refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing 2 of 2 results
Sort by

Filters

Technology

Platform

accession-icon GSE102722
Organotypic three-dimensional cancer cell cultures mirror drug responses in vivo: Lessons learned from the inhibition of EGFR signaling
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Complex three-dimensional (3D) in vitro model systems that recapitulate human tumor biology are essential to better understand the pathophysiology of the disease and to aid in the discovery of novel anti-cancer therapies. 3D organotypic cultures exhibit intercellula communication, nutrient and oxygen gradients, and cell polarity that is lacking in traditional two-dimensional (2D) monolayer cultures. In the present study, we could demonstrate that 2D and 3D cancer models exhibit different drug sensitivities towards both targeted inhibitors of EGFR signaling and broad acting cytotoxic agents. Changes in the kinase activities of Erb family members and differential expression of apoptosis- and survival-associated genes before and after drug treatment may account for the differential drug sensitivities. Importantly, EGFR oncoprotein addiction was evident only in the 3D cultures mirroring the effect of EGFR inhibition in the clinic. Furthermore, targeted drug efficacy was strongly increased when incorporating cancer-associated fibroblasts into the 3D cultures. Taken together, we could provide conclusive evidence that complex 3D cultures are more predictive of the clinical outcome than their 2D counterparts. In the future, 3D cultures will be instrumental for understanding the mode of action of drugs, identifying genotype-drug response relationships and developing patient-specific and personalized cancer treatments.

Publication Title

Organotypic three-dimensional cancer cell cultures mirror drug responses <i>in vivo</i>: lessons learned from the inhibition of EGFR signaling.

Sample Metadata Fields

Cell line

View Samples
accession-icon SRP107345
Induced pluripotent stem cell-derived primitive macrophages as a cellular platform to model tissue-resident macrophage differentiation and function
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Specialized tissue macrophages arise during embryogenesis from yolk-sac (YS) progenitors that migrate into developing tissues and terminally differentiate in situ. Until recently, it has been impossible to isolate or derive sufficient numbers of YS-derived macrophages for further study, but data now suggest that induced pluripotent stem cells (iPSCs) can be driven to undergo a process reminiscent of YS-hematopoiesis in vitro. We asked whether iPSC-derived primitive macrophages (iMac) can terminally differentiate into specialized macrophages using growth factors and organ-specific cues. Co-culturing murine iMac with iPSC-derived neurons promoted differentiation into microglia-like cells in vitro. Furthermore, murine iMac differentiated in vivo into microglia following injection into the brain, and functional alveolar macrophages after engraftment in the lung. Overall design: 24 samples, 12 iMac/iMicro, 12 BM-Mac/BM-Micro. Macrophages were analysed at 4 time points (day 0, 3, 6, 12), with 3 independent replicates for each time point. Non-cocultured samples from the same batch (Day 0 iMac/BM-Mac) were used as controls for the experiment.

Publication Title

Induced-Pluripotent-Stem-Cell-Derived Primitive Macrophages Provide a Platform for Modeling Tissue-Resident Macrophage Differentiation and Function.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
Didn't see a related experiment?

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact