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accession-icon GSE60998
Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE60994
Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways [set 1]
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely non-coding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent anti-viral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine anti-viral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of anti-viral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate cross-talk with BrCa cells by utilizing exosomes to instigate anti-viral signaling. This expands BrCa subpopulations adept at resisting therapy and re-initiating tumor growth.

Publication Title

Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE60995
Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways [set 2]
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely non-coding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent anti-viral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine anti-viral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of anti-viral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate cross-talk with BrCa cells by utilizing exosomes to instigate anti-viral signaling. This expands BrCa subpopulations adept at resisting therapy and re-initiating tumor growth.

Publication Title

Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP077574
Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The goal of this study is to investigate if interferon signaling regulates immune checkpoint blockade in mouse melanoma model. Overall design: Transcription profiling for B16, B16 after chronic interferon treatment, B16 derived checkpoint blockade resistant strain 499 and various knockout from 499, coupled with ATA-seq data.

Publication Title

Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade.

Sample Metadata Fields

Specimen part, Treatment, Subject

View Samples
accession-icon GSE65503
Radiation and Dual Checkpoint Blockade Activates Non-Redundant Mechanisms in Cancer
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Response to immune checkpoint inhibitors may be improved through combinations with each other and other therapies, raising questions about non-redundancy and resistance. We report results from parallel studies of melanoma patients and mice treated with anti-CTLA4 and radiation (RT). Although combined treatment improved responses, resistance was common. Computational analyses of immune and transcriptomic profiles (provided here) revealed that resistance in mice was due to upregulation of tumor PD-L1 that drives T cell exhaustion. Accordingly, optimal response requires RT, anti-CTLA4, and anti-PD-L1. Anti-CTLA4 inhibits Tregs, RT diversifies and shapes the TCR repertoire, and anti-PD-L1 reinvigorates exhausted T cells. Together, all three therapies promote the expansion of clonotypes with distinct TCR traits. Similar to mice, patients with melanoma showing high PD-L1 did not respond to RT + anti-CTLA4, demonstrated persistent T cell exhaustion, and rapidly progressed. Thus, the combination of RT, anti-CTLA4, and anti-PD-L1 promotes response through distinct mechanisms.

Publication Title

Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE83971
Expression data from hMSC-TERT4 cells during osteoblast differentiation
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Differentiation of human skeletal stem cells (hMSC) into osteoblasts is regulated by a few well described transcription factors. Our study used clustering and gene expression data to identify a novel transcription factor. ZNF25, which we showed is involved in osteoblast differentiation.

Publication Title

Transcription factor ZNF25 is associated with osteoblast differentiation of human skeletal stem cells.

Sample Metadata Fields

Cell line

View Samples
accession-icon SRP063620
Retroviral Replicating Vectors Deliver Cytosine Deaminase Leading to Targeted 5-FU-Mediated Cytotoxicity in Multiple Human Cancer Types
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Toca 511 is a modified Retroviral Replicating Vector based on Moloney g-retrovirus with an amphotropic envelope. As an investigational cancer treatment, Toca 511 preferentially infects cancer cells without direct cell lysis and encodes an enhanced yeast cytosine deaminase that converts the antifungal drug 5-fluorocytosine to the anticancer drug, 5-fluorouracil. A panel of established human cancers cell lines, derived from glioblastoma, colon, and breast cancer tissue was used to evaluate parameters critical for effective anticancer activity. As part of these analyses, we profiled relative mRNA levels across these cell lines via RNA sequencing. Overall design: mRNA expression profiles across nine human cancer cell lines.

Publication Title

Retroviral Replicating Vectors Deliver Cytosine Deaminase Leading to Targeted 5-Fluorouracil-Mediated Cytotoxicity in Multiple Human Cancer Types.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE38712
Gene expression in germinal center light zone and dark zone B cells
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identification of human germinal center light and dark zone cells and their relationship to human B-cell lymphomas.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE38697
Gene expression in human germinal center light zone and dark zone B cells
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarrays of gene expression in human germinal center light zone and dark zone B cells sorted according to the expression of cell surface molecules CD83 and CXCR4

Publication Title

Identification of human germinal center light and dark zone cells and their relationship to human B-cell lymphomas.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE38696
Gene expression in mouse germinal center light zone and dark zone B cells
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarrays of gene expression in mouse germinal center light zone and dark zone B cells sorted according to the expression of cell surface molecules CD83 and CXCR4

Publication Title

Identification of human germinal center light and dark zone cells and their relationship to human B-cell lymphomas.

Sample Metadata Fields

Specimen part

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)

fund-icon Fund the CCDL

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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