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accession-icon GSE9914
Expression data from early symptomatic Sca1154Q/2Q and Sca7266Q/5Q knock-in cerebellum
  • organism-icon Mus musculus
  • sample-icon 22 Downloadable Samples
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Description

Comparative analysis of cerebellar gene expression changes occurring in Sca1154Q/2Q and Sca7266Q/5Q knock-in mice

Publication Title

The insulin-like growth factor pathway is altered in spinocerebellar ataxia type 1 and type 7.

Sample Metadata Fields

Sex, Age

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accession-icon GSE15181
Expression profiles of cancer cells with anchorage-independent growth ability
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 56 Downloadable Samples
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Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Anchorage-independent cell growth signature identifies tumors with metastatic potential.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE15161
Expression data from retroviral vector-infected immortalized mouse embryonic fibroblasts (MEFs)
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
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Description

Cultured cancer cells exhibit substantial phenotypic heterogeneity when measured in a variety of ways such as sensitivity to drugs or the capacity to grow under various conditions. Among these, the ability to exhibit anchorage-independent cell growth (colony forming capacity in semisolid media) has been considered to be fundamental in cancer biology because it has been connected with tumor cell aggressiveness in vivo such as tumorigenic and metastatic potentials, and also utilized as a marker for in vitro transformation. Although multiple genetic factors for anchorage-independence have been identified, the molecular basis for this capacity is still largely unknown. To investigate the molecular mechanisms underlying anchorage-independent cell growth, we have used genome-wide DNA microarray studies to develop an expression signature associated with this phenotype. Using this signature, we identify a program of activated mitochondrial biogenesis associated with the phenotype of anchorage-independent growth and importantly, we demonstrate that this phenotype predicts potential for metastasis in primary breast and lung tumors.

Publication Title

Anchorage-independent cell growth signature identifies tumors with metastatic potential.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16522
Effector cells derived from nave or central memory pmel-1 CD8+ T cells
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
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Description

Effector cells for adoptive immunotherapy can be generated by in vitro stimulation of nave or memory subsets of CD8+ T cells. While the characteristics of CD8+ T cell subsets are well defined, the heritable influence of those populations on their effector cell progeny is not well understood. We studied effector cells generated from nave or central memory CD8+ T cells and found that they retained distinct gene expression signatures and developmental programs. Effector cells derived from central memory cells tended to retain their CD62L+ phenotype, but also to acquire KLRG1, an indicator of cellular senescence. In contrast, the effector cell progeny of nave cells displayed reduced terminal differentiation, and, following infusion, they displayed greater expansion, cytokine production, and tumor destruction. These data indicate that effector cells retain a gene expression imprint conferred by their nave or central memory progenitors, and they suggest a strategy for enhancing cancer immunotherapy.

Publication Title

Adoptively transferred effector cells derived from naive rather than central memory CD8+ T cells mediate superior antitumor immunity.

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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Developed by the Childhood Cancer Data Lab

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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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