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accession-icon GSE75325
Expression data transgenic mouse mammary tumors
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Immunosurveillance constitutes the first step of cancer immunoediting in which developing malignant lesions are eliminated by anti-tumorigenic immune cells. However, the mechanisms by which neoplastic cells induce an immunosuppressive state to evade the immune response are still unclear. The transcription factor Stat3 has been implicated in breast carcinogenesis and tumor immunosuppression in advanced disease, but its involvement in early disease development has not been established. Here, we genetically ablated Stat3 in the tumor epithelia of the inducible PyVmT mammary tumor model and found that Stat3-deficient mice recapitulated the three phases of immunoediting: elimination, equilibrium, and escape. Pathological analyses revealed that Stat3-deficient mice initially formed hyperplastic and early adenoma-like lesions that later completely regressed, thereby preventing the emergence of mammary tumors in the majority of animals. Furthermore, tumor regression was correlated with massive immune infiltration into the Stat3-deficient lesions, leading to their elimination. In a minority of animals, focal, non-metastatic Stat3-deficient mammary tumors escaped immunosurveillance after a long latency or equilibrium period. Taken together, our findings suggest that tumor epithelial expression of Stat3 plays a critical role in promoting an immunosuppressive tumor microenvironment during breast tumor initiation and progression, and prompt further investigation of Stat3 inhibitory strategies that may reactivate the immunosurveillance program.

Publication Title

STAT3 Establishes an Immunosuppressive Microenvironment during the Early Stages of Breast Carcinogenesis to Promote Tumor Growth and Metastasis.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP047171
Delineating Tumor-infiltrating Antigen Presenting Cell populations
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

The goal of this study is to compare tumor-infiltrating antigen presenting cell populations by global transcriptome profiling (RNA-seq) to help further delineate sub-populations of infiltrating myeloid cells in tumor. Methods: Four tumor antigen presenting cell populations were sorted from digested B78chOVA (melanoma variant) tumors in biological triplicate Results: RNA was extracted from the 4 groups (n=3 per group) and prepared for RNAseq. Sequencing yielded ~405 million reads with an average read depth of 33.7 million reads/sample. Reads were then aligned to the mouse genome (UCSC mm10) and those that mapped uniquely to known mRNAs were used to assess differential expression. Overall design: Examination of four tumor infiltrating myeliod populations

Publication Title

Dissecting the tumor myeloid compartment reveals rare activating antigen-presenting cells critical for T cell immunity.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP139944
Critical role for Lymphocytes in Producing FLT3LG in Tumors and Driving Checkpoint Therapy-Receptive Immune Microenvironments
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Intratumoral stimulatory dendritic cells (SDCs) play an important role in locally restimulating cytotoxic T cells and driving immune responses against cancer. However, the mechanisms that control SDC numbers remain poorly understood. In human melanoma, SDC numbers correlated with intratumoral expression of the gene encoding the cytokine FLT3LG, and we subsequently found in mouse and human tumors that this cytokine was predominantly produced by lymphocytes, notably including natural killer (NK) cells. NK cells stably formed conjugates with SDCs in the mouse tumor microenvironment (TME) and genetic and cellular ablation of NK cells in mice demonstrated their importance in regulation of SDC numbers through production of Flt3L. Although anti-PD-1 “checkpoint” immunotherapy for cancer largely targets T cells, we found that NK cells correlated with protective SDCs in human cancers, with patient responsiveness to anti-PD-1 immunotherapy, and with better overall survival. Our studies reveal that innate immune SDCs and NK cells cluster together as the best prognostic tool for T cell directed immunotherapy and that these innate cells are necessary for enhanced T cell tumor responses, suggesting this axis for novel therapies. Overall design: This dataset is n=11 biologically independent metastatic melanoma samples from patient tumors. There is no control dataset.

Publication Title

A natural killer-dendritic cell axis defines checkpoint therapy-responsive tumor microenvironments.

Sample Metadata Fields

Subject

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accession-icon SRP082988
RNAseq transcriptome analysis reveals developmental heterogeneity among mouse bone marrow monocyte subsets
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: In our study, we identified a heterogeneity among bone marrow (BM) Ly6Chi monocytes, which can be subdivided the expression of CXCR4. In order to understand the development of BM monocytes, the goal of this experiment is to compare the transcriptome of these 2 BM Ly6Chi monocyte subsets to those of the common monocyte progenitor (cMoP) and Ly6Clo monocytes. Overall design: 4 BM monocyte subsets (cMoP, Ly6ChiCXCR4hi, Ly6ChiCXCR4lo and Ly6Clo) from 3 different mice were sorted using a BD Aria III. Total RNA was extracted, converted to cDNA and run through deep sequencing using Illumina HiSeq 2500

Publication Title

CXCR4 identifies transitional bone marrow premonocytes that replenish the mature monocyte pool for peripheral responses.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject

View Samples
accession-icon GSE30268
Dynamic transcriptional events in embryonic stem cells mediated by the super elongation complex (SEC).
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dynamic transcriptional events in embryonic stem cells mediated by the super elongation complex (SEC).

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon SRP056899
Retinoids induce rapid dynamic changes in the non-coding RNAs and epigenetic profiles of murine Hox clusters.
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Physiologically relevant concentrations of retinoic acid are added to Mouse ES cells and a time course (0-72 hours) is examined with expression tiling arrays and RNA-seq to characterize the early dynamics of expression of coding and non-coding RNAs in and around the Hox clusters. Overall design: Gene expression is examined at various timepoints (0-72 hrs) after retinoic acid induced neuronal differentiation

Publication Title

Dynamic regulation of Nanog and stem cell-signaling pathways by Hoxa1 during early neuro-ectodermal differentiation of ES cells.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE30176
Retinoic acid (RA) induction time-course to profile gene expression during mES cell differentiation.
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Murine ES cell gene expression before RA induction are used to compare gene expression for time-points of 2, 4, 6hrs post-induction.

Publication Title

Dynamic transcriptional events in embryonic stem cells mediated by the super elongation complex (SEC).

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP007506
Determination of transcript abundance before and after serum induction in human HCT-116 colon cancer cell line.
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Transcriptional regulation of developmentally controlled genes is at the heart of differentiation and organogenesis. In this study, we have performed mRNA transcript abdundance analyses in human cells in response to serum activation signal by RNA-seq. Overall design: mRNA transcript abundance determined before and after serum activation signals using two biological replicates.

Publication Title

Dynamic transcriptional events in embryonic stem cells mediated by the super elongation complex (SEC).

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE34304
Poised RNA Polymerase II changes over developmental time and prepares genes for future expression
  • organism-icon Mus musculus, Drosophila melanogaster
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Poised RNA polymerase II changes over developmental time and prepares genes for future expression.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

View Samples
accession-icon GSE34279
Retinoic acid (RA) induction time-course to profile gene expression during mES cell differentiation
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Murine ES cell gene expression before RA induction are used to compare gene expression for time-points of 8, 12, 16, 24, 36, 48, 60 and 72 hours post-induction.

Publication Title

Poised RNA polymerase II changes over developmental time and prepares genes for future expression.

Sample Metadata Fields

Cell line, Treatment, Time

View Samples
...

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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