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accession-icon GSE22513
Markers of Taxane Sensitivity in Breast Cancer
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The purpose of this study was to identify molecular markers of pathologic response to neoadjuvant paclitaxel/radiation treatment, protein and gene expression profiling were done on pretreatment biopsies. Patients with high-risk, operable breast cancer were treated with three cycles of paclitaxel followed by concurrent paclitaxel/radiation. Tumor tissue from pretreatment biopsies was obtained from 19 of the 38 patients enrolled in the study. Protein and gene expression profiling were done on serial sections of the biopsies from patients that achieved a pathologic complete response (pCR) and compared to those with residual disease, non-pCR (NR). Proteomic and validation immunohistochemical analyses revealed that -defensins (DEFA) were overexpressed in tumors from patients with a pCR. Gene expression analysis revealed that MAP2, a microtubule-associated protein, had significantly higher levels of expression in patients achieving a pCR. Elevation of MAP2 in breast cancer cell lines led to increased paclitaxel sensitivity. Furthermore, expression of genes that are associated with the basal-like, triple-negative phenotype were enriched in tumors from patients with a pCR. Analysis of a larger panel of tumors from patients receiving presurgical taxane-based treatment showed that DEFA and MAP2 expression as well as histologic features of inflammation were all statistically associated with response to therapy at the time of surgery. We show the utility of molecular profiling of pretreatment biopsies to discover markers of response. Our results suggest the potential use of immune signaling molecules such as DEFA as well as MAP2, a microtubule-associated protein, as tumor markers that associate with response to neoadjuvant taxanebased therapy.

Publication Title

Identification of markers of taxane sensitivity using proteomic and genomic analyses of breast tumors from patients receiving neoadjuvant paclitaxel and radiation.

Sample Metadata Fields

Specimen part

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accession-icon GSE67225
Deciphering Cell-Specific Responses to Oncogenic Stress in the Liver
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Each cell type responds uniquely to stress and fractionally contributes to global and tissue-specific stress responses. Hepatocytes, liver macrophages (M), and sinusoidal endothelial cells (SEC) play functionally important and interdependent roles in adaptive processes such as wound healing, obesity, and tumor growth. Although these cell types demonstrate significant phenotypic and functional heterogeneity, their distinctions enabling disease-specific responses remain understudied. To address this, we developed a strategy for simultaneous isolation and quantification of these liver cell types based on antigenic cell surface marker expression in response to DEN and found that while there was only a marginal increase in hepatocyte number, M and SEC populations were quantitatively increased. Global gene expression profiling of hepatocytes, M and SEC identified characteristic gene fingerprints that define each cell type and their distinct physiological or oncogenic stress signatures. Integration of these cell-specific gene fingerprints with available hepatocellular carcinoma (HCC) patient microarray data demonstrates that the hepatocyte-specific response strongly correlates with the human HCC gene expression profile. Liver-specific M and SEC gene signatures demonstrate significant alterations in inflammatory and angiogenic gene regulatory pathways, which may impact the hepatocyte response to oncogenic stress. Further validation confirms alterations in components of two key pathways, AP-1 and p53, that have been previously associated with HCC onset and progression. Our data reveal unique gene expression patterns that serve as molecular fingerprints for the cell-centric responses to pathologic stimuli in the distinct microenvironment of the liver. The technical advance highlighted in this study provides an essential resource for assessing hepatic cell-specific contributions to oncogenic stress, information that could unveil previously unappreciated molecular mechanisms for the cellular crosstalk that underlies the development of hepatic cancer.

Publication Title

Deciphering hepatocellular responses to metabolic and oncogenic stress.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE8051
Gene expression in a resistance artery in 2 models of hypertension in the rat
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

We investigated morphometric structure and gene expression by microarray analysis in a small diameter artery, branch of the saphenous artery (a resistance artery), in representative models of renin-angiotensin system (RAS)-dependent and glucocorticoid hypertension, using the spontaneously hypertensive rat (SHR) and adrenocorticotropic hormone (ACTH)-induced hypertensive rat, respectively.

Publication Title

Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE63767
Expression analysis of wild-type and Tfam heterozygous knockout (Tfam+/-) murine embryonic fibroblasts (MEFs).
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The goal of this analysis was to utilize microarray profiling to identify basal alterations in gene expression in response to TFAM depletion and mtDNA stress.

Publication Title

Mitochondrial DNA stress primes the antiviral innate immune response.

Sample Metadata Fields

Specimen part

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accession-icon GSE29619
Systems biology of vaccination for seasonal influenza in humans
  • organism-icon Homo sapiens
  • sample-icon 273 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Human Genome U133A Array (hthgu133a), Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Systems biology of vaccination for seasonal influenza in humans.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE29618
FACS-sorted cells from Young Adults Vaccinated with Influenza TIV or LAIV Vaccines during 2008/09 Flu Season
  • organism-icon Homo sapiens
  • sample-icon 84 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Human Genome U133A Array (hthgu133a), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology.

Publication Title

Systems biology of vaccination for seasonal influenza in humans.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
accession-icon GSE29615
Time Course of Young Adults Vaccinated with Influenza LAIV Vaccine during 2008/09 Flu Season
  • organism-icon Homo sapiens
  • sample-icon 83 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology.

Publication Title

Systems biology of vaccination for seasonal influenza in humans.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
accession-icon GSE29617
Time Course of Young Adults Vaccinated with Influenza TIV Vaccine during 2008/09 Flu Season
  • organism-icon Homo sapiens
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology.

Publication Title

Systems biology of vaccination for seasonal influenza in humans.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
accession-icon GSE29614
Time Course of Young Adults Vaccinated with Influenza TIV Vaccine during 2007/08 Flu Season
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology.

Publication Title

Systems biology of vaccination for seasonal influenza in humans.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
accession-icon GSE94060
Human lung MPC
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A comparison of gene expression between control versus IPF human lung MPC using human Affy 1.0st chips.

Publication Title

Disruption of lineage specification in adult pulmonary mesenchymal progenitor cells promotes microvascular dysfunction.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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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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