessen Philippe P Bringuier Pierre Paul PP Decaussin Myriam M Martin Pierre Marie PM Adams Marjorie M Villers Arnauld A Lechevallier Eric E Rebillard Xavier X Rodriguez-Lafrasse Claire C Devonec Marian M Paparel Philippe P Perrin Paul P Lazar Vladimir V Ruffion Alain A

BJU international 20131031 2

<h4>Objective</h4>To try and identify a molecular signature for pathological staging and/or grading. through microarray analysis.<h4>Patients and methods</h4>We performed a prospective multicentre study between September 2007 and May 2008 that included 108 bladder tumours (45 pTa, 35 pT1 and 28>pT1). Microarray analysis was performed using Agilent Technologies Human Whole Genome 4 × 44K oligonucleotide microarrays (Agilent, Santa Clara, CA, USA). A 'dual colour' method was used vs a reference po ...[more]

PMID: 24053469

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Project description:Genomic rearrangements leading to intragenic gene fusion are mainly found in some types of haematopoietic malignancies and sarcomas. Recently they have been described also in carcinomas such as the papillary thyroid histotype (60%-70%) and the Hürthle thyroid tumours (58%). The presence of junction oncogene constitutes an area of exciting research for emerging therapy as targeting the RET-PTC1 fusion oncogene by using small interfering RNA (siRNA) strategies since it is present only in the tumour cells and not in the surrounding normal cells. Therefore, we developed a siRNA against RET-PTC1 junction and assess its efficiency on the human papillary thyroid carcinoma cell line TPC-1 which spontaneously harbours the RET-PTC1 oncogene. The targeted genes are assessed by microarray analysis by comparing the regulated genes by the siRNA_RET-PTC1 vs a siRNA_RET developed on the RET part of the mRNA minus the siRNA_control that contain four mutation within the RET-PTC1 sequence. To test the targeted genes in the TPC-1 cell line that spontaneously harbours RET-PTC1 junction of two siRNAs developed: Within the RET-PTC1 junction, and in the mRNA RET part. A non-specific siRNA harbouring 4 mutations within the RET-PTC1 sequence was used as negative control (siRNA_control). By real-time PCR (Q-RT-PCR) we demonstrated that both siRNAs (siRNA_RET-PTC1 and siRNA_RET) significantly reduce RET mRNA levels of about 85 % in TPC-1 cells. The negative control did not show an effect of RET mRNA levels. Three independent transfections were performed on TPC-1 cells using 5 µl of Lipofectamine 2000 transfection reagent (Invitrogen, Cergy-Pontoise, France) and 50nM of i) siRNA_RET-PTC1 or ii) siRNA_RET or iii) siRNA_control that harbour 4 mutations within its sequence. Total RNAs of untreated cells and transfected cells were purified using the RNA cleanup and concentration kit (QIAGEN, Hilden, Germany) and gathered in 4 pools : 1) TPC-1 harbouring RET-PTC1 ; 2) TPC-1 silenced for RET-PTC1 with siRNA RET-PTC1 ; 3) TPC-1 silenced for siRNA RET ; 4) TPC-1 treated with the siRNA control.

Project description:Docetaxel is used as a standard treatment in patients with metastatic castration-resistant prostate cancer. However, a large subset of patients develops resistance by mechanisms that remain largely unknown. It is thus important to define the relevant pathways implicated in docetaxel-resistance and validate predictive biomarkers that will allow approaches of personalized treatment. In this aim, we established resistant IGR-CaP1 prostate cancer cell lines to different doses of docetaxel (IGR-CaP1-R cell lines) and investigated gene expression profiles by microarray analyses. We generated a signature of 112 genes potentially implicated in docetaxel-resistance whose expression is highly modified (Fold change M-bM-^IM-% 5). Among these genes, significant modification of expression was observed among cell cycle components in the resistant cells. Hence, we focused on the role of the cell cycle regulator LZTS1 located on chromosome 8p which was under-expressed in all our docetaxel-resistant models. LZTS1 extinction was confirmed at the RNA and protein levels. DNA methylation analysis revealed a stretch of 20 highly methylated CpGs in the region encompassing the exon 1 of LZTS1 promoter in the docetaxel-resistant cells suggesting the existence of an epigenetic regulation of LZTS1 expression in the resistant cells. By using siRNA strategy, we found evidence that LZTS1 plays an important role in the acquisition of the resistant phenotype. In addition, immunohistochemical staining showed that LZTS1 protein was absent or down-regulated in 33% of diagnostic biopsies obtained in patients with metastatic castration-resistant prostate cancer. This heterogeneous labeling suggests that LZTS1 might constitute a predictive biomarker of response to docetaxel chemotherapy. Furthermore, as Cdc25C is a LZTS1 partner in the mitosis regulation, we observed that targeting of Cdc25C with the pharmacological Cdc25C inhibitor NSC 663284 specifically killed the docetaxel-resistant cells. These results strongly suggest that Cdc25C plays a role in docetaxel resistance and that Cdc25C might be a therapeutic target to overcome docetaxel resistance. Altogether our findings identify an important role of LZTS1 in developing docetaxel resistance in prostate cancer through its role in regulating phosphatase Cdc25C. The set of gene expression with 4x44K Agilent ( design 014850) correspond to 6 doses of docetaxel 2?5 to 200 ug/ml) in dual color and dye-swap versus the IGR-Cap1 cell line without docetaxel.

Project description:Context : Non Functioning Pituitary Adenomas (NFPAs), although typically benign, may be locally invasive. Few datas are currently available related to the molecular process of invasion in sporadic pituitary adenomas. Markers of invasiveness, important for helping the clinician in the therapeutic strategy particularly in the decision for adjuvant radiotherapy, are currently lacking. Objective: Evaluate if invasive NFPAs display a specific expression profile compared with non invasive tumors. Methods: To address this issue, we selected 40 NFPAs (38 of the gonadotroph type) and classified them as invasive (n=22) or non invasive (n=18) on the basis of MRI and surgical findings. Then we performed pangenomic analysis based on Agilent Human Whole genome Gene Expression oligonucleotide microarray (44k) Expression in order to identify genes differentially expressed between invasive and non invasive NFPA. Experiements are made in dual color with tumor samples labelled in cyanine 5 and a pool of all tumors labelled in cyanine 3.The expressions of some genes identified by microarray screening were confirmed by real-time quantitative RT-PCR. The selection of genes was made on the basis of Ingenuity networks and degree of upregulation between invasive and non invasive tumors. Moreover, some genes of interest already described in the literature were added to the analysis. Results: Prediction class analysis showed that 346 genes discriminated between invasive and non invasive NFPAs (p<0.001); 233 were up- and 113 were down-regulated between the two groups. We then tested On the basis of Ingenuity networks and degree of upregulation between invasive and non invasive tumors, a set of eight genes, including MYO5A, IGFBP5, FLT3, NFE2L1, PTTG, MMP9, NCAM and NR1H3, was tested in quantitative PCR analysis and. Results confirmed those obtained in microarrays results.analysis. At the protein level, Myosin 5A (MYO5A) demonstrated stronger immunostaining in invasive NFPAs compared to non invasive NFPAs. Conclusions: We propose a molecular signature of eight genes of grossly invasive NFPAs as compared with non invasive tumors: The product of one of these genes, MYO5A, may be a useful marker of invasive process in tumoral specimens. The role of these genes in the invasiveness process and as prognostic markers of pituitary adenomas needs to be confirmedinvestigated. Method: Microarray analyses the transcriptome of 22 invasive Non Functional Pituitary Adenomas (NFPAs) and 18 non invasive NFPAs in dual color (each sample labelled in cyanine 5 and a pool of all tumors labelled in cyanine 3).

Project description:'Prostate cancer is the second cancer diagnosed among men worldwide. Beside approval of new therapies in the last five years, chemotherapeutic agents, docetaxel and cabazitaxel taxanes remain key treatments for metastatic castration resistant prostate cancers. However, primary and acquired resistance to taxanes still emerged in about half of patients. There is therefore an urgent need to discover and understand the taxane resistance mechanisms in order to identify new therapeutic targets. Indeed, targeted therapies that exploit the signaling pathways involved in prostate cancer are required to overcome chemoresistance and improve treatment outcomes. Molecular chaperones play a key role in the regulation of cellular homeostasis and the development of treatment resistance, and are promising therapeutic targets. Using high throughput siRNA functional screening based on a gene expression signature, we identified FKBP7, involved in acquired resistance to docetaxel and cabazitaxel. FKBP7 is a molecular chaperone that has not been studied in human so far. FKBP7 is overexpressed in prostate tumors and its expression is correlated with recurrence in patients who received docetaxel as neoadjuvant therapy. Moreover, FKBP7 is upregulated in taxane resistant prostate cancer cell lines and its expression sustains their growth in vitro and in a mice model of Docetaxel resistance. Using a high throughput proteomic approach, we identified the signaling pathway regulated by FKBP7 which is responsible for the survival of chemoresistant cells. Finally, we proposed a promising therapeutic strategy to overcome both docetaxel and cabazitaxel chemoresistance by targeting the downstream effector of FKBP7. Gene expression was profiled using a 4×44K Human Whole Genome (G4112F, id : 014850) expression array (Agilent Technologies, Santa Clara, Cal.) with a dual color dye-swap competitive hybridization procedure, according to the manufacturer''s instructions. Total RNA from untreated parental IGR-CaP1 cells was used as the RNA reference (NN1). Total RNA from IGR-CaP1 cells resistant to 5nM (NN2), 11.6nM (NN3), 25nM (NN4), 50nM (NN5), 100nM (NN6), and 200nM (NN7) of Docetaxel respectively, were used as samples. Two independent replicates of each samples (a and b) were used. Image analyses (quantification, normalization) were performed with Feature Extraction software (Agilent Technologies) and gene expression analysis was performed using Bioconductor.'

Dataset Information

IGR_BLADDER_GE_STUDY_JA

Publications

Microarray gene expression profiling and analysis of bladder cancer supports the sub-classification of T1 tumours into T1a and T1b stages.

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