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accession-icon GSE41859
miRNA-mRNA networks in mouse testis during the 1st wave of spermatogenesis
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dramatic changes in 67 miRNAs during initiation of first wave of spermatogenesis in Mus musculus testis: global regulatory insights generated by miRNA-mRNA network analysis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE41858
Microarray profiling of total testicular transcriptome in mouse
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Gene expression during spermatogenesis is highly variable and this differential pattern is very important for the successive culmination of different stages of the process, leading to production of the male gamete. Taking the time window of first wave of spermatogenesis, we did a microarray profiling of total testicular transcriptome in mouse and found several significant patterns of variable gene expression, forming upregulated and downregulated clusters among the three stages analyzed here.

Publication Title

Dramatic changes in 67 miRNAs during initiation of first wave of spermatogenesis in Mus musculus testis: global regulatory insights generated by miRNA-mRNA network analysis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE13684
High-Resolution DNA Binding Specificity Analysis of Yeast Transcription Factors
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

We used microarrays to detail the global program of gene expression underlying rRNA processing gene regulation during heat shock. PBF1 is YBL054W (TOD6) and PBF2 is YER088C (DOT6).

Publication Title

High-resolution DNA-binding specificity analysis of yeast transcription factors.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP048701
Charaterization of genetic alterations and gene expression signatures found in BCR-ABL inhibitor-resistant KCL-22 subpopulations and single clones
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

KCL-22 is a chronic myeloid leukemia (CML) cell line derived from a patient in blast crisis phase and harbors the BCR-ABL translocation. The catalytic (ATP-competitive) BCR-ABL inhibitors imatinib and nilotinib have dramatically improved CML patient outcome, but the development of resistance remains a clinical challenge. The recent identification of allosteric BCR-ABL inhibitors, such as GNF-2, which target the enzyme by binding to the myristoyl pocket rather than catalytic site of ABL1, may provide a strategy to broadly overcome resistance to the class of ABL1 ATP competitive inhibitors. We therefore wanted to use the ClonTracer barcoding system to compare the clonal responses of KCL-22 to imatinib, nilotinib and GNF-2. RNA-seq was employed to characterize genetic alterations and gene expression signatures in the pooled cell populations resistant to BCR-ABL inhibitors as well as single clones showing differential response to the three inhibitors. Overall design: mRNA profiling of the subpopulations and single clones of human CML cell line KCL-22 that contribute to BCR-ABL inhibitor resistance

Publication Title

Studying clonal dynamics in response to cancer therapy using high-complexity barcoding.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP048700
Charaterization of genetic alterations and gene expression signatures found in erlotinib-resistant and erlotinib/crizotinib dual-resistant HCC827 subpopulations
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

The non-small cell lung cancer (NSCLC) cell line HCC827 harbors an activating EGFR mutation (exon 19 deletion) that confers sensitivity to the FDA-approved EGFR inhibitor erlotinib. By applying the ClonTracer barcoding system, we were able to show the presence of pre-existing sub-populations in HCC827 that contribute to erlotinib resistance. Prior studies implicated that MET amplification confers resistance to erlotinib in this cell line. Therefore we examined the effects of the c-Met inhibitor crizotinib on the barcoded HCC827 population when treated either sequentially or simultaneously with both inhibitors. Despite the significant reduction in barcode complexity, the erlotinib/crizotinib combination treatment failed to eradicate all of the resistant clones implying the presence of an erlotinib/crizotinib dual resistant subpopulation. We performed transcriptome profiling (RNA-seq) to elucidate the potential resistance mechanisms of the dual resistant subpopulation in comparison to vehicle-treated or single agent erlotinib-resistant HCC827 cell populations as controls. Overall design: mRNA profiling of the subpopulations of human NSCLC cell line HCC827 that contribute to EGFR inhibitor erlotinib and MET inhibitor crizotinib resistance

Publication Title

Studying clonal dynamics in response to cancer therapy using high-complexity barcoding.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP066956
Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Although mechanisms of acquired resistance of EGFR mutant non-small cell lung cancers to EGFR inhibitors have been identified, little is known about how resistant clones evolve during drug therapy. Here, we observe that acquired resistance caused by the T790M gatekeeper mutation can occur either by selection of pre-existing T790M clones or via genetic evolution of initially T790M-negative drug tolerant cells. The path to resistance impacts the biology of the resistant clone, as those that evolved from drug tolerant cells had a diminished apoptotic response to third generation EGFR inhibitors that target T790M EGFR; treatment with navitoclax, an inhibitor of BCL-XL and BCL-2 restored sensitivity. We corroborated these findings using cultures derived directly from EGFR inhibitor-resistant patient tumors. These findings provide evidence that clinically relevant drug resistant cancer cells can both pre-exist and evolve from drug tolerant cells, and point to therapeutic opportunities to prevent or overcome resistance in the clinic. Overall design: Examination of mRNA levels of PC9 parental, drug-tolerant, PC9-GR2 and PC9-GR3 cells after treatment with vehicle, gefitinib or WZ4002 for 24 hours.

Publication Title

Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE140179
Effect of SPINK1 and IL-6 knockdown in JHOC9 and JHOC5 ovarian clear cell carcinoma cells
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

Response of JHCO9 and JHOC5 cells to infection with NT (control) lentivirus or one of two knockdown lentiviruses, SPINK1 KD or IL-6 KD.

Publication Title

Targeting an autocrine IL-6-SPINK1 signaling axis to suppress metastatic spread in ovarian clear cell carcinoma.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE31244
Notch1 mediates cell fate decisions in the mouse uterus and is critical for complete decidualization
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Uterine receptivity implies a dialogue between the hormonally primed maternal endometrium and the free-floating blastocyst. Endometrial stromal cells proliferate, avert apoptosis, and undergo decidualization in preparation for implantation; however, the molecular mechanisms that underlie differentiation into the decidual phenotype remain largely undefined. The Notch family of transmembrane receptors transduce extracellular signals responsible for cell survival, cell-to-cell communication, and trans-differentiation, all fundamental processes for decidualization and pregnancy. Using a murine artificial decidualization model, pharmacological inhibition of Notch signaling by gamma-secretase inhibition resulted in significantly decreased deciduoma. Furthermore, a progesterone receptor (PR)-Cre Notch1 bigenic (Notch1d/d) confirmed a Notch1-dependant hypomorphic decidual phenotype.

Publication Title

Notch1 mediates uterine stromal differentiation and is critical for complete decidualization in the mouse.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE50931
MMP3 treatment of Panc-2 cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Response of pancreas cancer cells to treatment with recombinant MMP3

Publication Title

Tumor cell-derived MMP3 orchestrates Rac1b and tissue alterations that promote pancreatic adenocarcinoma.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE33377
Expression profiling of rheumatoid arthritis patients treated with anti-TNF
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Expression profiles of anti-TNF responders were compared to profiles of anti-TNF non-responders in order to identify an expression signature for anti-TNF response

Publication Title

Validation study of existing gene expression signatures for anti-TNF treatment in patients with rheumatoid arthritis.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment

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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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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