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accession-icon GSE40168
Expression profile of MCF7, CCD18 and Ramos human cell lines
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To uncover the chromosome 16 associated proteome and to take advantage of the generated knowledge to make progress in human biology in health and disease, a consortium of 15 groups was organized in four working groups: SRM and protein sequencing, antibody and peptide standard, clinical healthcare and biobanking and bioinformatics. According to a preliminary in silico study integrating knowledge from Ensembl, UniProt and GPM, Ramos B lymphocyte cells, MCF-7 epitelial cells and CCD18 fibroblast were selected as it is theoretically expected that any chromosome 16 protein coding gene is expressed in at least one of them. To define in detail the transcriptome of the above mentioned cell lines Affymetrix microarray based analyses were performed. Upon hybridization in Human ST 1.0 arrays, raw data were processed with RMA algorithm for background correction and normalization. Chromosome 16 gene expression pattern was then defined in each cell line and comparative analysis was done with R package statistics. Biological functions involving chromosome 16 genes were analysed with GO and functional networks were studied with Ingenuity Pathway Analysis. Expressed genes were compared with data from shotgun proteomic experiments to find the degree of correlation mRNA-protein. Expression of genes coding for proteins with weak or none MS evidence is shown. The integration of this information in decision-making process of the mass spectrometry group is discussed.

Publication Title

Spanish human proteome project: dissection of chromosome 16.

Sample Metadata Fields

Cell line

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accession-icon GSE51824
Reversible and irreversible differentiation of cardiac fibroblasts
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 2.0 ST Array (ragene20st)

Description

Aim: Differentiation of cardiac fibroblasts (Fb) into myofibroblasts (MyoFb) is responsible for connective tissue buildup in myocardial remodeling. We examined reversibility of MyoFb differentiation. Methods and Results: Adult rat cardiac Fb were cultured on a plastic substratum providing mechanical stress, with conditions to obtain different Fb phenotypes. Fb spontaneously differentiated to proliferating MyoFb (p-MyoFb) with stress fiber formation decorated with alpha-smooth muscle actin (-SMA). Transforming growth factor-1 (TGF-1) promoted terminal differentiation into -SMA positive MyoFb showing near absence of proliferation i.e. non-p-MyoFb (2-fold increase in cell number after 12 days vs 11-fold for p-MyoFb). SD-208, a TGF--receptor-I kinase blocker, inhibited p-MyoFb differentiation as shown by stress fiber absence, low levels of -SMA protein expression, and high levels of proliferation (32-fold increase after 12 days). Fb seeded in collagen matrices induced no contraction, whereas p-MyoFb and non-p-MyoFb induced 2.5- and 4-fold contraction. Fb produced low levels of collagen and secreted high levels of IL-10. Non-p-MyoFb showed high collagen production and high MCP-1 and TIMP-1 secretion. Transcriptome analysis indicated differential gene expression between all phenotypes. Dedifferentiation of p-MyoFb, but not of non-p-MyoFb, was induced by SD-208 despite maintained stress, shown by stress fiber de-polymerization in 30% of p-MyoFb vs in 8% of non-p-MyoFb. Stress fiber de-polymerization could be induced by mechanical strain release in p-MyoFb and non-p-MyoFb (2 day culture in unrestrained 3-D collagen matrices). Only p-MyoFb showed true dedifferentiation after long-term 3-D culture. Conclusions: Both reduction in mechanical strain and TGF--receptor-I kinase inhibition can reverse p-MyoFb differentiation but not in non-p-MyoFb.

Publication Title

Reversible and irreversible differentiation of cardiac fibroblasts.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE117247
Ruxolitinib inhibits Cyclosporine-induced proliferation of cutaneous squamous cell carcinoma
  • organism-icon Homo sapiens
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95 Version 2 Array (hgu95av2)

Description

Organ transplant recipients (OTRs) on Cyclosporine A (CSA) are prone to catastrophic cutaneous squamous cell carcinoma (SCC). Allograft-sparing, cancer-targeting systemic treatments are unavailable. We have shown increased risk for catastrophic SCC in OTRs via CSA-mediated induction of Interleukin-22 (IL-22). Herein, we found CSA drives SCC proliferation and tumor growth through IL-22 and JAK/STAT pathway induction. We in turn inhibited SCC growth with an FDA-approved JAK 1/2 inhibitor, Ruxolitinib. In human SCC cells, greatest proliferative response to IL-22 and CSA treatment occurred in non-metastasizing lines. IL-22 treatment upregulated JAK1 and STAT1/3 in A431 SCC cells. JAK/STAT pathway genes were highly expressed in tumors from a cohort of CSA-exposed OTRs, and in SCC with high risk for metastasis. Compared to immunocompetent SCC, genes associated with innate immunity, response to DNA damage and p53 regulation were differentially expressed in SCC from OTRs. In nude mice engrafted with human A431 cells, IL-22 and CSA treatment increased tumor growth and upregulated IL-22 receptor, JAK1 and STAT 1/3 expression. Ruxolitinib treatment significantly reduced tumor volume and reversed the accelerated tumor growth. CSA and IL-22 exacerbate aggressive behavior in SCC. Targeting the IL-22 axis via selective JAK/STAT inhibition may reduce the progression of aggressive SCC in OTRs, without compromising immunosuppression.

Publication Title

Ruxolitinib inhibits cyclosporine-induced proliferation of cutaneous squamous cell carcinoma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE55512
Gene-expression profiles of ovarian cancer regarding its microenvironment
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

PD-L1 suppresses host immunity and promotes tumor growth. We investigated how IFN- regulates PD-L1 in the ovarian cancer microenvironment. In clinical samples, the number of stromal CTLs in peritoneally disseminated tumors was correlated with PD-L1 expression on the tumor cells, and the lymphocyte number was significantly related to the IFN- signature score. In mouse models, PD-L1 was induced in peritoneal disseminated tumors, where lymphocytes were prominent, but not in subcutaneous tumors. Depleting IFNGR1 resulted in lower PD-L1 expression and longer survival in peritoneal dissemination model. Injection of IFN- into subcutaneous tumors increased PD-L1 expression and tumor size, and PD-L1 depletion abrogated tumor growth. These data suggest that IFN- works as a tumor progressor through PD-L1 induction. The source of IFN- in ovarian cancer microenvironment and its biological effect to the tumor cells is unclear. The immortalized human ovarian surface epithelial cell line, HOSE-E7/hTERT (HOSE) was treated with IFN- and expression microarray analysis was performed, and probes showing significantly higher values in IFN--added group were termed IFN- signature genes (295 probes). We then applied this signature to our ovarian cancer microarray data, which included 75 ovarian cancer clinical samples, by means of ss-GSEA. IFN- signature score was strongly correlated to the number of infiltrating CD4-positive or CD8-positive lymphocytes in the tumors. These data suggest that the IFN- in the ovarian cancer microenvironment is derived from lymphocytes, and an IFN--rich microenvironment is strongly correlated to a lymphocyte-rich microenvironment.

Publication Title

IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE70035
Expression data of squamous cervical carcinoma after chemotherapy
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The patients with locally advanced squamous cervical cancer (SCC) were examined in this study. All patients received neoadjuvant chemotherapy followed by radical hysterectomy. Tumor response against NAC was determined based on RECIST criterior. Gene-expression profiles of SCC were determined using Human Genome GeneChip arrays U133.

Publication Title

Genomic profile predicts the efficacy of neoadjuvant chemotherapy for cervical cancer patients.

Sample Metadata Fields

Specimen part

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accession-icon GSE55510
Gene-expression profiles of IFN-gamma-affected HOSE cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The source of IFN- in ovarian cancer microenvironment and its biological effect to the tumor cells is unclear. The immortalized human ovarian surface epithelial cell line, HOSE-E7/hTERT (HOSE) was treated with IFN- and expression microarray analysis was performed, and probes showing significantly higher values in IFN--added group were termed IFN- signature genes (295 probes). We then applied this signature to our ovarian cancer microarray data, which included 75 ovarian cancer clinical samples, by means of ss-GSEA. IFN- signature score was strongly correlated to the number of infiltrating CD4-positive or CD8-positive lymphocytes in the tumors. These data suggest that the IFN- in the ovarian cancer microenvironment is derived from lymphocytes, and an IFN--rich microenvironment is strongly correlated to a lymphocyte-rich microenvironment.

Publication Title

IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon SRP158590
Molecular Signatures of Multiple Myeloma Progression through Single Cell RNA-Seq
  • organism-icon Homo sapiens
  • sample-icon 138 Downloadable Samples
  • Technology Badge Icon

Description

Multiple myeloma (MM) is a malignant plasma cell disorder with well-defined clonal genetic/cytogenetic abnormalities. However, cellular heterogeneity is a key factor in MM's progression, therapeutic decision, and response to treatment. Single cell whole transcriptome profiling (scRNA-Seq) offers an opportunity to dissect this molecular heterogeneity during MM progression to better understand the disease and guide rational therapy. Here, we examined 597 CD138 positive cells from 15 patients at different stages of MM progression using scRNA-Seq. We selected 790 genes based on a Coefficient of Variation (CV) approach which organized cells into four clusters (L1-L4) based on unsupervised clustering. Plasma cells from each patient contained a mixed population of plasma cells at different state of aggressiveness based on gene expression signature reflecting the inter-cellular heterogeneous nature of MM. Cells in the L1 group is characterized by low level expression of genes involved in the oxidative phosphorylation, Myc targets, and mTORC1 signaling pathway having most cells from MGUS patients (p < 1.2x10-14). In contrast, low level of these genes in L1 group increased progressively and were the highest in the L4 group containing only cells from high-risk MM patients with t(4;14) translocations. Furthermore, 44 genes consistently overexpressed by pair-wised comparisons of the four groups strongly associated with a reduced overall survival in MM patients (APEX trial, p < 0.0001; Hazard Ratio (HR), 1.83; 95% CI, 1.33 to 2.52), particularly those in the bortezomib treated group (p < 0.0001; HR, 2.00; 95% CI, 1.39 to 2.89). No survival significance was observed for the dexamethasone treated group. Our study at the resolution of single cells showed that there is a mixed population of cells in each patient at different stages of MM progression and these cells can be organized into four different subgroups (L1 to L4). Consistent overexpression of the 44 genes from L1 to L4 groups is associated with patient outcome and treatment response. Our results show that oxidative phosphorylation, Myc target, and mTORC1 signaling genes are significant pathways for MM progression and affect MM prognosis and treatment stratification. Overall design: 597 single cell libraries passed QC and were included in the downstream analysis

Publication Title

Molecular signatures of multiple myeloma progression through single cell RNA-Seq.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP102431
RNA sequencing analysis of HL-1 cardiomyocytes
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

Analysis of murine cardiomyocyte cell line HL-1 treated with Ivermectin or Importazole. Results provide insight into the pathways regulated by the treatments. Overall design: RNA-seq of mouse HL-1 cardiomyocytes treated with vehicle (DMSO), Ivermectin, or Importazole for 24 hours, in triplicate, using Ion Proton System.

Publication Title

Antihypertrophic Effects of Small Molecules that Maintain Mitochondrial ATP Levels Under Hypoxia.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE39204
Gene-expression profiles of ascites-cytology-positive ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 61 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Ovarian cancer often progresses by disseminating to the peritoneal cavity, but how the tumor cells evade host immunity during this process is poorly understood. Programmed cell death 1 ligand 1 (PD-L1) is known to suppress immune system and to be an unfavorable prognostic factor in ovarian cancer. The purpose of this study was to elucidate the function of PD-L1 in peritoneal dissemination. Positive cytology in ascites was a significant poor prognostic factor in ovarian cancer. Microarray profiles of cytology-positive cases showed significant correlations with Gene Ontology terms related to immune system process. Microarray and immunohistochemistry in human ovarian cancer revealed significant correlation between PD-L1 expression and positive cytology. PD-L1 expression on mouse ovarian cancer cells was induced upon encountering lymphocytes in the course of peritoneal spread in vivo and upon co-culturing with lymphocytes in vitro. Tumor cell lysis by CTLs was attenuated when PD-L1 was overexpressed and promoted when it was silenced. PD-L1 overexpression also inhibited gathering and degranulation of CTLs. In mouse ovarian cancer dissemination models, depleting PD-L1 expression on tumor cells resulted in inhibited tumor growth in the peritoneal cavity and prolonged survival. Restoring immune function by inhibiting immune-suppressive factors such as PD-L1 may be a promising therapeutic strategy for peritoneal dissemination.

Publication Title

PD-L1 on tumor cells is induced in ascites and promotes peritoneal dissemination of ovarian cancer through CTL dysfunction.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE60135
Gene-expression profiles of BMP signaling-affected SK-OV-3 cells
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Bone morphogenetic proteins (BMPs) are extracellular signaling molecules that belong to the transforming growth factor beta (TGF-) superfamily. By regulating target gene transcription, BMPs control various cellular processes, such as proliferation, differentiation, apoptosis and migration.

Publication Title

The BMP signaling pathway leads to enhanced proliferation in serous ovarian cancer-A potential therapeutic target.

Sample Metadata Fields

Cell line

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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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