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accession-icon GSE27567
Integrating Factor Analysis and a Transgenic Mouse Model to Reveal a Peripheral Blood Predictor of Breast Tumors
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 252 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE27562
Expression data from human PBMCs from breast cancer patients and controls
  • organism-icon Homo sapiens
  • sample-icon 162 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We analyzed gene expression in human peripheral blood mononuclear cells (PBMCs) from breast cancer patients, patients with benign breast abnormalities, healthy cancer-free individuals as well as patients with other types of cancer (gastrointestinal and brain cancers).

Publication Title

Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE27563
Expression data from murine PBCs from mice with advanced mammary tumors and their tumor-free counterparts.
  • organism-icon Mus musculus
  • sample-icon 90 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Female MMTV/c-MYC transgenic mice expressed the c-MYC proto-oncogene or a more stable point mutation variant (T58A) of the gene under the control of the hormone-responsive MMTV long terminal repeat (LTR) in an FVB/NJ background (Jackson Laboratories, Bar Harbor, ME). The hormones released during pregnancy and lactation have been shown to enhance expression of the oncogene. Thus, the mice were maintained in a continuous breeding program. Mice were monitored twice weekly for tumor development by palpation and tumors were measured twice weekly. Once the tumors reached 3cm3 the animals were sacrificed and tissue was obtained to confirm the tumors by histological analysis. As a control, female mice of the same age and background strain were maintained in the same facility and under the same breeding conditions as their transgenic counterparts.

Publication Title

Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE9496
An E2F1-Dependent Gene Expression Program That Determines the Balance Between Proliferation and Cell Death
  • organism-icon Rattus norvegicus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

E2F1 has been shown to induce both proliferation and apoptosis.

Publication Title

An E2F1-dependent gene expression program that determines the balance between proliferation and cell death.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE22406
Heterogeneity in MYC-Induced Mammary Tumors Determines Outcomes Following Loss of Myc Activity
  • organism-icon Mus musculus
  • sample-icon 75 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

We used microarrays to compare gene expression profiles between mouse mammary tumors initiated by Myc to those that have escaped Myc oncogene dependence.

Publication Title

Heterogeneity in MYC-induced mammary tumors contributes to escape from oncogene dependence.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE61272
Expression data of U2OS ER-HA-E2F1 cells induced by OHT with and without knockdown of NFYB
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

E2F1 induces numerous genes, including transcription factors, upon activation. The transcription factors then further cooperates with E2F1 to regulate the target genes and enhance the transcriptional effect.

Publication Title

E2F1-Mediated Induction of NFYB Attenuates Apoptosis via Joint Regulation of a Pro-Survival Transcriptional Program.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE11039
Expression Data from wild type and E2F4 null MEFs
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

We have used primary MEFs derived from wild type and E2F4 null mice growing asynchrounously in serum to generate a signature for E2F4 pathway activation. 10 wild type and 10 E2F4 null samples were each assayed using the Affymetrics Mouse Genome 430A 2.0 array.

Publication Title

Patterns of cell signaling pathway activation that characterize mammary development.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE39136
Expression data from U2OS ER-E2F1 cells after FOXO knockdown and E2F1 activation
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Effect of FOXO knockdown on E2F1-mediated transcription

Publication Title

FOXO transcription factors control E2F1 transcriptional specificity and apoptotic function.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE15904
Genetic Heterogeneity in Mouse Mammary Tumors
  • organism-icon Mus musculus
  • sample-icon 126 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Human cancers result from a complex series of genetic alterations resulting in heterogeneous disease states. Dissecting this heterogeneity is critical for understanding underlying mechanisms and providing opportunities for therapeutics matching the complexity. Mouse models of cancer have generally been employed to reduce this complexity and focus on the role of single genes. Nevertheless, our analysis of tumors arising in the MMTV-Myc model of mammary carcinogenesis reveals substantial heterogeneity, seen in both histological and expression phenotypes. One contribution to this heterogeneity is the substantial frequency of activating Ras mutations, the frequency of which can be changed by alterations in Myc. Additionally, we show that these Myc-induced mammary tumors exhibit even greater heterogeneity, revealed by distinct histological subtypes as well as distinct patterns of gene expression, than many other mouse models of tumorigenesis. Two of the major histological subtypes are characterized by differential patterns of cellular signaling pathways, including B-Catenin and Stat3 activities. We also demonstrate the predictive nature of this approach though examining metastatic potential. Together, these data reveal that a combination of histological and genomic analyses can uncover substantial heterogeneity in mammary tumor formation and therefore highlight aspects of tumor phenotype not evident in the population as a whole.

Publication Title

Genetic heterogeneity of Myc-induced mammary tumors reflecting diverse phenotypes including metastatic potential.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE24717
Using a Stem Cell-Based Signature to Guide Therapeutic Selection in Cancer
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients.

Publication Title

Using a stem cell-based signature to guide therapeutic selection in cancer.

Sample Metadata Fields

Specimen part, Cell line

View Samples
...

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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