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accession-icon GSE50039
mRNA microarray analysis on HepG2 cells exposed to Grpahene oxide (GO) and reduced graphene oxide (rGO) Nanomaterials
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

In order to evaluate the identification of genes and pathways, the global gene expression profiles were assessed in response to GO and rGO on Human hepatoma (HepG2) cells. We performed whole genome DNA microarray experiments using HepG2 cells exposed to GO and rGO for 24h.

Publication Title

A systems toxicology approach to the surface functionality control of graphene-cell interactions.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE25585
Circadian transcriptional profiling of peritoneal macrophages
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

In the immune system various parameters and immune functions are controlled by the circadian system. To investigate molecular mechanisms that link the circadian clock and the immune system we analyzed the transcriptom of peritoneal macrophages from mice collected in a time course for two consecutive days. We found that more than 8% of expressed genes are under circadian control including many important regulators in pathogen recognition, signal transduction and cytokine secretion.

Publication Title

A circadian clock in macrophages controls inflammatory immune responses.

Sample Metadata Fields

Sex, Specimen part, Time

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accession-icon GSE135068
Elucidation of Ras homologous A: Systematic approach to identify potential signaling in gastric cancer
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Previously, we identified Ras homologous A (RHOA) as a major signalling hub in gastric cancer (GC), the third-most common cause of cancer death in the world, prompting us to rationally design an efficacious inhibitor of this oncogenic GTPase. Here, based on that previous work, we extend those computational analyses, and in silico modeling approaches, to further pharmacologically optimize anti-RHOA hydrazide derivatives for greater anti-GC potency. Two of these, JK-136 and JK-139, potently inhibited cell viability and migration/invasion of GC cell lines, and mouse xenografts, diversely expressing RHOA. Moreover, JK-136’s binding affinity for RHOA was >140-fold greater than Rhosin, a nonclinical RHOA inhibitor. Network analysis of JK-136/139-associated transcriptomes showed different functional contexts, compared to those following treatment with Rhosin. We strongly assert that identifying and targeting oncogenic signalling hubs, such as RHOA, represents an emerging strategy for the design, characterization, and translation of new antineoplastics, against gastric and other cancers.

Publication Title

Rational design of small molecule RHOA inhibitors for gastric cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE150965
Gene expression data of stromal cell subpopulations isolated from human lymph nodes (LNs) infiltrated with melanoma
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Clariom S Human array (clariomshuman)

Description

Metastasis of human tumours to LNs is a universally negative prognostic factor. LN stromal cells (SCs) play a crucial role in enabling T cell responses, and since tumour metastases modulate their structure and function, this interaction may suppress immune responses to tumour antigens. However the SC subpopulations that respond to infiltration of malignant cells into human LNs have not been defined. Using microarray, we sought to assess gene expression profiles of two distinct SC subpopulations isolated from melanoma-infiltrated LNs.

Publication Title

Distinctive Subpopulations of Stromal Cells Are Present in Human Lymph Nodes Infiltrated with Melanoma.

Sample Metadata Fields

Specimen part

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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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