Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

ANALYSIS OF GENE EXPRESSION IN EARLY-STAGE OVARIAN CANCER (1)

ABSTRACT: Gene expression was analysed in 68 stage I ovarian cancers and 15 borderline samples using microarrays. Tumors were obtained directly at surgery and immediately frozen in liquid nitrogen until analysis. Glass arrays containing 16000 genes were used. Data was interpreted by unsupervised and supervised analysis. All tumors had a wild-type p53. Unsupervised analysis identified eight major clusters one of which was statistically associated to overall survival, grading and histotype (cluster C) and another with grading and histotype (cluster D). Supervised analysis showed a clear association between histotypes and gene expression profile and distinguished the four major histotypes (serous, clear cells, mucinous, endometrioid). The data also discriminated between the different grades of the tumors. The subset of 15 borderline tumors were undistinguishable from grade 1 tumors. When patients, relapsing or not, were analysed, a subset of genes able to differentiate them was identified. The genes identified in the major clusters belong to general classes of lipid biosynthesis, transport and metabolism, immunoglobulins (antigen presenting and processing) and genes acting as metal, ion and anion transporters including ATPase activity coupled with ion transport. Keywords: disease state analysis Gene expression for 83 ovarian tumor samples was evaluated: 68 from patiens presenting stage I carcinoma and 15 with borderline desease. A common reference design was applied and each samples was cohybridizated with a universal reference. Also a dye swap control has been done so that for the two technical replicates of each sample an expression profile of raw data was obtained. These data were independently processed and combiend to have a unique normalized profile for each sample.

ORGANISM(S): Homo sapiens

SUBMITTER: Pietro Mariani

PROVIDER: E-GEOD-8841 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Analysis of gene expression in early-stage ovarian cancer.

Marchini Sergio S Mariani Pietro P Chiorino Giovanna G Marrazzo Eleonora E Bonomi Riccardo R Fruscio Robert R Clivio Luca L Garbi Annalisa A Torri Valter V Cinquini Michela M Dell'Anna Tiziana T Apolone Giovanni G Broggini Massimo M D'Incalci Maurizio M

Clinical cancer research : an official journal of the American Association for Cancer Research 20081201 23

<h4>Purpose</h4>Gene expression profile was analyzed in 68 stage I and 15 borderline ovarian cancers to determine if different clinical features of stage I ovarian cancer such as histotype, grade, and survival are related to differential gene expression.<h4>Experimental design</h4>Tumors were obtained directly at surgery and immediately frozen in liquid nitrogen until analysis. Glass arrays containing 16,000 genes were used in a dual-color assay labeling protocol.<h4>Results</h4>Unsupervised ana ...[more]

PMID: 19047114

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Project description:[original title] Combined gene expression and genomic profiling define two intrinsic molecular subtypes of urothelial carcinoma and gene signatures for molecular grading and outcome. In the present investigation we sought to refine the classification of urothelial carcinoma by combining information on gene expression, genomic, and gene mutation levels. For these purposes we performed gene expression analysis of 144 carcinomas, and whole genome array-CGH analysis and mutation analyses of FGFR3, PIK3CA, KRAS, HRAS, NRAS, TP53, CDKN2A, and TSC1, in 103 of these cases. Hierarchical cluster analysis identified two intrinsic molecular subtypes, MS1 and MS2, which were validated and defined by the same set of genes in three independent bladder cancer data sets. The two subtypes differed with respect to gene expression and mutation profiles, as well as with the level of genomic instability. The data shows that genomic instability was the most distinguishing genomic feature of MS2 tumors, and that this trait was not dependent on TP53/MDM2 alterations. By combining molecular and pathological data it was possible to distinguish two molecular subtypes of Ta and T1 tumors, respectively. In addition, we define gene signatures validated in two independent data sets that classify urothelial carcinoma into low (G1/G2) and high grade (G3) tumors as well as non-muscle and muscle-invasive tumors with high precisions and sensitivities, suggesting molecular grading as a relevant complement to standard pathological grading. We also present a gene expression signature with independent prognostic impact on metastasis and disease specific survival. We conclude that the combination of molecular and histopathological classification systems may provide a strong improvement for bladder cancer classification and produce new insights into the development of this tumor type. 144 bladder cancer tumor samples and 12 normal samples were analyzed on 2-color cDNA or oligo microarrays using the Stratagene Universal Human Reference RNA as the common reference sample. 24 samples are hybridized to both the cDNA and oligo platform and these were used for merging of data from the two different gene expression platforms into a single expression matrix and for subsequent evaluation steps. The merged gene expression matrix used for analyses is supplied as a supplementary file (at the foot of this record). 103 of the samples were also analyzed on a BAC array containing ~32 000 BAC clones. Arrays were produced at the Swegene Centre for Integrative Biology at Lund University (SCIBLU).

Dataset Information

ANALYSIS OF GENE EXPRESSION IN EARLY-STAGE OVARIAN CANCER (1)

Publications

Analysis of gene expression in early-stage ovarian cancer.

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