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accession-icon GSE52904
Impact of Gene Dosage on Gene Expression, Biological Processes and Survival in Cervical Cancer: a Genome-Wide Follow-Up Study
  • organism-icon Homo sapiens
  • sample-icon 66 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st), Affymetrix Mapping 250K Nsp SNP Array (mapping250knsp)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Impact of gene dosage on gene expression, biological processes and survival in cervical cancer: a genome-wide follow-up study.

Sample Metadata Fields

Age

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accession-icon GSE52903
Gene Dosage, Mainly 3q Amplification, Deregulates a Quarter of Genes in Cervical Cancer: It Induces Glycolysis, Anaphase-dependent Proteasome Proteolysis, and Low Survival
  • organism-icon Homo sapiens
  • sample-icon 66 Downloadable Samples
  • Technology Badge Icon Affymetrix Mapping 250K Nsp SNP Array (mapping250knsp), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The contribution of copy number (CN)-altered genes in cervical carcinogenesis is unknown owing to a lack of correlation with gene expression. We mapped CN-altered genes in 31 cervical cancers (CCs), and investigated the expression of 21,000 genes in 55 CCs using microarrays. Biological processes associated with genes deregulated by gene dosage and the relationship between gene dosage and patient survival were investigated. CN-altered genome (CN-AG) percentages varied widely among tumors from 0% to 32.2% (mean = 8.1 8.9). Tumors were classified as low (mean = 0.5 0.6, n = 11), medium (mean = 5.4 2.4, n = 10), or high (mean = 19.2 6.6, n = 10) CN. The highest %CN-AG was found in 3q, which contributed an average of 55% of all CN alterations. Genome-wide, only 5.3% of CN-altered genes were deregulated by gene dosage; by contrast, the rate in fully duplicated 3q was twice as high. Amplification of 3q explained 23.6% of deregulated genes in whole tumors (r2 = 0.236, p = 0.006; analysis of variance), including those in 3q and other chromosomes. A total of 862 genes were deregulated exclusively in high-CN tumors, but only 22.9% were CN altered. This result suggests that the remaining genes are not deregulated directly by gene dosage but by mechanisms induced in trans by CN-altered genes. Anaphase-promoting complex/cyclosome (APC/C)-dependent proteasome proteolysis, glycolysis, and apoptosis were upregulated, whereas cell adhesion and angiogenesis were downregulated exclusively in high-CN tumors. The high %CN-AG and upregulated gene expression profiles of APC/C-proteasome-dependent proteolysis and glycolysis were associated with poor patient survival, although only the first 2 correlations were statistically significant (p < 0.05, log-rank test). The data suggest that inhibitors of APC/C-dependent proteasome proteolysis and glycolysis may be useful treatments in these patients.

Publication Title

Impact of gene dosage on gene expression, biological processes and survival in cervical cancer: a genome-wide follow-up study.

Sample Metadata Fields

Age

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accession-icon GSE29570
The mtDNA Amerindian Haplogroup B2 enhances the risk for Cervical Cancer of HPV: de-regulation of mitochondrial genes may be involved.
  • organism-icon Homo sapiens
  • sample-icon 61 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Although Human papillomavirus infection is the main causal factor for cervical cancer (CC), there is data suggesting genetic factors could modulate the risk and progression of CC. Sibling studies suggest that maternally inherited factors could be involved in CC. To assess whether mitochondrial DNA (mtDNA) polymorphisms are associated to cervical cancer, HPV infection and HPV types, a case-control study was performed in the Mexican mestizo population. The polymorphism of mtDNA D-Loop was investigated in 187 cervical cancer patients and 270 healthy controls. D-loop was amplified from a blood DNA sample and analyzed by sequencing. HPV was detected and typed in cervical scrapes from both groups. mtDNA polymorphisms were compared in the whole samples and stratified by HPV types. The expression of 29 mitochondrial genes was analyzed in a subset of 45 tumor biopsies using the expression microarray ST1.0. The Amerindian haplogroup B2 increased the risk for CC (OR=1.6, 95% CI: 1.05-2.58) and showed an additive effect of 36% over the risk conferred by the HPV (OR=153, 95% CI: 65.4-357.5). The frequency of HPV 16, 18, 31 and 45 in cancer samples was similar in all haplogroups but one (D1). It showed a very low frequency of HPV16, any HPV18 and high frequency of HPVs 31, 45 and other types. Two mtDNA genes (MT-TD, MTTK) could be involved in the increased risk conferred by the haplogroup B2, since they were up-regulated exclusively in B2 tumors (p<0.05, t-test). These findings will contribute to clarify the importance of genetic factors in CC.

Publication Title

The Amerindian mtDNA haplogroup B2 enhances the risk of HPV for cervical cancer: de-regulation of mitochondrial genes may be involved.

Sample Metadata Fields

Specimen part

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accession-icon SRP061607
An ectopic network of transcription factors regulated by Hippo signaling drives growth and invasion of a malignant tumor model [larval wild type discs]
  • organism-icon Drosophila melanogaster
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Cancer cells have abnormal gene expression profiles, however, the transcription factors and the architecture of the regulatory network that drive cancer specific gene expression is often not known. Here we studied a model of Ras-driven invasive tumorigenesis in Drosophila epithelial tissues and combined in vivo genetics with high-throughput sequencing and computational modeling to decipher the regulatory logic of tumor cells. Surprisingly, we discovered that the bulk of the tumor specific gene expression is driven by an ectopic network of a few transcription factors that are overexpressed and/or hyperactivated in tumor cells. These factors are Stat, AP-1, the bHLH proteins Myc and AP-4, the nuclear hormone receptor Ftz-f1, the nuclear receptor coactivator Taiman/AIB1, and Mef2. Notably, many of these transcription factors are also hyperactivated in human tumors. Bioinformatics analysis predicted that these factors directly regulate the majority of the tumor specific gene expression, that they are interconnected by extensive cross-regulation, and that they show a high degree of co-regulation of target genes. Indeed, the factors of this network were required in multiple epithelia for tumor growth and invasiveness and knock-down of individual factors caused a reversion of the tumor specific expression profile, but had no observable effect on normal tissues. We further found that the Hippo pathway effector Yki/Sd was strongly activated in tumor cells and initiated cellular reprogramming by activating several transcription factors of this network. Thus, modeling regulatory networks identified an ectopic yet highly ordered network of master regulators that control tumor cell specific gene expression. Overall design: RNA-seq gene expression profiling across Drosophila 3rd instar larval wild type wing discs and genetic perturbations of wts.

Publication Title

An Ectopic Network of Transcription Factors Regulated by Hippo Signaling Drives Growth and Invasion of a Malignant Tumor Model.

Sample Metadata Fields

Subject, Time

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accession-icon GSE65216
Expression profiling of breast cancer samples from Institut Curie (Maire cohort)
  • organism-icon Homo sapiens
  • sample-icon 351 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptome analysis of Wnt3a-treated triple-negative breast cancer cells.

Sample Metadata Fields

Cell line

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accession-icon GSE65212
Expression profiling of breast cancer samples from Institut Curie (Maire cohort) -- BrainArray CDF
  • organism-icon Homo sapiens
  • sample-icon 176 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Transcriptome analysis of 130 breast cancer samples (41 TNBC; 30 Her2; 30 Luminal B and 29 Luminal A), 11 normal breast tissue samples and 14 TNBC cell lines.

Publication Title

Transcriptome analysis of Wnt3a-treated triple-negative breast cancer cells.

Sample Metadata Fields

Cell line

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accession-icon GSE65194
Expression profiling of breast cancer samples from Institut Curie (Maire cohort) --Affy CDF
  • organism-icon Homo sapiens
  • sample-icon 175 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Transcriptome analysis of 130 breast cancer samples (41 TNBC; 30 Her2; 30 Luminal B and 29 Luminal A), 11 normal breast tissue samples and 14 TNBC cell lines.

Publication Title

Transcriptome analysis of Wnt3a-treated triple-negative breast cancer cells.

Sample Metadata Fields

Cell line

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accession-icon GSE65238
Transcriptome analysis of Wnt3a-treated triple-negative breast cancer cell lines.
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

We analyzed the transcriptome of two different triple negative breast cancer (TNBC) cell lines to define a comprehensive list of Wnt target genes. Cells were treated with Wnt3a for 6h, 12h or 24h. We found up-regulated and down-regulated genes in response to Wnt3a treatment. They are involved in the Wnt pathway itself, and also in TGF, p53 and Hedgehog pathways. Thorough characterization of these novel potential Wnt target genes may reveal new regulators of the canonical Wnt pathway. The comparison of our list of Wnt target genes with those published in other cellular contexts confirms the notion that Wnt target genes are tissue-, cell line- and treatment-specific.

Publication Title

Transcriptome analysis of Wnt3a-treated triple-negative breast cancer cells.

Sample Metadata Fields

Cell line

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accession-icon SRP017407
The Aurora B kinase and the polycomb protein Ring1B combine to regulate active promoters in quiescent lymphocytes [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Expression profiling of resting B cells to classify active and silent genes based on expression levels Overall design: 4 biological replicates of mRNA extracted from freshly purified mouse CD43 negative resting B cells

Publication Title

The aurora B kinase and the polycomb protein ring1B combine to regulate active promoters in quiescent lymphocytes.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE46875
Association of maternal mRNA with the spindle in mouse oocytes
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The oocytes of many species, both invertebrate and vertebrate, contain a large collection of localized determinants in the form of proteins and translationally inactive maternal mRNAs. However, it is unknown whether mouse oocytes contain localized MmRNA determinants and what mechanisms might be responsible for their control. We collected intact MII oocytes, enucleated MII oocyte cytoplasts (with the spindle removed), and spindle-chromosome complexes which had been microsurgically removed. RNA was extracted, amplified, labeled, and applied to microarrays to determine if any MmRNA determinants were localized to the SCC.

Publication Title

Association of maternal mRNA and phosphorylated EIF4EBP1 variants with the spindle in mouse oocytes: localized translational control supporting female meiosis in mammals.

Sample Metadata Fields

Sex, Specimen part, Disease

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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