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accession-icon GSE35947
Suppression and Activation of the Malignant Phenotype by Extracellular Matrix in Xenograft Models of Bladder Cancer: A Model for Tumor Cell Dormancy
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A major problem in cancer research is the lack of a tractable model for delayed metastasis. Herein we show that cancer cells suppressed by SISgel, a gel-forming normal ECM material derived from Small Intestine Submucosa (SIS), in flank xenografts show properties of suppression and re-activation that are very similar to normal delayed metastasis and suggest these suppressed cells can serve as a novel model for developing therapeutics to target micrometastases or suppressed cancer cells. Co-injection with SISgel suppressed the malignant phenotype of highly invasive J82 bladder cancer cells and highly metastatic JB-V bladder cancer cells in nude mouse flank xenografts. Cells could remain viable up to 120 days without forming tumors and appeared much more highly differentiated and less atypical than tumors from cells co-injected with Matrigel. In 40% of SISgel xenografts, growth resumed in the malignant phenotype after a period of suppression or dormancy for at least 30 days and was more likely with implantation of 3 million or more cells. Ordinary Type I collagen did not suppress malignant growth, and tumors developed about as well with collagen as with Matrigel. A clear signal in gene expression over different cell lines was not seen by transcriptome microarray analysis, but in contrast, Reverse Phase Protein Analysis of 250 proteins across 4 cell lines identified Integrin Linked Kinase (ILK) signaling that was functionally confirmed by an ILK inhibitor. We suggest that cancer cells suppressed on SISgel could serve as a model for dormancy and re-awakening to allow for the identification of therapeutic targets for treating micrometastases.

Publication Title

Suppression and activation of the malignant phenotype by extracellular matrix in xenograft models of bladder cancer: a model for tumor cell "dormancy".

Sample Metadata Fields

Cell line

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accession-icon GSE9630
Expression data from mouse liver
  • organism-icon Mus musculus
  • sample-icon 59 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Exposure to high levels of arsenic in drinking water is associated with several types of cancers including lung, bladder and skin, as well as vascular disease and diabetes. Drinking water standards are based primarily on epidemiology and extrapolation from higher dose experiments, rather than measurements of phenotypic changes associated with chronic exposure to levels of arsenic similar to the current standard of 10ppb, and little is known about the difference between arsenic in food as opposed to arsenic in water. Measurement of phenotypic changes at low doses may be confounded by the effect of laboratory diet, in part because of trace amounts of arsenic in standard laboratory chows, but also because of broad metabolic changes in response to the chow itself. Finally, this series contrasts 8hr, 1mg/kg injected arsenic with the various chronic exposures, and also contrasts the acute effects of arsenic, dexamethasone or their combination. Male C57BL/6 mice were fed on two commercially available laboratory diets (LRD-5001 and AIN-76A) were chronically exposed, through drinking water or food, to environmentally relevant concentrations of sodium arsenite, or acutely exposed to dexamethasone.

Publication Title

Laboratory diet profoundly alters gene expression and confounds genomic analysis in mouse liver and lung.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE11056
Expression data from mouse lung
  • organism-icon Mus musculus
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Exposure to high levels of arsenic in drinking water is associated with several types of cancers including lung, bladder and skin, as well as vascular disease and diabetes. Drinking water standards are based primarily on epidemiology and extrapolation from higher dose experiments, rather than measurements of phenotypic changes associated with chronic exposure to levels of arsenic similar to the current standard of 10ppb, and little is known about the difference between arsenic in food as opposed to arsenic in water. Measurement of phenotypic changes at low doses may be confounded by the effect of laboratory diet, in part because of trace amounts of arsenic in standard laboratory chows, but also because of broad metabolic changes in response to the chow itself. Finally, this series contrasts 8hr, 1mg/kg injected arsenic with the various chronic exposures, and also contrasts the acute effects of arsenic, dexamethasone or their combination. Male C57BL/6 mice were fed on two commercially available laboratory diets (LRD-5001 and AIN-76A) were chronically exposed, through drinking water or food, to environmentally relevant concentrations of sodium arsenite, or acutely exposed to dexamethasone.

Publication Title

Chronic exposure to arsenic in the drinking water alters the expression of immune response genes in mouse lung.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE15939
Transcript profiling in LTR mutants
  • organism-icon Arabidopsis thaliana
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

STN7-dependent phosphorylation of an as yet unknown thylakoid protein triggers the signaling events associated with the long-term acclimatory response (LTR). The LTR-associated signaling events regulate the expression of photosynthesis-related genes on the post-transcriptional level (nucleus), as indicated by transcript profiling in LTR mutants.

Publication Title

Arabidopsis STN7 kinase provides a link between short- and long-term photosynthetic acclimation.

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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