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accession-icon GSE37645
The gamma secretase inhibitor MRK-003 attenuates pancreatic cancer growth in preclinical models
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pancreatic ductal adenocarcinoma (PDAC) is a nearly uniformly lethal malignancy, with most patients facing an adverse clinical outcome. Given the pivotal role of aberrant Notch signaling in the initiation and progression of PDAC, we investigated the effect of MRK-003, a potent and selective -secretase inhibitor, in preclinical PDAC models. We used a panel of human PDAC cell lines, as well as patient-derived PDAC xenografts, to determine whether pharmacological targeting of the Notch pathway could inhibit pancreatic tumor growth and potentiate gemcitabine sensitivity. In vitro, MRK-003 treatment downregulated the canonical Notch target gene Hes-1, significantly inhibited anchorage independent growth, and reduced the subset of CD44+CD24+ and aldehyde dehydrogenase (ALDH)+ cells that have been attributed with tumor initiating capacity. Ex vivo pretreatment of PDAC cells with MRK-003 in culture significantly inhibited the subsequent engraftment in immunocompromised mice. In vivo, MRK-003 monotherapy significantly blocked tumor growth in 5 of 9 (56%) patient-derived PDAC xenografts. Moreover, a combination of MRK-003 and gemcitabine showed enhanced antitumor effects compared to gemcitabine alone in 4 of 9 (44%) PDAC xenografts. Baseline gene expression analysis of the treated xenografts indicated that upregulation of nuclear factor kappa B (NFB) pathway components was associated with the sensitivity to single MRK-003, while upregulation in B-cell receptor (BCR) signaling and nuclear factor erythroid-derived 2-like 2 (NRF2) pathway correlated with response to the combination of MRK-003 with gemcitabine. The preclinical findings presented here provide further rationale for small molecule inhibition of Notch signaling as a therapeutic strategy in PDAC.

Publication Title

The gamma secretase inhibitor MRK-003 attenuates pancreatic cancer growth in preclinical models.

Sample Metadata Fields

Specimen part

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accession-icon GSE74903
Assessing concordance of drug-induced transcriptional response in rodent liver and cultured hepatocytes
  • organism-icon Rattus norvegicus
  • sample-icon 43 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived with would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), primary human hepatocytes (HPH) from TG, and mouse liver / HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA on a quantitative metric when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal low concordance for all methods. We investigate differences in the baseline state of cultured cells in the context of drug-induced perturbations in rat liver and highlight the striking similarity between toxicant-exposed cells in vivo and untreated cells in vitro.

Publication Title

Assessing Concordance of Drug-Induced Transcriptional Response in Rodent Liver and Cultured Hepatocytes.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE62254
Molecular analysis of gastric cancer identifies discrete subtypes associated with distinct clinical characteristics and survival outcomes: the ACRG (Asian Cancer Research Group) study [gastric tumors]
  • organism-icon Homo sapiens
  • sample-icon 294 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gastric cancer, a leading cause of cancer related deaths, is a heterogeneous disease, with little consensus on molecular subclasses and their clinical relevance. We describe four molecular subtypes linked with distinct patterns of molecular alterations, disease progression and prognosis viz. a) Microsatellite Instable: hypermutated intestinal subtype tumors occurring in antrum, best overall prognosis, lower frequency of recurrence (22%), with liver metastasis in 23% of recurred cases b) Mesenchymal-like: diffuse tumors with worst prognosis, a tendency to occur at an earlier age and highest recurrence (63%) with peritoneal seeding in 64% of recurred cases, low frequency of molecular alterations c) TP53-inactive with TP53 loss, presence of focal amplifications and chromosomal instability d) TP53-active marked by EBV infection and PIK3CA mutations. The key molecular mechanisms and associated survival patterns are validated in multiple independent cohorts, to provide a consistent and unified framework for further preclinical and clinical research.

Publication Title

Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE66229
Molecular analysis of gastric cancer identifies discrete subtypes associated with distinct clinical characteristics and survival outcomes: the ACRG (Asian Cancer Research Group) study
  • organism-icon Homo sapiens
  • sample-icon 294 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

No associated publication

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE13911
Expression data from primary gastric tumors (MSI and MSS) and adjacent normal samples
  • organism-icon Homo sapiens
  • sample-icon 66 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gastric cancers with mismatch repair (MMR) inactivation are characterised by microsatellite instability (MSI). In this study, the transcriptional profile of 38 gastric cancers with and without MSI was analysed.

Publication Title

Genome-wide expression profile of sporadic gastric cancers with microsatellite instability.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE11498
Identification of novel monosodium urate crystal-induced mRNAs
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Objective. To identify novel monosodium urate (MSU) crystal-induced mRNAs by transcript profiling of isolated murine air pouch membranes.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE18344
The Transcriptome of Nrf2-Deficient Mice in Cigarette Smoke-Induced Emphysematous Changes
  • organism-icon Mus musculus
  • sample-icon 110 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Cigarette smoke (CS) imposes a strong oxidative burden on exposed tissues resulting in a severely disturbed oxidant/antioxidant balance, which in the context of chronic exposure is assumed to be a key contributor to CS-related diseases. Because of its emerging central role in orchestrating the general cellular antioxidant response, the pathway leading to the activation of the transcription factor Nrf2 has received mounting attention over the past decade in investigations aimed at elucidating CS-induced patho-physiological mechanisms. To comprehensively characterize the impact of Nrf2 in acute and sub-chronic smoking scenarios, Nrf2 knock-out mice and their wildtype ICR littermates were exposed to either ambient air (sham exposure) or to one of three doses of CS for up to 5 months with two post-exposure endpoints of 1 and 13 days. The lungs of the mice were monitored for transcriptomic changes on a genome-wide level.

Publication Title

No associated publication

Sample Metadata Fields

Age, Specimen part, Treatment

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accession-icon GSE10841
SCLC cell line profiling on HG-U133A arrays set 2
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

RNA expression analysis was performed to compare patterns to sensitivity to BCL2 inhibitors (ABT-263).

Publication Title

ABT-263: a potent and orally bioavailable Bcl-2 family inhibitor.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE7097
SCLC cell line profiling on HG-U133A arrays
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

RNA expression analysis was performed to compare patterns to DNA copy number changes and sensitivity to BCL2 inhibitors.

Publication Title

Integrative genomic analysis of small-cell lung carcinoma reveals correlates of sensitivity to bcl-2 antagonists and uncovers novel chromosomal gains.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9166
Trovafloxacin-Induced Gene Expression Changes: Comparison of Primary Human Hepatocytes to HepG2 Cells
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Primary human hepatocytes (PHH) are a main instrument in drug metabolism research and in the prediction of drug-induced phase I/II enzyme induction in humans. The HepG2 liver-derived cell line is commonly used as a surrogate for human hepatocytes, but their use in ADME and toxicity studies can be limited because of lowered basal levels of metabolizing enzymes. Despite their widespread use, the transcriptome of HepG2 cells compared to PHH is not well characterized. In this study, microarray analysis was conducted to ascertain the differences and similarities in mRNA expression between HepG2 cells and human hepatocytes before and after exposure to a panel of fluoroquinolone compounds. Comparison of the nave HepG2 cell and PHH transcriptomes revealed a substantial number of basal gene expression differences. When HepG2 cells were dosed with a series of fluoroquinolones, trovafloxacin, which has been associated with human idiosyncratic hepatotoxicity, induced substantially more gene expression changes than the other quinolones, similar to previous observations with PHH. While TVX-treatment resulted in many gene expression differences between HepG2 cells and PHH, there were also a number of TVX-induced commonalities, including genes involved in RNA processing and mitochondrial function. Taken together, these results provide insight for interpretation of results from drug metabolism and toxicity studies conducted with HepG2 cells in lieu of PHH, and could provide further insight into the mechanistic evaluation of TVX-induced hepatotoxicity.

Publication Title

Trovafloxacin-induced gene expression changes in liver-derived in vitro systems: comparison of primary human hepatocytes to HepG2 cells.

Sample Metadata Fields

Sex, Specimen part

View Samples
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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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