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accession-icon GSE84758
Transcriptomic, (phospho)proteomic, and metabolomic analysis of tumor-comprising cells treated by photodynamic therapy
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip, Illumina MouseWG-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Multi-OMIC profiling of survival and metabolic signaling networks in cells subjected to photodynamic therapy.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE84757
Transcriptomic, (phospho)proteomic, and metabolomic analysis of tumor-comprising cells treated by photodynamic therapy [mouse]
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Photodynamic therapy (PDT) is a tumor treatment strategy that relies on the production of reactive oxygen species (ROS) in the tumor following local illumination. Although PDT has shown promising results in the treatment of non-resectable perihilar cholangiocarcinoma, it is still employed palliatively. In this study, tumor-comprising cells (i.e., cancer cells, endothelial cells, macrophages) were treated with the photosensitizer zinc phthalocyanine that was encapsulated in cationic liposomes (ZPCLs). Post-PDT survival pathways were studied following sublethal (50% lethal concentration (LC50)) and supralethal (LC90) PDT using a multi-omics approach. ZPCLs did not exhibit toxicity in any of the cells as assessed by toxicogenomics. Sublethal PDT induced survival signaling in perihilar cholangiocarcinoma (SK-ChA-1) cells via mainly hypoxia-inducible factor 1 (HIF-1)-, nuclear factor of kappa light polypeptide gene enhancer in B cells (NF-B)-, activator protein 1 (AP-1)-, and heat shock factor (HSF)-mediated pathways. In contrast, supralethal PDT damage was associated with a dampened survival response. (Phospho)proteomic and metabolomic analysis showed that PDT-subjected SK-ChA-1 cells downregulated proteins associated with epidermal growth factor receptor (EGFR) signaling, particularly at LC50. PDT also affected various components of glycolysis and the tricarboxylic acid cycle as well as metabolites involved in redox signaling. In conclusion, sublethal PDT activates multiple pathways in tumor parenchymal and non-parenchymal cells that, in tumor cells, transcriptionally regulate cell survival, proliferation, energy metabolism, detoxification, inflammation/angiogenesis, and metastasis. Accordingly, sublethally afflicted tumor cells are a major therapeutic culprit. Our multi-omics analysis unveiled multiple druggable targets for pharmacological intervention.

Publication Title

Multi-OMIC profiling of survival and metabolic signaling networks in cells subjected to photodynamic therapy.

Sample Metadata Fields

Cell line, Treatment

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accession-icon SRP089875
Zebrafish microglia transcriptome
  • organism-icon Danio rerio
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Purpose: Identify zebrafish microglia transcriptome in the healthy and neurodegenerative brain. Methods: RNA sequencing was performed on FACS-sorted microglia (3x), other brain cells (3x) and activated microglia (4x). Microglia activation was induced using nitroreductase-mediated cell ablation. 10-20 million reads per sample were obtained. Reads were mapped to zebrafish genome GRC10. Results: We identified the zebrafish microglia transcriptome, which shows overlap with previously identified mouse microglia transcriptomes. Transcriptomes obtained 24h and 48h after treatment appeared highly similar. Therefore, these datasets were pooled. Additionally, we identified an acute proliferative response of microglia to induced neuronal cell death. Overall design: Zebrafish microglia transcriptomes of homeostatic microglia (triplicate), other brain cells (triplicate), activated microglia 24h (duplo), activated microglia 48h (duplo). In data analysis all activated microglia samples were pooled.

Publication Title

Identification of a conserved and acute neurodegeneration-specific microglial transcriptome in the zebrafish.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP075828
NFIB is a driver of SCLC initiation, progression and metastasis in mouse and marks metastatic disease in patients
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Small Cell Lung Cancer (SCLC) is the most aggressive type of lung cancer with early metastatic dissemination and invariable development of resistant disease for which no effective treatment is available to date. Mouse models of SCLC based on inactivation of Rb1 and Trp53 developed earlier showed frequent amplifications of two transcription factor genes: Nfib and Mycl. Overexpression of Nfib but not Mycl in SCLC mouse results in an enhanced and altered metastatic profile, and appears to be associated with genomic instability. NFIB promotes tumor heterogeneity with the concomitant expansive growth of poorly differentiated, highly proliferative, and invasive tumor cell populations. Consistent with the mouse data, NFIB expression in high-grade human neuroendocrine carcinomas correlates with advanced stage III/IV disease warranting its further assessment as a potentially valuable progression marker in a clinical setting. Overall design: Genomic DNA from mouse small cell lung tumor samples was analyzed by mate pair sequencing and low coverage sequencing. And RNA from Nfib overexpressing mouse small cell lung cancer cell lines was further analyzed for high quality RNA profiles using Illumina Hiseq2500. This series contains only RNA-seq data.

Publication Title

Transcription Factor NFIB Is a Driver of Small Cell Lung Cancer Progression in Mice and Marks Metastatic Disease in Patients.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP064474
Patient-derived xenograft platform for metastatic melanoma: RNA sequencing of 4 melanoma PDX samples
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

The therapeutic landscape of melanoma is rapidly changing. While targeted inhibitors yield significant responses, their clinical benefit is often limited by the early onset of drug resistance. This motivates the pursuit to establish more durable clinical responses, by developing combinatorial therapies. But while potential new combinatorial targets steadily increase in numbers, they cannot possibly all be tested in patients. Similarly, while genetically engineered mouse melanoma models have great merit, they do not capture the enormous genetic diversity and heterogeneity typical in human melanoma. Furthermore, whereas in vitro studies have many advantages, they lack the presence of micro-environmental factors, which can have a profound impact on tumor progression and therapy response. This prompted us to develop an in vivo model for human melanoma that allows for studying the dynamics of tumor progression and drug response, with concurrent evaluation and optimization of new treatment regimens. Here, we present a collection of patient-derived xenografts (PDX), derived from BRAFV600E, NRASQ61 or BRAFWT/NRASWT melanoma metastases. The BRAFV600E PDX melanomas were acquired both prior to treatment with the BRAF inhibitor vemurafenib and after resistance had occurred, including six matched pairs. We find that PDX resemble their human donors’ melanomas regarding biomarkers, chromosomal aberrations, RNA expression profiles, mutational spectrum and targeted drug resistance patterns. Mutations, previously identified to cause resistance to BRAF inhibitors, are captured in PDX derived from resistant melanomThis melanoma PDX platform represents a comprehensive public resource to study both fundamental and translational aspects of melanoma progression and treatment in a physiologically relevant setting. Overall design: RNA sequencing of 4 melanoma PDX samples to validate the effects of a structural variant on BRAF mRNA in BRAF inhibitor resistant melanoma.

Publication Title

BRAF(V600E) Kinase Domain Duplication Identified in Therapy-Refractory Melanoma Patient-Derived Xenografts.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE15940
Sex-Dependent Programming of Glucose and Fatty Acid Metabolism in Mouse Offspring by Maternal Protein Restriction
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge IconIllumina mouseRef-8 v1.1 expression beadchip

Description

Analysis of glucose and Lipid metabolism in male and female offspring after protein restriction of the mother

Publication Title

Sex-dependent programming of glucose and fatty acid metabolism in mouse offspring by maternal protein restriction.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE18027
BTG1 regulates glucocorticoid receptor autoinduction in acute lymphoblastic leukemia
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

RNAi mediated knockdown of BTG1 in the acute lymphoblastic cell line RS4;11 causes this cell line to become resistant to prednisolone treatment when compared to control cells.

Publication Title

BTG1 regulates glucocorticoid receptor autoinduction in acute lymphoblastic leukemia.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE11151
Gene expression data from different types of renal tumors and normal kidneys
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Identification and evaluation of specific molecular markers is of great importance for reliable diagnostics and outcome prediction of renal neoplasms

Publication Title

High-resolution DNA copy number and gene expression analyses distinguish chromophobe renal cell carcinomas and renal oncocytomas.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE5054
Effect of INF-gamma and IL1-beta on thyroid cells
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Normal primary thyroid cells were incubated with vehicle, 100 IU/ml IFN-gamma, 50 IU/ml IL1-beta, or a combination of both IFN-gamma and IL1-beta for 24 or 72 hours. The experiment was repeated 5 times using thyroid cells from 5 different patients. RNA expression was analyzed using Affymetrix HG_U133A arrays for 3 of the thyroids, and HG_U133A_2.0 (small version of HG_U133A) arrays for 2 of the thyroids.

Publication Title

Microarray analysis of cytokine activation of apoptosis pathways in the thyroid.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE34378
Aging Experiment
  • organism-icon Mus musculus
  • sample-icon 90 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Lifelong murine gene expression profiles in relation to chronological and biological aging in multiple organs

Publication Title

Life spanning murine gene expression profiles in relation to chronological and pathological aging in multiple organs.

Sample Metadata Fields

Age, 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)

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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